National Academies Press: OpenBook

Opportunities in the Hydrologic Sciences (1991)

Chapter: SOME CRITICAL AND EMERGING AREAS

« Previous: THE HYDROLOGIC SCIENCES
Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Suggested Citation:"SOME CRITICAL AND EMERGING AREAS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Some Critical and Emerging Areas OVERVIEW Earth processes are driven by two engines. The sun maintains the external engine that is responsible for the weather, surface erosion, and most oceanic processes. Radioactivity and primordial heat drive the internal engine that maintains the dynamic plate system and cre- ates global topography. Hydrologic science plays a fundamental role in key mechanisms by which the external and internal engines make the earth such a singular planet. This chapter presents some critical and emerging areas in hydrologic science. It is not exhaustive; the intention is to convey the flavor of the challenges and frontiers that make hydrology so critical a field of study in understanding the earth system. Toward this goal, the connection between hydrology and the earth's internal engine is explored. It is precisely through hydrologic processes that some of the most important interactions between the internal and the external engines occur. The tectonic system and the hydrologic system come together in the earth's rigid outer skin, mainly in the upper 10 km of the continental crust. Hydrologic processes play an important role in the tectonic system; for example, subsurface waters, in responding to changing thermal and stress conditions, can have a significant impact on the mechanics of earthquakes. The evolution of sedimentary basins and the genesis of ore deposits are fundamentally influenced by ground water flows operating on time scales of 102 to 106 years and spatial scales 62

SOME CRITICAL AND EMERGING AREAS 63 of tens to hundreds of kilometers. The vastness of the scales in- volved brings enormous variability in the properties of the physical system, and new models to understand transport processes and their media of occurrence are being explored. The subsurface is also where one of the major environmental impacts of human activities takes place. This is the deposition of different types of waste and their water-borne migration from original deposit sites. The greatest concern lies in predicting the temporal evolution of a contaminant plume under highly heterogeneous soil and rock conditions, and where it is subject to a wide range of geochemical and biochemical transformations. Fractured rocks and karst terrain present particularly difficult challenges in understanding solute transport processes. Within the upper part of the earth's crust, rocks undergo an important sequence of chemical and physical changes, collectively called weathering, which gradually convert the rocks to soil. Soil lies at the intersection of the two major systems of the external engine, the physical climate system and the biogeochemical cycles. These two systems exchange energy and matter through their interactions, many of which are hy- drologically controlled. Whether adequate soils survive in which to grow crops; whether rivers are navigable; whether there is magnificent scenery: each depends on geomorphic processes driven by water. Much remains to be learned about the processes of erosion and sediment transport, including the effects of varying climate and land use. Rivers are the conduits for the transport of the water, sediment, and nutrients that control the fertility of floodplains. A quantitative understanding of the mechanisms that will allow the prediction of long-term landscape evolution and the effects of major human inter- ventions is missing. The mechanisms of transport in a river basin are organized around the channel network—a tree-like structure with remarkable properties. How topography differentiates into channels and hillslopes is one of the key questions in its development. What are the unifying principles behind the three-dimensional network geometry? These principles are central to the runoff-generating pro- cess, which is intimately linked to the growth and development of the drainage network. River runoff itself is a key flux in the physical climate system. It is an input to ocean dynamics and an output from the convergence of atmospheric water vapor. This flux highlights the relationship of hydrology and climate. One challenge we still face is to improve our understanding of the interaction between the hydrologic cycle and the general circulation of the ocean-atmosphere system. There is a

64 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES constant exchange of water between the reservoirs of these two sys- tems, mainly through precipitation, runoff, and evaporation, but the time and space scales of the exchanges vary greatly among the com- ponents and with location. Unanswered questions relate to the at- mospheric pathways of evaporated moisture and to the sensitivities of atmospheric dynamics to the exchanges of heat and moisture between land and atmosphere. The operational tools in these studies are the atmospheric general circulation models (GCMs) that are being developed to reproduce the basic patterns and processes of atmospheric systems. Only recently have these models been used to study the spatial and temporal patterns in the atmospheric and surface branches of the hydrologic cycle. It is critical to intensify these efforts to quantify the role of land surface-atmosphere feedbacks in the maintenance of climatic systems. For a GCM to successfully simulate climate and be useful in regional hydrologic studies, realistic modeling of land surface processes is essential. Given that GCM grids are typically 104 to 105 km2, the sig- nificant effects of spatial heterogeneities in surface hydrologic processes must be defined. Identifying those effects, what controls them, their magnitudes, and their appropriate parameters is among the challenges that lie ahead. Of all the processes in the hydrologic cycle, precipitation in its various forms has perhaps the greatest impact on everyday life. At- mospheric processes that produce precipitation operate over a variety of space and time scales. They exhibit control and feedback mechanisms, and they interact with surface topography, soil moisture, and vegetation. A characteristic feature of rainfall is its extreme variability over time intervals of minutes to years and in space ranges of a few to thousands of square kilometers. One of the major challenges for hydrologists, meteorologists, and climatologists is to measure, model, and predict the nature of this variability. In hydrology, a primary interest lies in the dynamics governing the time and space distributions of rainfall, especially heavy rainfall that can produce floods, and in understanding the dynamic interaction of the drainage basin with these storms. This requires a link between deterministic models of rainfall dynamics and stochastic models of rainfall fields. The interaction between land surface processes and regional weather is another exciting frontier in hydrologic science. For instance, under what conditions will the spatial distribution of evaporation generate regional circulations that could influence mesoscale rainfall and regional climate? In this and other questions, it is becoming clear that spatial distribution of the phenomena plays important roles in controlling the strength of the feedback mechanisms between the surface and Me atmosphere.

SO1\dE CRITICAL AND EMERGING AREAS 65 Surficial processes are those involving the transport of mass and energy through the interface between the lower atmosphere and the earth's surface. Once again it is necessary to understand the relevant processes on different temporal and spatial scales. How can local observations of infiltration and soil moisture be translated to larger regions? At the laboratory scale, many important issues remain theoretically unresolved, an example being the effect of the chemical constituents of the soil on its hydraulic properties. At the hillslope scale, debate exists over the role of different factors on the effective- ness of the various flow paths. At the mesoscale, much progress is needed in the formulation of appropriate parameters for regional evaporation, and we need to learn more about which phenomena in the atmospheric boundary layer control evaporation from the land surface and from large water bodies. The frozen environment presents its own challenges: the behavior of surface and subsurface waters at all scales of description is complicated by phase changes and by the peculiar properties of ice. In alpine terrain, there is a need for methods that integrate the radiation balance over large areas to provide estimates of times and rates of snowmelt. Surficial processes not only provide key interactions between ter- restrial surface moisture and energy and atmospheric dynamics, but also constitute a vital link between the physical climate system and biogeochemical cycles. The hydrologic cycle provides a useful framework for interpret- ing key biological processes. From an ecosystem perspective, water is important as a carrier, a cooler, a substrate, and a mechanical force. The dependence of life on water is fundamental since water is the major constituent in essentially all functioning organisms. Their intricate life cycles are organized in most cases around their access to water. Thus the hydrologic cycle represents a fundamental physical template for biological processes. Hydrology and biology interact over a wide range of spatial scales, from the microscale of small habitats, through the mesoscale of drainage basins, to the macroscale of continents. Similarly, their temporal interactions range over minutes to centuries. It is precisely in the interplay between the different scales that the hydrologic cycle of- fers unique scientific challenges in the search for general principles. In plant dynamics it is known that the abundance of species and their spatial distribution are related to environmental conditions called ecological optima. A natural speculation is that these conditions are the preferred operating domain of the climate-soil-vegetation system. The key question relates to what the optimality criteria are that direct the functioning of this system. Where water is the driving force of

66 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES the system, a logical hypothesis is that the optimality criteria are related to the key hydrologic variables. Among the exciting scientific challenges are the search for the optimality criteria under different types of constraints and the mathematical representation of these cri- teria. The fluxes of the key biological variables (e.g., biomass) are also intertwined with the operating chemical processes (e.g., carbon assimilation), which in turn are linked to hydrologic processes (e.g., evapotranspiration). From such relationships it is clear that hydrology is a fundamental structural component of the biogeochemical cycles. Knowing where a parcel of water has been, and for how long, often is the key to understanding its chemical evolution. Hydrologic residence times are basic unknowns related to many contemporary environmental concerns. Acid rain is a clear example of the importance of understanding and predicting the effects of the chemical composition of precipitation. The use of rainfall composition data as tracers of the hvdrolo~ic cycle offers singular opportunities to better understand J ~ J V 1 1 the relationship between the chemistry of rainfall and the chemistry of soils, ground water, and surface waters. Hydrology and a number of chemical processes also are tightly connected in understanding the effects of soil and vegetation systems on the biogeochemical cycles of nutrients and toxic elements that affect water quality. Sediment transport, a process long of interest to hydrologists, is receiving much renewed attention as an important vehicle for the storage and movement of chemical species. The nature of organic coatings on stream sediments and the transport rate of polluted aggregates play important roles in the quality of stream waters. Understanding the interaction of processes at widely different scales is again a pivotal challenge. For example, soil history at a point is largely controlled by microscale chemical kinetics that can be studied in the laboratory, but how is this related to weathering rates at the regional scale? The biogeochemical cycles of elements like carbon and nitrogen are intimately linked with hydrologic processes. The importance of this linkage cannot be overstated because it affects the very nature of life on the planet and is a major component of the earth's external engine. A recurrent theme throughout this exploration of the frontiers of hydrologic science is the dynamic nature of the processes involved. These processes are highly nonlinear and have a wealth of feedback mechanisms operating over a wide range of temporal and spatial scales. These features are common to many scientific fields, and their study draws on the same mathematical ideas.

SOME CRITICAL AND EMERGING AREAS 67 How does one contend with the scale issues that are so pervasive in hydrologic phenomena? Is there hope for unifying relationships across scales? A challenging task is to uncover the organizing struc- ture hidden in the highly irregular patterns that hydrologic phenomena show at different scales. A striking feature of many natural processes is that changes in their scale of description lead to fluctuations that look statistically similar except for a factor of scale. A characteristic irregularity seems to exist that reflects an underlying structure. This characteristic irregularity can be described in terms of what is called the fractal dimension. Recent analyses of spatial rainfall and channel gradients in drainage networks suggest a more subtle type of structure where more than one factor of scale is involved. This is called multiscaling invariance, and it offers an exciting perspective for bringing unifying principles across scales to highly erratic hydrologic phenomena. The issues of nonlinear dynamics and the limits of predictability are other frontiers of contemporary science intimately related to hydrology. Recent developments in the theory of dynamical systems show that many nonlinear deterministic phenomena are sources of intrinsically generated complex behavior and unpredictability. In fact, they look as if they were a stochastic process, and thus the phenomenon is called deterministic chaos. Is this phenomenon detectable in hydrologic processes? If so, then, there is hope that through its characterization many important features can be understood regarding the complex nonlinear dynamics underlying the processes. What follows is a more detailed examination of selected frontiers in hydrologic science. In choosing these topics, the committee has subjectively sought the interesting and exciting, seeking to transmit the flavor of the science rather than to provide either an exhaustive or a rank-ordered list of the most important opportunities. HYDROLOGY AND THE EARTH'S CRUST Introduction Geoscientists describe the earth in terms of its three major struc- tural zones: the core, the mantle, and the crust. The crust is the rigid outer skin of the earth; in continental areas, it varies in thickness from approximately 15 to 70 km. Two aspects of the upper 10 km of the continental crust that make it unique are that (1) it is the only region of the earth's subsurface to which humans have direct access, and (2) it forms the interface between the earth's two major dynamic

68 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES systems the hydrologic system and the tectonic system. The tec- tonic system and the concept of plate tectonics involves a grouping of processes that lead to the formation and deformation of crustal rocks. Whereas the hydrologic system is set in motion primarily by solar energy, the tectonic system is driven by the earth's own internal thermal energy. When the role of hydrology in tectonic processes is considered, the depth scale of interest is kilometers, with horizontal distances usually on the order of tens to hundreds of kilometers. The processes of interest are the movement of fluids and the transport of mass and energy in the earth's crust. Hot springs provide an example to illustrate the nature of the interaction between the tectonic and the hydrologic systems. Hot springs develop when meteoric water originating from rainfall or snowmelt circulates to depths of several kilometers, adsorbs heat from the surrounding rock matrix, and then is able to move relatively quickly to the ground surface along fault zones. Figure 3.1 shows how heat flow from deeper levels of the earth's crust can be captured by the ground wa- ter flow system and diverted to a major fault zone. In areas where subsurface temperatures are increased by local intrusions of molten - O 4 -\ ~ ~ 6 —' e- ·cO~ ^ J -2 ~ ",,1 - .; . . . . . ... ... . . .. _ JO ::::::::::::::::.:; L-.-.. =— Vat . - . ................... ...................... ........ : ::::::::::: ::::::: ::! _ be;. ................ : :::: :,: l: ::::::: :::::::: :: :: :~;; .; ............ .~ O ~ ~ ~ ~ 6 ~, ~ ' 2] :-:-:-:-:-: :~:-:-:-:-:-:-:-:-:-:-:;:;:-:;:;:-: :;:-:~. ,; ... ;.;.;.;.;.;.;.;.;.;.;... L:: :, ,:,:,:.:,:.:, .:.:, I:,:.: , .:.:.:.:., , . ; _ = = = = by: =: 8 10 12 DISTANCE (km) FIGURE 3.1 Patterns of fluid flow (dotted lines) and heat transfer (dashed lines) in an asymmetric mountain valley. This diagram shows how ground water flow can modify the subsurface thermal regime, by adsorbing heat and transferring it to a fault zone (thick line). A warm spring discharges in the valley. SOURCE: Reprinted, by permis- sion, from Forster and Smith (1989). Copyright O 1989 by the American Geophysical Union.

SOME CRITICAL AND EMERGING AREAS 69 rock, hydrothermal systems may develop. The hot springs and gey- sers of Yellowstone National Park are dramatic examples. Active hydrothermal systems are potential sources of geothermal energy. Relic geothermal systems are targets for mineral exploration because metals may have been transported by the hot fluids, and geochemical conditions may have promoted precipitation of those metals to form ore deposits. Different issues arise when we focus on processes occurring within the upper several hundred meters of the earth's surface. This vadose zone normally comprises the weathered, unconsolidated soil material that is present at the land surface. In the vadose zone, both air and water are present within the open pore spaces between the solid grains. The medium is the site of innumerable chemical transforma- tions mediated by solar radiation, wet and dry atmospheric deposition, and biologic activity. The vadose zone is a storage component of the hydrologic cycle, a reservoir of water, air, and reactive inorganic and organic solid matter. It influences the runoff cycle and ground water recharge by affecting both the flow patterns and the quality of surface and percolating subsurface waters. The water table marks the transition from the vadose zone to the deeper saturated ground water zone, where all the pore spaces are filled by water. Like the vadose zone, the saturated zone is a reservoir of water and supports a range of chemical reactions. Issues at this scale center on the characterization of the physical, chemical, and biologic processes occurring within the subsurface hydrologic envi- ronment, their link to hydrologic processes occurring on the earth's surface, and the development of techniques for quantifying these processes and monitoring their effects. Many research questions here have direct relevance to the serious environmental problems facing our society. A number of processes must be addressed at the microscale, that is, the scale of the individual pore spaces within a soil or rock. The transport of chemical species dissolved in the water is a complex and dynamic process. Solutes entering the subsurface can interact with other dissolved solutes, with the solid matrix, and with the native ground water and can take part in the life cycle of microbes present within the subsurface. There is feedback between these biochemical processes and the patterns and rates of fluid flow. Greater under- standing at the microscale is necessary to build a framework for developing predictive models that apply at the mesoscale, the scale at which it is feasible to tackle most applied problems in subsurface hydrology.

70 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Some Frontier Topics The Role of Ground Water in Tectonic Processes To what extent can the app! ication of quantitative hydrogeologic concepts provide new insights into geo- fogic processes that occur in the earth's upper crust? l- Water originating as precipitation is thought to be able to pen- etrate to depths of at least 10 km. Water present within the void spaces of sediment or rock is a central feature in a number of geologic processes because (1) fluid pressures influence the strength of sediments and rocks to resist shearing and thus influence processes such as landslides, faulting, and earthquakes, and (2) fluid flow is the key process for large-scale redistribution of mass and heat within crustal rocks. Although rates of ground water flow are much lower than those in the upper few hundreds of meters of the earth's surface, and time scales may approach 106 years or longer, from a geologic viewpoint ground water circulation within the upper crust is no less important than the near-surface component of the hydrologic cycle. Permeability is the parameter that quantifies the ability of a fluid to flow through the interconnected pore spaces of a rock or soil. Figure 3.2 identifies typical values of permeability for a variety of geologic deposits and rock types. Hydraulic conductivity, the permeability when the fluid is water, often is used to characterize the flow of water through near-surface soils or rocks. More permeable sediments or rocks, capable of transmitting significant quantities of water, are referred to as aquifers. The wide range of variation in permeability implies that subsurface fluid fluxes (flow per unit area) can vary by orders of magnitude, depending on the nature of the geologic setting. Recognition of the significant role of circulating fluids in tectonic environments is not a recent development. The geologic literature contains a vast array of models that have been proposed to explain innumerable sets of data. However, for many years the science pro- ceeded no further than well-reasoned qualitative analysis. To quan- tify this link between the hydrologic and tectonic systems, the nonlinear interaction of the hydraulic, geochemical, stress, and thermal regimes must be tackled. Stresses in the crust originate from movements of the earth's tectonic plates, and more locally, from the weight of over- lying rock units. A benchmark paper by M. King Hubbert and William

SOME CRITICAL AND EMERGING AREAS unfractured metamorphic and igneous rocks - shale unweathered marine clay ~ sandstone limestone and dolomite fractured igneous and metamorphic rocks permeable basalt- - karst limestone - ~11~, c,allu - clean sand 1 1 1 ~ I 1 1 1 1 10-12 1011 10-10 10-9 10-8 10-7 71 gravel 1 1 1 1 1o 2' 10-20 10-19 10-18 10-17 1o~16 10-15 1014 10-13 PERMEABILITY (m2) FIGURE 3.2 Permeability of common geologic media. SOURCE: Adapted, by permis- sion, from Freeze and Cherry (1979). Copyright (31979 by Prentice Hall, Inc. Rubey demonstrated the importance of pore fluid pressures . . ha, . . - . .. ~ . . · . · . ·. . ~ in the mecnamcs ot faulting, and ultimately, in mountam-oullamg processes (Hubbert and Rubey, 1959~. This work, probably more than any other, set the stage for interactions between ground water hydrologists, ge- ologists, and solid-earth geophysicists. In the early 1970s, Barry Ra- leigh, Jack Healy, and John Bredehoeft, in what have become known as the Rangely experiments, provided field confirmation that fluid pressure can be a key parameter in triggering earthquakes associated with faulting (Raleigh et al., 1972~. Others documented the fact that filling a large reservoir behind a new dam can induce local earthquake activity. Dennis Norton and his colleagues at the University of Arizona were among the first to promote a quantitative framework to link geochemical processes, fluid circulation patterns, and heat transfer (Norton, 1984~. Recently, attempts have been made to quantify the role of ground water flow in regional metamorphism, where, for ex- ample, a rock such as limestone is transformed to marble. The concepts and tools of hydrologic analysis are being adopted to solve a number of fundamental geoscience problems, and opportunities abound for collaborative research. Earthquake Cycle Earthquakes occur when slip is initiated along a fault and stored energy arising from long-term tectonic movement is abruptly released. Subsurface waters, in responding to changing pressure, thermal, and stress conditions, can have a significant impact on the

72 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES EM. KI N AH U~B {HE RT~: ~ it's ~~: ~~ ~ ~ :~ ~ ~ :: : ~ A:: ~~ ~~ ~~ ~~ ~~ ~ ~ ~ aft: ~~ :: ~ Buff 9Q~3~1~9~891~ ~~:~: :: :: ~~ ~: I: ~ : i: ~ ;~: : A:: : ~ : I: ~ Hi: ~~ i: ~ : ~: ~~:~:~I~Ngeoph~ys~i~cs"~:s~ ~~m~uch~:br~er ~that~:~t~na::rr~a~ppl~c~ion~:~:~: Amp; ~~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~~ ~ ~ ~ ~ ~~ ~~ ~ ~ :~ ~ ~ Amp;. ~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~~ ~ ~ ~ ~ :~ ~ ~ i. ~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~~ ~:~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~~o~hvsi calls to mi r era I aide: Detroleum~ex~oldration .:: I t ~ i mul ire Can ~~:~ ~i ntegration:~matherr Them i say, physics~and gear orgy i n t:he~stddy :: ~:~t~earth~.~lri~th~is~c~ontext~:~did~be~argued That M:~K~ing~H6bbert~is ~~ ~ I: ~ ~ ~ ~ ~ ~ ~ ~~ ~: ~ ~ ~ W~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~ / ~ F~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~~ i: ~ ~ ~ : ~ ~ ~: ~ ~ ~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~~ it, ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ I; At, ~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~ ~ ~ ~ A, ~~ ~ ~ ~ ~~ ~ ~ ~~ ~~ ~ ~ ~ . ~ ~ ~~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ i. ~ ~ ~~ ~ ~ ~~ ~~ ~: ~ ~ ~~ ~~ ~ ~~ ~ ~ a At; :~ ~~ ~ At; ~ ~ ~ ~;~ hi; alit ~~ ~e~o~ge~ eyes As.: ~ in :~ also lee ~uc~n,~ 1~IS~:~eer,~ ~lM;~tesea~ 1~,~ 1~S~ :: : :~ ~~:::~ ~~ essays,~and- Ah i:s~:speech~ps;~ th ask outsp~ken~maverick~ t~l~earth~ ~:scie - es; ~ ~ ~ ~ ; ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~~ I:: ~~ i: : ~ ~ ~ ~ :: ~ :~ ~ ~ ~ i: ~ :~ i: ~ ~ ~ : ~ :: ~ : ~ i: ~ i: ~ i: ~ ~ ~ i: i:: ~ ~~ ~ ~ i:: ~ ~ ~k:~c~king~:a~ sct:eamirlg~:~:~a~largely~bbserv~a~nal ~and:l~descriptlVe~style~ ~ ~ ~ ~ ~ :~ :~ ~ ~ ::: ~ ~ ~ ~ ::: ~ ~ ~: ~ :: ~ ~ ~: ~ ~ ~: ~ ~ ~ i~ ~ ~ :~: ~ ~: ~:~: ~: ~: :: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~:: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~to ~a~mo'e~;~q~ntl~tative ;~exper~e~n~ta ~, ~e~ ~'ctufe~sc~tence~.~ ~: ~ ~:: ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~: ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~: ~: ~ ~ ~ :: ~ ~ ~: ~ ~: ~ ~: ~ ~ ~: ~: : ~ :~: ~: ~ ~ ~ ~: :~ :: ~ :~ ~ ~ ~ ~ :~ ~ :~ :~: :: ~ :~ ~ ~ : ~ ~ ~:~ ~~ : ~ ~:: ~ ~ ~:: ~ ~ :: :~ ~ :~ : :: : ~ :~: :~ ~: ~ ~: :: : ~: ::: :: ~: ~:~ ~ ~: :~ ~kl Ob~t:~ wa~s~ ~:bor~n~:~i n~: 1~9~3~ ~:~Attended~ ~:a~ on - ~m ~ T ~as~: sthoo~l house ~:~ ~ ~ ~:: ~ce~ed~ :tmcanventianal~ ~ high~ school~ucation:/~ an:~m ~ ~ ~ ~:~. ~-~_~ ~. ~: ~ - ~ ~r ~: ~:~:~ ~:~ ~:~t:~l~:~ ~:~:~ ~tJnwe~ty~Or~nIca~In~Y~~n,~navI~taKen~a~raesl~ ~araGemIc p~grarn t ~ t ~ ~ e r ~ p h a s i : ~ ~ ~ ~ p h y s i c s , ~ ~ ~ m a t h e m a t i c s , ~ ~ ~ ~ ~ a n d : ~ ~ ~ e o l o g y . : ~ ~ : ~ : ~ ~ ~ p u t I : i t t l ~ : s t o r e ~ ~ i n ~ : d~ and ~i—~his~.~—y~'n~ 1 937,~:on~the ~basis~ of ~his:publitation~ :~71he;~TheoryofScale~Mode/s~:Applied~to~:~sfudy::of£eo~c~stn)~ures~later ~;seJ into~his~c1~assic~paper~"The~Strength~of~e~E~arth.~"~is:career:spanned~:~ ~ :: ~ ~: ~ ~: ~ ~ ~ ~ ::~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~ ~ ~ ~ ~ :: ~ ~ ~; ~ ~ ~: ~ ~: ~ :: ~ ~ ~ ~ ~ ~: ~: ~ ~ ~: ~ ~ : ~ ~ ~::: ~ :: ~: ~ ~: ~: ~:: ~ ~ ~ ~: ~ ~ ~: ~ ~ : ~ ~ ~ ~ ~ ~ ~: ~: ~ ~: ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ata~ia~ governmer~ :~abd industry ~He~ t~3ght~at ~001umbra~rs~y in~:: :~ :~ ::: ~ ~: ~ :~ ~ ~: ~:: ~ ~ :~ :~ ~ ~ :~: :~ :: ~ :~: ~ ~ : ~ :: ~: ~: ~ :: ~ ~ :~ :: ~ ~ ~ ~ :;~ :~: ~: ~: ~ ~:~ : ~ ~ : :~::: ~ : ~ : ~:: ~ :: ~ : ~: ~ ~ :~ ::: ~ ::: ~ :~ :: ::~ ~ ~ ~ :::: ~: :~ : :: ::: ~: :: ~ ~ ~ :~ ~: : ~: ~:~?3~and~at :~5:tanford~versit¢~n~the ::l~96()s.~From~1:943 ~ ~1 964 ~he~w~as~a~l~ :~ ~ ~: ~ :~ ~ :: ~research~wiendst wi~She] De~pmei~ Houston,~ar=~ :fr~n~1964~:1976~ ~:~a~search~a~pb~:with the~:~.~al~Su~in~ington~.~:~:~:~ ~ ; ~ ~ ~ ~ ~ ~; ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ i; ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ I ~ ~ ~; :~: ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~, ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ., ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ .~ ~: ~ ~ ~: ~ ~ ~ ~ ~ : ~:~:: ~ ~ ~ ~ ~ 3 ~er t ~ e ~tn~ree ~ =ntr~to~ t0~ t 1e~ eart 1 ~ sc~temes~:~ a~nc ~=e ~ ~ ~ :~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ;~: ~ ~ ~ ~ ~ ~ :~: ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ ~ ~, ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~a~a~ ~t 1em~w=~ d ~ ~ guaran~ec ~ ):im~ :a~gooc ~measu:re~ ~ ~ ~ ~; 4~.~ ~. ~. ~ ~ ,~ ~ :.~ ~: .~,. ~ ~.~;~.~ ~ ;~ ~, ~::~=me; ~ ~Is~recogn~t~on ~ w:m ~ ~ pu~c~mn~ot tne:~J~ne~ ot~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ;~ ~ ~ ~ ~ ~ ~ ~ ~:; .~: ~ ~ ~: ~~ ,~ ~ ~ ~ . ~ :; ~ ~ ~ ~. . ~ ~ ~ ~ ~ ~ . . ~ ~ ~ ~. ~ ~ i~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~. ~ ~ ~ ~ .: ~. ~ ~ ~: :. ~ ;~. . ~ ~ ~ ~; ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~: ~ ~ :~ ~ uw~monor~a treatrse~e~uy~c'~arlr~me~t~=aarnental~pnysicis~:~ ~ ~ W~ ~ :~ ~ :~ ~ ~;~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~;: ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~:tha~t~ he~a~li6:t~ ~ples ~ ~i~H~lradynamic~i ondi-~ ~:~ ~.~,~ ~:,, ~:~: ~:~ ~: :~:~;~ ~ ~ ~: ~ ~? :~ ~ ~:~.~: ~ ~ ~.~.~ ~ !~ :~:~: ~ ~ ~:~ ~: ~ ~: ~ ~ ~:t~ a ~paper~that~eschew~ ~corrver~a~ ~w~ ~ar~a~ally~ ~h~:~a ;~:~ ~:~:~ ~:~:~:: ~:~:~ ~:~:: ~ ~:~: ~:~ ~ ~:~ ~:: :~:~:~: ~:~:~:~; ~:~::::~:~:~:~ ~: ~::~:~:;~:~::~:~:~ ~:::~:~ ::~:~:: ~ ~:::~:~:~:~::~::~:~:~:~ ~;~:~:: ~w ~ :: ~ ~ - ~ a~.~ ~ ~e:of the m:ost~i~gm:a1:ic ~b~, ~*e~p~ess~6f~thru~ul~ng ~Their~classic~paper,:~the~l6bf l:~iid~Prdssure~in~ ~: ~ ~ ~ ~, ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ;~*eh~hanicsof~hrgst~Faulting,~lntrucaced~the~im :~stress~;n:~:a ~u~ ~eolo~k ~ ~ooen~d~to~later~work bv~:~: ~othe~on~eaithi3uak~DredicUlan~l~.~:~ ~:~ ~: ~ ~: ~ ~Hiu:~be~ms~s~l~e~ton~it)u~l=~revoil~ves~a:round~ h~s~:~c~l~l:m~ ~tirst~:~m~ade: ~ ~ ! ~~ ~ ~;~ ~ ~ ~ ~: ~:~:~~ ~ :~ ~ ~;~ ~f ~ ~:l ~:~ :~:~ ~ ~ ~ ~f:~ ~ ;~ ~:~:~ <:~ ~ ~ ~:~ ~ ·~; ~ ~ ~ ~ ~ ~ ~ ~; ~e ~ ~ ~e ~ ~I~:n~:~1~4~, tna~e~:toss~:~:~:~era~ot~en~ergy:~,or~c ~t~on:~;v~u m~ne ~rera~t:~vm~y ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~:~: ~ ~ ~:: ~ ~:~ ~: ~ ~ ~ ~ ;~ :~ ~ ~ ~ ~ ~ ~ :~ ~:~ ~: ~ ~ ~::~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~: ~ ~: W: ~ ~: ~ :: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~: ~: ~ ~ ~ ~ :~: ~ ~ ~ ~:: ~ ~ ~:~ ~ ~: :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ :: ~sh~;t~liVed ~H:is~bel~h~ped~:curve~(often: called~t:~e~"~Hubbert ~Pim~pl~)~,: ,. . ~: ~:~:~: :~ :~ :: ~ ~: :~ :: ~: :: :~ , ~ which traces the comFfI~ete~cy:cle~ of U.S.:~and~:world~trucle~ o~l~pro~ction:~:~:~ :~ fro~m dNiscovLery~to ~ exl~stion,~ fi~rst :~aleTrted~the~ic~: t:o:~the~:~ct ~that~::~ ~eum~:~msolJrces~are~:ndt~ inexhaustibl~e.~ :~41though~hot~:- contested ~ : ~ ~:~ ~ ~ ~ :;~ :~ ::~ ~ ~ :~ ~: ~: ~ ~ :~:: ~ :~ :: ~ ~ :::~;: ~:; ~ :~ ~ :~ ~ ~ :: :~ ~ ~ ~ ~ ~ ~ ::: ~ ~:: : ~ ~ ~over~tt~ years ~ his~;p~ralJections~have~ had:~:a :: ma~or~ impact ~on~the~interna-~:~:~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ - rat~4i~ast rv~ a4:or ~U .S. ~owrr~ment~oo I f~CY.~::~ ~ :~s papers are modeb4~egant:~tl:arity.~ I—:~talJght~three~gen-~ ~e~ration~s~ :~ear~h~sc~ientis~:his example,~:~:think~c eatli, :~to~ write~ ~ceaN~andJo~6lv~auest~atce~ted~e~i~l~wi~orn~iT~it~ei:~ ~ :~ ~:~:~ : : ;~ ~: ::~ ::: ~:: ~ i: :~:~ ~ - t~c:oriform~:to ~fundam-entdI~ p~sic~aT~ and~:chem~mal ~pri nciple§.~: ~:~l~ :: ~ ~:~ :~ :~ ~ ~ ~: :: :~: ~ :~ ~: ~::: : ~; ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

SOME CRITICAL AND EMERGING AREAS 73 earthquake cycle. Three aspects of earthquake mechanics are rel- evant here: (1) the generation of high fluid pressures within fault zones, (2) expansion in the presence of pore fluids, and (3) pore pressure fluctuations prior to and during earthquake events. Expansion refers to the change of pore volume in the presence of an applied differen- tial stress. Lithostatic pressure at a particular depth is equal to the total weight of the overlying rock and water. As fluid pressures approach lithostatic pressures, rocks lose their strength to resist a shear force. When rocks slide past each other along a fault, friction generates heat. Thermal pressurization within a fault zone during faulting can cause fluid pressures to rise to near-lithostatic values, leading to strain weakening as the earthquake progresses. Richard Sibson (Sibson, 1973), and Art Lachenbruch and John Sass (Lachenbruch and Sass, 1980), carried out early studies of the process. More recent analyses using computer models have shown how this behavior can influence the character of fault motion, including earthquake magnitude. The hydraulic characteristics of the fault zone and the surrounding rock are key parameters in this process. Currently, there is only limited observational evidence to confirm the results of theoretical models. Limited knowledge of the hydrologic and deformation properties of fault zone materials restricts progress in advancing the theoretical framework to explain the mechanics of shallow earthquakes (depths less than 15 km). Such information is basic to the development of a capability for earthquake prediction. Spatial variations in hydraulic properties along the trace of the fault may be important in explaining the size and magnitude of barriers that act to resist fault motion and influence the magnitude of slip during single events. Research is needed to identify methods by which these data can be obtained. As tectonic stresses accumulate in the rock adjacent to a fault, changes in fluid pressures cause water level fluctuations in wells and affect the strength characteristics of the rock. Detailed observations of water level fluctuations that can be clearly linked to the earth- quake cycle may be available within several years. The hope is that measurements of this kind may eventually help us predict the timing and location of earthquakes. Volume recovery due to earthquake- induced stress drops may cause a pore pressure rise and act as a triggering mechanism for further earthquakes. Improvements in our understanding of field-scale hydrologic properties of rocks under changing stress conditions, and methods for obtaining those data, are key research needs. Intervention in the earthquake cycle to "manage" earthquake hazards remains a distant goal. . . ~ ~

74 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Sedimentary Basins Sedimentary basins form a substantial portion of the land mass of North America. They originate as regions of the continent where the crust was downwarped in the geologic past and infilled by sediments. These sediments eventually are transformed to sedimentary rocks. Near-surface regions of sedimentary basins, to depths of roughly 500 m, have been developed extensively to meet water supply demands. Other resources occur at greater depths. All of the continent's oil and gas reservoirs are located within sedimentary basins. Ground water flow plays a role in the transport of oil from source rocks to entrapment in a reservoir. Because ground water flow can modify the thermal regime of a basin, it is also a key consideration in the maturation of organic matter to produce oil. Fluid pressures approaching lithostatic values can develop during the evolution of a sedimentary basin because of the combined effects of compaction of the sediments, heating of confined fluids, and dehydration of clay minerals. These overpressures modify the flow patterns from those that would be predicted solely on the basis of ground water recharge from regions of higher elevation within the basin. The presence of overpressured zones also increases the hazards and costs associated with drilling operations to find new oil and gas reservoirs. Hydrologic models are being developed to investigate physical, chemical, and thermal relationships among ground water flow, transformation of sediments to form rocks, hydrocarbon accumulation, and evolution of the basin through geologic time. The availability of supercomputers has allowed researchers to investigate the nature of these coupled processes on large spatial and temporal scales in ways not possible only 10 years ago. However, important gaps remain in our understanding of the mechanisms involved. For instance, the deformation of porous media is a time-dependent process. For short- duration events with time scales up to 10 or 100 years, elastic models are adequate to describe deformation. In an elastic model, deforma- tion is reversible (examples of this include the stretching of a rubber band or compression of a steel spring). Blot (1941) presented an elegant theory to describe the elastic deformation of porous media. The coefficients that describe the elastic deformation can be measured in laboratory experiments or from tests in boreholes. However, for processes that operate on a geologic time scale, such as sediment deposition and basin subsidence, elastic models appear inappropriate. Long-term deformation is dominated by physical and chemical changes that are irreversible. Inelastic coefficients are thought to be of significantly greater magnitude than short-term elastic coefficients. Better under- standing of inelastic coefficients, and the development of methods for estimating their values, constitute an important area of research

SOME CRITICAL AND EMERGING AREAS 75 toward improving our capability to simulate patterns of ground wa- ter flow on a geologic time scale. Discharge areas for mesoscale ground water flow sometimes are associated with important mineral deposits of metals, such as lead and zinc. Metals released from source rocks are transported to sites where geochemical conditions promote the formation of sulfide minerals. Over geologic time, large ore deposits can accumulate. Such a situation is thought to explain the lead-zinc deposits of the upper Mississippi Valley. If it were possible to reconstruct the hydrogeologic and geo- chemical evolution of a basin, including transients imposed by erosion, tectonic stress, and thermal stress, then better exploration methods might be developed. Recent research has formulated the theoretical basis for carrying out these kinds of simulations. However, theories on transient flow are difficult to test with observational data because of the long time scales involved. A key research goal is the development of methods for building a sufficiently robust data set to constrain models of flow patterns that existed in the geologic past. Large-Scale Flow and Transport Processes The greatest obstacle to progress in understanding the role of pore fluids in tectonic processes is the lack of in situ data on the hydrologic properties of crustal rocks and fluid pressures, together with the lack of knowledge of their spatial and temporal variability. A new quantitative approach that builds on sound hydrogeologic principles and techniques is fostering great strides in our understanding of the complex nature of tectonic processes within the upper crust, but experimental confirmation is needed. Research teams of geologists, geophysicists, and hydrologists are being formed at institutions around the world. Hydrologists are contributing a realism to the models of fluid flow that was lacking in many earlier studies. Progress is limited, however, by data deficiencies. For the great variety of geologic environments that constitute the continental crust, insufficient data exist on the magnitude and variation of pore pressures, fluid properties, and the nature of porosity and permeability. This creates fundamental problems in identifying realistic values for medium properties to use in model calculations. Most studies are based on the concept of homogeneous rock properties, but there is little reason to expect that spatial variability will be any less important at depth than it is for near-surface environments. Similarly, there is a paucity of detailed data to test hypotheses and model assumptions rigorously. The National Science Foundation's Continental Scientific Drilling Program is one coordinated effort to provide data of the kind needed to guide · · .- · - sc~enht~c Inquiry.

76 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES :: :: RAD~I~OACT1 EVE WASTE ~~n~;Pf1~A~I~:~;~:~:~ ~~ ~ ~ ~ ~~ ! i: i: ~ I~ ~: ~ ~ ~: ~: . ~~ ~~ ~~ ~ ~~:~ - :~l~g 1~ A rac ~l~oact~l~v~e~:wa~ste~ mater ~~s~:g~en~eratec ~~ourin~:t~ ~e~:oro~< Lion ~:~ : it: :~ : :: of ~~nucle~a~:r~power ~are~curreritly: held An ~~te~orary ~~storag;e~at~n~lea : ~~power;lpl~arits~:~across~ the~UrYited~:States.~:~lf:~notclear~ power~i~s~t: 0 remain ~ ~ ~ ~ ~ ~ ~~ ~ ? ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~? ~ ~ ~ ~ ~~ via '~ e,: ~ong-term~p~ Sanest to :~dea~l ~~ :wi~t~ 1~n~uc ear ~waste~mu~st~$et~i~n~ place. ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ . ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~~ ~~ ~ ~:~ ~~ e ~ ~uc ~ear~:w:as~e~ JO ~J:cy~Aci:~:ot~ 1~982~ ~~a~s:~a~menc Alec ~~:~ i:~n~l~9~87~' ~~ d: that ~ ~:~ Mu. Uepartmerit ~~ot:~:~t::n~ergy ~~d:eve—~~a~:~moaram ~~for~ce:rm~:~ ~~n~r~:~ste~l~n~a~n~w~erg~round~:geolOgic ~~l~e~: p:Iart I: finis To buildup: a~repositorNf~thdt~would~be~ much lace a ~wnvent~iona~l~m~i~ Anti Edit; ~~:wtt l Alit 1e~waste~m~er~i~a s ~~;: aced:~i n~c=~ta~i~ne~rs~:~and~th~e~n:~s~i n~ha:lb5~:~ I~:~ialong~the~wa:l:ls~ 0 r f~or~of~e~reposl~tory~.~ ~~:~ :~£e:ivi~ was:te~a~:~ ~:~3~i0d~:~3~to ~~J~th~e~::~u~nde~rgroun~d o~i~gs~:~wo;uld~be ~batk~lled ~~ ~~ ~~ ~ ~ ~~ :~ :~ ~ :1~ ~ ~:L ~~ ~ ~ ~ ~ · ~ :~ ~~ ~ at ~ ~~:~ ~ ~ 1:~ ~: ~~:~ ~ :~ ~~: ~~ ~~ ~~ ~an(l:~tr,~e:~site~Insen: ~~ ~~: ~~:~ ~:~ ~ ~~ ~~:~:~ ~~Rad~ioa~ive~waste~is:~haza~o:us~f~r Time periods That: exce~len:~s~of~: ~ ~ it: ~ it: i: ~ ~ i: ~ ~ ~ ~ i:: ~ ~~ ~ ~ ~ ~ i: : ~ ~ ~ ~ ~ ~ i: ~~ ~ ~ i: it: it: it: ~ i: it: ~ i: ~ i: ~ ~ ~~ ~ :~ i: ~~ ~ ~ ~ ~~ ~ ~ ~ it: i: it: ~ i: ~ ~ i: ~ ~: ~~ ~~ ~ ~~ ~ i: ~ :: ~~ ~ it: ~ ~ ~ ~ ~ ~: ~ ~~ ~ it: it: ~ it: it: ~~ ~ ~~ :~ ~~ it: ~ ~~ thousands~of~Nears.~:~ The ~~concept~of~geol~gic~disposal~i~s: founded Non The ~~ ~ ~ ~ ~ ~ ~~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ . ~ ~ ~~.~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ .~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~: ~ ~ ~ ~ ~ ~ :~ :~ ~ ~~ ~ ~ ~ ~ it, ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~~ ~~ ~ ~ ~ ~~ i~ ~~ :~ ~: ~ ~ ~ ~~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ i~ ~ . ~:~i¢ ~ea~ot~:mw~ltipte~ers~.~tirst~:an~e~:nginee~rec~:~system~::~to~e=apsul~e~t~:~ i ~ ~~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ T~ ~~ ~ . ~ ~~ ~ .~ ~~ ! i~ ~ ~ ~ ~: ~~ ~ ~ ~ ~~ :~ ~ ~~ ~ ~ :~ ~ ~~ ~ ~ ~ ~ ~ ~ it; ~~ ~~ ~ ~ ~ ~~: ~~ ~~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~~ ~~ ~~ ~ ~~ : ~ran~loa~ctwe ate ~w:ltnm~tn~e~re~posit~y~anfi,~ ~hd,~*~rd~s~em~, I: I ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ it:- ~ ~~ ~ ~ ~ ~ ~ ~ ~ t ~~ ~~ ~~ ~~ ~ ~~ ~ :~ ~ ~ · ~ ~ ~ Hi;: ~~ ~ ~ ~ ~ : ~ ~~ ~ ::~ ~ ~ ~ ~~ ~ ~:~ ~~ ~~ ~~ ~ ~:~.~ ~~ ~ ~~ ~ ~ ~~ ~ ~~ ~ ~ :~ ~~ a: ~~ ~ it: ~:~e~surmunct - ~~ rocK~:rOr~matlons.~:~:~lt:~mnst~be~antl~c~ipated~that:~the~ ergo-::: i: i~ ~ ~ ~: ~ ~ ~ ~~ ~ i: it: ~ ~~ ~~ ~~ it: ~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~~ ~ ~~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i~ If: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ neered~barriers~witl eVentbal1V fail~;and~ That th6~ioriuc~l~ides~:wil At - Alien ~~ : ? i:: : :~ ~~ ~ a~slo:w~Jpurne~:hack to the gr~surface,: :;carried~a~lorlg~by~ Naturally ~~ . ~ ~ ~~ ~ ~ ~ ~~ :: ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~~ ~ ~ ~ :~ ~ ~ i: ~:~occU~m:ng~ground~water~flow~r~i~thd~h~ott~ro£ks.~ ~~T:lds~: - wr~:~watet~travel~ ~ ~ ~ ~ ~: ~ ~~ ~~ ~ ~ :: ~ ~ ~ ~ i: ~ ~ ~~ ~~ ~ ~ i: i: ~ ~~ ~~ ~~ ~ ~ ~ ~~ ~~ ~~ ~~ ~ ~~ ~ ~ ~~ ~ i: ~ ~ ;~ ~ ~~ ~~ i: ~~ it: ~~ i: ~ ~ ~~ ~ ~~ i; ~ ~ ~ ~ i: i: ~~ ~~ i: i: ~: ~: ~ ~ ~ ~~ ~ ~ ~ ~ :~ ~~: ~~ tln~e~trom~the~repos~itory~to~the~ Accessible environ~merit ~is~:a~ key~facto:r~ Ian ~~ ~ ~~ i; ~ ~ ~ ~ ~ ~ i, , ~ ~~ ~ ~ ~ J ~ ~ ~ ~ ~ ~ ~ i, ~ r ~ ~ ,, ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~~ ~ ,~ ~~ ~~aete~l~n~g tn~e~:s~uJtan~:t ~~ m:~a~F=icu la:~l~oc~ation~:l~e~repository.~ :~:~:~ ~~:~: ~ _ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ , ~ ~~ ~ ~ ~ ~ ~ ,~ ~ ~ ~ ~ i,: ~ ~ ~ ~ ~ _ ~ Hi: ~: i: ~ ~ ~ ~ ~ :: ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~: ~~: ~ ~~ ~ ~ :~ ~~ ~:~:~ ~~u~r~r~it~pe~rT:ormanc:e:~ ~~c~rlter:l~a~set~Own ~~nY~::U .~.~:~:~r:e~a~torv~a~erlc~ie~s~:~ ~ :~incl~ude~s~c~Itlc~ations~relawl~ra~onUclide~;arii~val~:~:at~the~e~th~ If; ~ ~ ~ ~ :~; ~~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ :~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ :~ ~ :~ i; ~ ~~ ~ ~~ ~~ W~ ~~ ~ ~ i: i; :~ ~ ~ ~ : i: ~~? ~ ~; ~ ~ :~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: :~:~:~surfaLce~:~and~tl~'e-e~mplacement~groun~d~ water~tra^~ tim~e:~from~the~ ~ : ::: i:: i: :: i: it: i:: ~ ~ : :: ~ ~ : :~ :~ ~ :::: ~ ~ :~: :~ ~ ::: i:: ~ ~ ::~ ~ :~ ~ ~ ::: ~:::~: :: :~ ::: ~ :~ ~ : ~~ :: :~ ~ :~: : ::: :: i: :: ::: :: ~ ~ i: :: :~ ~ ~ ~ ~ i: ~ :~ :~ :~ :~::~ ~ ~~ : i: ~ i: ~ :~ :~: :~ i: :: ~ i: ::: ~~ :: :~ :~: :~ :~ ::~ ~ i: :~ : : ~~regi~on:~:~of~he~re~i~f~to:~:~th6~Ce~s~sib~env~ir~nme~ngt.~Tlle~p~re em- ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : W~ ~ ~ :! ~ i: ~ ~ : 1~ p lacemerlt:~grou~nd~ water travel Eli melt alo~thi~fastest pith: of ~1 likely radio nub ode ~~ i: ~ ~ : i: i::: i: ~ ~~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i:: ~ :~ :~ :~ ~ : ~ ~ i: ~ :: ~ ~ ::: i: ~ i: i: ~ :~ ~ :: i: :::::: ~ :~: :: ~ ~ i: i: :~ ~ :: ~ :: ~ ~: :~: : ~ i: : ~ ~ :~ :: i: i: ~ ~ ~ i: :: ~ ~~ ~~ i:: ~ i: i: ~ ~ ~ ~ ~ : ~ i: ~: ~~ ~ i: ~ ~ ~ ~ ~ ~~—: i: ~~ ~~ ~ ::— ~~ : ~ ~~ truest must ~~:~:~at~ Beast: ~~:~:~:~yea:rs.~:~:~3~u~r~an~Hity~ ~pred~iu~the Grid ~~ : ~ i: ~ i:: :~ i: ~~ ~~ ~ ~ ~ ~ i: : ~ ~ ~ ~ i: :~: ~ ~ ~ ~ :: ~ ~ : ::- ~ ~ :~: i: ~ ~ ~ ~ ~ ::: ~ ~ ~ :. i: i: :: i: :: :~: ~ ~ i: ~ ~ ~ :~ i: ~~ i:: :: :~ B :: ~ : ~ ~ ~~ ~ ~ i:: ~ ~ :: :~ ~ :~ ~ ~: ~ :~ ~ :~ : ~ ~:wa~er: 1rave~l~t:l~me~ Manna tne concentrate ot~raolonu~es~ Stan: Then ~~: :water, :wi:1J :determinet in: large :oart.:~the environ~menta:l risk::th::at ~:futu~re~ ~g,e:nerdt~on~s~ walls facet if ~~:th~is~disposal option ~is~adopted:.:~:~Given~k length:: : Time ~:~i nvoi:ve~,~ oi~servati:ons~:~oresent~:Y~co~hd itionsl~i ~~ tel I tlie ~;~ ~~i~ com:pl:ete~story;~ii:Ptedithons~: must be~ba:sed~lo~n~sour~ph~ysicil~a~chemical ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i: ~ ~ ~ : ~ i: ~ :: ~ ~ ~ :~: if: :~ :; ~~ ~ ~ ~ ~ i: ~ ~ ~ ~ :~ i: ~understandi~:ne.~ :: ~ ~~ i: :::::: ~ ~ ~~ ~~:~:~:~: ~ : ~ ~:~:~ i: ~~:~ :::: :::: ~:~A;:~ Site ~ at ~IYucca:~ ~ Mo:unta'~n~ ~i~nl~ ~:~southern i:N:evada~l:~is~: be no: stud Girl: ~~ i: ~ ~ i: :: :: :: I: ~~ Assess:: its ~~:feasi~bi laity as ~~ a: repository. because ~:~ of If: the ;~ deserter: :climate,~ :~: ground~:::wa~r~ recharge is~:l~imited~ and~:~the~wate~r~ta~e Is very deep. Thetis ~~: : repos:itory~ would be located withy Nina ~~ vo~l~can ic~:~roc~k Mu nit: taboo: the~:~water~ : : ~:~I~:table~:~:~but sti I 1~ some :~300:~m:~:; below the~:grou~nd~surfac~e.~U nderl~lcurren~t~ :: : ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ i:: ~ i:: ~ i: ~ ~~ : ~ ~ ~ ~ : ~ ~ ;~ ~ ~ ~:~conctJ:t~ons,~: rate~s:~:or grourm~wa~r~:t~t:~ ~a:re~thoug~t~be~:on~:the~torder~ol:~:~ :~:~a~fewi~meters~peir:~centur(::~OIle~oft~he~concernsl~atmust:::~:~d~ressed~is~ : ~:~:~h~ow~:~:~these~ vel:ociti:es~i~:~mi:gh~: c~hange~:~at: ~~some~'int~in~the~ :~ture~if~the~: ~c~l~i~m~ate~of~sou~t~he~rn ~~:Nevada:~:were~:to:~beco~me~ wetter: ~~ ~~ ~ ~~ ~~ ~~: :: ~~ ~~:

SOME CRITICAL AND EMERGING AREAS : ~~ A: major researches program has bee:n ~ funded to address the scientific:: ~ and tec:h~n~i~c:al :issues:~ass~oc~iated with predicting how groun:d~water~:and : ~ ~ I: dissolve radionucl ides May move through the subsurface environment: If: at Yucca :Mou~ntain. if: The problem is Complex. A broad: ran~ge:::of geo- : :: : logic, h:ydrolog~i~c~:: and geochemical~questions must be~an~swered to evalu:ate flaw jet her or not t ire :site is cape :~ e of iso Sting rac ioact:ive waste. T he g~eologic~:reposi~tory pres~en:ts:~hydro~logists with~:~a~ta~s~k~ never before:~faced: ~ ~ ~ ~ ~ ~ . . ~ ~ ~ :, :: ~ ~ , ~ Spree :lcting, wit ~ reasonao e assurance, t: he occurrence ano movement or :: around: wa:te:r flow: and: rad~on:uclide concentrations on a time sca:le that Ail: extends thousands :of years into the future. 77 Even in a favorable funding climate, it is unreasonable to expect that more than several deep boreholes will be available at any one site. Each borehole yields data representative of conditions a short distance into the surrounding rock mass. It is not yet known to what extent these (already expensive) measurements carry information helpful in quantifying larger-scale flow and transport processes. Methods for integrating these measurements with higher-density geophysical data must be explored if we hope to adequately characterize the sub- surface environment. To what extent do small-scale measurements provide in- formation about large-scale flow and transport processes? How can we relate these measurements to other large- scale geophysical data? The pore space between the grains of a rock such as sandstone, or the interconnected microcracks within crystalline rocks such as granite, generally decreases with depth. As a result, it is probable that large- scale patterns and rates of fluid flow and mass transfer at greater depths within the crust are controlled by fractures and shear zones. It has yet to be established that conventional modeling approaches, based on assigning medium properties such as permeability to repre- sentative volumes of the rock mass, provide the correct framework to quantify mesoscale ground water flow and solute transport in deeper crustal rocks. Furthermore, in active tectonic environments existing fractures and shears will repeatedly open and close, and new fractures will appear. There is much speculation on the cyclic fluctuation of

78 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES fluid pressures between lithostatic and near-hydrostatic values, with pressure buildup and consequent release associated with fault rup- ture and locally enhanced permeability. The framework within which to treat the hydraulic properties of rock as transient variables is largely unexplored. Perhaps the greatest challenge comes in dealing with hydrologic processes that operate on time scales of 103 to 106 years. Here we are limited to observing the outcome of nature's past experiments. Analyses based on steady state assumptions can only be crude approximations of reality. Although the geologic record contains a wealth of infor- mation, we do not yet have the knowledge base to extract the quantitative measures that are needed for experimental validations. Fractured Geologic Media What are the links between geologic models of fracture formation, geochemical models for mineral infilling and dissolution, mechanical models of in situ stress conditions, and the statistical descriptions of network geometry used in stochastic fluicl flow and solute transport models? The hydrology of fractured rock is important for several reasons. In many bedrock aquifers, fractures provide an appreciable contribution to the capacity of the medium to transmit a fluid. At greater depths, they may account for the primary contribution, with a much smaller fluid flux occurring within the rock matrix. Because geologic units with low permeability are targeted as preferred sites for land-based disposal of toxic and radioactive waste, fractures represent the most likely pathways for off-site migration of contaminants. The scientific basis for describing fluid flow and solute transport in fractured media lags behind the state of knowledge for describing these processes in porous media systems. There are two approaches to the description of ground water flow in geologic media containing fractures: (1) the continuum approach, which treats the fractured medium as if it were equivalent to a porous medium, and (2) network models based on an explicit representation of the fractures. Figure 3.3 is an example of a computer-generated model of a fracture system; it shows a three-dimensional network of disc-shaped, orthogonal fractures. The rock matrix between fractures is not shown in this diagram. If fracture density is high, then the

SOME CRITICAL AND EMERGING AREAS /~ \ I-,,,. \45' 79 FIGURE 3.3 An example of a computer model of a fracture network. Fractures are repre- sented as disc-shaped features of variable size. SOURCE: Reprinted, by permission, from Long et al. (1985). Copyright (31985 by the American Geophysical Union. continuum approach is appropriate. The last decade has seen impor- tant advances in the continuum representation of fluid flow in frac- tured rock. The transport problem is more difficult. Advection and dispersion are understood only in general terms. In the early 1970s, de long developed a continuum model for solute transfer in networks of fractures with uniform spacing and infinite length, but a corre- sponding theory does not exist for the realistic case of finite-length fractures, irregularly located within a rock mass (de long and Way, 1972~. Even less is known of solute transport processes in unsaturated fractured rock. In media with relatively sparse fractures, or those where a signifi- cant proportion of the fractures are partially or fully sealed by mineral precipitates, transport for a considerable distance may be required before solutes encounter a representative sampling of fluid velocities. Until that distance is reached, continuum models are not applicable. It is also possible that several scales of fracturing occur within the rock mass, with a small number of areally extensive fractures exerting a predominant influence on patterns and rates of fluid flow. In either of these situations, discrete network models are appropriate. Sto- chastic concepts underlie the development of this approach, with probability distributions defining fracture locations, dimensions, ori- entations, and apertures. The suitability of models of fracture geometry that are based on concepts of statistical homogeneity has yet to be evaluated critically. Field-based hydrologists must take a lead role here.

80 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES If existing approaches for modeling fluid flow and solute transport in fractured rock are of questionable reliability, what new methodologies may be better suited for application in this important geologic setting? Uncertainties exist in the hydrology of fractured rock at both the microscale and the mesoscale. Fluid flow laws have yet to be determined for rough-walled fractures, with basic questions to be resolved on the nature of fluid pathways in single fractures and on the dependence of fluid flux on the stress field within the rock mass. Little quantitative work has been carried out on the transport of reactive solutes in fracture networks. Geologic studies indicate a close relationship be- tween the hydraulics of flow and the geochemical environment. Ex- isting models of mesoscale solute transport, and their application in practice, are of questionable reliability. Conventional continuum models may not be applicable, especially in sparsely fractured rock or in media with multiple scales of fracturing. The existing alternative, based on a discrete representation of network geometry, is limited in practical application by computational constraints, even when supercomputers are used. It may be that distributed parameter mod- els, based on an assumed form of the differential equation representing fluid flux and transport processes within a representative volume of the rock mass, are not suited to field-scale prediction. Alternative modeling approaches should be investigated. What are the measurement techniques needed to characterize field-scale hydraulic and transport properties of fower- permeability rocks, including fractured rock masses? The development of in situ techniques to characterize the proper- ties of fractured media has been, and will continue to be, an important research field. An integrated approach is evolving wherein a broad range of techniques is used to identify the geometric and hydraulic properties of fracture networks. Options include direct methods based on hydraulic and tracer tests and remote sensing methods using seismic, radar, or electromagnetic tomographic techniques to detect, map, and assess the properties of dominant fractures within the rock mass. We cannot yet accurately measure parameters that characterize the fluid

SOME CRITICAL AND EMERGING AREAS 81 flux and transport properties of individual fractures. The next five years should see important advances in the methods for making field measurements. Spatial Variability and Stochastic Simulation What are the relationships between the spatial structure of medium and flow system variables, such as hydraulic conductivity and fluid velocities, and the geologic processes forming soils, unconsolidated sediments, and rock units? Spatial Variability and Geostatistics One of the key advances in sub- surface hydrology over the past decade has been the incorporation of the spatial variability of the hydraulic properties of porous media into our theories of fluid flow and solute transfer. Textural and structural variabilities in soils and geologic media are the principal causes of spatial variability. Transport phenomena also exhibit spatial and temporal variability because of sporadic inputs of precipitation, irrigation, and contaminants. Pioneering studies of spatial variability in water and solute transport within the vadose zone were performed by Donald Nielsen, James Biggar, and co-workers at the University of California, Davis (Bigger and Nielsen, 1976~. The corresponding pioneering work in the saturated zone was done by R. A. Freeze (1975; Canada), L. W. Gelhar (1976; United States), and J. P. Delhomme (1979; France). These early studies clearly showed the extremely variable nature of water and solute transport parameters (e.g., hydraulic con- ductivity and velocity of solutes) as compared to the more modest variability of water retention parameters (e.g., degree of saturation and bulk density). These trends have been confirmed in many subsequent field experiments (Table 3.1~. Characterization of spatial variability entails field sampling and statistical analysis to infer means, standard deviations, and the length scale over which correlations are significant. This so-called correlation length is a measure of distance over which neighboring values are likely to be of similar magnitude. These ostensibly simple operations involve challenging problems, both physical and mathematical. Sub- surface hydrologic data are collected from a limited number of sites, each of which is used to sense, with some degree of error, conditions in a small volume around the measurement point. Adding to this

82 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES TABLE 3.1 Spatial Variability of Water and Solute Transport Parameters Observed in Field Studies Parameter Coefficient of Variation (percent)a Porosity Water content Bulk density Hydraulic conductivity Infiltration rate Solute velocity 6-12 4-45 3-26 48-320 23-97 61-204 aThe coefficient of variation equals 100 x standard deviation/mean for samples collected over a field-scale region. SOURCE: Copyright O 1985. Electric Power Research Institute. EPRI EA-4228. "Spatial Variability of Soil Physical Parameters in Solute Migration: A Critical Literature Review." Reprinted with permission. observational problem is the prohibitively large number of samples required, in principle, to characterize a parameter that varies by sev- eral orders of magnitude. Statistical methods to characterize spatial variability have been ap- plied in a number of hydrogeologic settings. Recent studies have demonstrated the extreme sensitivity of the estimate of the correlation length to the precise nature of the procedures used in estimating its value. Failure to subject a data set to a comprehensive analysis may result in estimates of correlation length values that have little physi- cal meaning. Other issues that warrant further study include (1) the identification of regions with similar medium properties and possible multiple scales of heterogeneity, (2) the incorporation of interpretive geologic models to augment borehole measurements, and (3) an as- sessment of the viability of statistical methods when only sparse data sets are available or can be collected. This latter situation is frequently the case in studies of deeper ground water flow systems. Measurements of fluid pressure and the collection of representa- tive water samples can present significant technical challenges, especially in deeper boreholes and in lower-permeability systems. Recent im- provements in instrumentation, such as modular multiport samplers and borehole velocity meters, have expanded the capability to obtain more detailed and accurate data from individual sites. New compu- tational techniques are required to process the higher-density data sets available from multiport samplers. An important research opportunity lies in the development of gen-

SOME CRITICAL AND EMERGING AREAS 83 eral relationships linking the processes forming a soil or geologic deposit, and the resulting spatial structure in transport properties for water and solutes. Observations are required from a wide range of soil and geologic environments throughout the mesoscale (1 to 100 km) range. The same kinds of improvements are needed for field observations of solute concentrations, with the added complexity that high-quality data varying over time scales of months and years are required. Improved data bases are needed to examine the critical issue of whether or not the statistical properties of a porous medium are spatially uniform or if they change with location. Virtually every model of fluid flow and solute transport in heterogeneous media is predicated on the assumption of spatially uniform statistical proper- ties. Current stochastic theories of transport predict only ensemble averages. What criteria should we use to establish the equivalence between the transport response in a field experiment and the ensemble average? Stochastic Analysis and Prediction Uncertainty Solutes that enter a ground water flow system are carried away from the point of entry in the direction of ground water flow. This process is known as advection. As the "plume" of solutes moves farther from its source location, it continually expands in size, in much the same way as a plume of smoke that is carried away from a smokestack by air currents. This spreading process is known as dispersion. Because of the many het- erogeneities within porous media, processes should be modeled mathematically as random functions of space and time, that is, as stochastic processes. A stochastic process consists of an ensemble of realizations, which is the set of all possible numerical values of the process. The common assumption in stochastic modeling has been that the dispersive and advective properties of a mesoscale soil or aquifer are single realizations of random functions, based in turn on an assumed stochastic model for hydraulic conductivity or solute velocity. This form of the transport equation is termed a "stochastic advection-dispersion equation." Stochastic models based on this ap- proach predict the ensemble-average solute concentrations. In modeling solute transport in the subsurface, the main interest is not with the ensemble behavior, unless its relevance to prediction for a single field soil or aquifer can be established. There is a need to develop rigorous methods to connect the predictions of an ensemble-

84 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES based stochastic model to experimental observations made in a field study. A single field experiment measures a single realization of a stochastic process, not its ensemble average, but nearly all current theories predict only ensemble averages. Studies of the variance of a random function under conditions found in subsurface environments are needed to establish the criteria for equating a measured transport property with its ensemble average. What kinds of field experiments are needed to assess the calibrations and predictive application of stochastic transport models at length scales of 100 to 1,000 m? The current use of stochastic concepts represents an initial attempt to capture field-scale variability in terms of a set of physical and mathematical approximations. However, many of the approximations remain both untested in detailed field experiments and underived from rigorous re- sults in the theory of random processes. Calibration and the predictive application of stochastic models make demands on experimental data bases that no field study to date has met satisfactorily. One requirement that is self-evident but surprisingly difficult to fulfill is mass conservation: the field sampling procedures and data interpolation methods should lead to a calculated total mass in the subsurface zone that agrees with the mass known to have entered the zone. Another important requirement that is not typically met in field studies of transport is specification of the initial conditions. If a stochastic model is to simulate the evolution of a solute plume, for example, it must have as input a precise numeri- cal account of the solute distribution at some initial time. Stochastic transport theory has yet to be evaluated critically in settings where the transport distance is on the order of 100 to 1,000 m, the scale of greatest concern at most hazardous waste sites. These experiments will be time consuming, tedious, and expensive, but of great scientific value. What are the theoretical approaches and experimental methods appropriate to aid in the identification of mode! structure and parameter estimation for simulating subsur- face fl uidflow? Before a model can be used for prediction, it must be calibrated. In 1935, C. V. Theis set the stage for estimating aquifer parameters by

SOME CRITICAL AND EMERGING AREAS 85 first reporting how ground water flow to a pumping well can be described as a mathematical boundary value problem (Theis, 1935~. Given this formulation, it is possible to estimate medium parameters such as hydraulic conductivity by measuring drawdown in one or more observation wells. Since that time, innumerable analytical techniques have been developed to characterize more complex hydrogeologic settings. With the introduction of numerical computer models, cali- bration took on a different format. Today, methods that can be collectively titled as "inverse simulation" are at the research frontier. These methods are closely linked to stochastic simulation. In most instances, there is considerable uncertainty in the values of model parameters and in the assignment of boundary conditions. This problem is compounded when measurement error is considered. Continued research is needed to aid in the identification and validation of model structures, in the determination of their scale dependence, and in the estimation of parameter values incorporating both direct and indirect measurement, geologic models, and hydrologic judgments. Progress here will ulti- mately improve efforts to develop a more precise understanding and assessment of valuable aquifer systems. Dealing with the Complexity of Reactive Solutes Although there has been growing appreciation of the effect of the "unmappable" heterogeneity of water-bearing strata, much of our understanding of basic subsurface processes depends on our still rather imperfect capability to quantitatively analyze solute transport under homogeneous and piecewise-homogeneous (i.e., "mappably" hetero- geneous) circumstances. To understand the reasons for this still- limited capability, consider the complexity of the situation. Imagine a small volume about some point within the vadose or saturated zone, which is initially in physical and chemical equilibrium. Suppose some new solution invades this pore space, perturbing the original equilibria and throwing the system into a rapid state of change. The new and original solutions mix in a complex way that is determined by the pore geometry. Their solutes react with each other, forming new compounds. Many of these solutes also react with substances encountered on the mineral surfaces or in the gas phase. Some of the original solids slowly dissolve. Newly formed solids precipitate on certain mineral surfaces, but some of the minute particles are carried by water for limited distances before getting stranded in the pore- space maze. A similar fate awaits colloidal particles formed by chemical reactions. These processes change the fluid-conducting properties of the subsurface. In turn, these changes influence the magnitudes and

86 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES .: V~.~I-~H:t~lS~:~ 1 ~ 9 0 0 - 1 ~ ~ 9 ~ 8 ~ 7 ~ ~ ~ : : ~ ~ : : ~~A~s~earch~::sc~i~enti~ses~rt~e~m~ay~:re~st~on~: a~:~li~i~:~m~e:~:~s~m~a~t~l~stepWi~se~ ~ ~ ~~ ~ ~ ~ ~ ~: ~~ ~ ~~ ~~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~~ ~~ ~: ~ ~ ~ ~~ ~ :~ ~ ~ ~~ ~~ ~~a~ch~m~e~n~ts~J~:o~r~i t~:~m~a~y~:~o~n~: ~::a~s~'n~g~le~:~::co~n~t~u~t~i~:o~n sofas ~g~i~m~por-:~ : _ i, . ~ ~ · ~ ~ ~ . .. ~ ~~ Dance ~~:~u TV.;: ~ fess ~e~n~su:~c ~~ 1~t~s~tame~:~w~i~t ,~:a~si~n~g~l~e~ five pa - ~~pa~pe~:~t~t~::~ ~ :~: : :~ ~~ ~~ ~ ~~ I: ~~ ~~ ~ ~~ ~ :~ :: If: ~~:~: ~ ~ : ~ :: ~ ~~ ~~: ~~: ~ ~~:: I: : :: pppeared~i~n~1935 ~i~n~:thd~sa:ttions~offf~7erican~1~i~n: ~E:ntitled~N~e~ Reunion ~en~Lo~weri~n~g4~the~ Piezom~eiri~c~: Surface ~:~:and;~th~e~Rate~an~d~ Burton of Discharge ~ ~~a~ ~\Nell~sirfg~ Ground~Wate:r ~:~ "I: Ed ~~ T Hi said b ~ With e Suer ~~:of:~t~ a pp :~ ~~: ~~: ~ :::::::: ::::: ~~:~: ~~:~::~ Or:::: If: ~~::~: ::: :: .::: ~ :~: : ::: ::::: :::: :::: ~ : ~~ ~~:::~ :~ :~ ::::: ~~ :: ~ ~~:e~n£e~:~or~tsa~n~s':en~t~:gro~u~te~:r~ftow.~: :~ ~1~ ~~:d~a~of ~~ ~pu~bl~ic~at~i~o~n~:~ ~i~s~ end: ~~ : : ::::::: ::::::: I:: ~ ::::: :::: :: ::::::: :: :~ :: : :: :~: :: :~ l~take~n~as~e~b~i~tt~h~e~:krl~i:the~ap~:pl~i:~cati~on~of~ode~rn~q~u~a~:ntimive:~m~eth-~: :~: ~~o~d<~of~field~:~i~nvestigation~in~; h~yi::lrolgrgy~.~T~he~is's~contr:[bution ~ is not likely: if: ~:~en~;~i~n~most:~h~;dr~geology~textt~oks,:~onlyG~ fwo~headi~ngs::~reflect~ : t~l~arne~(tie~i r:~;nators:~D~ar~cy's jaw ::a~;~the~: T~h~ei~s:~c~urve~.~ ~~:~ ~~ : T~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ . ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~~ ~~ ~~ ~ keys was 3arn~i:~n~:New1po~rt' ~~Kentucl~,~ ink 9~00.1~ ~~e~graduate~d~:lbo~m ~~ ~~:~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ,:, ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ ~:~ go ~ So: Solo ~~:l An ~~ ~~o No ~~r :m~:~t '~e~:u~n~l~v rsl~ty~ot~Ci~n ~i~nn~ati fin:: Civil ~:~en~i~-~ ~~ aft: :~ ~ ~ -~:::::~--~-:~:- ~ ~~- ' —~'~-~- _ ~ ~ ~~ —: ~— ~~~ :: ~ :~e · s~ B~ ~~ :~ ~~:~_~:~:~ : ::_:—:: air:::: ~ a, i; · . ~ I. ~ ~ :: ~ ~ ~ ~ ~ ~ ~ ~ —~ ~nee~rl~ng~l~n~ ~~. ~ ~~ nit ~ :, ~ a~ter~:~serv~l~r~g:~::a~s~not ,~i~n:stru~ctor~a~n~d~:~stude~nt in::: aft: ~the~geol~y~de~par~tm~ent atone the~:On~ive~rsi~ty~of ~ (~nc~i~n~n~ati~ he~:~rece~ived ~~ ~~ i:: ::: r.::~::: ::::::::: I:::::::: A:: ::: ::: ~::::~ ~ ::::: :: :::::: ::::: : ::~:: :::::: ::::: ::~: : ::: ::::: : :: :::::: ~ ~ ~ :~::~Fst~: P:n.~Dr~.~:eve~r~:~a~ward~ed~:~::bv~th~at ~d~er)a~:rtm}~n~t~.: ~:~ ~~:~ ~~ ~~ ~~:~:~Hi~s::~ca:reer~ w~as~s~i3e:n~t::~a1~:rri0~e~nti~re~1Y~—h ~~e~:~ ~ ~ ~Cen~l:~lr~l~S~~I:mPv~ ~~:~ W~ t:i~rst~::~n~Wds~hi~n~gton~ ~ ~~a~the~n~:n~ A~uq~:erque ~~New~M:e~x~ico~.~ He ::::::::::::: :: ~~ : ::::::: :: : :~: :::::: : ::::: . :~ ::::::::: : ::::::: : ~~ I:: :: I::::: : :::::::::::: : : ::::~: : ~ :: : ::: :::: : : :~::: :: :::~:::~::~ ::::: ::: Hi:: :::::: ~ ::: :::::: : : Was Sac ~:~ng~:~t ~e~g~rou~nc ~~wam~r~re~sou~rc~s Of the. ~~30rta:les~ hey ~~ New: :::::: ::: :::::::::: ::::::::: :~::~:::: :::: ::::::::: :::~::::~: :: ::::::: :::::: ::::::::: :::::::: : I:::: ::::::::: I:::: :: :: :: :~:: : :: I::::: : ~ : :~: I:: :~: ::: Mexito~l~f~r :the~USGS ~w:h~en~lh~e~l~tiegan~to~l~i~r~l~:a~bQut lain in~5it~i~ ~m:~l~:~ ~,~ measure ng alit ~i~pe~rmeab~i~l ity~bisedl~:~:o~n:~reco~rd~:i~ng~lp~ie~z~om~ricl~ draw-l: . ~ ~ ~ ~ ~ ~ :. ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ :~ ~~:~cown~s~:~n~:~a~n ~obse~rvat'~o~n~wel l~nea~r:~pump~:i~g Apt .: HA rnetho;~i~s~se~d:~: ::~ : :::: ~ ~ ::: :::: : ::: : ~ ::: :: :~:: :::: ~ :: :::::: ::::::: :::~:: :::: ::: ~ :::::: ::: :: :::::: ::: :: :: :::::: : ::::: I: :: :::: :::: :::: ;~ ode mat ,~e~m:~6t'~c~a So :ution~th~e~appropriate:~boanda~ pry: ~:~ it Hat bier Developed any Analogy ~~with~:~e~ a:vai:l~l~e~ heat flows: solutions :: ::::::~::: :: ::::::: :: :::: :::: :: ::: : : :~ ~ ~~ : :~ :: ::: :::::: :::: :: ::~: ::~ :~ If: , ~ , . : ~~tn~:l:s~exe~rc~s~e ::n~e~:~w~a~s~: ne~:t ~~h~is~i~er~c~.~:~l~.~:::~lL~u~bi~:ll ~~of~th~e~u:n~ive~rs~:i~ty~of~::~ ;:~:~ ~Cin~c:~in~n~ati~, ~~whol~:~is~:~ac~kn~ow~l;edged~:~in~paper~:~bL:it~:~:ec~:l i~nid~:~£:Q-a~ut~r:-~:~ :: ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ship.: The is's ::~:1 93~5~:~ ~p~a~per~in~sp~i~r~d ~~a~:~len~gthy:~s~:ucces~s~ion;~of~aq~w:i:i~r~h~y-~ : ~d~ra~ul~i:cs~:~re~sea~r£h~i~n They:: 1~940s,:::: 1~:~950s,:~and~1960s~: by~:~ot:h~ers~.~;~ I The : ~ ~ ~ ~ ~1 :~ ::-::: ~ ~ 1 :: ~ ~~ : ~ : :: ~ _: : :. ~ : If: I: ~ : ~ ~ :~: : ~ : : ~ ~ : ::: : I: : ~ : : : ::: ~ I: :::: :: ~ : ::: ~ : ~ ~ ~ ~ : ~ I ~ ~ ~ ~ ~ U S , ~ ~ ~ ~ I ~ n e ~ : S ~ ~ ~ ~ e C a m e ~ ~ ~ t n e ~ ~ U S ~ S ~ ~ ~ ~ l ~ l : a ~ : i ~ S o ~ n ~ ~ ~ W ~ i ~ t h ~ ~ ~ t h e ~ ~ ~ ~ m : ~ i C ~ ~ : ~ E ~ n ~ r ~ ~ ~ ~ C o m ~ m ~ i ~ S S ~ i o n ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ I, , ~: ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ : analog net wrote ma:ny~ea~rly a:rt~;cle~s~on ~~the~h~ydrogeologic~ issuei::~ass~oci:a~ted:: ~:~ :: ~ : :::: I: ~ I:: I::: ~ :~:: I: ~ :: ::: : : : :~ :: :: ~ ~ : : : : : : : ~ 'i ~ 1 : ~ 71 · : l: elan nuclear waste alsnosal ~ ~ ~ ~ ~ ~ r ~ : : ~—_ 1: 1:~ :~ 71_ 1 ~ _ ~ : · . . ~ : ~ ~ _ _ _ ~ . . : . . : ~~ ~c~l~l~e~agu~e~s wno Knew i Nelson at thou recall hl~m:~:as~: :a~::~:har:d-nosed, i: ~ : : ~ ~ : ~ : : :: :: ~ ~ ~ ~ :~: ~~fie~sty~:lea~d~er~:of :~the~ ~:h:ighest ~:p~e:rsonal ~~integ~i~, alar ~ man who admired: clear ~~ ~:~ ~~ . . . . ~ ~ If: ~~tn:~,~nkin~g~and~wh:~o~ a~lwa~y~s~:ha:d~ time ~fo~r:~:youn:~er ~~:c~o:ll~ea~ues~ :~ ~ ~~ ~ ~~ ~ ~~ ~~: ~~

SOME CRITICAL AND EMERGING AREAS 87 Distributions of solute fluxes and concentrations. Some of the incom- ing solutes may activate dormant spores, which germinate and become microbes, which then absorb and transform some of the solutes pass- ing near them, creating a variety of new substances. No doubt, a considerable intellectual challenge is presented by the problem of understanding such a tangled, dynamic, multivariable system. Yet such an understanding is necessary to analyze the processes that determine the chemical evolution of natural or human-influenced waters. Early methods to deal with the transport of reactive solutes often were adopted from the chemical engineering literature. How- ever, significant differences exist between solute transport processes taking place in fixed-bed chemical reactors and those occurring in sediments of aquifers or soils. Methods for describing solute transport in geologic media have had to outgrow their roots in chemical engineering and other nonhydrologic sciences. This state has now been reached, calling for special efforts and opening interesting possibilities. The physics of solute transport in homogeneous porous media is now fairly well known. The main exceptions involve transport in porous media containing both air and water (or other immiscible fluids). This process is poorly understood and requires much attention. For instance, unexplained and contradictory data exist concerning the dependence of solute-mixing processes on volume proportions between air and water within the pore space. A frequently used assumption that may require examination is that, in porous media, only dissolved substances are mobile. Mobility of small particles and microorganisms has reemerged as an important topic of study, in- volving surface chemistry, biology, and physics. What are the kinetics of geochemical reactions involving more than one phase, and what mode! should be used to account for the complex geometry of the solid-fluid interface that exists in geologic media? The transport of reacting solutes involves still imperfectly under- stood geochemical kinetics. Particularly insufficient is our understanding of extremely important reaction kinetics that involve more than one phase (e.g., one involving a mineral solid and a water-carried solute). These kinetics need to be studied in situ so that the influence of the subsurface pore geometry can be taken into account. In the case of heterogeneous kinetics, transport analyses are generally based on the so-called pseudohomogeneous approach or approaches developed in

88 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES connection with chemical reactor problems. The pseudohomogeneous. approach assumes that the location of the reaction is within the body of the solution rather than at the solid-solution interface. It is very important to study experimentally and theoretically the correctness and limitations of such a basic assumption. The second type of ap- proach is a reasonable one for a reactor with man-made components. In the subsurface the pore geometry may be very different. The influence of "geologic" pore geometries is yet to be fully understood. How can we quantify microbiological processes that oc- cur in the vadose and saturated zones, and the interactions with the physics and chemistry of subsurface transport? Consideration of microbiological processes in the integrated analysis of the physics and chemistry of subsurface transport, especially the deeper subsurface, is a relatively recent phenomenon. It adds another level of complexity that in all probability will be as large and as important as the chemistry level. Many of the mathematical expres- sions used for the relevant process rates involve an analogy to enzyme kinetics. The completeness of this analogy should be the subject of more critical studies. The entire field of quantifying microbial effects is in its initial stages of development. The theory of biological reactors, which assumes that an excess of nutrients exists, is still very influential. Microbial ecology under field conditions of severely limited mineral nutrients and energy-yielding compounds has yet to be critically studied. Contamination of Ground Water Flow Systems . How should we quantify the processes that determine the transport and fate of synthetic organic chemicals that enter the ground water system? A major environmental focus of the past decade has been the rec- ognition of the extent to which ground water has been, or potentially is, at risk of being contaminated by inorganic and synthetic organic chemicals. Many examples are available where industrial waste management practices, agricultural production, and natural resource developments have led to the introduction of hazardous chemicals

SOME CRITICAL AND EMERGING AREAS 89 into a ground water system. Contaminants found in ground water are of three general types: (1) chemical species that are miscible with the pore water and migrate with the ground water flow as a dis- solved aqueous phase, (2) organic liquids that are only sparingly soluble in water and move as a-separate phase through the pore space, and (3) bacteria and viruses. The impact of these contaminants, both on the natural environment and on water supply, can be severe. Cleanup of a contaminated aquifer is a difficult and expensive task, if it is possible at all. Many basic physical, chemical, and biological issues must be resolved if society is to have the scientific basis to deal rationally with contamination in the subsurface environment. Research oppor- tunities fall into three categories: processes, models, and field mea- surements. A number of research needs are linked to general questions, discussed earlier, of the transport of reactive solutes in heterogeneous media. There is a real need for improved methods to predict solute transport over distances of 102 to 104 m, in porous and fractured rock masses, in karst terrain, and in unconsolidated sediments. Attempts to model the chemical evolution of ground water at the field scale have met with limited success. Extensive reliance is placed on experimentally determined equilibrium partition coefficients. These coefficients express, for example, the ratio of the mass of a solute species sorbed on the solid surfaces of the porous matrix, relative to the mass of the species present in the pore water. Conditions under which the use of partitioning coefficients may be adequate have not been defined clearly. There are uncertainties in transferring laboratory-determined coefficients to field settings. Little is known about the heterogeneity of the geochemical environment and the nature of its role in the transport of reactive solutes. The subsurface behavior of synthetic organic liquids that are only sparingly soluble in water is not well known, in either the vadose or the saturated zone. Current theories describe the transport of organic liquids using concepts of multiphase flow adapted from the petroleum literature. The validity of this approach requires further examination. At the microscopic scale, the nature of interactions between the pore geometry, organic liquid, and capillary pressure-retention character- istics needs to be understood physically and described mathematically. At the mesoscale, interactions between geologic stratification and spreading patterns need to be defined, especially for organic liquids that are denser than the native ground water. Existing multiphase transport models for predicting the distribution of organic liquids in the subsurface require estimates of many parameters and functional relationships. Effective techniques to obtain these data are required.

9o OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Microbial populations indigenous to the subsurface hydrologic en- vironment can strongly influence rates of transport and transforma- tion of synthetic organic compounds. The nature of microbe colonies, their growth dynamics in a complex hydrologic and geochemical sys- tem, and the transformation of organic compounds into other mo- lecular forms constitute an emerging active research area. Detailed understanding of the dynamics of this system has yet to be developed at both the microscale and the field scale. Research needs include (1) controlled experiments using multidimensional flow cells In laboratory settings, in addition to studies in field settings, (2) development of methods for parameter measurement, and (3) improvements In simulation capabilities. HYDROLOGY AND LANDFORMS Introduction Geomorphic processes driven by water shape the land surfaces on which human populations and all other terrestrial biota live. In shaping the land surface, they determine He nature and distribution of hydrologic features such as river channels and soil profiles. Thus geomorphic activity exerts a feedback on the hydrology that drives it (Figure 3.4~. Recent technological advances give geomorphologists access to landforms below the oceans and on other planets and moons and FIGURE 3.4 The feedback relationship between hydrology and landforms. Hydrologic | L Processes I _ _ 1 Geomorphic | Processes . l Landforms and their Hydrologic Characteristics (e.g. soiler channel densities' gradients)

SOME CRITICAL AND EMERGING AREAS 91 have extended the scope of this formerly earth-bound discipline. In some of these exotic environments water or ice is, or has been, an important agent shaping the planetary surface. However, most hy- drologically based geomorphology concerns the surface of the earth, and thus involves processes that affect the habitability of this planet and its capacity for sustaining life in the face of sometimes radical human impacts. During its movement over or just beneath the earth's surface, wa- ter sculpts the land and determines the nature and distribution of features such as rivers, floodplains, and soil-covered hillslopes. Societies depend on these features for their survival. Whether adequate soils survive in which to grow crops; whether rivers are navigable; whether there is magnificent scenery to inspire and delight us: these depend on the activity of geomorphic processes, driven by hydrologic processes. Within the upper few kilometers of the earth's crust, rocks are subjected to a number of influences that weaken them, making them susceptible to erosion and transport. These influences include fracturing on a variety of scales from microcracks to regional fracture zones- as a result of gravitation, tectonic and thermal stresses, and chemical decomposition by circulating fluids, particularly those that carry at- mospheric and biogenic gases from near the earth's surface. As rock material approaches the land surface due to the stripping of overly- ing material by erosion, it undergoes an important sequence of physical and chemical changes and is invaded by biota. These complex changes, collectively called weathering, gradually convert the rocks to soil. The altered earth materials are the hydrologic media that determine how ground water moves, whether rainfall is absorbed by soils or flows over the ground, and how chemicals (including pollutants) are immobilized or transmitted in percolating waters. These media are also erodible and are thus involved in soil erosion, landsliding, fluvial sedimentation, and landscape evolution; they also provide substrates for human activities. Various processes erode the decomposing materials into landforms, ranging in complexity from single hillslopes or small channels to the complex assemblages of surfaces that constitute a mountain range such as the Himalayas or an intricate alluvial plain such as the Amazon River lowland. Regional-scale landscapes develop over time scales of 10 million to 100 million years as a result of the interaction between large-scale movement of the lithospheric plates (plate tectonics) and the fluctuating climate and hydrology that drive erosion processes. Climate and hydrology in turn may be affected by the movement of continents, the growth of mountain belts, or the intensity of volcan- ism, as well as by changes in land use or drainage. Within these regional landscapes, on time scales of significance to

92 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES humans, geologic materials are mobilized and redistributed as poorly sorted mixtures of slightly weathered rock or as thoroughly weathered fine sediment. For example, glaciation and intense landsliding in the high Himalayas are feeding a poorly sorted mixture of sediment, ranging from boulders to silt, into steep torrents and thence to the main trunk streams flowing from or through the mountain chain. The rivers transport the various size fractions of sediment at different rates, and leave the coarser fractions behind as long-lived sedimentary accumulations (including alluvial fans, floodplains, and river terraces) in mountain valleys. The finer fractions (sand and finer particles) are transported hundreds of kilometers and deposited in adjacent basins, usually located in major downwards of the earth's crust. Adjacent to the Himalayan chain, the vast Indo-Gangetic lowland is composed of alluvial landforms (including channel bars, floodplains, river terraces, FIGURE 3.5 Channel network formed by ebbing tide in the Gulf of California. SOURCE: Photograph by Anne Griffiths Belt. Reprinted, by permission, from National Geographic 176(6), December 1989, pp. 717-718. Copyright (I) 1989 by the National Geographic Society.

SOME CRITICAL AND EMERGING AREAS : ~ ~ ::~: : :~: : : : ~ ~ ~ A: : ~~ ~ ~ :: ::::: :: :~::: i: :~ ~ ~ ~ ~ ::: 93 ~~ ~~I~N~TER~RU~PTI~ON~OE~iSS~~Pl~:RI:VER~S~E~Fl ~~X~:~:~:~ ~:I~:~n~t~ :~:~r~tli~s~s~isNipp~:~R:~ve~r:: ~:~d~ta~th:e~ra;te~:~o~f~:~la~nd ~~l~s~has~ ~acce~le~r-:: . ~:~ Gina named. by :~ o rang ~~e~x~ ~~rit6~ water ~~ i s Ha ~ nag - mpen~sate ~~ r~t~i~ alluvial fans, river channels, and lake basins) that are being formed and destroyed as sediment from the mountains is deposited and later eroded again and moved downstream. As a land surface is eroded, water is concentrated along depres- sions either by surface runoff from higher parts of the landscape or by ground water discharging into the depressions. The result is a stream network in which water flows faster and deeper than over the surrounding landscape and has a greater capacity for transporting sediment evacuated from hillslopes. The resulting branched, hierar- chical network of channels exhibits a high degree of regularity and spatial organization (an example is shown in Figure 3.5~. The land surface draining to any point on a channel network is defined as the drainage basin of the stream at that point. The geometry and sedi- mentology of channels are scaled by the magnitude of the water flows that they receive from their drainage basins and also by the magnitude

94 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 100 ^ 80 C`i` a c,' 60 U) o J 40 20 o ~ 1 1 1 / / 1920 1940 1960 1980 YEAR FIGURE 3.6 Land loss In the lower Mississippi River delta of Louisiana. SOURCE: Reprinted, by permission, from Gagliano et al. (1981). Copyright @) 1981 by S. M. Gagliano. and grain size of the sediment load that the water transports from upstream. Since drainage area and thus water and sediment fluxes change in a regular manner along the stream network, so also do the characteristics of channels. Perturbations of the water or sediment fluxes from the drainage basin, as a result of environmental change or human activity, cause changes in channel and valley floor char- acteristics, often with widespread effects on human habitat. Some Frontier Topics Prediction of Landscape Evolution Most geomorphological research has been aimed at understanding the nature and chronology of landscape development, and it has yielded many important insights concerning the large-scale form and domi- nant erosion processes of most of the earth's regional landscapes. However, almost all of this work has been qualitative or empirically quantitative, and explanations generally are given a posterior). At the other end of the spatial scale, the past 40 years have witnessed improvements in understanding individual erosion processes and predicting their effects on the sediment yield and shape of individual hillslopes, including the effects of varying climate and land use. There is still much to be learned about the mechanics of individual

SOME CRITICAL AND EMERGING AREAS 1n~ _ o :r: UJ z p IL o Williston a) | GARRISON DAM ~ 1 954 1~_ u __ . ~ ~ .... an, ~ ., 0 0 0 0 u, (D ~ a: al ~ ~ a) I OAHE DAM 100 - ~ '; 1958 I_ Pierre n ~ 0 0 A) ~ _ _ ! SHARPE DAM 1 1 963 FORT RANDALL DAM r 1953 | GAVINS POINT DAM 200~' 1963 ........... o 200" a) ,. . S. ~ _ on Yankton by =` 400 1 u' C) LL by LD co co Bismarck Omaha 2001 ~ _~ I ~ Kansas City 400 r 1 on 200 o 0 0 0 600~ ~ a, a' lo - 400 1 200 St. Louis Hi Baton Rouge 1_ h~ ^! WATER YEAR 95 tton ierre - _4mphis 0 100 . '~ MILES Baton Rouge New Orleans GULF OF MEXICO &~,^~ ~4~ salt Ricm:~r~l~ Yankton - Minneapolis `( Omaha Hi> ~ _. . ._. ._ - ~ St. Louis FIGURE 3.7 Annual discharge of suspended sediment at six stations on the Missouri River and two stations on the Mississippi River showing the effects of reservoirs on downstream sediment loads, 1939 to 1982. SOURCE: Reprinted from Meade and Parker (1985) courtesy of the U.S. Geological Survey.

96 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES processes of erosion and sediment transport, including such wide- spread and important processes as the interaction of raindrop impact and surface runoff in causing soil erosion, the buildup of stress as a root-reinforced soil approaches the threshold of landsliding, and the initiation and motion of catastrophic landslides and debris flows. These hillslope sediment transport mechanisms now are being studied with new instruments for measuring turbulence, strain, and other charac- teristics of deforming media, and with faster computers to analyze geometrically complex situations. Understanding these processes is important for forecasts of natural hazards and sediment yields in the context of anticipated changes in climate and land use, or in catastrophic geologic events such as volcanism. How are water, sediment, and nutrients exchanged between river channels and their floodplains? Both the understanding of mechanics and the capacity for predic- tion of geomorphic processes decrease as one moves to interactions between processes on larger scales, but the problems and prospects are exciting. For example, research on the exchanges of water, sediments, and nutrients between river channels and their floodplains is in its infancy, despite long-standing assumptions that the fertility of floodplains is the result of nutrient-rich sediment from certain favorable rocks. Such issues are brought sharply into focus by major engineering projects (such as the High Aswan Dam) that interrupt the sediment flux and diminish overbank flooding, but the fundamental research necessary for quantitative prediction of the effects of such projects on floodplain sedimentation is just beginning. How do regional-scale landscapes react to changes in climate and the biosphere? Interactions between erosion and sedimentation processes are even more complex and important when one considers how regional-scale landscapes react to changes in climate and the biosphere, and therefore to anticipated global warming and land use changes. A landscape is an ensemble of hillslopes with different shapes that shed sediment episodically into river channels bordered by floodplains where the sediment is transported and stored for various lengths of time. The

SOME CRITICAL AND EMERGING AREAS 97 sediment includes plant nutrients and organic and toxic substances, which can be altered and separated during storage and transport. With the insights provided by process studies and with the aid of increasing computing power, geomorphologists are developing use- ful simplifications of erosion-sedimentation models to make regional- scale prediction computationally tractable while retaining a useful degree of realism that could be checked against field observations or geologic records. Prediction of landscape-scale erosion and sedimentation requires viewing landforms in a wider context, including soil and vegetation covers. Changes in the condition of land surfaces therefore depend on the link between erosion and the regional soil-water balance, vegetation cover, and land use. Impetus for such modeling of large-scale processes will probably soon emerge from the capacity to link general circulation models, regional-scale water balances, and erosion processes. Because of the need to predict changes over large regions, one must consider the response of entire river and valley floor networks to sediment influx and therefore the link between hillslope and floodplain sediment. Current methods do not take account of the storage of sediment in floodplains and alluvial fans, which modulates sediment- yield response most strongly during periods of environmental changes. An important task is to develop generalizations about storage and remobilization from the field studies now being undertaken with the aid of radiometric dating and chemical tracers. In the process of accumulating this understanding, much will be learned about · the basis for the fertility of floodplains, · the geomorphologic and hydrologic basis for the ecological di- versity of floodplain flora, and · the fate of toxic chemicals sequestered in sediments and concen- trated at drainage basin outlets. Development of Drainage Basins and Channel Networks How should one model the mutual dependence of chan- ne! and hilIsIope surfaces as a key factor in theories of drainage basin evolution and channel network formation? River channel networks like leaf veins, blood vessels, and trees- are branching networks that transport fluids to or from three-dimensional surfaces. Biological and physical scientists have long been fascinated

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SOME CRITICAL AND EMERGING AREAS 99 by questions of form and function, such as what causes leaf cells to differentiate into stems and matrix and how topography differentiates into channels and hillslopes. Some geomorphologists have studied the mechanics of the erosion processes that form channels in particular hydrologic environments; others have attempted to define more gen- erally the necessary and sufficient conditions for channel incision on an erodible surface; and still others have formulated a mathematical description of channel networks as outcomes of a random selection process. Recent studies have focused on the differentiation and mu- tual dependence of the channel network and the hillslopes that constitute most of the drainage basin surface. Researchers studying a variety of tree-like structures have concluded that they all have some common growth characteristics. In hydrologic terms these characteristics require the existence of an erosion regime that depends strongly on the magnitude and frequency of water flow per unit width, leading to a progressive change in the processes and forms of sediment transport from hillslopes to rivers. The position of channel heads is determined by the long-term balance of sediment movement. Upstream, valleys tend to fill with sediment, whereas beyond a threshold distance from the drainage divide channel incision becomes established. The location of channel heads is controlled through an interaction between gradient and catchment area, which together influence surface and subsurface hydrology and sediment transport. Competition for runoff, and therefore drainage area, between growing channel networks leads to a land surface that is differentiated into hillslopes and channels connected in a regular, dendritic, space- filling pattern. The change of the sediment transport mechanism from hillslope to channel may be modeled through the attainment of a threshold value by the function describing the mechanics of the particular erosion process (such as surface erosion, seepage erosion, or mass failure) that extends channels in the particular landscapes to which the model is applied. Pioneering work in the quantitative description of basin evolution was carried out along those lines by Smith and Bretherton (1972~. Three-dimensional landscape evolution models incorporating ideas of this form first require an equation describing the sediment balance at any point. The sediment transport in this balance is nonlinearly dependent on the local water discharge and slope. The resulting equations are solved numerically in space and time. To initiate the process, a small random elevation perturbation is assigned to every point in the catchment. Figure 3.8 shows examples of networks gen- erated in this way. Analysis of planar and elevation properties of many of these simulations indicates behavior consistent with that

100 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES observed in nature. The generated networks are extremely sensitive to initial conditions. This is reminiscent of chaotic behaviors that may look like the outcome of a random process, although in fact they may arise from completely deterministic equations (see the last section of this chapter, "Hydrology and Applied Mathematics". Important questions remain to be addressed, such as what the pa- rameters are that control the growth and differentiation of the chan- nel network and how they depend on climate and topography. Three-Dimensional Network Geometry and Hydrologic Basin Response What hidden unifying principles lie in the three-dimensional geometry of channel networks and how are they related to the hydrologic response of a basin? A key idea introduced by Horton (1945) and modified by many others is that of the ordering of a channel network. In the 1960s, Shreve (1966) provided an analytical framework under which Horton's laws of network regularity could be studied. In spite of many efforts, the analytical theory of channel networks has remained almost purely planimetric. A challenging and crucial problem is the incorporation of relative elevations and their ties with the planar characteristics of the drainage network. In the 1970s, mainly through the work of Rodriguez-Iturbe and Vaides (1979) in Venezuela and Kirkby (1976) in England, it was shown that the topology and geometry of the channel network are intimately linked with the hydrologic response of drainage basins and particularly with the flood hydrograph that results from storms occurring over the basin. The geomorphologic unit hydrograph (GUM) derived from this work is a first step toward rigorously connecting the unit impulse response function of a basin with its geomorphological characteristics. Nevertheless, the connection is only related to the planar structure of the basin; the altitude dimension is still missing in the efforts to link the structure of the channel networks with the hydrologic response. Moreover, the GUH and other similar schemes are only routing procedures, since they work with effective rainfall and do not address the question of runoff generation. Because of the many circuits of reciprocal control between the system of hillslopes and the drainage network, one could expect that the understanding of the three-dimensional organization of the network will also hold the key for the organization of the runoff production process in natural basins.

SOME CRITICAL AND EMERGING AREAS 101 Stream networks are the result of dissipation of energy in the envi- ronment by water flowing downhill. This simple observation shows that drainage networks, beyond their purely topological and plani- metric attributes, are dissipative physical systems. The ability of drainage networks to erode into landscape is affected by a balance between the ability of the network to do work versus the resistance of the landscape to erosion. Therefore it is reasonable to suspect that the three-dimensional geometrical patterns manifested by drainage systems record a variety of states and conditions, including the total flux of material through the system (related to climate), the distribu- tion in time of such fluxes (related to weather), and the rates of change of fluxes. Recent research shows that a promising avenue in understanding the analytical structure of the three-dimensional geometry of river networks is to identify the precise nature of the scaling property in the network geometry. As explained in the last section of this chap- ter, scaling refers to an invariance property of the probability distributions of physical variables under a change of spatial scale. Although predictions based on the simple scaling hypothesis are quite good, the data also show a need to generalize to multiscaling. Another important issue in this context is the determination of the scaling exponents, appear- ing as parameters in a scaling theory of river network geometry, from physical considerations about climate, geology, landforms, and so on. Moreover, a physically based determination of these scaling exponents is expected to identify some general physical principles, e.g., uniform distribution of energy expenditures in channel networks, as a basis for discovering the signature of river basin dynamics in the geometry of channel networks. Investigations outlined above involve only the spatial variability and neglect the issue of time. In this sense they constitute only the first step toward developing a mathematical theory of river basins. Extensions of such spatial theories to space-time evolutions, and the solution of the novel and important problems that would arise through such generalizations, remain among the major long- term research goals. Interpreting Records of Environmental Change What new techniques can be used to retrieve the information on potential geomorphic alterations and climate changes that is stored i n sed i meets ?

102 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Geological and historical records of the postglacial era indicate that widespread changes in erosion and sedimentation resulted from subtle climatic changes during the past 10,000 years. These climatic fluctuations alter plant cover, frequency distributions of rainstorms, the presence and rates of snowmelt, evapotranspiration, and other factors that in turn control the condition of land surfaces (e.g., their erodibility, moisture status, and radiative properties) and the response of rivers and valley floors to changes in runoff and sediment supply. For example, vast quantities of sediment were deposited tens of meters thick over thousands of kilometers of valley floor in subhumid regions throughout the world as a result of climatic changes during postglacial times. These valley deposits have been trenched and re- plenished repeatedly by streams. In some areas the sequence of ero- sional and depositional events has been complicated by the effects of land use. One of the most studied cases is in the southwestern United States, where there is a controversy about the relative roles of climatic change and land use in initiating a regional cycle of arroyo entrenchment late in the nineteenth century. Throughout the world, there are many other such records of the morphological and sedimentation effects of subtle changes in climate and/or land use on stream channels, valley floors, and the soil cover of hillslopes. In some localities, chemical tracers and isotope distributions also provide information about sources of sediment and rates of accumulation. If anthropogenic disturbances cause future climatic changes with rates and magnitudes at least equal to those in postglacial times, it is reasonable to anticipate that there will again be widespread alterations of the vegetal and hydrologic condition of subhumid land surfaces, and changes in the magnitude of hillslope erosion relative to the sediment transport capacity of trunk streams. If the sediment yield of the hillslopes exceeds the transport capacity of the streams, sediment will accumulate and raise valley floors. Such changes will affect riparian ecosystems, agricultural land, irrigation systems, and urban areas. Some means of anticipating these effects is needed, and the alluvial deposits of valley floors provide the most useful indicators of analogous changes in the past. However, it is difficult to make predictions of the effects of future environmental changes on erosion and sedimentation, and their enormous influence on human welfare, from qualitative interpretation of sedimentary records. A major challenge for hydrologists concerned with sediment redistribution is the quan- titative interpretation of morphological and sedimentological records of environmental changes, and the use of these records for testing prediction models or simply for making more secure predictions by analogy with past changes.

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Y: l:~::~LC:' A:: ~ ::::: : ~~ ::::: ~ ~ : ~ : : :: ::~:: :: :::: ::~::~ :: ::::: : :: :::::: ::: I: ::: ::: :: : :: : ::: : : ~ : : ::: :: : I: Examples of other regions where such predictions could be useful include the following: · the Amazon basin, where the effects of land use changes on river sedimentation have not yet been well documented or predicted; · the Mississippi basin, where impoundment of sediment in reser- voirs has reduced the sediment supply to the lower valley and delta

104 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES and caused widespread erosion, but where important climatic changes may occur that could affect both river flow and sediment; and · the Ganges-Brahmaputra basin, where there are major uncer- tainties about the future roles of Himalayan erosion, land use, in- channel sedimentation, intensified monsoonal weather patterns, and rising sea level on the geomorphology and therefore habitability of the alluvial zone of Bangladesh. The keys to making and testing such predictions lie in the physical and chemical characteristics of alluvial sediments. The thorough in- vestigation of these sediments, combined with process-based math- ematical modeling of their accumulation, constitutes the best source of information for anticipating changes in sediment redistribution. Researchers in this field need training and equipment for using isotopes and other chemical tracers, as well as skills in stratigraphy, sedimentology, and geomorphological modeling. HYDROLOGY AND CLIMATIC PROCESSES Introduction Water has physical properties that significantly influence the glo- bal climate. Large amounts of heat are associated with the phase transitions between water vapor, liquid, and ice. The release of latent heat during surface evaporation is the major mechanism through which much of the absorbed solar energy at the surface is transferred to the atmosphere. The evaporated water then moves within the atmosphere in the form of water vapor and clouds, eventually condensing into precipitation. The released latent heat drives air motions important to the atmospheric general circulation. Water vapor is also the most important of the greenhouse gases, which efficiently absorb and then return the thermal radiation emitted by the heated earth surface. In this manner, vapor in the atmosphere regulates the temperature regime at the surface as well as in the atmosphere. The heat capacity of water makes the oceans an important regula- tor of global climate. At high latitudes, sea ice and snow exert sig- nificant influences on global climate because of their enhanced capa- bility to reflect incident solar radiation. Given the myriad ways in which the occurrence and abundance of water can influence the climates of the world, some major goals for hydroclimatologic research must include (1) improved understand- ing of the interaction between the hydrologic cycle and the general circulation of the coupled ocean-atmosphere system, and (2) eluci-

SOME CRITICAL AND EMERGING AREAS 105 cation of the role of this interaction in maintaining climate and influencing its variabilities. An important first step toward these goals is the quantitative determina- tion of water fluxes at the ocean and land surfaces as well as in Me atmosphere. To address this need, a plan is being developed for comprehensive in situ and remote observations of the land surface and the atmosphere. This plan, put forward by the World Climate Research Program (WCRP) of the World Meteorological Organization and the International Council of Scientific Unions, is known as the Global Energy and Water Cycle Experiment (GEWEX), and it is described in Chapter 4. Remote sensing methods, also described in Chapter 4, have already been developed to assess such variables as surface soil moisture, surface temperature and reflectivity, vegetation cover, large-scale patterns of rainfall and cloudiness, and vertical profiles of water vapor in the atmosphere. We still need to improve and verify calibration techniques, however. A major tool for the study of climate and the hydrologic cycle is the numerical atmospheric general circulation model (GCM). During the post- war period, GCMs evolved from simple dynamical tools to help forecast daily wind patterns into more complicated mathematical algorithms that capture the dynamics and linkages between general atmospheric circulation and the hydrologic cycle. Results of computer simulations with GCMs can, for example, illustrate Me role of land surface fluxes from a local area on the regional climate (Figure 3.9~. Numerical models can serve as laboratories for evaluating the impact of such phenomena as deforestation in the Amazon and extensive droughts in Africa. A comprehensive approach involving both observation and mod- eling of the coupled ocean-atmosphere-land surface system is essen- tial for the effective study of climate. Some Frontier Topics Diagnostic Studly of the Global Water Balance How can general circulation models simulate the quanti- tative structure of the global hydrologic cycle and help to evaluate its effect on climate? The hydrologic cycle is imbedded in the general circulation of the atmosphere. The capability to simulate and predict the general circu- lation of the atmospheric fluid is thus of crucial relevance to hydrol- ogy.

106 90 60 30 o -30 -60 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 1 ` A,=. : ,_ : _, ~ ~ ' in ~ I::- ~ ~ :~ ~~ ~ -90 -180 -120 -60 0 60 120 180 FIGURE 3.9 Contours showing the general circulation model estimate of precipitation (mm) originating from evaporation on the Sudd region (shaded area) of Sudan for 30 days in July. SOURCE: Reprinted, by permission, from Koster et al. (1988). Copy- right O 1988 by Ralph M. Parsons Laboratory, Massachusetts Institute of Technology. General circulation models have an impressive history in atmo- spheric science not only as operational tools in weather forecasting, but also in climate research; only recently, however, have GCM mod- elers and hydrologists discovered that they have interests in common. To the GCM modeler, storage and flow paths of water in the ocean- atmosphere-land and surface-ice system are central to the proper simulation of weather patterns and climate. Coupled land surface water and heat balances have strong influences on the distributions of water vapor, temperature, and flow in the atmosphere. Other significant hydrologic factors in the model include the extent of snow and ice cover, which affects the surface heat budget. The accurate representation (or parameterization) of the processes involved in the hydrologic cycle is essential for successful general circulation modeling. To the hydrologists, GCMs offer a fresh approach to two main principles of hydrologic science—the hydrologic cycle and the water balance. The GCM can serve as the experimental apparatus for studying the spatial and temporal patterns in the atmospheric and surface branches of the hydrologic cycle. Furthermore, with GCMs the large-scale

SOME CRITICAL AND EMERGING AREAS 107 atmospheric water balance and surface hydrology may be analyzed for their influences on regional climates; the role of land surface- atmosphere feedbacks in maintaining climate and controlling its sensitivity may also be examined. One of the challenging research tasks facing climate modelers is the elucidation of the processes that take place at the surface of major continents and influence the distributions of climate and hydrologic conditions. For example, one can ask what role land surface-atmosphere interaction plays in maintaining the arid and semiarid regions of the world. We know that the radiation energy reaching the continental surface is ventilated through evaporation and the upward flux of sensible heat into the atmosphere. When a continental surface is dry, the ventilation through sensible heat becomes larger than that of evaporation, thereby raising temperature and decreasing the relative humidity, cloudiness, and precipitation in the lower troposphere. The reduction in cloudiness, in turn, increases the radiation energy reaching the continental surface, and thus increases potential evaporation. Both the reduction of precipitation and, to a lesser extent, the increase of potential evaporation further deplete soil moisture from the dry con- tinental surface. This description indicates that the land surface- atmosphere interaction has a positive feedback effect on the aridity of a continent. The role of the land surface-atmosphere interaction is critical in maintaining climate and controlling its temporal variation. Thus a realistic modeling of the land surface process is essential for the successful simulation of climate by a GCM and for its use in regional hydrologic studies. However, it is extremely difficult to determine realistic rates of evaporation and runoff over each grid box of a GCM, given that the dimensions can vary from a few kilometers to several hundred kilometers and that each grid box contains highly heterogeneous surfaces. For example, the evaporation rate is influenced by vegetation in each grid box through physiological processes involving stomata and a root system. Such an effect is not explicitly incorporated into most GCMs. Devising reliable parameterizations of evaporation and runoff from a macroscale grid box with a heterogeneous surface is one of the most challenging tasks for reliable simulation of climate and the hydrologic cycle. Given that GCM grids are typically 104 to 105 km2, the significant effects of spatial heterogeneities on surface hydrology need to be represented. Similarly, procedures need to be developed to link regional heat and water balance to those at sparse GCM grid points. To develop and validate a more realistic land surface model for a GCM, a series of field experiments was planned by the WCRP. Called

108 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~ :::: ~ ~ :~ 1~ ~~ ~:~:A:I:MOS~PH~ERIC:~ GE:NERAL:~::CIRC~U~LATION~MODE;ILS~ ::~I ~:~ : ~ ~ :~:~ ~~:~ ~~:~Ear~ly~:~:~in:; then twentieth century,: ~L.~:~:R~i~6hardso~n ~~p~ro-ppsed~th~,~s~ince~ :~:::~the~ ~atmos~pfie~re ~ isle ~:~a~m~wi ng ~ fl uid~ ~:~: its motions ;~cou lo pred~itl:ed Phi nag. ~:~e~:basic~:~equati~ons:~of :hy:d rod~ynam~ic~s.~ ~ Un:fo~nately j~th~e~:sh~er~s~ize~:~ i:: ::::~th~e~ p~rob~le~m~:m~ade: ~th~e~:~::num~be~r ~:of~::~n~ecessa~:ry~c~altu~J:~ation~s:~:~to~o:~il~a:Fge:~to:~be :: : ::: ::~ : :::: :: :: :: :: :: :: : ~ ::~ ~ ::::: ::~:~ ~~ :: :~: :~ : ~ an: amp:: :~: i: ~ca~r~ri~ed~0ut~:~ desk :~:c~a~Icu~I~ators~ At i: the:~ti~me.~:~:~After ~:W0rId: :~:W:a~r~ II~,:~:t~hk ~~:~:~ ~:~dev~lop~men~t ::~of~ele£tr~onic~comp:ute~rs~ v~in~c~reased ~~the~calcO~l:a—~~; :~ :~ bower ~~th~at~:~::c:ou lode directed: to ~ ~solvt~:n~g ~~me~eq~u:at:~ons:~nt~atmos:pher:~Ec~ :: . ~ . ~ ~ , ~ ~ ~ ~ ~ ~ ~ , , ~ ~ motion. ~~:tl~m~:~ Aztec ~ joys: t bier success fin ~~n~u~m~er~l~c~a~ ;::~weat her torec~astl~ng,~ ~ ~ :.: ~~: ~ ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~:~ Ail. Phil I ins Added: the Effect of thermal :~fomi~n:g~ ~to:~th~e~ h~rody~nam~al:~ 1~ : a:::: ~::~ ~ :~:: I: a: :~ ~:~ : :: ~~:::~: ~ ~::::: ~ :::::: a::: ::::~: :~:~ : : ~ ~:::~: :~ ~~ ::::::: :::::: ::~:::::~ : ::: ~:::::: :~:::~: :::: :~: ::::: :~::::::: :::~ :: a: ~ ~ ~ ~ ~ ~ T: ~ :~ eq~u:ation~s~ano~ :~p~onee~rec ~ culls l ng~ Sac ~ ~ genera ~: :~c~l~rc~u~: ~at~o~n~moc ~e: so ~~M~S~J~::~:~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ : ~ ~~ ~ : ~ ~ : ~ ~~ ~: ~ :~: ~::~::~r~;th~e ~stuc~6f the:~atmosphe~ric~:~c:ircu~l:~ion.~:~l~n:~thellate~1 960s~the~hyd:ro-~ ~: ~::~ ~lo~ic:~:~ln~roc~es~se~s ~l~were i;n~corDoratdd~ ~ in~GCMs*~resu:~lt~i~n~in~sruc~£~ess~1~:~ ~ ~ simu lat~i~on~of ~e~ ~b:asi:c~be~havior ~of~:~the:~ ~hYd~rol~o~ic~ ~:cYcle~ and~;tts ~oi~:~l~ ~ I J~ ~ .~ ~ ~ ~ ~ :~ ~::£ ~I:m~ate. :~:~:~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~ ~ ~ ~ :~ A~g~e~nera I ci~rc~u~l:~ation~ mod:el: ::pred~tcts~th~e~ cha~nges~of~the ~a:t~mos~pher::tc:~:~ ~ ~ :~ ~ : , ~ ~ ~. ~ . :~ ~ ~ ~ ~ , ~ ~ ~ ~ ~ . ~ ~ ~ , ~ ~:, ~ ~ ~ ~~ ~ :: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ T : O ~ W ~ ~ ~ ~ T ~ ~ e ~ ~ ~ : : ~ ~ ~ C ~ : ~ ~ t e m ~ ~ e r a : t ~ u r e ~ : : : ~ : ~ a s : e c ~ o ~ n ~ ~ ~ ~ ~ ~ t ~ e ~ : ~ ~ ~ e q ~ u ~ ~ ~ ~ o n ~ s ~ ~ ~ ~ ~ : o ~ ~ : ~ ~ ~ ~ ~ y ~ ~ ~ r o c ~ y n : ~ a ~ ~ m ~ ~ ~ c ~ s ~ ~ ~ ~ ~ ~ ~ I ~:a~ ::thermody~na~mics,~ re~s~pectigel y~. ~:~ :~ Based ~lon~ ~t~he~ :~equ:at~:i~on ~:of~radiati~v:e~ ~transfe~r~,~it~lcds~i:0to~considerdtion~t:hie ~h~t~inn~iand::~coolinn~ctaused~:~:: ~ghlar~i~add~ ~l:er:restri~al~r~hon~.~ ~Th~e~ ~t~hie:e-dim~e~n~sion~ill~d:i$r tb~tho~n~:of~ I ~::~:::~ ~ ~ mo~sp~he~ric~w~ate~r~vapo:r: ~is~ ~p~r~ic~ted~ ~by :~consi:~der~i~ng~the~eft~ts~of ~advec~-:~ : ::: :: :~:: ::~ :: : :::::: :: ~:: :~:~::::: : ~:~: ~ ~::: ::: : :: :~: : ::::::: ~:::~:~ : :::::: : ~ :::::~ :~ :::~:: :: :::::::~::~ ::~ :::::~:::::::::~:~ :: :~:: ~ :~:~::: ::~ : ::~ ~ ~ ~ tio~n~ ~: :co~nc ~ens~ation~, ~a~nc ~ ~;moist ~ ~c~onvec~t.ion .~: ~ ~ ~ ~T ~e~tem~pora~ ~:~v~a~riatio~n~ ~ot:~ :~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~: ~ ~: ~:~ :: ~ :. :: : :::: .:: :::: ~ : ~ ~ I ~ ~ ~ ~ ~ ~ ~ ~ . : ~ ~:: ~ ~ ~: ::~: ~ ~: ~:~~ :~:: ~ ~: ~ ~. ~ ~ ::::SO~I~ ~mo~l~stUre ~ ~ :usua~ : y~ ~ i~s~ ~ Cete~:i~neO ~:~tF~ro~m~:~ ~a~: ~sl~mp~l:~:w~e~r~::t~u~get~ :~wl~tn~ :: ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~:~:~contribu~3n~s:~:from~rainfall'::evaporatio:n,~s~now~mell,~aTn~d~rCtnoW~:~The~m- ~o~ ~ :: ~: ~ ::::: ~ ::: ~ ~ : :: ?:: ~ :~ ~ :~ ~ ~: ~ T: :::: ::::: ~: : :~:~: : :~: ~:~::~pera~ture~ the:~lconti~nen~t~su~c~e~is:~d~min~ fron~ ~at~b:ila~nc:~e~l-~i ~ ~ ~:~ ~ ~: ~ ~: ~:~ ~ ~ ~: ~:~ ~ ~ ~:~:. ~ ~ ~:~ ~ ~ ~ ~.~ ~:~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~: ~ ~ ~ :~ ~ ~:~ ~ ~ ~cu:l~ati~on~s~.~ :~::~F~:gu:~re~:~3 .1~0~ ~dem~onst:rates~ the~GCM~capab~l ~W ~to~rep~du~ce~ :~ ~:~:~::~:~: ~ :::::~:~:~:~:::~:~ ~:~:~:~: ~:~:~:~:~:~ ?~::: :~:~ ~: ~:~::~ ::::~:~:: ~:~ ~:: ~:~ ~ :~:~:: :: ~ ::::~:~ ~ ~::~::~ :~ ~:~:~ ~ :~ ~ ~the~observed~va:l~ues~ of ~:temPerature:~:~prec~l~p~t~t'~onr :~and ~evapor~a~t~wer-:~ ~:~ ~an:ed~ - e~r l~titude~cTi~rcles.~:~U~tu~nattilV~ve~r~.~at:~ tt~i~D~nt ~ :ot ~(iC::M~ ~deve~l~c:p~menU~reproduction:~bt the:~o~e:r~d~regior~:~ Variabii Ity ~:~:::~ of these~ed~qua~rit:~Ri:es~i~s~at~ b~st:lonly:~c~ail~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~:~il~:lu~*rai:edlk~: ~:run~off~ :by ~ F;gure~3 .1~t . ~ ~m i~s~ficien~cy~i~m~ust~ be~ :: :~ :~: :: :~: ::~: :: :~ ~:~re:mov~d~be4~3~re~th~eY~ca~n~ ~:become~o':a~cti~ca~l~l~s:~for~ ;~nation~al ~a~nd~:~:~ I :~ g~lon~a~l~oe~cIsion~:~m~aK~ng.~ ~ :: ~ ~:: ~ ~ ~ ~:: ~ : ~ ~ ~:: ~::: ~ ~:: :~: :~:~::~: ~ ~:~B¢~th~use ~ G(:PAs'~:~s~om~e~c~:~ l~s:~en~:~ie~v~n~i+~iH;~£~ :~::~: ~v.~a~ri~ou~s:~rs~ ~th~at~ ~:pl~a~y~a~:~ m~aJo~r~ro~le~n~ma~:nta~i:n~:g~ :~cl~r~te~.~:~e~s~:th~:Y~:~ ::~: :~:: : ::::::: ::~:~: ::~:::: :::: ::::~: ::::~:: ~:::: ~: : ::: :~:::::~ ::::: :: :: :~ ::~: :::::~: : :::: :::~::::::::~:: :~:: :::~:;:: :::::: :::~:::::::: :::::~: :::::: :: ~:::: ::::~::::::::::::~::~::::: ::::::~::::::~::: ::::~ ~ ::::::::~::: ~:~ :~::~factor~:~ is~m~aJor ~ m~ou~ntain:~l~r~anges,~sut}l~ ~as~ ~::the~:~Roc~lty~:~Mou~ntain~s~ - d~ tte ~Ti:betan~PJ6teau.~T~y l~ati~not~o~nly~ as ~stacles: f&~:a~rr flow ~bLi~as : ~ ~ ~ ; :~. ~ ~ :: ~ ~ . ~ ~ ~ : ~ ~ ~ i ~ ~ ~ ~ ~ ~ .~ ~ ~ ~ . . ~.~ ~ ~ ~: ~: ~e~le~vatec~ ~n~e~at ~::~sou~rces~ ~:til~et~eD~y~e=~rtI~ng~p~roto~u~t~t1~e~n:ce:s~:on ~:~:ge~ne~ra~ ~:~ci:rc~u lati~on a~n~dl~the: ~h~y~d rol:ogicl::~cycl~e~ i~n~:t~he l~atmc~sph~e~re.~:~ I ~By~:: :~com~pari ng~:~ ~:~s i rn~u ati - :s wit~hi~ I a:nd~ wi~t ho ut~ese~:ma i ~o:r~n~ntatri ~ran:Res, th - ~es~ ~ ~: ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : ~:~ t:h~e~T:~bet~ Plateau~and~e ~ Ro—~ Mou~ntain~::~r~ges~in ~-~shapi~ng~t ~ ~ :::: : :: ~: ~ ~:~: ::~ :~strea~m,~devel~pi~n~g~t~ra~iny~:~l~lan~s:ulmmer~ ~n~so~on, ~and~: m~ain~ta~im:¢g :~ l~the:: extreTme:~ld~rY~:~cond~i~tion~s~over::~ithel:~:~3~Ddse~rt~h~ave~lbeen~investi--~l ~: ~gated~.~ ~ ~::~ ~ :: ~ ~ :: : ~ ::: ~General:~ci~rculation~:m:od:els~al~so ~have~:::~been~:~:Used~to~e:~p~l~ore~:the~:rol~e~:~:~l~ : :~:: ~ ::::~::

SOME CRITICAL AND EMERGING AREAS :~: ::~: ::: A:: :~ :: ::: :: I: i::: :~: ~~ : . , ~ ~ . . . . , :~ cedes ink flint :~uen~c::l~n~g~ its gel ~~ge~rap ,:~'ca: ~~ c Astir Outruns at ~~: 1yc :ro ogy :anc ~cl:~i~ma~te~at ~~the~::co~nti~n:~ta:l~ ~ surface. ~ i: :~:S:i~nce:: oceans ~:can~be thought of Was ::~th:e flu lti~mate~:sources~ of ~~water;~thei r~im~po:rtan~ce:~ i n~m~aintai:~n~ing~the h~yd:ro-~ Ail: - lc~le~an~ ::~l~an:~:~ su:rtac~e~ n~o~l:og~y~ cannot: ne :ov~ere~mphasized:. lint ~ :: ~~: , ~ I. i, ~~ ~ ~ ~ ~: :: ~ ~ ~~ ~~ ~ ~~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ,. ~ ~ ~ : ace Toot - ~~:~ Heat ::~tra~nsport ~~ By: ocean :curre:n~t:s affects Anti Be::: sea surface: i: 109 ~pe~rature:~i:~the:mby~::~infl~uencin~g~:~th~e ::::evaporative s:u:p~ply~ ~ off water: ~ into :~ the atmosphere.~For~i~nstance~,~:~w ~:~know:.th~at:the th~erm:al~::in~ertia.of decants :: I:: :~respans~ble for:~the:seasonal reversa~l:~tn~ the ~land-sea~contrast~ of Surface: ~ ~ ~~ ~ ~~: ~~ ~~ ~~ ~ ~~ ~ ~ ~ it. ~ ~~ i. ~ ~ ~ A. ~ . ~ ~~ ~~ . ~~ ~ ~~ ~ ~: ~ ~ ~ ~~mper~re'~thereby:~ inducing :~the~:mpaJor~monsoons::.~: it:: ~ ~~: ~~ :: ~~ ~~ i: : ~ ~ ~ ~~ ~ ~ ~ ~~ ~ ~ ~~ ~ . T. ~ ~~ . :~ ~~ .~ ~ ~~: ~ ~ . ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ : :: :: : : ::: :~1~ ~~::~1~:~Be=:us~e~ofl~ t:heir~lla~rge~ Thermal: :~lnerI:ia~: ~ oceans also play :an :~i~mportant: ~~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ::~ro eon:: o~:term ~c~ll~mate~c range.: -::or ex~arro ~e, t Recrate ot~tuture c Mate:: ~~::~;cha~ge~c~au~: d~:~:~by~greenhou~se~ gases~wi~ll:~:~be:: :dete:rmine:tl ~~ i n: part ~:~ by:: the ~~penwati~n~tiebt~:~er~e~i:nto~the~::~deeper~:~layers of::::oc~ean~s.:~ :::~For th~e~:~:~study~: ::: ~ ~~ :~ :~ ~::~ Ail: :::: ~:~ :~: ~ i: ~ ::: :: :: it: At: :~: :::: :: ::~: :~: :: :~ :: ~::~ ~~~ :: :~: ~~ ~ i:: ::~: i::: :: ::: :::: i:: ~::~ i: : ::: A:: : ~ ~:~n~m~am~:~:chan9~e.~ It: Id ~:esse~i:~::~to~:~use~ i: ail climate: ~ ~~m:odel: in: ~ i:: ~ ~~whith~a~n~dtmospheri£~:~GC~M Is coupled ~wi:th~a:n :~ :ocean~ :ci:rcu latio:n::~ model:.:: the Hydrologic-Atmospheric Pilot Experiments (HAPEX), this series measured basic components of water and heat budgets and other relevant quantities over a land area of approximately (50 km)2 to (100 km)2. HAPEX is described in detail in Chapter 4. For the validation of a climate model, it is also necessary to deter- mine more accurately the thermal and water balance of the global atmosphere and the exchange of energy and moisture between the global atmosphere and the land, ocean, and ice-covered surface based on the comprehensive observations from satellite and ground sta- tions. One of the main objectives of GEWEX is to accomplish this by a comprehensive strategy combining both observational and modeling approaches (see Chapter 4~. What are the states and the space-time variabilities of the global water reservoirs and their associated water fluxes? The total amount of water in the earth-atmosphere system must remain relatively constant; therefore, an imbalance in the three exchange processes of precipitation, runoff, and evaporation must be offset by changes in the storage reservoirs of the ocean, land, cryosphere, and atmosphere. There is constant exchange between the reservoirs via these processes, but the time scale of the exchanges varies greatly among the many components of the system. An understanding of

110 6 8 O 4 eC o LL 2 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 8 · e · · ~ · O. 04 ~ ;S~; o 90 60 30 0 -30 -60 -90 LATITUDE (degrees) o°:~o°~. · 1,/: : b - r o _ 04 :d Go? r - ~ Or !~ 1 1 1 90 60 30 `_ ~ . O ~ or OoO \__ \.. \\~: \\N 1 1 1 \~_ ~ . 0 -30 LATITUDE (degrees) -90

SOME CRITICAL AND EMERGING AREAS 24 12 - o - LL Ad ~6 -12 LL o -24 -36 -44 60 30 0 -30 LATITUDE (degrees) 111 -sumac) ~ °~ Q - - o to Ado o.) on on/ ,~/ J 90 Mode1 ...... 4x~ 8 x 10 12x 15 ° Observabons 1 1 1 1 1 1 1 1 1 1 1 1 0 : o o o o 1 1 1 -60 -90 FIGURE 3.10 Results from the general circulation model of NASA's Goddard Institute for Space Studies. The model, with nine vertical layers and various horizontal resolu- tions, has been integrated for 5 years, and the seasonal zonal values for temperature, precipitation, and evaporation are averaged. SOURCE: Reprinted, by permission, from Hansen et al. (1983). Copyright @) 1983 by the American Meteorological Society. the global water balance and its variability requires accurate assess- ment of both reservoirs and fluxes. The emergence of an accurate global picture of the water balance has been hindered by several factors: 1. Observations are spotty in their spatial coverage, being concen- trated where the human and financial resources have been available. Underdeveloped areas such as arctic and alpine regions, deserts, the tropics, and, of course, the oceans, have been neglected. Attention must be given to filling these gaps by remote sensing and unattended devices. 2. Observations are of uneven quality owing to the differing local and national standards. The World Climate Data Program (WCDP) is addressing this issue. 3. Observations are limited in character primarily to the quantities of traditional engineering interest, namely, precipitation, streamflow

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4 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES : I: ::: :FRO:M::~D:ES~E~RT TO:iRAlN:~FO~R~F~r~:~ :: : :~ ~ :: ~ ~ ~~ ~~:~ Aver ~~rece~nt~geol~ogic-~:~:t~l~me~l~ghl~y visible changes: i n Other global water :: I ::: : : ~ I:: ~ ~ : :: I: :: ~ 1: : ,:: ::: :' : : : : : : : ~ :: ~~ Ail: gal ~ance~na~ve occurrence ae~::rl~se~:~:anc ta Tots Sea :~ Never ~ it lies a Vance And I i: ~~retreat~:~of~cont:i~nental~; :~ :ice~ s~h~eets,i~and~:~:th~e~ formation land ~Ide:sicc-~ation~ 0 f I major bakes and ~~ waterways. ~~:At~th~e::~ ::peak~:~:of:~:~:the last;:~:: :Ice~:~ :Age,:~ some ~~ ::: ~ ~ : :::: :~ ~ I:: :: ~1~8~000 y:e~ars:~ago,::~when::a~s far::south~:a:s ~Ke~ntuc~ky~:s:om~e:~:1 500 m of i:ce~:: ~ . ~ ~ . ~ ~ ~ ~ ~ ~~:~c~o~ve~rec~:~:t: ~e~:~ Zinc ~~n:creas~ec Arm ~i~ty~gene:ra~ ~ ~y~;~preva~i:led:~in~l:ower:::lat:i-~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ ~ :: : :: :J: ~ ~ ~ ~ _ ~ ~ ~ ~ ~ ~ ~ ~~ ~~ Etudes. ~~ ~~ ~ ma Sara: Desserts ac vanc~ec ~ near By: ~000 km Southward toward :: ~ ~ ~ ~: ~ ~ ~ ~ i ~ , , ~ . , , ~: t 1~e~pre~ser~t-~:a~y~r~al~ n torests~,~v~rt:ua~ ~ y~:~: ':uryi~n~g~t 1e~lriver:~:s~ystems~ of~:West: i: ~~ Mica:. ~~ The :~;ra~i nit Forests of ~Afr~f~ca, South America, and~:~p~roba~bl~y Asia Al 1~ , ~ ~ ~ ~ ~ ~ if: ~ o~ut:~l:~sao~oeare~d~,: retrain pro :~a~few: anomalously: l~mid~ih~i~:hln~n~il~::~r~:;~f~n~c~: ~ :::: :: ::: :: :: I:: :~l~ ~~ht~:he~ same t~i:~me~:~v~ast~l~es~coverLd ~~m:uch~of~t~western~ U~ni:ted~States~: ~ : ~ ~ r ~ ~ ~ ~ ~ ~ ~ ~ ~ i, ~ :. ~ . ^ . ~ ,* . ~ I. ~ ~ ~~ ~~ ~~tne: ~~ rem n~a~n~ts Lot low n iliac half: Are hi:: Seen: ~ In: :tne ~~ Cart Ill ants ~ of:: ~~ t- a~l~i~tor:n~ ~ At i: N puff ~ ~ -aim I: ~:~:~a~nd~Uta~h~:~M~illion~s~of~ton:s~:~glacierice~on~:::~:la~nd::tied~u~p:~a~;1~00-m~laye~r~:~ ~ ~: ~ ~ , :: , :, , , ~ ~ ~ , ~ ~ ~ ~ : ~~ OTIS: ~i~ne~wo~r~l~ ~~ocea~ns,~:~e~xp~osing:~;~n~uge~:~ areas Tot The continental shelves ~ : I: ~ ~:Within ~ a~fe~w~thousand ~~y~ears,~:th~e:~g~lac~iers~::melted~,: sea~:~lev~l :~:ro~se,~:::andl~ ~~ it::: s:ava~nnas~ ~a:no~l~a~es::~ re~p~f:a~c~ed ~~most:~of~l~the~l~l:ce~: Age~:~dese~rts.~ ~ ~AboUt:~5~:~000~:~ ~:~;~: : ~years~:~a~go ~~th~e~:~:~e~s~etts ~~ in~clu~tl:i~n~gl the~:~:S§h~ara l~h:ad~ n~e~arly~:~va~nis:h~d~:~: ::ln:~ I:::: .~ .^ .~ ~ ~ ~ . ~ ~ ~ . ~.~ ~ . ~ , ~ :~ ~ ~ :, ~ ~ ~ , ~ ~~ , ~ , ~ ~: . , ~ ~ ~ ~ ~~ ~~AT~rica~a~no~ Au~stra~l~la~ ~~a~:e:s ~~ as~:~l~a~rge ~ as ~~:L:a~ke ~~::~had~ e~x~pa~n~ded~to~:~ :many~: ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~IN~m~es~n~el~r~:~:p~resent:~s~ze~,~so:m~e~Klt~t~V~a~l~leY~l~ake:s~:we~re~u~::~to~::~1 5~0~m~dee:D~er ~ i: ~~ ~~l~na~n~lneNf~ar :~:now:~.~ ~~N~eol~l:tn:~c~::~t~s~nnooK:s~ touno~:~:'n:~th:e~:~centra~l ~~:ah~a~ra~::bear i: ~ ~ ~~ ~ :: ~ ~ ~: ~ ~ ~~ ~ ~ ~ ~ ~: ~ : ~ ~ ~ ~~w~n~es:s~to~th~e;~eMste~nce~:of~:~S~aran:~la~kes~suggested:~by~geolog~ic~al~e~po~s-~: ~~:~:~ :::~:~In~i~1he:~past~t~:~:e~v~i~e~n~c~e~-~su~ch~l~o~n~£-ter~m~c~;a~n~£es ~deri~ved~:~r~i~n~c~i~D:a~ll~v ~:~ ~ ~~trom~gi~:~gi~c~ st~i~e~s~a~hd~l~Q~@c~as~ional Iy~p~alynolog~ical~;nd~Warc~haeo;l62aical :~ ~~:~ ~~::~n~to~r~lonp.:~:::~ ~Aauva~nce~d ~~:sat~l~lte~tt~ch~n~olog:ies~ Inow~are~:~provid:i n:g ~~i~n~:~n~ova-~ ~~ ~~:~ ~ ~ ~ ~ :: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~t~i~ve~:::~ay5~to ~~:st~u:~dy~p:ast~condi~ho:ns~on~a~lla~r~ge~:~:~scale.~ ~~On:~el~example :~li~5 Al: : if: ~~ s~ur~pt~i si~n~g~ld~i~sc~overy~ Ma: hom:l~ the:~: ~~m~c:rowave ~~rada:r~s:Y~ste~m~:~::~a~3a~rd~:~:the ~1 ~~tit~rst~sh:~0tb~:~fli~g~ht.~l~n~hy~pe~rarid~e~nv~i~ro~n~meh:t~s~m:i~row~aYe~s~:~,~n~et~rate~ ~~ ~ ~~ ~ ~ ~ ~ , :: ~ ~ ~~ ~ ~ , ~~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ :~ ~ ~ ~ ~~ ~~seve~rat~mete~rs~n iow~h~e~s~urfa~ce~:~re~bb:~n~g-~r~efle - Id ~~:s~pa~ce~wafd~: the :~: ~ ~ I. ~ ~ ~ ~ ~ ~ ~ ~~ . ~ ~ ~ ~~ ~ :: ~ ~ ~ ~ ~ ~ ~ ~ : ~~:~ ~s~n:uttl~e~ra~a r snowen ~ ~~sun:s~nace~:~pa:tterns~:i n~l~th~e~:~wes~ern :de:s~e~ft 0f~:~Egypt~ :: :: . ~ :~ . ~ . . ~ ~~t:n~at~:~ovea~::~:~tQ~De:~a~Io~n~:Ou~r~l~en~:waterway:,~a:~:o:ng~t~h~e~:a~n:~ks~of~:~:wh:i~ch~a~ :~ : ~—ergot:; a~r~chaec l~g:~ic~a~l~s:i:tes~ were ~~ Ones rehem. ~ ~~The~:~c~ha~n Deli were: :~11 I: :: ~~ekt~A~h:l~h~: in ~ ~ lop rt:~i~rv:: ~ t:i m~:~c~ ~ m~l ~l~:in~n:c~ ~ Arc ~:~^ age: Ah:::: f l:~\A/ ~ tAJ ~ Ceil n=~r:i:~::i _:: ~~ ~~ca~l~l:~y~ :ree~stab:l::i sheds u ri~ng~:~t:lie ~ ::lce~ ~ Angel and the Region l:~reocc:u~p:ied ::by: ~ ~ ~ ~ :, , ~ ~ ~~ ~ ~ ~~earl~y~n~u~m~an:s~.~:~:~Sl3e=~tion~:~that~:th~e~se::~now~ry~1~th~ann~els~oncel:~in~kedl:~th~e~i:~: : ~ ~ 1 ' ~ ~ : ~ : ~ ~ ~ -:~: ~ ~ · ~ : ~ ~~ : :~ ~ ~ :& ~ ~ :: : :::# ~ : : :~:: ~ ~ ~~ : : :~ r~ger~:~an~a all :~'e~ ~~ avers As was ~ tne~t~rac~' groin :~' fin ~~ Alr~ca:n~ 1~ege~0s ~~ was :re~i:n-: ~ ~ :~ :::: ~ : :: If:: ~ :::: I:: ~ I:: ::: ::::: ::: ~ ~ :: ::::: : : :::: ::: :: :::::: :::: :: :: ::: :: : :~ : :~ :: :: :: :: :~ :~': ~ :: :: ~ : :: ~ : ~~ ~~T:orcea~w:~t~n:~tne~:~:scovery~ot~a~to:ss:~l~:t:~s~h~s~ke~e~°on~ in~th~e~:::::dries:t core:of they: ~~ I:~i~ ~ [desert. i: Pith Nisi ~h,~llth~e~i:''el:~ ~Ca:oittin . "I ~l~nowi~ i~n~ha~bits~l~thel~Nliae~:~an:d~l~ KEN i l e. about ~ i::: ~~:~:~few:~oth~e:r,:l~rive~rs:/~:it:s~l~lp~resen~ce~i:r1:th~e~hara~stro:ngly~suggests~ap~ast~:Iink~:~i~ ~~:~De~een~:tn~ese~two~:r~v:e~r~sY~ste~:ms~.~:~ ~~:~:~:~ ~~:~:~:~:~ ::: :: : ~~A:ltl1~O~U~£h~:~:SUC~h~: kF#~ow~l:e~dae~:of The Cast he'd: to ~u~nli~ersta::n~`i: the ret' or: ~ , , ~ ~ . ~ ~ . ~ ~ ~ . , ~ ~ ~ :: 0r::~:nu~ma~n n~st:~:ry,~:~maY~al~so~orove~:~:eY~:~to::~:~so:Ivin~:::manv c~u~rre:n:t~orob-: I~ ~ ~ ~ ~ ~ . ~ :, ~ ~ ~ ~ . ~ ~ ~ , ~ ~ ~ :~ ~~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~~ ~~:~ ~~e:m~s.~:~ ::~A~:~:~:~ am ~~al~o~n~:~ot~::o~u~r~ aground :~:~w~a~te~r~ :~ resource ::: ~wh ich ~ ~ today ~ Is ~~ :~ ~ ~ ~ ~~ ~ ~ ~~ ~~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~:~bei~n~g~depiete:d:~a~nd~:con~t:a~minate~d~,~:is~ia~:remnant:~of~t~h:~ese~l~past:~hu::mid~:~ :: :: :: : :: :: :::: :: :~::

SOME CRITICAL AND EMERGING AREAS : :: A: : : : : : ~ : : : : :~ : : : ~ :: :: ~ ::: : ~ ::: :::: I: : : :: :: : :: ~ ~ periods.: :: Facing the: :pote:nti~al~for~global acclimate change' we must know ::: t~he:~:~l i kel~y~:~range~:of:~ex~pected~cond~itions~: ~:~:~:~ ra~i~6fal:ll, fl~ow~l~:of~ rivers:, ~~ size::~of i:: :~:~::la::kes,:~la:nd :~:sea :~Jevel changes. ~ ~:lt~::a~l:so is:~: i m~port:ant~ :to~:k:now::~w~h~et: Her,: on ~a: ~ : : :o Cat ~:~::sc~a~ e :t le~: :pa:rtiti:on~l ng: Otis water a:mon:g:~:t He ::varlous: reservoirs; Cant : ~~:~ ~ r ~: ~ ~ ~ ~ ~ ~. ~ ~ :~ ~ ~ ~ T: ~ ~ ~ ~ ~ ~ ~~ . ~~ ::: its Ares crates at t~ranste r Between :t 1em~:::(~l:.e.,~t He rat :uxes:)~ we ~:::c~ ~an~ge~:~s:lgn~rl- ~ it: ;: Scantly.::: ~ l~n~:~ot~her ~ Words, ~ ~~;:~s ~ The t otal~: gl;obal~::~pr~ec<~i~pitation ~:~:co:ns~ta:nt :I:~a:nd ~ ~1~: ~:~:lmerely~geog~:r~a~ph~ica~l~ly:red~i~:stributed~ ove~r:time?:~Or~:~d~oes th~e:~efficiency of ~ ~ ~ ~ :: ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ :~ ~ ~ :~ ~ ~ ~ :~ ~ :: ~ ~ ~ ~ ~ ~ ~~ :~ :~ ~ ~ ~ ~ ~~ ~ :~ Aim, ~ :~ ~ ~~ ~ The h~yd~rologic~c~y~cle:,~i.:e:.~, th~e~globa~l:~ra~tes: of precipitation an evaPo:ra-~ ~ ~ :~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ::::: ~ti:on:~ change through time? ~~::ls :the: a~mo:un:t~of::a:tmos:ph:eric;~:::~w~ate:r vapor , . . ,. ~ ~ ~ , :1~ and clouds constant: or :::v~aria : e' ~ ~~:~tu~:les Allot :~: ong-term: c a~a:nge~s~:::ot~ ~~ t Ale :~g~l~obal::~:wate:r:~: ba:lance:~help~to:~ provide ~answe~rs~ito ~~su~:~q~ue~stio:n~s:~:wh:ich : ~ ::: : ~ :: :: :: ~ ~ : :: ::: ::: ~ : : :: :: i: ~ ~~ ~~: arts Dosed:~:~b~viitlie~ ooss~ibi I irises :of h~u~ma~n-ind~uced~:~ Icl i:mate c~h~a:neel~:t~h~rou~gh 115 ~ : : : :~ :~:::~ :: :: : ::: :::: : Green house ~~ warm i:ng flora other: factors. and surface water reservoirs. Observations of the atmosphere (par- ticularly the troposphere), soil moisture, ground water, and evaporative fluxes have been relatively neglected. Advances in technology are badly needed in these cases. 4. Observations are largely unavailable in the form of coordinated, homogeneous, global data sets. Again, the WCDP is attacking this problem. .. . . . .. . In addition, most measurements of parameters such as rainfall, soil moisture, and evapotranspiration are point measurements from which we attempt to extrapolate large-scale fields. Unfortunately, these parameters are highly variable in space over small distances, and assessing them on a regional or global scale has proven difficult. A major component of climatic change involves the interactive re- lationship between global climate and regional-scale hydrology. On the regional scale we lack knowledge of such basic questions as the geographical source regions of atmospheric moisture, the net moisture transport into or out of the region, and whether or not local evaporation is a significant source of atmospheric moisture supply. Fortunately, as has been discussed above, computer simulations are now helping to answer these questions (e.g., see Figure 3.9~. Such knowledge is important to validating numerical models before they can be used to evaluate the impacts of such phenomena as deforestation in the Amazon and the extensive droughts in Africa. In summary, scientific challenges pertinent to global water balance include accurate assessment of the atmospheric reservoir and its exchange processes, determination and prediction of long-term changes

16 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES in the global water balance, and assessment of the human impact on the water cycle. To fully understand the global water balance, its regional interactions, and long-term fluctuations, numerous aspects of the atmospheric water cycle require further study. These include (1) the global distribution and seasonal variation of rainfall, evaporation, and runoff, (2) the temporal variations of rainfall regionally and for the earth as a whole, (3) moisture transport pathways and storage in the atmosphere, (4) global space-time variations of cloudiness, (5) the contribution of the land surface, especially tropical forests, to atmospheric moisture supply, and (6) the residence time of moisture in the ground and atmosphere. A scientific frontier in the investigation of the atmospheric reservoirs and fluxes is the development and refinement of appropriate satellite measurement techniques. In particular, techniques for estimating rainfall and evapotranspiration, assessing wind fields and moisture profiles, and monitoring clouds would help to develop a detailed picture of the atmospheric component of the global water cycle and its role in global climate. This is a prerequisite to deriving estimates of long- term changes in the global water balance, an area of ever-increasing concern in view of the prospect of human-induced worldwide changes in climate. Surface-Atmosphere Interaction What are the roles of atmospheric dynamics and surface processes in determining the variabilities in climate? The factors determining the variability of climate can be divided into two types: factors that affect the internal dynamics of the atmosphere, and surface or boundary factors external to the atmospheric system. The boundary forcing is exerted as the fluxes of heat, water vapor, and momentum between the surface and the atmosphere. It is influ- enced by the fluctuations of sea surface temperature, soil moisture, snow and ice surfaces, and vegetation. The atmosphere is relatively transparent to solar radiation. Therefore its primary direct source of energy is the earth's surface, which absorbs solar radiation and transforms it into forms of energy that are readily transferable to the atmosphere. Thus boundary forcing from the surface is an important determinant of climate. In contrast to rapidly fluctuating internal atmospheric conditions,

SOME CRITICAL AND EMERGING AREAS 117 surface characteristics (e.g., sea surface temperature and soil mois- ture) vary much more slowly. This suggests a potential mechanism for predicting atmospheric behavior on long time scales. Thus, with adequate understanding of the surface forcing and accurate charac- terization of it in predictive models, seasonal or multiseasonal fore- casts might be realized. The ocean's influence on the interannual variability of weather and climate has been recognized for some time. The E1 Nino/South- ern Oscillation phenomenon, which at irregular intervals evokes a global pattern of anomalous weather conditions, is a prime example. An opposition or seesaw of sea surface temperatures in the eastern and western Pacific induces major temporal fluctuations of precipitation, soil wetness, and river runoff over Australia, Central and South America, and other parts of the world, and these can persist for a year or more. Ocean-atmosphere interaction is fundamental to this oscillation. A1- though the mechanisms of this interaction lie outside the committee's definition of hydrologic science, the results of the interaction are crucial to the hydrologic cycle at global and regional scales. What is the interactive relationship among rainfall, cloudiness, soil moisture, surface temperature, reflectivity, and vegetation cover? Many processes by which the land and atmosphere interact in- volve the exchange of energy (e.g., sensible heat, latent heat, and radiation), mass (e.g., moisture and aerosols), and momentum. Modification of surface temperature and heat balance by changes of albedo, soil moisture, and vegetation cover most directly influence the energy exchange. The surface also transfers mass to the atmosphere in the form of water vapor and dust. This indirectly redistributes energy in the form of latent heat and alters the patterns of atmo- spheric heating. Changes in albedo, soil moisture, vegetation, and evapotranspiration play key roles. Land surface processes have im- portant effects not only on the availability of moisture, but also on patterns of surface and atmospheric heating, which in turn influence the dynamic behavior of the atmosphere. If altering the land surface can influence the hydrologic cycle, we must know in what locations, under what conditions, and on what time and space scales. Likewise, we must establish which of the potential processes are most important and on which time and space scales. Only then can we determine if feedback between the land

~ :Q 118 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES surface and atmosphere is sufficiently large that drought or wet con- ditions might be self-reinforcing, leading to multiyear persistence of the moisture state. Charney (1975) suggested that land surface plays the decisive role in the droughts that plague the West African Sahel. He noted the increase of surface albedo that results from the deterioration of veg- etation, caused by overgrazing, and theorized that intensive deserti- fication in the Sahel might have been responsible for the reduction of precipitation in the early 1970s. Charney's ideas have been partially reformulated by studies that show the drought to be part of a conUnental- scale rainfall anomaly (Figure 3.12~. It is now believed that the onset _ -40 ~ —- ~ _ MU 1 ~ W: :~: FIGURE 3.12 Map of African rainfall departures (percent below normal) for 1983, superimposed upon a Meteosat satellite image (any areas with rainfall exceeding the long-term mean are shaded). SOURCE: Reprinted, by permission, from Nicholson (1989). Copyright (31989 by the American Geophysical Union.

SOME CRITICAL AND EMERGING AREAS ~ +30 - - z G +10 J 6 o of o 11 lo Cal -30 LL o -10 -20 119 Preceding December-March snow cover June-September monsoon rainfall A ~ \ I\ ~ -3 1 — -2 -1 r \ ~ \ \ \~1 1 , . . . 1 o LL +1 cr CL LL +3 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 YEAR c Cal O of o lo - LL o C: of En FIGURE 3.13 Indian summer monsoon rainfall and Himalayan snow cover of the preceding winter. Reprinted, by permission, from Walsh (1984) as adapted from Dey and Branu Kumar (1983). Copyright (31983 by the American G.eonhv~ical Union. - -or --, of dry or wet conditions is initiated by large-scale atmospheric fac- tors but that land surface processes reinforce them. Also, the emphasis is not now on albedo alone, but also on more comprehensive treatment of surface hydrology, which is presumed to play a role in maintain- ing prolonged drought patterns in areas like the African Sahel or the American Great Plains in the 1930s and in promoting the northward advancement of the Indian monsoon. Most of the evidence for land surface influences on such large- scale climatic anomalies has come from numerical modeling studies. Thus far, the only strong observational support at the regional scale derives from studies of snow cover, an extreme case of land surface change. Namias (1978) argued that the persistence of certain weather patterns over the United States, such as the 1976-1977 winter with severe drought in the West and intense cold and frequent blizzards in the East, can be explained only by considering such factors as the extent of snow cover. Similarly, Eurasian snow cover appears to influence the Asian summer monsoon and other large-scale weather patterns with remarkable consistency (Figure 3.13~.

20 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~;~ ~ ~ ~:~::~GRE~J~HoitSE~IGASE:S~A~N~D ::~£ LOB~AL ~ ~HYOROL~OG~Y :: : :~ ::: : ::: ~:~:~ ~:~:l~ne:~atm~osp~re ::~con~ta~i~n~s: ~va:r~i~ous ~t:race~:~ ~aa~ses~. both::~ n~at~r~l~:~:~n~fl~ ~mA:n- ~: :: >ac~:~that~effecti~vely~trap ~:tlie~o~ptgo~ n~g~ ~ te~r~strl~a 1~ :~ - iation:~ ~a~nd~:~::warm :~:~ ~:~ the~cli:mate.:~Si~nce :the~ ir duistr~i:a~l~Revolution~,~;:~concentra~ti~ons~of some~of ~::~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ , ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ - , e s e ~ ~ ~ s o - c a ~ l ~ e a ~ ~ ~ ~ ~ g r ~ e e i n ~ 1 0 u ~ s e ~ ~ ~ ~ ~ g ~ a s e s ~ ~ ~ : S U ~ £ ~ ~ ~ : a s ~ ~ c a r 3 0 ~ ~ n ~ ~ ~ : ~ ~ c ~ ~ i o x i d ~ e ~ ~ ~ m ~ e t h a ~ n e ~ , ~ ~ ~ : n i - ~ ~ ~ : : : : ~:u~s~ogiJe,~a~nd~l~c~hiovfluorocar~b~ns ~h~ave~ been~incre~sin~:st~ilu; n :~ : ~ne~: ~:~rmospne re.~ ~ '~ ~ ~tne ~esen t~em~iss i on ~:~rates ~: ~co~n ti~n u e~,: :~ ;tl~:~:~com b~; ned~ ;:~:~:~:~ I :: ~:::::~:: ~: :~ ::::~:~: :::~ :::~ : ~::: ::::: ::::: - ::::: ::::: :::~ :~ :~:~ ~ ::~ :~:~ :: : ~ ::~ :~ ~ ~t: ~e:~r~m~a~ ~ totci~tro~m~:~atrn~pheric~carbon~diox~ide:~a~nd ~: other ~ green~hou~s~e:~:~:~ : ~:~gases~:id~entified ~:above~cou~ld:~doubl~e~from~:th~e~ prei~ndu:strial ~:l~evel~s~ometime~ ~ :~ ~:~d~ip~e~ ~fi:r* ~half~ of ~the~n~ekt:~ centu ry.~ ~:::~:lt:~has~ :~bee~n ::~:suggested~:~ th~at:~suc:h::~ : ~i~n~c:rea es~eenhhuse~ga~ses:~ m~a~y~::have ~a:~ ~profound:: im~pa~ct:~: on ~:ou:r~::envi- :~ ~ent.~ ~ us~::~ ma:ior~ ~ ~ha~s ~been ~ devoted~: :::to:~ ~the~ ~ s:tudvl ~Of~ the ::1~:1 i~ ::~ ~i~ ~ ~m~at~l~c~radomc~than:~that~m~av~res~ult~ffo:m ~a ~hiture~:~i~ncrea~se~:of green ho~wse 1~ ~:~ ~^s~e~ar y~::~as~: ~ 1 938,~ ~C~a~l~l~end a r:: ~su ~ested ~ ~that~:~::: th:e~ :~ i~n c:rease ~:::~of ~ ~::atmo-: ~ ::~: ~ ~ , ~ . . . . ~ ~ ~ ~ ~:~sp~ 1er~c~:~ca~ oo~:~c ~l~oxlce~oue:~to:~tossi ~t~u~e ~ :c~om~ awstion:~can ~varm the cl im:ate ~H~is~stuc\~:~and ~several~:~ others~th~at:l ~f~l~lowed~:::~:::a:re~ based :on: ~ ~the~;~ radiat:ive:~ ~:: ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ :~ ~ ~ ~ ~: ~ ~ eat~ ~ ~t ~f ~the :~ earth:~s ~surface~:~and~did: ~not ta:ke~l~i:ntb~:~:~:c~on~s:iderat:io~n~ ot '~e~r~=mpolle:~of~:su~ce~ ~he~at:~bu:4get'~suc~h:::la~s~ ~:the~ tur~bulent: ~:fl:~u~x: ~of ::::::~ ~ ~ ~ 1 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~ 1eat~ano~water~:v~apo~r~t 1~ro~ug~h~th~e:~atmospheri~c::bow~nda~ry~:~:laye~r.:~;~::~:~lt ~w:as::: :~ ~ ~ 1~: :: : :::: :: :. :::: 71 ~ . : . ~ ~ :. ~ : : :: : : : ~ : : ~ ~:r~o~ea~t~ lat~:~t 1e~c;aroo~n~-c IOX~:C e-~lnc :ucec ~wa:rming of::the :system is en~hanced~ :~ ~ ~ : : ~::~ ~:a~n~a~£~co~m~p~apy~l~:ng ~Inc~rease:~l~n~t 1e~water::vapor~content:~:of: t he::~:::air: ~:~ ~w~hiLh~:in~c:re~es~the ir~fra~red:~opac~ity ~ the~:~atmospliere ~thereby red:uc~i~ng~ :~ ~: ou~tg~ir~g~ terrestrial ~radiatti~on.~ ~With ~the:~adva~nce:~::of::~c:ompute~r~tech~nology :: ::~ :::: .:: .::::: ~ :: ::: :.:::: ::: :::: :~ :~: ~::: :: : :.:: ::::~: ~ ::: :: ~:: : :: ::~ : :: ~ :: : : ~ :: : : ::: : :: :~ ~ ~lt~na~s~De~com~e~teasi~ble~:~t0~u~se~th~ree-di~mensional~:~ge~neral ~:circulai:ion:~: models:::~ : :::~__:::~ ::::: :::r: :~:~: : ::::::: :~: :: :. :::: : : :: :. : :~ ::: ~ : :: ~:: : :: ~: : : ~ ~:~ ~ ~ums)~:~of~e~ a t:mosphere ~for~t~h~e:~:stdd~y ~ of ~ :~th is:: p:roblem . ~ :~:Accom~p~a n ie~d 1 ~ :: ::::~ ::~: ~:::~::: ~:~:~: :~::~ ~::~: ::::~:~::~:: ~:::~:~::: ~:::::~::: ::~ ~::: :::~:~:~:: ~ ~: : ~: :: :: :: :: ~:: ~ :: ::: ~ :::: ::~: ::::: :::::: :: : : :::: :: ~ ~ ~oy~E~ne~ ge~neral~: rl~se~ot~:s~rtace ~tem~pe~eature ~ ~the~ glob~al m~ea~n rates~ of both ~ ~ , ~ev~ration~a~preci~p~itat~ion~l~i~nc~re~a~se~i n~the ~mod~el~ ~th~ere~by~ ~i~ntensifyin~g ~ ~ ~ ~ ~ ~ :~ ~ ~: ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~the~hy~rNogic~c~le~ ~as ~a~ ~ho~le.~ ~Th~e~in;crease~of~ ~downward~ terrestri~al ~ ~~ ~ ~ ~ ,~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~raniation ~d~e ~to~t~he~i~ncrease~ ~of carb~n~ ~d~iox~ide~;~and~atmos~ph~eric~ ~water ~ ~ ~ ~ ~ . ~ ~ ~ ~vapor~ ~maKes ~more~energy avai lab~te for eva~poration. I n addi~tion, owi~ng ~to:~tne~ln~c:re~ase ot~:~tne:~satu:~ration va~por:pressure at:~the~:su~rface~r~::::a~:l~arger~ ~:: ~fra~ion~ energLy:~ is ~ removed~ from~ th~e ~ earthrs~su~rface ~through~ ~evapora~- ~i~ ~tion~rath~er th~a~n i~rc,~uo~hi sens~ihl~h~ ~ fil lY ~ ~ :::: :: :: ~ ::: ::: : ::~:~ ~ ::; ::: :: :: :~::::~: :::: :: :: :: : ::: ::: : ~: :~:::: :: :~:: ::: : :: ~n~e~res~u~lts~tro~m~so~me~n~umerical ex~periments~a~lso indicate that the :~tu~ture~lncrease~of gree~n~ho~use~gases m~ay ~affect ~regional as well ~as global . ~ . . ~ ~ ~ ~ r ~yaro'~ogy.~For~exa~m~e, owing~to the penetration of warm, moist~ure- ~ · 1 · ·: , . , , . ~ ~ , ~ rl~cn~a~lr ~nto n~'gner ~at~tune~s prec~p~tat~on ~and riYe r runoff in the subarc- :::::: :: : ::: :: ::- ~:: :~ :~ ~ r ~ tic~ ~river ~basins arel shown to~increasel~ma~rked~ly. Some of these experi- :: : ::: ::: :::: ::: : : : : : : ~ ::::: :: ~:ments~ lalso~ :~predic t that, in ~ middle ~and~ high~ latitudes o f the Northern : :~: :: :~ :~:: :: :: ::: : : :~ : ~Wemi~sphere,~mi~d-co~ntinental soil wetness~is re~du~ced in~slJmmer due to ~tne s~ligil~t ~northward~shib of ~the middle latitude rainbelt and~the ~earlier : ~:: ~ ·: :: . ~ r: . :: :: :: : : : :: ~te~rm~l~nabon~ot~tn~e snow~melt~period~ i~n spring.~: ~On th~e other: ha~nd~, winter~ : · l : ~ :: . r :~ . : .: ~sol~l~wetness~l~s ~ou~no to~l~ncrea~se~in middle and~high latitud~es~. Th~e shift ~of ~the ~rain~belt~ also:~induces~th~e reduction o~f ~winter~ precipitation i :: : :: : :::::: ~ : : ::: :::: ::: :~ :: : : : ::: : : :~ :: : :: :: : :: ~ : ~subtropi~cal~ stepp~e ~regio~ns ~of the~ Northern H~emisphere. in th~e

SOME CRITICAL AND EMERGING AREAS i:: ::: ::: : ::: 121 i:: The future :hyd~rologi:c :c~hanges: mentioned :above~ are::::ve~ ~broad:::::~:scale ~ ~ : ~ ~ ~~ : ~ : i: ::~ph~enome~n~a:~ and: lack: Geographical:: details. ~~ It ~should~alm:~be~ n~ot~dl~that ~ som:e:~of~the: changes~do:~not~:re:p~resent:th:e:c:onse:n~su:s~::ho~ml~all~: numerical ~ ~ : i: :: :~ :: :::::: :::: :~ : :~:: ::: ~ :~ ::::: ::: :~ i::: ::: :::: : ~ : : ~ ~::~ex~p~eri:rnerit`,~:~r~lectino~ ::th~e~ ~~uns~at;:sfactor:Yr state ~I:~tthe::~ aortas of ~~c:~:fre~nt £ is I mate~modeJin~g.~:~:~::J~here~re ~m:aio:r~:~:::effort :is~n~e~eded~to~improve:~variou~s ~: basic componer~ts of cl ideate models:, Such: astir: the:: ~paraimeterizations~: of ::~: ~ ~ ~ i, ~ ~ ~ ~~ ~ ~ ~ · ~ ~~: ~ ~: ~ ~ At, . ~ ~ ~~::mo~l~st~icor~ton::,: ally ~~< ~e::~:foRnostlc~ Hems ~~:~cQnvec ~~a:m ~~;=nconv~uve ~ , ::~ : :: : :: ::: :: :: :~::~: : :::: ~ ~ :: ~ c~loudl~cover.~ ::: J~n::~pa ~~t~icu~l::ar:, More accu~rate~mac~rosc~ale ::Deter~rn~~at~~ns~ ot:~ :: ::::: ::: :: : :: : ~ : :::::: :: : in: ::::: :: ::: ::: ::::: :: :~ ::: ::~: :: : :: :: :::: ::~: : :: : ::: :: :: ::: : ~ ::::: ::: :::: ::: :~: ::::::: ::: :: ::~:: ::: :::: :: ~ i: ::: eva~poration~,~:~snowmili': leaned; ~ ru:noff~:over~::~eac:~h:~: ~fini~te:-d'ffe;rer`~:c~e~:~gr~d~ boll : ::: elf :a:~w~h~und~red~ ~sau~are~ kilometers fare Needed: fo:r~:~:the~ relia~bl:e~oredic~-:::~ ~ I:: ton:: of ~::future~:::c;hanges A::: cli:~mate~ anodes ~~l~a~nd::~s:u~rta~c~e~: condition.: ~~ ~~:~:~ ~ ~ : ~ : ~ : : : ~ ~ ~ : : : :: ~ ? : ::::: :~: : :::: :: ~ :: :: :: ::~ I ~O:ne:~ :::of the:~:i m~po:rtant :~fac~tors:~ thatch :pr~undl~y~::~ai~ctl:l:~th~e~l~llong:-term~:::~ ~: ::~ ~~res~ponse~of:~:climate:~and~:hydiol~ogy~to~ future Increases: ~gree~n~:tiouse~ : ~~gas:es~:is~: the thermal ~~:~i~nerti:a ~ ~of:~:the~: Oceans. ::~To:~st~y~:~this~ top~c:,~:~it:~is~: ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~~: :: i: ~ th:ere~re~ n~ec:essary::~to ::use :: a ~couple~d::::~ocean-atrnosphe~re:~:~model~:~ ions Which: ~a; GCM of ~ the atmosphere is coupled tog: an: :ocean:::~=M.: ~ Such: a study Elf: :: :~ ~::tr~n~sient~:cl;~ma~tic ~ response ~ chase j~u~st~0eg~un .: ~~::~: ~: ~:1~ :: T~he:~pre~dictio~nl~of: cl image change: by the m:od~ell: s:h:ou~ld~i: :be~:~:val:idated~ ~ ~ :: ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ Against :~:the~:~obsemat:ion:~of factual: ~cl:i~m~ate~:~c~h~a~ge~. ::~:Therefore~in~::~:~sim~ :~ ~~:and::~s~ate~l lite~monitbrings~1he~ coup Ad: o-c~ean-atmosp~t~re-lan:d:~ surface ~ ~ :: ~~ ~ ~ ~ ~: ~ ~ ~ ~ ~ :~ ~ ~~: ~: ~ ~ ~ ~ ~ ~~: :: ~~ ~~ ~ :: ~ s:ystem~: a:nd~: thief factors ~c=a::us~i~ng: ~~:g~Iobbl :~cl~i~:ml:ate:::: ch~ang~e~:~are~esse~htiat :~:1br~ i::: :::: A: Hi: :: A: ~ : ~~ : :~ :: :: ethos ~purpose.: ~~ ~ i: ~~ i: i: ~ i: ~ Despite ~~ various ::~n~c~e~rtainties: ident~ifi;ed~::a~b~ov~e: ~~ ~th~e::~resu;lts~l~fro~m~ cu~r- ~ ~ ~ ~ ~ ~ ~ , ~ ~ ~ ~ ~ ~ :: reran: m~odels~su~ggest that: tlie::future~:chan~ges ~~i:rl~cl i:mate ~and~the~hydro~gic ~~ ~ ~cw~:i~llJ~uc~ed::~:~by~gree~n~h~se~:~ga:~s;:~:~may~be~1~arge:~::~enou~gh~to~have~::~fir-~:~: ::::::: : :::: ::: : : : ::: :::: ::: ::: :~:: ::::: ::: :~:: : :~: beaching: implications ~ lint ~~i~agricw:~ltu~re~:~ and ~~ in The ~:~managem~en~t~ Of water 1~: ~~I:~r~esou rces~.~: ~ There; resee Arch i: inner: this ~~ltoo:ici l~s~h~o~:ld ::: received ~~ i~n~creasec ~ :~::~ :::~: :: ~ ~:~:~ ~ en,:ph~asis: so:: that: ou~£~::::a:ddap~tatio:r~to~: the tuture~::~c~h~ange~s~ ~ ot~cl~:i~m~ate~::and~:::~ ~:~ : land: surface: conditions is~:facil:itated. Air: The snow cover of the earth's surface is highly variable both sea- sonally and annually (Figure 3.14~. Because the albedo of snow (the reflectivity over the entire solar spectrum) is very high compared to that of other common surface materials (Table 3.2), its presence or absence has an enormous influence on the earth's energy budget, both globally and regionally. A high albedo over a significant por- tion of a continent has a profound cooling effect on air masses in What are the physical factors that control the snow cover- climate feeciback process and its role as amplifier of cli- matic change?

122 50 ,x, 40 o ~ 30 Or LL > o 20 o oh 10 o . . . . . . . . . . . . . F M A M J J A MONTH FIGURE 3.14 Areal coverage of Northern Hemisphere snow cover (106 km2) from the climatology of K. F. Dewey and R. Heim (1981). SOURCE: Courtesy of the U.S. Department of Commerce. high latitudes while reducing the total input of solar energy absorbed by the earth's surface. The cold air mass flows out of the Arctic and reaches and interacts with the surrounding, warmer water bodies. The cooling effect of snow cover also increases the summer-winter contrast of surface air temperature in high latitudes. The interaction between snow cover and overlying atmosphere TABLE 3.2 Reflectivity (in percent) of Various Surfaces in the Spectral Range of Solar Radiation Bare soil Sand, desert Grass Forest Snow (clean, clry) Snow (wet and/or dirty) Sea surface (sun >25° above horizon) Sea surface (low sun angle) 10-25 25-40 15-25 10-20 75-95 25-75 <10 10-70 SOURCE: Reprinted, by permission, from Kondratyev (1969). Copyright O 1969 by Academic Press.

SOME CRITICAL AND EMERGING AREAS . 123 constitutes a snow albedo feedback process that substantially affects the sensitivity, variability, and stability of climate. When the near- surface temperature of the atmosphere drops, a larger fraction of precipitation falls as snow and the melting of snow becomes less likely, resulting in expansion of the snow-covered areas. Because of the increased reflection of solar energy from the expanded snow cover, the sensible heat flux from the earth's surface to the atmosphere is reduced, further reducing the surface air temperature. This positive feedback process amplifies the temperature anomalies in high latitudes. In addition, it contributes to the persistence of such an anomaly. The process is also responsible for the predicted polar amplification of the global warming induced by future increases of greenhouse gases. Our concerns with snow albedo necessarily start at the scale of snow grains (about 1 mm) because the albedo of snow itself varies significantly with a variety of snow properties as well as the wave- length of the radiation (Figure 3.15~. Snow properties change in time. First, the grains are always growing and change shape often, especially near the surface, where wind and other processes affect the snow in a continually changing sequence of events. Second, when wetted, snow assumes a noticeably darker appearance because of its reduced reflectivity. 1.0 0.8 ° 0.6 c, LL m 0.4 0.2 o - \ \ \ r = 50 Em V 200 Em W 1,000 Am 0.6 0.8 1.0 1.2 1.4 WAVELENGTH (,um) FIGURE 3.15 Albedo of snow of semiinfinite depth for various grain sizes and solar zenith angle of 600. SOURCE: Reprinted, by permission, from Dozier et al. (1981). Copyright (31981 by the American Geophysical Union.

24 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ISI~ ~i~rr~ru~n4ff~ TO pi ls~j^~ Invest-: Id wit: _ ~~I—~~ma.s:;es Em ~p ~d: i: [= ur~; ~ eat ~~ ~

SOME CRITICAL AND EMERGING AREAS ~~:::: :::::: 125 ~:l~o$i£~:sy~d:. ~~:these~same~processes~im~partant~ip,:~for:instance,~G~reen:land~ ~:~ar~:A:nta:r~etic~ey Weld be~iti=~l ~~:~ ~e~:stabil ity~i~c:e:~:~sheets~:~ ~~:~ ~;:~ such :~as~t: A:ntarctic:~i:£e~ ::sheet, Ah ich~ ~i~s~:;~grou:~:ed;~:l I :~low~sea; ~ ~:~ the ;~ - n~;~ : ~~ :; ~~: ~: ~~ ~ :~ ~~ :~ ~~: ~~ ~~: ~~ ~~ ~ .~ :~ ~~ ., ~ ~~ ~~,~ :~ ~~ :ct'~ili:=c:~ cl l~cra":ct~:~h~1: the :~m~l~nt~ A t:n:{1usa:n:Os~ ot~vea:rs~. :~ :~ ~~ ~~ ~~ ~ ~~ :: :~ ~~ __-— ~~-~—----- :--- ~ ~~:: ~~:~:~:~:~ :: ~~::~ :::: Gil:: ,: ~by:~ pl:an~nirtg,:;:~politic~a:l,~::an~:~ - ~~uch~of:~ Score My an:d:~L Costed be ~r~e~ fore Wang ~ can be given The l~rnporta ~r~t~question;~:~ Hi - ~~others~i:n~t~oscie~n~ce~ corn:rnunity ~~i~s~:whethe~r the :~+Q~ ¢~:c=~ ~~a~n~h"~:~nr"~wi~: Hir~'en:t~£o~n~ce ~ Laid ~~i~n~ ~~:~a:~Mfffiti~l~i~jinieiNf~mahne:r,~:~0pproprI~afte~Ions~:~c:an~ne~:aKen~.~ ~~ Third, the albedo of snow is very sensitive to contamination, and our planet is greatly contaminated by our activities. The underlying im- portance of this subject to large-scale processes affecting the entire planet has led to continuing investigations of this single property of snow (e.g., Warren, 1982~. The basic information generated is needed to determine the albedo of snow in large-scale models of atmospheric circulation. The measurement of albedo and many other important snow properties by large-scale remote sensing is a rapidly developing field (see Chapter 4~. Remote sensing offers many possibilities for data collection that should be fully exploited to gather information about the snow cover over the large scale of interest for snow-climate studies. The use of remote sensing includes measurements of fundamental interest to snow hydrology such as snow-covered area and, more recently, the possibility of determining albedo directly. Remote sensing offers the advantage of averaging a snow property over large areas. The single most important thing to recognize about snow is that it is always changing, especially at the surface, where winds, solar input, temperature, moisture, condensation, and precipitation are always changing the textural characteristics of the upper layer. This greatly influences the albedo. It is only in a very shallow layer at the surface that the albedo is determined because visible radiation does not penetrate snow to a great depth. Nevertheless, the depth of snow is a very important parameter in the determination of snow-climate feedback because the amount of snow that must be melted to reduce the albedo back to that of the underlying surface is an important consideration in detennirung climate variability. For example, there are some model indications

126 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES : I:: ~ Ail: of: ~~T~H~o~NT:~WA~lT~E~ :~ :~ ~~ ~ ~ ~ ,,_ ~~ ~~ s~ ~ ~ .~ ~~ I: : I: ~ ~ : :~ :: ~ :f~1~:Q~_:~1~:~::~ :~ ~ ::~ ~~ :~ ~ ~ : ~:~::~::~:~:~i~W~a-r~re~n~T~ho~r~n~th~w~a~i~td~h~as~:~b~ee~n~:~:~d~e~sc~r~:i~bed~:~by~:::~s~om~e~:p~ee~r~s:~as~:~"th~e~mo~st ~influ~e~ntial~climamlo~ist of ~ hilt ~eene~rat::i~on."~ ~This: ora~lis~e~w~as ~:earn~ed~in~ ;~ ~~pa~rt~i~r~ h~is~fu~n~dame~nta~l~stu~diies~ into Ethel n~atu~re~of~ev~aporation~ ~an:d~h;~s~ ~fo~rm~u:~la~t~'o~n~ of~the~concept~of~potential eV~a~potran~s~pi~;rati~o~n~:,~:~for~h~i~s~ out-: :~ I: sta~d~ing~l~9485~ paper ~~An~:Approach~ Towards ask Rati~onal:~l~as~sifica~tio~n:~ of ~CIimate '' Air his establishment of the~Laboram~CI imato~l:o~r~at ~Sea~b~o~k~ ~~:~ New Jersey ~ which Became acid m~ecca~r~c~limatologists And hydrologists ~~:~ From All: ~~pa~s:~:~of i:h~e~wo:r~ld~ ~~ and his Early ~lea~dersh~i~p~of~th~e ~~ World Aim: ~:eteoro~Io~ical~ ~~O~r~an~zat'~on~is~Com~m~s~sion Or Clim~atoi~o~v:.~ ~~ ~~ ~ ~~ = ~He~hi' ~ Early ~~ ~~ :: ~~:U~nliversity ~i~(th~e:n:l~l:a:l~te~ac~h~e:r~s' ~ co:lil:~e~ge)ll li~n~l~ :~1 ~:9~2211~a~n~d ~~ Undertook:: ~so:m:~ell~g~radu- ~ :~:: l Mat work at The ~Un;~vers~ity~of~ Michigan before moving onto ~th~e~De~pa::rt-~ meant of ~~ Geography at the tLJniversi~ty~of~ Ca~l~i~lb:rn~ia, ~~ Berkeley:, ~ where he ;~c~a~m~u~n~;d~er The Influence Of ~ ~~Car~::~Sa:ue~r~a:~n~d ~ gra~d~-u~ated~:~:w~i:~h A Ph. Din: I: ~92:9~.~ ~~A~:hou~gh Whisked i sse~rthtio~n~i~n:vo~lved~ ant urban Geography Study of ~::~Lou~sv~i~e~Ken~t~u~cky~h~is~fi~r~st~ a~c~ad~e~m~i~c~appoi~ntm~e~n~wa~s~at~he ~~:~U~n~i~ve~r-~:~ pity of ~ Ok~lahoma~92~7 to 1935), ~where,~w~i~th~t:he :beginn~ing~ of the Adjust ~:~ Bowl: :~h~e~::~ca~me~c~e ~~to~::~:l>:c~e~:~w~i~t~h:~t~h~e~:~i~m~p~o~rta~nt~ ~~r~o~e:~::~mo~st:u~re~ ~p~l~:ayed:~::i~n~:::~ ~~ ~~::~ ~~:~:~ ~~ ~~.~:~:~ ~~:~ ~~ ~~ ~~ :~:: ~~:~ .: ~:~:~ ~,:~ ~~ ~:~ ~~ ~~:~ :~:~;u~h~u~m:~an ~l~v~e~s~.:~::~Here::~h~s First tw~o:::pa~pers:were p::ubl'~s~hed on a n:ew:~system~ ~~of~c~l;imati~c~ cIassifitation sopersed:ing~Koeppen ask wi:dely~aceepted Class- :::~ I:: f':cat~lo~ns.~ These New ~ c~l~a~s~s~f'~cat'~Q~n~s~ ~r,~volved:~::~deas:~ of:;:t~h~errnal:~::and~: rain- ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ : : ~ ~ : ~ ~ ~ I ~ ~ I ~ ~ ~ : : ~ ~ e ~ ~ i ~ ~ c : i ~ e ~ n ~ ~ c v ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ a ~ ~ n ~ d ~ ~ ~ ~ ~ ~ ~ u : s ~ e d : t ~ h e ~ ~ : ~ ~ ~ ~ ~ : r ~ a ~ i : ~ ~ ~ n ~ ~ ~ l ~ ~ ~ l - ~ e ~ v ~ a ~ o ~ e a t ~ o ~ n ~ ~ : ~ ~ ~ ~ ~ : : : ~ b : a ~ l a ~ n ~ : £ : : e ~ ; ~ : : ~ a ~ s t h ~ e : ~ : ~ : ~ ~ : b ~ a s ~ i ~ c ~ : ~ : : : : : : ~:~ ~~ I: ~ contra: ~~:of~:w~o~r lid ~~:s~o~;~:l~s~:~a:~n~d ~~vegetat~;~o:n~ :~d~i~§~ri~b~t~i'~o n:~,:~ From l~g3i~to~1946~T~ho~rnthwa~ite~was~chief~of~he~Cl~im~ati~c~a~nd;::~ :Ph~ys:~o~g~ra~ph~'c~:~D~v~'s'~on~ ~~of~the~So'~l~::~Cons:e~rv~a~:on :~:~S~e~rv:~ce,::~::U~.:S.~ ~~D~epart~-~::;:~:~ me~nt:~of~Agr~cul~tu:re~where~ h~e~:b~egan ~~60th~th~eoreti~c~al ~st~ud~ies~and~:~fie~l~d:~ :;:::: :: ~ ~ ~~ ~~:~ ~:~:~i~:::~:::~:~ ~ :: .~ ~~:~ :: ~~:~ ::: ~~ ~~ ~ ~~ i:::::: ::: ~::~: :: ~~ ~ :~: I:: it: ~~ ::::~: ::: :. ~~ ~~:~ :::.::: ~ ~ :~ :o~b~s~e~rvat~on~s::~:~o~:n~: ~e~va~potra~ns~p~ra~t~o~n:~.~ :~ Th~s~:~:work~ ~::led~ to many pap:e~rs::on i: ~ ~ ~ ~~ ~~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~: ~ ~ ~ :~ ~~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ I: ~ ~ : : ~ : ~ ~: : :: ~ the ~~moi s1::u~re ::~factor:~ i~n~:~::c:~l~i:~mal:e~ Wands So Hi s ~ d~evel o~p~m~e:nt: of the;: concept ~ of i: : : :: ~ ~ ::::: I: :: . ~ :: ~ ~ :~ :: :~ :: ~~ :~ : ::: ::~ ~ .~: ::::: ::, ~~ :~ : I: I:: ;:: ~~ ~ : ::: ~ : ~: ~ ~ :: ~ ~~ Act:: ~ ~;~ :~: :~:~:poten:t~al e:va~potra~ns~p~rat~on:~t~h:at~::~be~c:a~rn~e thief basis of::h:~:'s famous 194~8:~ ~~ climatic: ~~c~las~sifi~ca~tion. ~~ T~hornt~hw:aite~took~ :~:I:eave From the government in ~~: ::: ::::: ::::::::::::::: it: I:: ::::::::: I:::: ::::::::: .:::::: ~~: ~:~:~: ::: :::::::::::: :: :::::: : ::: ~ :::~::~:~:~::~: ::: ::::: ::::~: :~ :: Air: :::::: ~~ ~~ ~1~:946:~ to~a~dv~se~Sea~brook :~Farm~s ~~ :~a ~~ large ~ grower and:~pa£kager :of~froze~n~ :~::~ivegeta~bi;l:es: ~o:n~ ~:i:rrigat::i:on.~ whiles there ~he: was :as~ked by:t:he Air Force to:: :: :: ~ ~~ ~ ~~ ~ ~ ~ ~~: ~ ~ ~~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~~ I.:: ~~ : ~~ ~ :~ ~~ ~~ :: ~ If. ; ~ I: ~ : :~ ~und:ertake:~:b~asl:c m~lcrometeo:rolog:l~cal: ::studles. ~ He :es~tab:lIsh~ed the lohns ~1~ ~~ i: Hopkins University Laboratory of ~~C:l~imatology~ ~~i:n::~:Sea~b~roo~k~ (~l~ate~r~moved:~ ~ ~ ~ ~ ~ : :::: :: : :~::: : ~ . .~ :::.: : :: ~ ~ ~ :: :. : : ~ : it: : I, I:: ::::: :: ::U nder :h~l s: ~ ns:l~ghtfu I g:u l:dance, outsta~nd'~:ng :: ~:~to:C:e~n~terton New Jersey) : ~ contr~t:~ut~ons ~::w~ere:: ~:a~c~h~leved In :~ basic: ants ap~p:l:l:en Coil I matology~: ~ In m:- : ~ ~~ ~c~rometeorolo~gica~l ~ ;i~n~st~r~u~m~enta~tio~n ~:::~ End ~~ Eli n: i: these :~:of~ spraying ~~i~rri~gat:io~n~ To :: ~~ purify ~~fciod:~-~p~roces~si no ::~effl u~ents:.::: Aft:: Th~e~l ~~re~p:u1:a~ti:on I of: i: the :~l~aboramry:: ~~:wa:s: Such :t~h~at~ leading ~~c~l~i~m~ato~l~og~i~sts~ and ~~h~yd~rolo~gi~sts~from~ ~~a~l~l~parl:~s~of~ Lither ~~:~ world v:i~s:i~ted:~ to ~~c:onfe:r~:~wit~h The ~rese~a~rc~h:::sta~ff~.~:~:~l ~ ~::~ ~~ ~~ ~1~::~ ::::: I:::: ~ :~ ~~ ~ Warren Thornth~w~alte~wa~s:~a~ complex :~ man. his: wri:~i~n:~g ~~was~s~i:m~p;~le~ I: : ~ ~ ~ ~ :: ::: :: :~: :: ~~ At: I: : ~:~ ~ : ~ ~ ~~ :: ~ ~~ ~ ~ ~

SOME CRITICAL AND EMERGING AREAS ~~:~::~a~nd ~~c~l:~ea~r.~:He~: w~a~s~:not~ receptive ~to~c::r~iti~cism,~ but, ~~at:~ti m~e~s,~he~:cou lobe I: i: cr~i~:ti:cal:~::~:of:~:~ others:. ~ Few: of:~::~::his Peers Could ~:~be: e~nti:rely ~~neut:ra~l~ about ::: :~Th~ornth~waite~,~but: those who knew: h:~i~m~we~l~l~recog~n~ized~the~ deeip-s~e~ated~:~:: D ed~;c~at~i on ~~ a nd~ ~~ l ova that He h aid ~ Far ~ His ~~ chosen ~f~i Old of wo~rk~ an do r ~~ His ::~:::: fellow man::. ~ ~ ~ ~:::~: : i: ~ :~:: :: :~: ~ ~ :::: ~ 127 :: ~ ::~:~::~ i: ~~ ~ : ::: :: ~~ ~ ~~ ::: ~~::~ ~ :~:~:~:~:~ that increases in carbon dioxide could cause soil desiccation in some of our prime agricultural areas because of the early meltout of the snow cover in the spring. In general, any climatic change in the temperature of polar regions will directly involve the seasonal snow cover or permanent snows of the polar ice sheets. The climate-snow cover feedback involves not just albedo but also the effects of temperature and airborne particles, including aerosols. For example, the fact that the albedo of snow is so sensitive to con- tamination implies that the scenario of "nuclear winter" (the climatic response to the aerosols and dust injected into the atmosphere following a major nuclear exchange) would be sensitive to the wide range of albedos that a typical snow cover experiences, from fresh snow to slightly dusted snow. The temperature-snow cover feedback must include the reduction in albedo associated with the onset of melt in snow. To understand the climate or even short-term weather patterns of a snow-covered continent, it is necessary to understand a wide range of the physical properties of snow and to use these to determine the boundary conditions for models of atmospheric circulation. HYDROLOGY AND WEATHER PROCESSES Introduction Of all the processes in the hydrologic cycle, precipitation in all its forms probably receives the most public attention. It is easy to grasp its importance in replenishing surface and subsurface flows and wa- ter levels; floods and droughts affect our lives and livelihood in no small measure. Weather processes include all the atmospheric pro- cesses that produce precipitation, from the microphysics of cloud and precipitation particle growth to the continental and global patterns of airflow that control the behavior of weather systems. Because precipitation is a product of this complex combination of

128 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES dynamic, thermodynamic, and cloud microphysical among the most difficult meteorological quantities to model and forecast. These processes operate over a variety of space and time scales, which exhibit control and feedback mechanisms among themselves and also interact with surface orography, roughness discontinuities, and soil moisture. The nonlinearity in the governing equations makes the predictability problem a major scientific challenge, as demonstrated in the now-classic works of Edward Lorenz on chaos, a topic further discussed in the last section of this chapter, "Hydrology and Applied Mathematics." Therefore understanding the interactions between hydrology, weather, and climate and applying this knowledge to solving real-world problems point to research frontiers that go well beyond the traditional concerns of these disciplines. A ubiquitous feature of rainfall—ranging in time from a few min- utes and hours to months, years, decades, and even centuries, and in space from a few to several thousand square kilometers- is the presence of extreme variability. There is now widespread interest among me- teorologists, climatologists, and hydrologists in measuring, modeling, and predicting the nature of this variability, using a variety of new mathematical tools and observational capabilities from land and space. The emphasis in meteorology is largely on the physics of rain formation, the dynamics governing the temporal and spatial rainfall distributions, and short-term forecasting. In climatology, dealing with the problems of global climate, precipitation is recognized to be an important source of energetics both in tropical regions and in extratropical climates. For example, efforts are under way to measure global rainfall using satellites. In hydrology, the interest is in its effect on streamflow, on soil moisture, and on understanding and predicting the response of river basins and aquifers to climatic fluctuations spanning a broad range of space and time scales. Evaporation and transpiration from the continents affect the weather. In the tropical rain forests of the Amazon there is a high degree of recycling between evapotranspiration and rainfall. On the other hand, in desert latitudes the absence of significant surface water vapor sources may have some influence in maintenance of the desert itself. Human- induced changes in land surface characteristics are accelerating around the globe, and thus it is urgent to understand the influences of land surface processes on weather and climate. Once again, we stand on the threshold of a time in which a new array of tools, notably remote sensing of the land surface from satellites, in combination with targeted field experiments, promises advances on this challeng- ing and important set of problems. processes, it is

SOME CRITICAL AND EMERGING AREAS Some Frontier Topics Land Surface-Atmosphere Interaction What are the reciprocal influences at the mesoscate between land surface processes and regional weather? 129 What happens to the surface fluxes of water and energy when an area of natural grassland, 100 x 100 km, is plowed and converted to irrigated agriculture? When a comparable area of tropical rain forest is cut down and converted to agriculture? When a rainstorm soaks a comparable area of the midwestern United States that had been parched by drought? Do the resultant changes have an impact on weather? Statistical studies have established the role of land surface charac- teristics in determining mesoscale meteorological patterns and in the development of severe weather events. Irrigation in the Great Plains appears to have a significant influence on convective activity, enhancing rainfall and locally increasing the frequency of thunderstorms and tornados during the warm season. Thus a better understanding of land surface-atmosphere interaction may lead to improved forecasting of severe weather events. This aspect of land-atmosphere interaction is particularly exciting because it can benefit from advances in the rapidly developing research area of mesoscale meteorology. Historically, meteorology has emphasized the larger scales of planetary waves, cyclones, and anticyclones (synoptic meteorology), and also micrometeorology, describing turbulent transfer in the surface and planetary boundary layers. For decades, the scales in between (literally how the mesoscale was defined) were thought to be scales where not much was happening, and this supposed "spectral gap" permitted turbulent and convective processes to be parameterized in models of the synoptic scale. However, the atmospheric mesoscales include such energetic phenomena as thunderstorms, squall lines, and other mesoscale convective systems, important in their own right and not yet treated properly in larger-scale models, including GCMs of weather and climate. Progress in mesoscale research has long been impeded by a lack of observational capabilities, techniques, and models applicable to spa- tial scales of kilometers to hundreds of kilometers. This situation is changing rapidly. Satellites are providing much of the needed data,

130 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES and appropriate ground-based instrument systems will soon provide mesoscale information from which detailed energy and water bud- gets can be derived. For example, in the early 1990s a network of 30 surface-based radar wind profilers will be deployed on spatial scales of 200 to 400 km over a large area of the central United States. A next-generation weather radar (NEXRAD) network of Doppler radars (see Chapter 4) will provide greatly improved precipitation and boundary layer wind estimates over most of the United States by the mid- 1990s. Because these networks will be operational, data potentially can be made available at low cost, and the research community can concentrate resources where they are needed the most; i.e., it can supplement the operational data with targeted campaigns to add high- quality research data in specific test regions. This will be the strategy of the National STORM Program (see Chapter 4), a decade-long part- nership between research and operational atmospheric scientists in the 1990s. These test regions can be used, in turn, to validate and improve remote sensing methodologies for use on next-generation satellite systems. Appropriate techniques for bridging the various spatial scales from microscale to mesoscale to synoptic are also emerging, in part because of a number of field programs aimed at improving the compatibility of field and satellite observations with the needs of hydrologic and atmospheric models. These include the HAPEX project in France and the First ISLSCP Field Experiment (FIFE) in the Great Plains, both described in Chapter 4. State-of-the-art numerical models of the at- mospheric general circulation, necessary for climate studies, use horizontal grid dimensions of the order of 100 km and may soon be in the 50- km range, but not much less. These are also spatial scales character- istic of important catchments. Thus it is imperative that we improve techniques for diagnostic studies on these scales. One of the crucial terms in atmospheric water budgets, the horizontal flux divergence, can be measured with reasonable accuracy on a 500- km scale, but the error is inversely proportional to the length scale, and experimental estimates are very poor on scales of 100 km and less. Hydrologists who study processes that govern the surface water balance, and hence evapotranspiration, must consider variations in the properties of soils and vegetation that are important on scales of a few meters, and there are no accepted methods for estimates on kilometer and greater scales. Multidisciplinary studies are under way that attempt to bridge this scale gap by increasing understanding of the fundamental hydrologic processes that can lead to parametric formulations for land surface processes on the 10- to 100-km scale.

SOME CRITICAL AND EMERGING AREAS Under what conditions does the spatial distribution of evaporation generate regional circulations that have a marked i nfl uence on mesoscale rai nfal ~ ? 131 For a long time, laypersons and scientists alike have assumed that simply increasing the rate of evaporation will increase precipitation. However, recent research suggests that at the mesoscale it is the spatial distribution of evaporation, rather than its absolute magnitude, that influences precipitation. The largest factor, it appears, is circulation generated by differential heating between wet and dry areas. To show that this is a plausible hypothesis, consider how little rain falls over much of the subtropical oceans, where evaporation is very great. Yet along coastlines, where a greater fraction of solar energy goes into sensible heating over land (and less into evaporation), such as Florida's, a temperature gradient develops and generates a circulation, well known as a sea breeze, which in turn generates thunderstorms almost daily. It remains to be seen whether boundaries between wet and dry areas (for example, between irrigated and nonirrigated land) can generate analogous inland sea breezes strong enough to affect precipitation patterns. Testing such hypotheses will require field data to establish water budgets over 100-km-scale regions, and the new operational networks are an important step toward this capability. Before we can answer such questions about how alterations in land surface properties can alter weather and climate, and improve predictions of elements of the hydrologic cycle regionally, we must learn how to make quantitative estimates of regional water budgets on both the atmospheric and the terrestrial sides of the interface. We want to know the daily and seasonal cycles of these fluxes and storage terms and their sensitivity to soil and vegetation type, state of growth, and precipitation history, including the effects of uneven distribution of precipitation. Models for Mesoscale Convective Systems and Applications to Flash Flooding What kind of weather system produces excessive rainfall and flash flooding? .. .. .. .

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Be ~~:~l~ - rlo~'lea~.~:~u~n~:~s—urns ~:a~no~::anout:~4 i:: ~:~ :~:::: :::::: :: ::::::: ::::: :~:: ::::: :: ~:::~::: :: :::~:;::~::~:: :~ :~:: ~:~ ::::~:: ::~::~: ::::: ::~::: i::: ::: :::: :~: i: ~ i:: : :~: ::: ::~:: :: :: : : i:: : :: :: :~: : :~ :: :: ~~:b~I~i~in~perty~e ~as~::~::~l~m~na~n~:::~, 'one ~:~s~pro- : : :~:: ::::,:: ~::~:::: ::::::: ::~, :: :: ::::::: ::~:: ,:~:~:~ ::: :: ::~::: :: :,: :: :::::::::: ~ : :::, :~ :: :: : ::::: ::: : :: :: ~ ~ :: ::: :: ~ : ~ ::: : : : ::: : :: : :: :: : ~ : ~:~ ~:~ ~~'en~wi~espman~a,~ ~~es~.£tive~oodi~ng~:~arid:~ :~:ash~ Flowing Oft, om.~vir-: if: : : if: ::~:: :.: :: ::~:: Ail: ~ ::: ~~ ~ ~~: :~:: ~ :~: :: if:: ~ :: i:.: :~: ~ ~ :: :: i:: ~ :::: :::. :: :~ ~ ::~ ::' ::: :: ~:~ :: i:: , :: i: :: : . :: : : : :: go - wage ~ 1~4~i~ncues:~ot::~ra~i~n~:~i:~n~24~:~howrs.~::~:: ~ :~ ~~::~: :~:~: :~: ::: ~~:::~:: ::::: :: :: : :: ~ ::: ::: ::: :: :::: :::: if: ::::: :: :: :~:: :::::, ~ ::: :: ::: if: ::: :? ::: :::: ::: :: :::: ::: :: ::: :~ ~ ::: ::: ::: :: :: :: : :: ::~: ~ : ::: :: :: ~ :~ :: ~: : : : : ~~: ~;:~-~)~y~1~9~76WB~ig~Thompson~Cany~ :~ Colorad~1~39~deaths~ anile more :~ ~ : :~:: ::::::: ~~ ::: : :~::: ~ in:: ~ : :~: :: hi:::: i::: i:: : hi: i:: ~ ::: : ~ :~ in: :~ hi: no: : ~ i: : : ~: t ~~ ~ ~ ~ ~ ~~ :::: ::::: t: :~::: ~::::::~: _ ~ :: ::: ·:~ I ·:: : if: a::::::::: ::: :: ::: :::::: :::~::: : ~ ::: i: :~: ::: : ::: ~ ::: : :: :::: : :::: ::: s:: ::: :: : A: ::: ::: ::: ~ :: ::: :::: : ~ ::: : ~ ~ : : :~:~n ~u~:~m~,~,~l~:~prope - ~~.~e~alter~ a~nea~,~l~y~:~statl~onary~ ~rnesosca~e ::: :~: ::: i:: ::: :~ ~ ~~::~:: ::: ~ : :~:: ::: I:: i:: :: ~~ ~ : ~ ~ ~ ~ :~ :: :: if: : :: ~~: :~: :~ :~ :~ : :~:: I: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ r ~ ~ v e ~ i v e ~ s ~ ~ m ~ ~ : o v e , ~ ~ ~ ~ t h ~ ~ ~ : ~ e a s ~ ~ ~ ~ s ~ ~ e ~ ~ : : ~ ~ o f : t h e ~ ~ : : : R o c k i e s ~ ~ ~ ~ d e I : u g e ~ ~ : : t h ~ e v v ~ s : ~ : : ~ ~ ::~::::: :::: ::::: :::: :: :::::::: :::~: :: :: ::: ::~::~ :::~::: :: : :~: :::::::: :: if:: ~ :~:: ::::: i: :::: :: :::: :::: ::~::: ::::: i:::::: :: A:::::: ::~: :: i: :: ::::: :: :::: ::::: :::: if::: i:: :: :: ::: Ail: ~:~e~r~:the ~cany:on~w~ith~ ~41~2~:;~n~c~h:es~ :~ ra~ia~::~i~n~:1~ess~ than:::: ~6~ :hou~rs~.~ ~~:~:~ i:: ~~ :~: ::: ::: ::::: : :~: ::::::::: ::: : :::: :::~::: ::: ::: : ~ :: ~ ::: :~:::: :::: i:: : : ::: ::: ::: :: :: ~ if::: :: ::: : :: ::: ~ :: :::: ::: :::: :: ~ : :: :: :: :: : :: : :: : :: :: :: ~ :: : :~: : ~~:~ ::; .:~ ~~ Ju ~:~1 ~7 - oh~nstown:: :: ~n:~:l.~van ia—~76 ::~a~eaths Hand ~ ~more~:::th~an~ : ~ ::: ~ A: I: ::: a: I: : : ~ : ~ : : :: :: i:: :: I: ~ i: ~ :: :~: :~: If: i: : i: :::: ~ :::: : : :: :: ~ if: ::~uu~;:~m~l~ul~on an ~:~property~ na:rnage::~when :a: rlea:rl:y: stat~onary~ :,nesosca~ :::~::: :: if: ::~: :::::::::::: if:: :::~: ::~::~:: :: i:::: :~: : :::: ::~ :::: :::: :::: :::: If: : :~::: ~ :::: i,: ~ :~: :~ ::: :~: ,:: :: : ,: ::: ,:: : :: : ~ , :: : ::~ :~ ,, A: .:: :, Ail: ~~c~on~v~t:we::~s,~stem~ - er central: rennsy~,~vam:a~:~ue~pos~teo:~ up to l ~ mcnes~: : i: :: ~ ::::: ~ : i: : I:: if:: :~:: ~~ ~:~ if: :::: : :: ~::~ Ail: : ::: ::: :~ ~~ :: i: : Ail:: ~ :~ :: :: : :: :: :: ::: :: : ::: :: : :: :::::: ~ :: : :: : :: :::::: :~::: ::~: ::: .: :: :::::: if: ::: :: ::::: ::: :~:::: ::::::::: :: :: ::: ::~: ::::: :: ::: :: :: :: :: :: i: . : : ::~: , ::: :: ::~: :: :: : : ::: :: :: :: : : ::: :: : i: : : : :: ~~:~ ~~ Bra .~ ~ You - Ada: ~'n~:~Y~:~n'O~urS.~:~:~ ~~ :::: ~~ :: ~~ I:: ~~:~ ~:::~ :~ ~ ~ aid:: ::: :: ~~ ~~ :~: ~ ~ ~ ~ ~ ~ ~ ~ :: :~:~1~ ~i~Seple~ber::~1 97~7—Kansas City: ~ M~issou~ri~5:~deaths:~an~d:~ $90 roil-: :~ ~ ::: :~I:io~n~:i,1ctamage:wh~en:a~nearl~ystationaryl:;~m~esosc:aleconve:~ive~systern.~: . i. ~ :. ~ ~ . ~ . . .^ ~ ~ ~ : ::~:leposlmo 1:1~l~n~cnes~ot ral:,~.:l~n a tew~hou:rs ~:tu~r:nin~g "gentle Brush Creek ~ , ~ ~ , ~ , a, ~ ~ , , ~ . . ~ ~: . : ~ :~w~n~'cn::::t~lows~tnrougn t:n:e neart:ot tne city Into a raging torrent. : ~ : , · ~.e _~ if._ ~ ~~ ~ ~~ ~. ~ovem~oer OF ~—Accra,: ~~eorg':a—4~:peop~e:, :::na:lr or: tnem:~:cn.:~- ~::~dren,~::died:~whe~n~:heavy::rain:s ruptured an: earthen:d:a:m::~an:d~demol:ished~a: i: :~:::~mobile~:~h~ome~:c:ommuni:ty i~n~t:he::valley~bei:ow.~: ::: :~: i: :: ~ :~ ::: i: i::: :: I ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ :~: :~I~:~i~:~:~- ~::~:~A~ugu:st:~1~97~centr~al ::~Texa~3~3~ :idea:th~s~ Wands tens of ~m:illions ~ of:: , ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ::: Dollars ::~in :~da~mage~a~s fiery ~heavy: rains ~associ:ated:~wi:th :the remnants of I: : :~ i::: :: :: ::::: ::~ : :~: A: :~ :~ ~~ :: : :~ ~ : :: ::: ~: : :::: :::: :::: :::: ::: :::: : :::::: :: :: :: : ~ : : ::: ::: :::::: : : ::: :::: ::: : :~:~:~lrop~lc:a~l~>torm~;~A~mel:la~tel~l:~over::tne~area. ~ :::: :~ :: ~ ~~ ~ if: :: ~ _ i, ~ i.. ~ , ~ , ,~ , , , ~ ~ ~~::~:~:~:~eD,~:ary~:~Y~out:.r)westerTnTu:nl~teo~::5tate~s~:~:oeatnsana~more ~ :~ ~ ~~ ~ ~ ~ ~: ~ ~ : ~ ~ : ~ t h a n ~ : ~ ~ ~ ~ $ ~ 3 0 0 ~ ~ ~ ~ m ~ i : 1 1 ~ ~ ~ i o n : : ~ ~ i n p r o p : e r t y ~ ~ d a : m a g e : ~ : a s : : ~ ~ h e a : v y : : : r a i n s : : c a u s e c l ~ : f l : : o o d s , : flood~s,:~a:n~d:~:i~rnUdslides~.~:~:: :: ~~ i: ::: :~: ~ ::: ::: :: :: : :: :: :: :: :: :: : : : : , , , , .

SOME CRITICAL AND EMERGING AREAS 133 go:: : ~ : :: ~ ~ :: : : ~ ~ I: : i: : ~ :: i: ~ ~ :~ ~ :~ i: i: ~ :~: ~ :~ ~~ ~ ~ ~ :: : :~ :~::~1~ ~~ :~ ~~ :: :~ :: ail: ~~:~:~Octobe r 1981—northern~Texas~:~a~so:uther~n:~Okla:ho~m~5:~aea0 ~ ~ ~~ ~ ~ ~:~ i: ~ ~~ :: :~: T ~ i:: ~ :: ~~ ~ i: ~~ i:: ~ i:: ~ i: ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~a~nd::~damage:~approachi n~g~:$~200:~mi~i~1~:o~n~as~a ~n:on~^l ~~:sw~e~m~mm- ~:: ban; w~th~:~decay:~ng~ Tropical ~~storm~bJo:rm~a:~to :~pro:du:ce~ ve~ry~heav~y~:n~ :: Off :~:~:~:~^r~c+~:r~ A: ~ :: ~ ~ ~ ~ ~ ~ ~ i: Ll:! ~ ·C:: Ll lo:' ·~! O:LV': a:. : ~ ::: :: ~ :: ~ : I: ~ ~ ::~::~:::~January:1:98~2—west:-:ce:ntralL~alitornia—more~::the:n:~:~:~aths:;~and~ ~ ~ ~ ~ ~ ~ ~ . . . ~ .~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ , ~ ~ ~~ ~~ ~ ~ ~: ~~ ~ ~: ~~ of, ~ ~ ~: . ~ ~ ~ ~ ~ a: most~300 me ~ lon In: c ama~e:uue to: heavy rains, t ooc in£,~ano~ m::uc Is tic es. ~ ~~ i: SOURCE: ::~ ~~ ST()RM~DATA.~:~Dw::til~i~s~hed~monthlY~bY National Cl;~ma~ ~ Data~Ce~nter~.~ nation al ~ ~E:nvi ron~menta~l~Satel~l~ite~~E)dta~a~nd~ l:nformation~ : Series.: ~~:Nationa:l:~ Oceanside Cants Atmospherics: Ad m~l~n~:~ratl~on:~ A~I:II~e: ~ :~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~~ ~ i; ~ ~~ ~ ~ ~~ ~ ~ ~~ ~ ~~ ~~ ~ ~ ~ ~ Airy ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i/ ~ I; : Although several plausible relationships between weather systems and extensive precipitation exist, such as large-scale cyclones and their associated fronts and tropical cyclones, the size and strength of large-scale disturbances are at best poorly correlated with rainfall intensity. For example, a meter of rain fell in four days in Manila from a barely detectable wind disturbance. The Rapid City, Big Thompson, Kansas City, and Johnstown flood disasters are all examples lacking a significant cyclonic storm or strong front. The apparent paradox extends to tropical cyclones; many powerful hurricanes produce moderate rainfall, whereas some of the worst flood disasters are associated with weak or dissipating storms. Failing an explanation in the large scale, we turn to the scale of the building block of many rain events, that of the thunderstorm. Our basic knowledge of the individual thunderstorm owes much to the classic 1946-1947 field program known as the Thunderstorm Project (Byers and graham, 1949~. There are two basic difficulties in attributing flood-producing rains to the thunderstorm scale. First, the individual storm lives only about an hour, and its intense rain may cover a swath just several kilometers wide. Second, there is little evidence to support a significant correlation between thunderstorm severity and rain volume. Examples abound of violent storms producing hail, winds, and even tornados without flooding, whereas, paradoxically, few flood disasters (including those cited above) are accompanied by thunderstorms of exceptional severity. Meteorological analysis of flood-producing rain events themselves has given us some important pieces of the puzzle. The spatial scale of these events ranges from tens to a few hundred kilometers, and the temporal scale is several hours, not minutes or days. This is firmly within the atmospheric mesoscales, literally intermediate between

134 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES the typical cyclonic and thunderstorm scales. Knowledge of mesoscale processes has advanced greatly during the last two decades, aided by the application of satellite remote sensing, radars, and in situ mea- surements on the mesoscale. The essential new finding is that large-scale disturbances do not merely produce scattered "popcorn" convective clouds and storms that remain closely coupled to the large-scale controls. Often, the convective clouds quickly become organized into obvious mesoscale structures that can move independently of and occasionally away from the large-scale disturbance. Certain mesoscale systems resemble two-dimensional lines of convective storms that are called squall lines. Others develop a nearly circular cloud shield as viewed by satellite and are called mesoscale convective complexes. The generic term "mesoscale convective system" (MCS) is used to refer to most convection organized on the mesoscale. The conceptual model that describes the essential features of most MCSs and their life cycle is shown in Figure 3.16. The deep convec- tive clouds form and quickly become organized, often into one or more lines. The convective clouds continue to grow and die along this same line for many hours; the line may be slow or fast moving and may propagate with a velocity different from that of the ambient wind at any level. After some hours, the stratiform precipitation region forms, its water source a combination of water vapor and ice crystals adverted from the debris of the continually dying convective clouds in the adjacent line, and independent mesoscale ascent. There is a formidable challenge to theoreticians to explain circula- tions on the scale of MCSs. There appear to be no fundamental modes of atmospheric waves on this scale. Convective clouds scale with the depth of the troposphere (10 to 15 km), whereas consideration of the effects of condensation heating in a stratified rotating fluid suggests circulations on the order of 1,000 km in horizontal scale. Only in the past several years have theories been proposed, and only for the squall line type of MCS. Theories and numerical models emphasize the importance of low-level vertical wind shear and of the cold pool of air produced by the organized convective downdrafts. The ubiquity of MCSs represents an outstanding example of how new observations in a geophysical science, in this case from satellite and radars, led the science in new directions. Not only was there no place in accepted theory for such mesoscale weather systems, but they are also a major inconvenience for atmospheric modelers, whose lives would be easier if the mesoscale spectral gap were free of energy- producing systems. As Palmer (1952) so well put it, ". . . it is not only that the griffins and basilisks described by the philosophers are

SOME CRITICAL AND EMERGING AREAS N A' If<, 250 km Aid,\ 21OO/'`` B' 2 50 k: ~~/ \ \ \ ~ / / / 250 km I\\ ~~ - Jig (d) ~ 135 16 14 12 loo 6 2 o 16 14 12 tO 8 6 . A A'. - 50 1 00 1 50 200 250 - B B' 2 0 50 100 150 200 250 16 -C 14 12 10 8 6 4 2 O _ - 50 0 50 1 00 1 50 200 At_ 16 14 12 _ 10 8 6 - 171 4 ~ 2 i 50 0 l Distance from radar (km) 50 100 150 FIGURE 3.16 Schematic of the structure of a mesoscale convective system as viewed by radar in horizontal and vertical cross sections during (a) formative, (b) intensifying (c) mature, and (d) decaying stages of its life cycle. SOURCE: Adapted, by permis- sion, from Leary and Houze (1979). Copyright (31979 by the American Meteorological Society.

136 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES absent; it seems that the country is occupied by creatures of which they have never dreamt." Descriptive models of a particular kind of MCS, the mid-latitude prefrontal squall line, were developed from data obtained during the Thunderstorm Project (Newton, 1950~. Newton also pointed out the likely role of the cold air outflows in continuous triggering of new storms and therefore in the propagation of the system. It took more than two decades for researchers, stunulated by tropical field experiments, to point out the essential similarities among MCSs around the world. Within the last 15 years, many investigators have developed concep- tual models of the structure, propagation, and life cycle of MCSs, including the central role of evaporation of precipitation in producing downdrafts and how they aid the upscale development of these sys- tems. We are now in a position to describe the phenomena of most flood- producing rainstorms. The basic ingredient is an MCS, with the addition of a fairly restrictive condition: the convective portion of the MCS must remain nearly stationary for a period of a few hours. Basically, many individual convective storms must form and move along the same track. This amounts to a requirement that the propagation vector of the convective system be opposite to the vector describing the motion of individual cells (Figure 3.17~. It is quite possible that just the right thermodynamic and wind shear environment exists to produce a stationary MCS. More frequently, the environment favors an MCS that would move very slowly, and some focusing mechanism "locks in" the process over a particular region. This can often be the edge of the cold pool from a previous MCS; over flat terrain this may be the frequent cause of flash flooding, as, for example, in the Kansas City event. In many cases, however, the lifting associated with airflow interacting with topography can anchor the convective region; notable examples are the Rapid City and Big Thompson disasters. New mesoscale data sets of unprecedented quantity and quality will be available to both researchers and forecasters during the next several years. Numerical models have now attained the sophistication required for simulation of MCSs, and they will assist in developing a theoretical basis for understanding MCSs of various types and their evolution and interaction with their environment. There is an important additional factor that must be supplied by hydrologists: what will be the response of the river basin? Improved warnings of flash floods require that better rainfall observations and predictions be coupled with hydrologic models of runoff production on the basin scale.

SOME CRITICAL AND EMERGING AREAS :/Synoptic Rain Area) al ~ MCS An/ Convective Cells 137 ~ Mean Wind O O / ') / (Cell Propagation Vector) °.oOv/~ Cell Motion I; ~ (System Propagation Vector) ,~; Resultant System Motion MCS B (Heavy Rain) Mean Wind \ ~ ~4 (Cell Propagation Vector) Id (System Propagation Vector) \~\~° -~ Resultant System Motion \ i`' Cell Motion FIGURE 3.17 Schematic mechanism for flood-producing rains. MCS A moves rapidly and produces a few brief heavy rain bursts as its convective cell region passes any given location. MCS B is the same size, shape, and intensity as MCS ~ but produces a very different result. Its system propagation vector is nearly equal and opposite to its cell motion vector, giving a resultant system motion so slow that many convective cells will form and drop heavy rain over the same limited area. SOURCE: Adapted from Chappell (1987). Stochastic Modeling of Space-Time Variability in Rainfall What is the adequate statistical structure to represent the organization and evolution of mesoscale storm systems in space and time? The scales of the physical and dynamical processes that produce and distribute precipitation constitute a continuum. Therefore for both theoretical and practical reasons a model describing or predict- ing precipitation can have only limited temporal and spatial resolution.

138 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Atmospheric processes at the unresolved scales have to be treated statistically because the information needed to describe these pro- cesses is not available or because the physical processes themselves lead to inherent fluctuations at such scales. In this latter case, owing to the nonlinear and turbulent nature of atmospheric flow, even processes resolved by a model have only limited ranges of predictability in the deterministic sense. (For further discussion see "Hydrology and Ap- plied Mathematics," the last section of this chapter.) Beyond the limits of predictability, only statistical treatment of the processes is possible. A major task in precipitation modeling is to determine the statistical structure of the unresolved processes and to couple this statistical structure to the physics and dynamics of the processes at the resolved scales. Much of the recent emphasis in precipitation modeling in hydrology has been on identifying an appropriate class of stochastic models to conceptually represent the organization and evolution of mesoscale storm systems. Typically, the building blocks of these models constitute the life cycle and motion of a convective rainfall cell, and the spatial organization of cells as groups of clusters within a moving mesoscale storm system. The cells can move with the same velocity as the mesoscale system or with a different velocity relative to it. The rainfall intensity in time and space is spread deterministically around the center of each cell. The rainfall intensity at the ground level is then represented as the sum of rainfall contributions from the groups of cell clusters within a moving mesoscale storm system. Various statistical assumptions are introduced on these components of a storm system so that the statistical features of the resultant ground- level rainfall intensity can be evaluated analytically or numerically and tested against rainfall observations. Typically, these features include space-time correlations, probabilities of extreme rainfall, and crossing properties with respect to different thresholds. The available empirical information regarding mean intensity at the center of the cells, cell duration, birthrates, spatial extents, and mean number of cells in a cluster allows for incorporation of these values as parameters in stochastic models. Moreover, a stochastic model also allows for the incorporation of variability in these entities. Such variability is ubiquitous among different storms in a given climate and among storms in different climates. Figure 3.18 shows an example of a stochastic simulation of air mass thunderstorm rainfall. Although the line of research explained above was initiated about three decades ago, not much progress has been made in this realm owing to mathematical difficulties inherent in analyzing the space- time stochastic structures described above. However, recent research

SOME CRITICAL AND EMERGING AREAS 139 shows the promise of statistical models in providing a physical un- derstanding of mesoscale precipitation over a broad range of space and time scales. For example, Waymire et al. (1984) derived an ana- lytical expression of space-time rainfall correlation from a stochastic model that shows that the pattern of temporal fluctuations propagates in space as a frozen field through the velocity of the storm system. This is known as Taylor's hypothesis in fluid turbulence. After time intervals of the order of the mean lifetime of a convective cell, the storm reorganizes itself, and a new pattern of temporal fluctuations appears. Therefore the range of validity of Taylor's hypothesis in space-time rainfall seems to be controlled by the mean life span of a convective rainfall cell. In this sense, stochastic models are helping to unify disjoint empirical observations of rainfall, such as the observed mesoscale organization of storms, on the one hand, and the observed correlation structure of space-time rainfall, on the other. One of the major thrusts of future research in stochastic modeling concerns the testability of conceptual mathematical constructs, as described above, against empirical observations of rainfall. These observations typically are available only as averages in time over different intervals such as hours, days, months, and years and in space over regions of different areas. Stochastic models of temporal rainfall are being tested by analytically computing statistical properties of the integrated rainfall over different time intervals (e.g., extremes, proportion of wet/dry periods) and testing these predictions against empirical observations. The goodness of the mathematical construct is judged by its ability to predict the statistical characteristics of the aggregated rainfall over different intervals that are not used a priori in specifying the model parameters. Indeed, the stochastic models exhibiting clustering in time, as suggested by the space-time constructs, have shown the most promise in this realm. How can the necessary and fundamental links between the deterministic (dynamic) and stochastic models of rainfall fields be estate! ished ? Preliminary analysis of spatial rainfall data over different-sized regions shows the presence of fundamental structures that are likely to be of great theoretical and practical importance. For example, the variance of area-averaged rainfall from the Global Atlantic Tropical Experiment (GATE) of the Global Atmospheric Research Program is observed to decrease very nearly as A-~/3 with area A, as A ranges from

140 . . . OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 16 to 40,000 km2. This phenomenon suggests that spatial rainfall may not have a unique length scale, for otherwise the variance would decrease as A-~. Such processes are statistically self-similar, or scal- ing, insofar as the large-scale fluctuations remain statistically similar to the small-scale fluctuations. Simple stochastic models recently have been proposed that exhibit these types of scaling relationships in spatial rainfall. Most of these models consider spatial rainfall or temporal rainfall at a fixed point, and extensions to space-time are introduced by appealing to Taylor's hypothesis of fluid turbulence. The empirical basis for Taylor's hypothesis and the range of its validity 14 12 - 10 u' ~ 8 O 6 4 2 - Contour Interval: 2mm ......... ,~ . ~~ 4~_: ,,~,,,,~ \ ~ ~ w' ~ ~ n \ -my ~ ~ u ~ ~ Isohyet ,—\~/-~ ~—~;S ----- Catchment :"~~ )'r,~',,,,, ,~ """I"" Boundary O ~ 1 1 ~ 1 ~ ' ~ ' ~ 1 ~ ~ ~ ~ I 1 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 KILOMETERS 14 - 12 - 10 - 8 - 6 - 4 - 2 . Contour Interval: 2mm ''',~,, ~~ ,,,\,,> it as ,' :'1,~8-,-'::'' - O - 1 1 1 1 1 1 1 1 1 ~ 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 KILOM ETERS 4,,,,,~ Isohyet ----- Catchment Boundary

SOME CRITICAL AND EMERGING AREAS 141 in diverse rainfall systems still remain to be established. The short lifetime of intense rainstorms argues against universal validity. Therefore a major goal of research in stochastic modeling is to characterize space-time intermittency or spottiness in rainfall as it pertains to various notions of scaling as well as the physically observed features of clustering, growth, and decay of convective cells, and larger-scale spatial forms observed in mesoscale rainfall systems. The intermittency problem has a long and rich history in the stochastic-dynamic theories of fully developed turbulence and is still a very active area of scientific research. Further discussion of this topic appears in the last section of this chapter. 30 - 28 - 26 - 24 - 22 - 20 - ~ O con 10 - LL ~ ~ 1~- o 14- y 12 - 10 - 8 6 4 2 o Contour Interval: 2mm 0 2 4 6 8 10 12 14 16 18 2 0 22 24 26 28 30 it, ~,,q,...... 7~',,, ) ~ ~ J<,~ 1 CN , o ,,.,,,,,,;,.... ........ . In.. ·. , .,,, ,, ~ ~ ~1 o ~ ~ . — -get ~- '-- 2 ,(' - Catchment boundary Simulation fields \O- ,,'~" A, KILOMETERS FIGURE 3.18 Stochastic simulation of air mass thunderstorm rainfall (catchment area = 154 km2). SOURCE: Reprinted, by permission, from Eagleson et al. (1987). Copy- right ~ 1987 by the American Geophysical Union.

142 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES The dichotomy in the current state of the art between the stochas- tic approaches and the deterministic approaches is unsatisfactory. It is important to understand the physical and analytical connections between these two types of approaches in modeling rainfall fields. For example, the dynamics involved in the formation and mainte- nance of mesoscale rain bands are not well understood, and several theories have been proposed. These theories generally appeal to the growth of one of several kinds of instabilities known to exist in the solution of the nonlinear dynamical equations governing atmospheric behavior. We can be optimistic that the combination and improvements in both the dynamical models and the data sets will lead to the rejection of some theories and the validation of others. We will then be in a better position to make the connections between the dynamical and the stochastic descriptions of rainfall, to determine their range of validity, and to obtain parameterizations of stochastic models in terms of measurable physical quantities. HYDROLOGY AND SURFICIAL PROCESSES Introduction Surficial processes include the transport of mass and energy at and through the interface between the lower atmosphere and the earth's surface. As precipitation falls over land, part of it is intercepted by vegetation and other surface structures, and part of it reaches the ground, where it may infiltrate into the soil or run off directly over the surface into the nearest stream. Where precipitation falls in the form of snow, these same processes occur, but they are delayed until melting occurs. Over ocean and sea surfaces the precipitation reaches the water body directly. Between rainfall events, there is a continuous return flux of the water available at the surface to the atmosphere in the form of evaporation. Clearly, mass transport of water is the common denominator of these surficial processes in the hydrologic cycle. In addition, processes such as evaporation, dewfall, snowmelt, and hoar frost formation involve the redistribution of large amounts of latent energy under nearly isothermal conditions, so that they profoundly affect the near-surface environment. Thus it is useful to consider these surficial hydrologic processes not only as mass transport phenomena, but also within the context of energy transport. In fact, it is almost impossible to do otherwise. Precipitation, as the primary source of water, and solar radiation,

SOME CRITICAL AND EMERGING AREAS 143 as the primary source of energy, are the external forcing agents for all surficial processes. -- ~ ~ ~ ~ However, on land the state of the surface generally dictates the disposal and the distribution of precipitated water among the main surficial processes, such as infiltration and soil moisture flow, evaporation, and runoff. Again this state is char- acterized from two viewpoints: the surface budgets of water itself and of energy. Thus, as long as the surface soils remain partly satu- rated, rainwater and snowmelt water infiltrate into the permeable soil layers to join fully saturated flow regions. Wherever such zones of saturation occur at the ground surface, there is surface runoff. This runoff may initially take place as a thin sheet flow, but local irregularities soon cause the flow to gather in small gullies. This flow in turn collects to form rivulets and small streams. In areas where soils are deep and permeable, the water remains underground on its way to the stream channels. The combined availability of moisture and energy near the surface controls the return of surface water to the atmosphere through evaporation. In colder areas, these phenomena involve further interactions and phase changes between water in the frozen, liquid, and vaporous state. The state of the art of accounting for and describing surficial processes holds both formidable challenges and unique opportunities. One theme common in the hydrologic literature today is that it will be possible to describe the global hydrologic cycle only when we understand the relationship among relevant hydrologic processes on different temporal and spatial scales. This is certainly the case for the hydro- logic processes taking place at the surface. Indeed, one of the main obstacles in understanding surficial processes is the high spatial variability of surface features and hydrologic variables. Over the past decades, we have made great progress in the devel- opment of appropriate formulations of hydrologic processes at various scales. However, the issue of the linkage and integration of formu- lations at different scales has not been addressed adequately. Do- ing so remains one of the outstanding challenges in the field of surficial processes. Recent advances in remote sensing from aircraft and satellites promise to shed light on these problems, however. Satellites, in particular, offer a unique opportunity to obtain homogeneous data sets relevant to surficial processes. When used in conjunction with surface observations, satellites are the ideal tool for investigations covering a broad spectrum of temporal and spatial scales. Conversely, however, it will be necessary to improve our present understanding of the physics of surficial processes if satellite technology is to reach its full potential.

144 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Some Frontier Topics Characterization of Spatial Variability of Soil Properties and Its Relation to Infiltration How can local observations of infiltration and soil mois- ture be translated to larger regions? Can the impacts of chemical and microbiological pro- cesses on unsaturated soil properties be quantified? The retention of soil moisture and the attendant runoff from natu- rally occurring rainfall, snowmelt, or irrigation are fundamental processes upon which civilization depends for food production, potable water, and navigable streams and waterways. Infiltration the process that partitions precipitation or irrigation into that part temporarily stored in the soil and that part remaining on or flowing over the soil surface depends on the soil, its relief, and its management. Early research on infiltration is associated with the names of Green and Ampt, Kostiakov, and Horton. Most of our present understanding of infiltration stems from theoretical investigations made in the laboratory and on 1-m2 field plots isolated from many of the factors that are relevant in natural and large-scale environments. The contemporary, scientific challenge is to extend this small-scale understanding to larger domains watersheds of different climatic regions, irrigated and rainfed agricultural and silvicultural areas, and intensively managed fields smaller than 1 km2. The transition from point observations and models to field or regional scales is extremely difficult because soils vary from location to location. They are a product of the processes of soil genesis, and they continuously change in time and space over the earth's surface. Over 10,000 soil series have been identified in the United States alone. The degree of this heterogeneity is heightened because of the unique behavior of one physical proper~unsaturated hydraulic conductivity. Hydraulic conductivity is a parameter in the equation first proposed by Darcy in the middle of the nineteenth century to describe the flow of water in soils. However, as pointed out by Buckingham early in this century, this conductivity depends on the water content of the soil. In fact, its

SOME CRITICAL AND EMERGING AREAS 145 value for any given soil can decrease 10 million times as the soil dries from water saturation to complete dryness. This unique property is a benefit in that it accounts for a soil's ability to absorb, retain, or transmit water under a variety of initial and local conditions. Yet it markedly exacerbates the heterogeneity problems, as illustrated in Figure 3.19, where the unsaturated hy- draulic conductivity measured at two different locations separated by a distance of only 50 m is plotted against soil water content. Ran- dom variations of field-measured soil water content typically exhibit a range of + 0.05 cm3/cm3 and may be related to each other over dis- tances on the order of only 10 m. Note that the two curves differ by nearly 2 orders of magnitude for the same water content. Such vari- ability forces estimates of hydraulic conductivity even at short dis- tances to have an uncertainty of a hundredfold. Deterministic models of infiltration and unsaturated soil water flow are giving way to spatially stochastic concepts. Interest now centers 1o2 ~ _ I 1o1 1 PLOT 1 / PLOT 2 I ~ ~ I .1 0.3 0.4 0.5 SOIL WATER CONTENT (cm3 cm~3) FIGURE 3.19 Illustration of the spatial variability that exists within a small region of a naturally occurring field soil. SOURCE: Reprinted, by permission, from Nielsen et al. (1973). Copyright (31973 by the Regents of the University of California.

146 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES on how to describe the random distribution functions of unsaturated hydraulic conductivity and related soil parameters and the extent of their spatial correlation at various scales. This interest also has intensified the search for improved methods to collect and interpret sufficient quantities of data to ascertain the spatial variability within each soil series or soil-mapping unit. A conceptual framework defining the expectation and variance structure of the spatial and temporal het- erogeneity of soil-water properties from local to global scales is greatly needed. Some current research is unraveling the interactive physical mys- teries of infiltration in field soils, but many additional challenges remain, particularly those that embrace chemically and microbiologically induced alterations of the energy status of water in the unsaturated soil. More than 80 years ago, Edgar Buckingham defined the concept of the "capillary potential" for unsaturated soils (Buckingham, 19071. No one has yet measured the water content or its potential energy within a single soil pore. The possibility of measurement becomes 10° 10-, /~74) 10-4 10-5 meg/l SAR -/ 2 3 1 000 100 50 25 o 40 40 40 1 'I I 0.35 0.45 0.55 0.65 (3 (cm3/cm3) FIGURE 3.20 The impact of water quality (a) on the value of the unsaturated hydrau- lic conductivity (K). SOURCE: Reprinted, by permission, from Dane and Klute (1977). Copyright (3 1977 by the Soil Science Society of America, Inc.

SOME CRITICAL AND EMERGING AREAS 147 greater as tomography and differential tomography using gamma- and X-ray radiation, nuclear magnetic resonance, and other energy sources are applied to soil materials. These measurements will allow a microscale examination of the physics of water flow in films along soil particle surfaces, and, it is hoped, will reveal how the concentration and distribution of chemical constituents in the soil solution alter the macroscopically measured hydraulic conductivity. Figure 3.20 shows that the value of the hydraulic conductivity is drastically altered by the quality of the soil solution. Quantifying the many coupled and time-dependent microbiological-chemical-physical processes at the pore scale into a unified approach is an unmet challenge. At the pore or laboratory scale, a number of issues remain unresolved. These include the hysteretic nature of the unsaturated hydraulic con- ductivity and soil-water characteristic curve, the effects of temperature on the hydraulic properties, the displacement of air during infiltration or drying, the simultaneous movement of water vapor and transport of heat, the impact of localized macropore geometries on leaching efficiency during infiltration, and the quantification of soil-water properties for soils that shrink and swell or crack and consolidate upon drying and wetting. Infiltration of organic liquids into moist soils is another issue. It is complicated by volatilization and the potential presence of co-solvents. Indeed, multiphase flow including the migration of partially miscible and immiscible fluids offers a challenge to the hydrologic community that only recently emerged, albeit in the form of a practical problem resulting from ground water contamination. Runoff Production by Precipitation One of the major difficulties in understanding and quantifying runoff generation in river basins stems from the presence of spatial variabilities in topography, geology, soil type, and vegetation, as well as in climate fluxes such as rainfall, infiltration, and evapotranspiration. Because of these spatial variabilities, even in a single basin, the spatial struc- ture of runoff varies greatly from one rainfall event to another. Con- sequently, each rainfall event frequently contributes to only a part of the channel network system in a river basin, and this part changes from one rainfall event to another. Even though only a few experimental studies have attempted to monitor the time-varying nature of a channel network in runoff generation, the occurrence of this phenomenon must be widespread because it reflects the effect of spatial variability in runoff generation in basins. A central problem in river basin hy- drology is to understand how river runoff is organized spatially, which also includes the issue of intermittency or spottiness.

148 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Traditionally, the development of quantitative estimates of the transformation of precipitation to runoff has resulted primarily from the need to answer design and management questions related to civil works, and agricultural, rangeland, and silvicultural practices, and to forecast shortages and excesses of water at particular locations and over large geographical regions. Pioneering work in determining the mechanisms of flow production from catchments when the rainfall intensity exceeds the rate at which the rain could infiltrate the soil was done by Robert Horton between 1933 and 1945. At about the same time, Hursh and Brater (1941) demonstrated that in steep, forested landscapes significant volumes of stormflow could enter channels by subsurface paths. In the 1960s, it was shown mainly through the work of Hewlett and Hibbert (1967), and Dunne and Black (1970), that another mechanism of overland flow generation arises from rain falling on saturated zones of hillslopes from which water is already emerging. What is the relationship between the flow paths and the geochem istry of h i l lsiope ru noff? For many predictive purposes in the past, it was considered ad- equate to use simple empirical models to estimate merely the precipitation excess as the water available for delivery to the channel network. Little attention was paid to investigating spatial variability in runoff production in river basins or issues such as the spatial distribution of delivery points to the channels. More recently, however, questions have arisen concerning the acidification of streams and the contamination of ground and surface waters by pesticides, herbicides, and fertilizers, which have underscored the need for the investigation of the space- time structure of river runoff to the channel network as a result of rainfall and snowmelt. This need has intensified debates about each process of runoff generation at the smallest contributing catchments, such as the role of flow in macropores, the effect of microtopography and vegetation on surface flow hydraulics, and the relative importance of random and trending spatial patterns in land surface and near- surface characteristics. Indeed, there has been a continuous advancement in the understanding of the physical processes that control the response of a given hillslope to a precipitation input under certain simplifying assumptions of homogeneity in rainfall, soil, and vegetation characteristics. Further advances are expected from catchment-scale field studies such

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SOME CRITICAL AND EMERGING AREAS 151 as studies of the use of chemical and isotopic tracers (especially i8O and i50) to trace flow paths of water delivery to channels. Also required are models of runoff production that use information that can be measured and incorporated from field studies. In river basins, at spatial scales larger than the smallest contribut- ing catchments, significantly new issues emerge regarding runoff production. Basins contain a very large number of hillslopes, and these hillslopes typically display a large overall spatial variability in precipitation, topography, soil, and vegetation properties. Therefore knowledge of the individual process of runoff production from a single hillslopc which is both necessary and valuable by itself cannot be expected to lead to an understanding and prediction of how river runoff is organized in basins over a wide range of space and time scales. For instance, at the larger scales the space-time variability in precipitation becomes an extremely important variable in governing runoff production. Consequently, statistical methods become crucial in measuring and interpreting field observations and in modeling. What are the scaling properties of river runoff in basins, and how are the space and time scales connected? Recent analysis of data on spatial variability in river runoff in basins suggests the presence of multiscaling properties in runoff (see the last section of this chapter). Therefore an important problem is to identify and test the precise nature of scaling in averaged spatial runoff over successively larger scales. Physical connections between scaling models of river runoff and other physical variables such as rainfall, soil properties, vegetation, and topography constitute another important area of research in understanding rainfall-runoff relationships. Long-term research on this topic includes investigations regarding connections between space and time scales governing river runoff. River Basin Evaporation Precipitation is the ultimate source for replenishment of the earth's waters. In turn, all the atmospheric water required for precipitation is supplied by evaporation. Evaporation is a major component of the hydrologic cycle, as on a global basis its temporal average is equal to that of precipitation. Even on the land surfaces, it still amounts on average to about 60 percent of precipitation. Moreover, because of the large latent heat involved in the vaporization of water, evaporation

152 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES allows the transfer of large amounts of energy. For this reason, it has a great impact on the human environment and climate. The partition of the available energy at the earth's surface into evaporation and sensible heat flux is dictated by the nature and the state of the veg- etation and the attendant soil moisture stresses. In spite of the importance of the problem, in current hydrologic practice there are no operational methods available to measure, fore- cast, or otherwise determine the actual evaporation from river basins. Available representations of physical surface processes, related to evaporation in models, are crude and of limited applicability. Thus it is difficult, if not impossible, to determine the relevant parameters . ~ a prlorl. One of the major milestones in the development of our present understanding of evaporation was the work done by John Dalton in Manchester, England, in the early nineteenth century. He proposed that the rate of vaporization of a wet surface is proportional to the vapor pressure deficit between the air and the surface, and that this proportionality is a function of wind speed. The eddy-correlation method for measuring evaporation follows the early work by Osborne Reynolds, again in Manchester, England, in the 1870s. The energy budget method was pioneered by Homen in Finland toward the end of the last century and further developed through contributions by Bowen in the United States in the 1920s and Albrecht in Germany in the 1930s. The profile method, used to measure evaporation, has been developed mainly in response to advances in similarity formulations for turbulent boundary layers in the 1930s by Prandtl and Van Karman and later in the 1950s by Monin, Obukhov, and others. Progress in evaporation theory has followed developments in radiative heat transfer and fluid mechanics and transport phenomena in turbulent flow. Much of the present activity related to evaporation and transpiration from surfaces covered with vegetation can be traced back to the seminal contributions by Penman and his co-workers in England in the 1950s (for further discussion of evaporation theory and applications, see Brutsaert (1982~. How do we parameterize (or represent in models) the effects of vegetation and its biophysical mechanisms on the evapotranspiration from a river basin? Major areas of the earth are covered by vegetation, in varying states of development, senescence, and water availability. Unlike the

SOME CRITICAL AND EMERGING AREAS 153 Ha A:.

154 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES underlying soil, vegetation is not a passive substrate, but an active transmitter and metabolizes of water. The hydrologic aspects of the concomitant biophysical processes are far from understood. Plant physiologists have been able to elucidate the cellular mechanisms of stomata! control of water vapor exchange between leaves and ambi- ent air. However, this has not yet been translated into effective pa- rameterization to describe the plant canopy in the hydrologic con- text. This is not surprising: descriptions at a given scale cannot be obtained by mere superposition or addition of known phenomena at the scales one or several steps below. Indeed, an entirely different conceptualization may be needed. A useful concept being applied for this purpose is the bulk stomata! or canopy resistance. This parameterization is usually intended to express the control on transpiration exerted by the plant for certain conditions of moisture availability. Numerous experiments have been conducted to determine the stomata! or plant resistance for various types of vegetation and climate. Although the concept is effective as a diagnostic index, it is still very difficult to use for prognostic purposes in hydrology. Understanding the intervention of active vegetation, within the partly saturated soil-turbulent atmosphere complex, is one of the major pressing problems in this field. How do surface radiation balance and boundary layer dynamics control land surface evaporation at the me- soscale? The region of the atmosphere that is most directly affected by the land surface is referred to as the atmospheric boundary layer. It extends up to elevations of about 1 km, and within it occur all the physical processes that control the exchange of water, energy, and momentum between the atmosphere and the surface. Predominant among these processes are the surface radiation balance and the at- mospheric turbulent transport. As far as the latter is concerned, an important property of this layer is that the characteristic vertical length scales are typically 2 orders of magnitude smaller than the horizontal ones. Thus atmospheric observations made a few meters above the surface can be representative only of fetches on the order of hundreds of meters; this represents roughly the so-called field scale. In a similar vein, it is clear that measurements taken higher up in the boundary layer may be expected to be representative for surface conditions over larger areas extending upwind over distances of the order of tens of kilometers; these characterize the meso-gamma scales (2.5 to

SOME CRITICAL AND EMERGING AREAS 155 25 km), which are typical scales for source watersheds of similar hydrologic regions. The much-needed progress in the formulation of parameterizations for regional evaporation and related surface fluxes will likely depend on a better understanding of both boundary layer dynamics and surface radiative properties. Developments in this field will be significant for hydrology. Currently, natural evaporation is not being measured operation- ally. Yet it would be useful to set up a worldwide network of land- based index stations where surface energy fluxes and turbulence pa- rameters were measured systematically and routinely. As an initial goal, the density of this network could be designed to be of the same order as that for the upper air (radiosonde) observations gathered for synoptic purposes. The anticipated deployment of various sounders and profilers for the lower atmosphere, as planned for the coming decade by the U.S. National Oceanic and Atmospheric Administration, may provide additional opportunities to accomplish this. Remotely sensed data from satellites have great potential in this regard and should be developed. In water resources planning and management, catchment evaporation must be known since it is a consumptive use and cannot be recovered. During periods of drought, soil moisture is one of the main measures of water availability, and evaporation is one of the main depletion mechanisms. However, for many flood situations there is strong evidence that an important factor governing flood severity is the in- filtration capacity of the catchment; the capacity to store water in the soil profile depends largely on the soil water content and hence on the antecedent evaporation from the watershed as a whole. During the nest 20 vears continuous Progress has been made in ~— - --- r ' ' - r - =~ the development of physical-dynamical models to describe the gen- eral circulation of the atmosphere as it affects the evolution of weather and climate. The theoretical basis for these models, discussed earlier in this chapter, consists of the relevant thermohydrodynamical equa- tions for the atmosphere (and the oceans) and suitable formulations for the boundary conditions, including those to calculate momentum, heat, and water vapor fluxes. One component of these GCMs, to which they appear to be quite sensitive, is the proper formulation of the hydrologic budget of the land surfaces of the earth, namely, soil moisture, evaporation, and related variables. For example, numeri- cal experiments have shown that large-scale changes of land surface evaporation in such models produce significant changes in the pre- dicted atmospheric circulation and precipitation. This and other evidence indicates that there is a critical need for sound parametric expres- sions for evaporation and related land surface processes over areas with scales of 10 to 100 km.

156 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Surface and Subsurface Water in a Freezing Environment How do heat and mass flow in frozen soils control water seepage in such media? What mechanisms characterize the effects of pollutants in the hydrologic behavior of freezing soils? A large fraction of the earth's land surface freezes seasonally, and about one-fourth of the land contains perennially frozen ground (permafrost) that partially thaws in summer. The hydrology of these cold regions is dominated by freezing and thawing processes and by the presence of ice on and below the surface. Surface water and ground water interactions involve the usual multiphase porous media flow, coupled with heat flow, phase changes, and other complications such as solute rejection, water pumping, and ice segregation. This complexity challenges our understanding, but research is needed be- cause of the impacts of these problems on hydrologic and water resources applications, geotechnical considerations, the development of cold- region landscapes, ecosystem dynamics, and biogeochemical cycling. The unusual nature of cold-region landscapes was noted by early explorers: polygonal networks of ice wedges, mountain-like pingos, moving soil aprons, vast fields of icings (Aufeis), and similar features attracted the attention of geologists and geomorphologists. By the beginning of this century, it was realized that the peculiar motion of water in freezing soils played a vital role in producing these structures, but quantitative experimentation and theoretical investigations did not become important until World War II and thereafter, when the interests of defense activity and petroleum exploration brought engineers to the high latitudes and the Soviet experience with permafrost became known in the West. Driven largely by geotechnical considerations, engineers built up a satisfactory general understanding of the processes involved in soil freezing, but predictive ability was limited. Thermodynamicists, soil physicists and chemists, and quantitative geomorphologists, as well as hydrologists, have become interested in the processes, and now a basic understanding of many of these phenomena is developing. However, owing mainly to the complex physics involved in the cou-

SOME CRITICAL AND EMERGING AREAS 157 pling of surface and ground water systems, the field is still underde- veloped scientifically. Infiltration into frozen or partly frozen soil involves complicated interactions. The hydraulic conductivity, for instance, depends not only on the physical properties of the soil and the fluid, but also on variables such as temperature and the amount of ice in pore spaces. Ice lenses restrict infiltration during spring melt, influencing surface water runoff and ground water recharge. These ice lenses form behind the freezing front, separated from it by a "frozen fringe" through which water is transported from the unsaturated, unfrozen soil below. The hydraulic conductivity in the frozen fringe is one important fac- tor in determining where and how much ice segregation will occur. The capillary pressure gradient depends on the freezing process and may be an order of magnitude greater than the gravitational pressure gradient. Because of this, the net flow of water in the soil is generally from warmer to cooler areas, in the direction of the heat flow. Solutes affect the freezing point, and on freezing, solutes are ejected and concentrated in the soil water. The structure of the soil is also affected by freezing and ice segregation and by thaw compaction, causing subsequent changes in the hydraulic conductivity. An extreme case may result where frozen ground persists for years to millennia. Massive horizontal ice beds, from one to many meters thick, may form at the base of fine-grained soils underlain by sand. In addition, repeated expansion and contraction of the near-surface materials caused by temperature fluctuations may produce vertical ice wedges, resulting in a complex array of permeable and impermeable structures. Water in the permeable, unfrozen layers may be trapped under high pressure, so that any disruption of the confining system can lead to spectacular results. For instance, liquid water may intrude, like a laccolith, into the soil, resulting in the growth of a conical body of ice under the turf mat (a pingo). Or water may be trapped in unfrozen soil between frozen ground below and a freezing front moving down from the surface; this can occur in stream channels or on slopes. The pressurized water may break through the confining layer and pour out onto the surface, forming icings that may extend for tens to hundreds of kilometers. Although a basic understanding exists of why these phenomena occur, the ability to predict where, when, and to what extent they will occur is limited by our lack of quantitative understanding of heat and mass flow in freezing soils. A related problem is the motion of water through cold snow. This influences the timing of runoff, extent of soil moisture, and rates of ground water recharge, as well as the concentration of atmospheric

158 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES pollutants ("acid snow") delivered to the earth's surface during spring melt. Improved understanding of the snow problem could aid in the solution of the soil problem, as similar processes of heat and mass transfer are involved in both. Many opportunities exist for scientific advancement in this field of surface water and ground water interactions in the presence of freezing. Perhaps the most critical and challenging aspect has to do with the microphysics of the transfer of water through soil to and into a freezing front and with the segregation of this water into ice lenses. Related problems include the physical and chemical processes involved in solute motion and the effect of overburden pressure on the state of water (as ice and liquid) and the soil matrix. These basic processes will have to be addressed on all fronts: by theory, laboratory experi- mentation, in situ field experiments, and numerical modeling. Special attention needs to be paid to spatial variability and the problem of scaling. The results of a better understanding can then be used to parameterize larger-scale models and thus obtain solutions to practical problems. Basic hydrologic data for the cold regions of the world are sparse. Even such fundamental information as streamilow and ground water levels is rare, partly because there has not been an active user constituency demanding such information, but largely because it is difficult to collect such information in this harsh environment. A vast spectrum of needs in the high latitudes would be served if data collection in the following areas were pursued: 1. Hydraulic conductivity in different soil materials, as a function of temperature, pore ice content, and other conditions; relation of water saturation to capillary pressure, for different soils and ice con- tents; and changes in solute content and movement in different soils for different freezing scenarios and different chemical species. 2. Pressures before, during, and after freezing in liquid water, ice lenses, and the soil matrix. 3. Liquid water velocities and fluxes through different frozen soils and snow with differing driving potentials. 4. Basin studies, perhaps in coordination with interdisciplinary research areas such as biosphere observatories, to determine energy and mass in different phases of the hydrologic cycle. 5. Remote sensing, to scale up observations of soil moisture (if possible) and other hydrologic variables from detailed study sites to basins and even regions. Although understanding of the interactions between surface and subsurface water in freezing conditions is needed for improved knowledge

SOME CRITICAL AND EMERGING AREAS 159 of our earth system, it would also benefit a broad spectrum of practi- cal applications: · Biogeochemical cycling in cold regions depends on the ground water table and other hydrologic conditions in summer, and these depend in turn on freezing and thawing processes. Whether high-latitude peatlands and wetlands are sources or sinks of carbon dioxide and methane depends on the aerobic versus anaerobic microbial processes, which depend on water table level. The flow of dissolved organic carbon and nutrients within and between high-latitude terrestrial ecosystems and from them to marine ecosystems also depends on the processes of freeze and thaw. · Global climate depends on the surface radiation balance as well as evaporation, transpiration, soil moisture, and other factors. The surface radiation balance in high altitudes is characterized by the presence of highly reflective snow, and the persistence of snow cover involves interaction (heat and mass flow) with the substrate. Soil moisture, evaporation, and transpiration depend on infiltration and drainage, which are controlled in cold regions by freezing, ice segre- gation, and thawing processes. One of the best records of climate change in the past decades to past century is found in the temperature distribution in perennially frozen ground, but full use of this information involves better understanding of heat and mass flow through freezing soils. · Studies of the global hydrologic cycle in a greenhouse-affected cli- mate will require knowledge of potential long-term changes in some of the major global reservoirs. Land ice masses (glaciers and ice sheets) will most likely diminish in volume, causing sea level to rise. Any estimate of the timing of this effect requires an understanding of the flow of water in cold snow, which is related to the problem of understanding the flow of water in cold soils. · Water resources development in arctic and alpine lands will be aided if many problems caused by freezing can be solved. Water quality is affected by solute rejection during freezing, ground water between or under perennially frozen layers may be under high pressures, and modification of these systems by humans may lead to untoward results unless a proper understanding of heat and mass flow in freezing soils is at hand. · Geotechnical problems such as the stability of pilings, structures, and transportation arteries continue to plague development in cold regions. The main problem is frost heave, caused by the buildup of ice lenses and other ice segregations in frozen soils. Obviously, a better understanding of heat and water flow in these frozen soils and

160 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES in the frozen fringe is critical to the improvement of geotechnical · . engineering. Hydrology of Snow-Covered Areas The distribution of snow deposition is not uniform, and the processes of snow metamorphism and melt proceed at different rates in differ- ent parts of a single drainage basin. Seasonally snow-covered areas of the earth, especially in mountain ranges, are important components of the global hydrologic cycle, even though they do not cover a large portion of the earth's surface area. They are the major source of water for runoff and ground water recharge over wide areas of the mid-latitudes, they are sensitive indicators of climatic change, and the release of ions from the snowpack is an important component in the biogeochemistry of alpine areas. Alpine watersheds are particu- larly sensitive to damage from acidic deposition because they are usually weakly buffered and their acid-neutralizing capacities are limited. Examination of the chemical and nutrient balances of such water- sheds is difficult, however, because their hydrologic characteristics are only partially understood and difficult to measure. The amount of snow accumulation varies because the rugged topography causes snow to accumulate at varying depths at different elevations and different exposures, and wind and avalanches subsequently redistribute the snow. Once the snow is on the ground, significant variation in the surface climate results from local topographic effects. The major contributor to this variation is solar radiation, although there are also important topographic variations in long-wave radiation, wind speed, temperature, humidity, and moisture in the underlying soil. As a result of these variations, energy exchange at the snow surface proceeds at widely different rates within even small drainage basins, and therefore the rates of the processes of snow metamorphism and melt also vary. Part of the basin may be melting, releasing water and soluble ions to the soil, whereas another, shaded part of the basin may still require significant energy input to bring the snowpack to 0°C. Our knowledge of snow processes at a single field site where measurements are available must be integrated over the drainage basin. This integration over larger areas is difficult because data collected at a meteorological station or snow courses will seldom represent conditions throughout an entire drainage basin. Intensive field sampling of snow properties is possible only in very small areas and even then only for research purposes. The only method of obtaining widespread measurements is through remote sensing of the snow cover, from

SOME CRITICAL AND EMERGING AREAS 161 aircraft or satellite. Therefore we need to understand the relation- ship between the physical characteristics of the snowpack and its electromagnetic properties. How can we integrate the radiation balance over large areas to provide estimates of times and rates of snowmelt in alpine terrain? In a seasonal snow cover, newly fallen snow is thermodynamically unstable, undergoing continuous metamorphism until melt occurs in the spring. These metamorphic changes and melting, along with chemical fractionation, are driven by temperature and vapor gradients within the snowpack and by energy exchange at the snow surface and at the ground. In the absence of strong temperature gradients in the snowpack, dry snow acts to minimize its surface free energy, and slow grain and neck growth occurs by local vapor diffusion and heat flow. On the other hand, strong temperature gradients imposed on the snow cover cause spectacular changes in grain morphology and grain number density, depending on the temperature, the magnitude of the imposed gradient, and the initial density. As the snow recrystallizes, the density often remains constant. Some crystals grow at the expense of others, causing a decrease in the number of crystals per unit volume. The crystal forms resulting from snow metamorphism have widely varying shapes, sizes, and continuity, which affect mechanical, radiative, and chemical processes in ways that are poorly understood. By accounting for energy fluxes to the snowpack, one can estimate the temperature profile of the pack and account for loss of snow mass through sublimation and melting. The spatial and temporal distribution of these processes in the basin could intensify or attenu- ate any ionic pulse in the meltwater. Loss of snow directly affects the solute concentration of the remaining snow, and the spatial and temporal distribution of the onset of melt within a watershed further determines the effects of the ionic pulse. The distribution of chemical species with depth in the snowpack—that is, the initial conditions for melt has less influence on the chemical hydrograph than does the grain-scale distribution of solutes. Knowledge of energy fluxes to the snowpack, combined with bulk snow chemistry measurements, should therefore provide a method for estimating the chemistry of runoff to aquatic systems. Most energy exchange studies, in a variety of snow cover conditions and locations, have shown that usually the radiation balance is the

162 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES dominant term. Recent research in solar radiation absorption by snow has involved attempts to account for terrain effects in mountainous areas and to measure the spatial distribution of albedo. The hope is that the radiation balance can be integrated over a drainage basin to provide more accurate estimates of the time of initiation of snowmelt and subsequent rates than are possible with degree-day methods, which are accurate enough in forested areas but often unreliable in alpine terrain. The long-wave portion of the spectrum the radiation emitted by the atmosphere and surrounding terrain has received less attention. In alpine regions the places most likely to have a positive radiative energy balance early in the snowmelt season are near the valley bot- toms because radiation is emitted from the surrounding valley walls throughout the day and night. In forested environments the long- wave irradiance accounts for the major portion of the snow surface energy exchange; hence the good correlation between snowmelt and degree-day variables in such areas. The radiation balance usually accounts for most of the energy exchange for snowmelt and is the source of most of the spatial variation, but sensible and latent fluxes can be large. Usually they are of opposite sign; under most conditions, sensible heat exchange adds energy to the snowpack and latent heat exchange removes it. However, this is not always the case, and the topographic distribution of the contributing wind speed is a significant unsolved problem. What is the three-climensional distribution of the concentration of chemical species and particulate and colloidal contaminants in the winter snowpack, and how does it change throughout the season? The amount and chemical composition of water entering streams and lakes in alpine areas depend on the quantity and composition of atmospheric deposition of water and chemical species and on the hydrologic and biogeochemical processes occurring in the snowpack and in the drainage basin. Understanding these processes requires a coordinated, interdisciplinary effort. First, we must understand the spatial distribution of the rates of snowmelt and metamorphism. This will require innovation both in measurement techniques and in modeling of the processes. Second, we must be able to estimate the spatial and temporal dis- tribution of rates of chemical elusion throughout a watershed. This

SOME CRITICAL AND EMERGING AREAS 163 will require data on the initial distribution of chemical species and knowledge of their elusion from the snowpack in response to melt and metamorphism. Third, biogeochemical processes in the watershed must be inte- grated with our knowledge of the snow hydrology. The processes in the snow interact with those in streams, lakes, sediments, soils, and vegetation. How can a combination of remote sensing data and field surveys yield the most reliable information on the distribution of the snow resource and on the rates of snow metamor- phism and melt over alpine watersheds? In the visible and near-infrared wavelengths, from 0.4 to 1.0 ~m, snow is the brightest substance in nature, and its reflectance is rivaled only by that of clouds and bright soils. In satellite imagery, delineation of the snow-covered area is usually straightforward, and clouds can be distinguished from snow if the correct wavelength range is available, from 1.55 to 1.75 ~m. Thus the principal use of remote sensing of snow in these wavelengths has been to map the extent of the seasonal snow cover. Throughout the world, in both small and large basins, maps of the snow cover throughout the snow season are used to forecast melt. These maps are useful both in areas with excellent ancillary data and in remote areas with few supporting measurements. Since the first mapping of snow cover from a satellite, the spectral and spatial resolution of the available sensors has improved significantly. Emissivity in thermal infrared wavelengths is not very sensitive to snow properties, and therefore measurement of snow surface temperatures from the thermal infrared emission of the snowpack requires only correction for atmospheric attenuation of the signal. However, reflectance in the visible wavelengths occurs over the top 10 to 50 cm of snow, depending on the grain size and density, and emission in the thermal wavelengths comes from the top few millimeters. Therefore neither wavelength region can provide measurements of the snow water equivalence. In fact, only in the microwave frequencies can we estimate snow water equivalence from satellites. Microwave remote sensing can be accomplished by measuring either emitted radiation or the intensity of the return from a radar. Microwave measurements have the capability to penetrate clouds and thereby permit observations of snow under nearly all weather conditions. For instance, the Nimbus series of

164 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES spacecraft and the Defense Meteorological Satellite Program have provided data on global snow cover since 1979. The relationship between hydrologically important characteristics of a surface and its electromagnetic signature, reflected or emitted, is one of the central issues in remote sensing for wavelengths from gamma radiation to the microwave. Different properties of snow affect the electromagnetic signal at different parts of the spectrum, but present understanding of these relationships must be sharpened to be fully practical. The electromagnetic properties usually are investi- gated at the scale of a study plot (a few meters), but the application of the findings is essential to solving problems at much larger scales- from drainage basins (10 to 100 km) to continents (1,000 to 10,000 km). Current work on the electromagnetic properties of snow in the visible through infrared wavelengths fails to consider two issues. The angular distribution of the reflectance has not been fully investigated, and we do not know the relationship between the grain sizes that we interpret from measurements of the reflectance and the physical properties. Similarly, in the microwave frequencies, the major difficulty in experi- mentally testing models of emission and backscatter is that the snow property observations made by field scientists are usually inadequate to determine the theoretical model parameters to allow comparison with radiation measurements. In the mountainous regions especially, our interpretation of the properties of the snowpack from measurements of the electromagnetic signature is not precise. Therefore comprehensive measurements of radiometric properties should be combined with precise measurements of snow properties. Unfortunately, we do not know how to measure some of the important snow properties. For dry snow, stereological methods can be used, whereby the snow sample is saturated with a supercooled fluid, which is then frozen. Such samples can be sectioned and photographed, from which dimensions and shapes of grains can be obtained. In wet snow, however, theoretical calculations show that the electromagnetic behavior of snow in the microwave frequencies is sensitive to the geometry and volume fraction of the water inclusions, but we have no method for measuring the shapes of the water inclusions. Thus future progress in the use of remote sensing to measure snow properties , , . ~ ~ . . . . .~. . . .. . ~ ,. . Of hydrologic interest will require scientists who are well versed m radiative transfer theory, so that they can analyze the relationship between the physical and the electromagnetic properties of snow. Evaporation from Large Water Bodies Oceans, lakes, reservoirs, and other large inland water bodies con- stitute a valuable resource available to society. More than 70 percent

SOME CRITICAL AND EMERGING AREAS 165 of the earth's surface is covered with water. To preserve these natu- ral resources and to allow their optimal use, a better understanding of the physical properties of such large water bodies and of their interaction with the environment is required. Of critical importance is the mass and heat exchange at the interface between the water and the surrounding atmosphere. Most methods available are based on similarity formulations for the profiles of mean wind speed, temperature, and humidity above the water surface. These formulations are usually in the form of bulk transfer equations, some with adjustments for atmospheric stability and for waviness of the water. These methods can give good results when the water surface temperature is available. Methods based on energy budget considerations are less commonly applied. Over the ocean the necessary measurements can be obtained from instruments aboard research vessels or mounted on buoys. In the case of lakes and reservoirs the data often are measured onshore, but these require some type of calibration or transformation to derive mean surface fluxes for the entire water surface. The main problem in ascertaining evaporation from the oceans of the world is the general dearth of data. For lakes and reservoirs, advection effects caused by the proximity of the surrounding landscape create serious difficulties. Evaporation from the oceans and from the lakes has fascinated human beings since prehistoric days. Best known perhaps is the description in Ecclesiastes 1:7, from the fourth century B.C.: "All streams run into the sea, yet the sea never overflows; back to the place from which the streams ran they return to run again." This seems to have been a universal preoccupation, because similar descriptions have appeared in writing throughout the ages, starting with ancient Chinese, Indian, and Greek texts. In the seventeenth century, Edmund Halley, geophysicist avant-la- lettre of comet fame, was concerned with evaporation of the sea and obtained an estimate by experiment. But again, it was John Dalton's work at Manchester, England, at the beginning of the nineteenth century that provided the initial impetus for more fundamental approaches. More recent advances in the development of heat and mass transfer formula- tions generally have followed the formulations in turbulence similarity by such well-known scientists in fluid mechanics as Prandtl, von Karman, Taylor, Obukhov, and Monin. Sverdrup in the late 1930s was one of the first to apply these ideas to ocean evaporation (Sverdrup, 1937, 1946~. The difficult problem of advection in lake evaporation was first dealt with in a fundamental way by Sutton in the 1930s (Sutton, 1953~. The experimental research of Harbeck at Lake Hefner in Oklahoma in the 1950s has set the standard for much of the subsequent work in lake evaporation (Harbeck, 1962~.

166 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES What are the microphysical mechanisms of evaporation from a wave-disturbed water surface? The oceans and other large water bodies are a major source of the water vapor in the hydrologic cycle that falls to the surface of the earth as precipitation. Yet the microphysical mechanisms of evaporation and related transport phenomena from a water surface disturbed by waves are poorly understood. The fluxes of water vapor, sensible heat, momentum, and other admixtures near the water surface are primarily the result of the turbulence in the air, but this turbulent flow interacts strongly with the irregular wave field of the underlying water surface. The turbulence in the air is conditioned by the presence of the moving waves and thus is naturally different from the classical case of flow past a solid rough wall. At the same time, the sea state and the waves, and the distribution of their shapes and sizes (i.e., their spectral characteristics), are normally a direct consequence of the nature and the intensity of the wind and the turbulence in the air. These interactions with strong built-in nonlinearities and feedback mechanisms are usually accompanied by wave breaking. In open seas and along shorelines, this wave breaking is a dramatic surface phenomenon a force that has long held people's imagination and elicited powerful expressions in poetry, painting, and music. Wave breaking is responsible not only for the transfer of mechanical energy from the atmosphere to ocean currents and turbulence, but also for the enhancement of the exchange of water vapor (and other gases as well) between the atmosphere and the ocean. Wave breaking, which is manifested by whitecap formation, directly entrains air into the water in the form of bubble plumes. A phenomenon closely related to this is the production of water spray and marine aerosols (salt) as a result of the shearing of the wave tops by the wind and of the bursting of the bubbles in the whitecaps. To monitor ocean evaporation, it would be essential to deploy a network of buoys, with the necessary instruments to measure the standard variables for the application of profile and bulk mass transfer methods. With the anticipated improvement of satellite monitoring for wider coverage, this buoy network would provide the needed ground truth for anchoring and calibrating the satellite data. With increasing pressures on the world's water resources, it will become critical to monitor the water budgets of freshwater lakes and reservoirs. Because evaporation is such an important component in these budgets, this will require the installation of proper instrumentation.

SOME CRITICAL AND EMERGING AREAS 167 Solving these problems will require scientists with general back- grounds in physical science and engineering, and also with a special interest in hydrology, oceanography, and atmospheric science. Water entering the evaporation process from lakes and reservoirs becomes nonrecoverable locally. Thus evaporation is a "consumptive" use, and this fact is fundamental to water resources planning and management. The vapor transfer at water surfaces must be predicted as accurately as possible, because such information is indispensable in designing the capacity of storage and flood-control reservoirs and assessing the value of natural water bodies for municipal and indus- trial water supply, navigation, irrigation, and recreation. Large reservoirs, lakes, and the continental shelf have become attractive as sites for construction of power-generating plants and related industries because of the abundance of condenser cooling water. The increase in the past few decades of steam electric power plants makes the need for cooling water especially critical. The environmental impacts of these plants can be evaluated only if the evaporation and cooling rates are known for the ambient waters subject to warmwater effluents. On a global scale, the oceans with their huge inertia provide the flywheel for the earth's climate engine. Since evaporation is one of the key components of the oceanic energy budget, an understanding of it is essential in any assessment of climate or of climatic change. But oceanic evaporation also plays a critical role in air-water interaction at more local scales. For instance, there is evidence that in hurricane genesis the rate of sea-air transfer is the principal limiting factor governing the ultimate intensity. A satisfactory explanation for this would require more strongly nonlinear transfer coefficients than were hitherto surmised. HYDROLOGY AND LIVING COMMUNITIES Introduction The dependence of life on water is fundamental, for it is a major constituent in essentially all organisms. The life cycles of most ter- restrial and freshwater organisms are organized around their access to water; seasonal thermal cycles and concomitant chemical changes in the water exert strong influences. The hydrologic cycle the dis- tribution of water and associated nutrients on the planet in space and over time and the annual thermal and day-length changes are elements of fundamental physical templates for biological processes. Throughout history, many of the efforts to understand and predict

168 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES hydrologic processes, and attempts to manage them, have been moti- vated by biological concerns most often our human requirements. An understanding of the hydrologic cycle can provide a frame- work for interpreting key biological processes. Hydrologic and biological processes interact over the range of spatial scales, from the microscale of small habitat units, through areas the size of major drainage basins (mesoscale), to the macroscale of continents; temporal scales can vary from minutes to centuries. The influences of hydrologic patterns and events on biological processes are pervasive. In turn, through feed- back loops the biological processes may modify the hydrologic setting. For example, the distribution of vegetation and its productive potential can be directly or indirectly related to climate gradients associated with the amount and seasonal distribution of precipitation. In turn, vegetation affects both precipitation and temperature through tran- spiration, and forests play a strong role in determining surface al- bedo, particularly in snow-covered terrain. Another example of how hydrologic processes can drive biological responses is the transport of organic material and sediments in running water environments. Transport and storage of sediments affect the distribution and abundance of aquatic microbes, plants, and animals. Moreover, the nature of organic coatings on stream sediments is an important factor in the quality of runoff, which in turn deeply affects the stream biota and all the living communities in the watershed. The hydrologic cycle clearly is fundamental to the patterns of adaptation of terrestrial and aquatic living systems. Its importance arises from the multiple roles through which water acts on natural ecosystems: carrier, cooler, substrate, and mechanical force. The fluxes of most key biological variables (e.g., biomass) and the operating chemical processes (e.g., carbon assimilation) are intimately intertwined with hydrologic processes (e.g., evapotranspiration). Thus the hydrologic cycle represents a fundamental physical template for biological processes. This template presents some of the best opportunities to search for general principles that may guide the organization of living commu- nities. It also offers guiding physical principles at different scales that are invaluable in the study of the interactions among the funda- mental processes governing the evolution of living communities. Many of the adaptations of aquatic organisms- from bacteria to fish are related to patterns of stream runoff. These include adaptations for maintaining position in flowing water or avoiding the thrust of the current. However, the most significant adaptation of freshwater organisms is the matching of their life cycles to variable hydrologic events. That is, biotic populations in freshwater environments have evolved to survive and perpetuate, in the long term, in response to

SOME CRITICAL AND EMERGING AREAS 169 stochastic hydrologic patterns. Thus many biological processes re- spond to hydrologic events and may even be driven by them. How- ever, as stated in Chapter 2, the committee's definition of hydrologic science is restricted to processes that are significantly interactive with the hydrologic cycle. That is, the biological processes of interest here are not just affected by hydrology but in turn affect hydrology in a significant manner. Some Frontier Topics Physiological Explanation of Boundaries of Major Vegetation Formations What is the physical basis for the geographical distribu- tion of the major vegetation types on the earth's continents? The earth's vegetative cover is coupled physically to the climate system and to the soil by the fluxes of thermal energy, moisture, and nutrients. Different vegetation types have different physiological needs and tolerances that develop over time in a process of co-evolution with their soil and climate partners. The current manifestation of this evolution and migration, as modified by human activity, is the distribution of vegetation formations. Figure 3.21 presents an example for eastern North America. What are the physical reasons for a par- ticular type of vegetation being confined to a certain geographical zone? For example, going south at constant longitude, why should the forest type change from evergreen (boreal) to deciduous and then back to evergreen (southern pine) again? It is important to gain quantitative understanding of these boundaries if the effects of climate change are to be forecast accurately. The transitions from one vegetation type to another are known as ecotones. Because they represent marginal conditions, ecotones are especially sensitive to changing climate, and predicting their location is an important test of the atmospheric general circulation models. Researchers have recognized the relationship between the distri- bution of vegetation and climate since at least the beginning of this century. Most of this work is empirical, however, and it correlates the location of vegetation type with climatic parameters such as tem- perature, precipitation, and potential evapotranspiration without specifically considering the causal physical relationships. Some in-

170 Y o of OPPORTUNITIES IN THE HYDROLOGIC SCIENCES /Tundra >~ \4 Lit W~ _/,,,. , Mixed Deciduous ~ Forest 5: Forest Broad leaved ~ Evergreen ~;J Forest .. . 1 1 1 0 300 600 Kilometers FIGURE 3.21 Forest formations of eastern North America. SOURCE: Map from Little (1971) courtesy of the U.S. Department of Agriculture. Boundaries, by permission, from Eyre (1968); copyright (31968 by Edward Arnold. vestigators have used such correlations as the basis for predictive models, but there is no guarantee that they will hold as climatic conditions change. A more recent modeling direction "grows" individual trees in a stand incorporating both competitive interactions and climatic con- straints. While these models have successfully simulated both past and present vegetation distributions, they contain a great many pa- rameters that are difficult to evaluate. Stepping back from the individual tree and the complexity of its interactions with its neighbors to take a wider view of the forest admits simpler physically based models that can capture the primary distributional features of a given community. For example, modeling savanna vegetation as a tree-grass system where the two vegetation types compete for water and solar energy has provided insight into the conditions for both equilibrium and stability of such communities. Models of this last, competitive type may help forecast ecotone location even where water is not limiting. However, since they are

SOME CRITICAL AND EMERGING AREAS 171 essentially equilibrium models, their applicability requires that the time scale of climate change be small with respect to that of adapta- tion and yet large with respect to that of migration. The basic premise is that the relationship between different vegetation types is competitive and that the prevailing environmental conditions are important in determining vegetation distributions only as they affect the relative competitive abilities of the plants. Where water is not limiting, dominance in a given environment may go to the plant type that produces the most biomass and hence wins the race to grow and reproduce. Bio- mass production is a function of carbon assimilation through the process of photosynthesis. Since both carbon dioxide and water vapor exchange occur through the stomata, the evapotranspiration rate is often used as the basis for estimating productivity (Figure 3.22~. Optimality Constraints on Vegetation Communities Do adaptive or evolutionary pressures lead plant communities to states of development or to physical characteristics that are in some sense optimal with respect to a critical clirnension of their environment? Ecologists studying the population dynamics of plant communi- ties have long noted the existence of environmental conditions called ecological optima under which certain species occur most abundantly in nature. For the controlled conditions of the laboratory, where competition among species can be prevented, these optima are called physiological optima (Figure 3.23~. Observations of such optima lead to speculation about whether there are preferred operating points of the climate-soil-vegetation system toward which it is driven by natural selection and/or adaptation, and at which it is stabilized by inherent (homeostatic) feedback processes. In 1974, M. I. L'vovich presented the variability of the components of the mean annual water balance as a function of hydrophysical properties of the soil (Figure 3.24~. Because of the relationship between evapotranspiration and plant productivity (see Figure 3.22), this takes on the characteristics of an ecological optimum. It has led subse- quent investigators to suggest that soil building and plant community development may occur synergistically over time along a path that carries the soil-vegetation system to the point of maximum evapo-

172 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 2,000 1 ,000 z , O 500 O (D ~ ~ 200 >a O 6 100 50 z / A. . 1 1 1 1 100 200 500 1,000 2,000 ACTUAL EVAPOTRANSPIRATION, mm/yr FIGURE 3.22 Net primary productivity in relation to actual evapotranspiration. Re- printed, by permission, from Whittaker (1975) after Rosenzweig (1968). Copyright 1968 by the University of Chicago. z in O I a: PHYSIOLOGICAL OPTIMUM 1/ \ VARIABLE HABITAT FACTORS FIGURE 3.23 Idealized ecological optimum. SOURCE: Reprinted, by permission, from Eagleson (1982). [After Walter (1973). Copyright (3 1973 by Springer-Verlag, Heidelberg.]

SOME CRITICAL AND EMERGING AREAS llJ z LL o z LLI J lit PRECIPITATION \EVAPOTRANSPIRATION / SURFACE ~ \YIELD / GROUNDWATER RUNOFF X ~—RUNOFF ~ \1 INFILTRATION CAPACITY OF SOIL ' · WATER RETENTION CAPACITY OF SOIL 173 FIGURE 3.24 Variation of water balance with soil characteristics (total yield equals surface runoff plus ground water runoff). SOURCE: Reprinted, by permission, from Eagleson (1982) after L'vovich (1979). Copyright (31979 by the American Geophysical Union. transpiration and that this is the so-called climatic climax state of the community. Where vegetation types having similar physiology are present at the same site, competition for resources will occur. At the geographical boundaries between communities of different vegetal type, such as the boreal-deciduous ecotone discussed earlier, we might expect the states of the two communities to be equal, as sketched in Figure 3.25. When water is the limiting resource in community development, species and fractional canopy covers result that minimize the stress induced in plants by an atmospheric evaporative demand that exceeds

174 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES : ::: :: : : ::: ~ i: M~ICH~AE~L:::EVE:IWARI: : (:1 904-11989~) ~ I I ~ :: : ~ Michael Evenari ~ is best~known~ in The field of Plant ecology,~especially~as A :~ ~ _ _ _ :: : _ ~ ~ ~: : A:: :: ~ ~~ : A:: ~ : :::: ~~ ~ Pioneer i n plant ecoph~ysiolog;y,~ but ~~ his~ll~Gareer ~ illustrates l~h~v~imp~ortant:~landl interrelated~hydrology~i~s to~other~fiel~ds.~Evenar~i wasl~rn~in Gerrnan~y~;n~1~904 as; Walter Schwartz. As a university student,~he~studied~ ~~botany,~zoo! ~,~physics,~:~ Stands lips 1ilosoph~y, and their moved~qu~ickly~alor~g~ ettablished~routes ~towa~a~l~ppsition as a university p~mfessor.l~ ~ Butlhis~brillia~rit~ sta~rt~sta:lled~:labruptly o~r,~April~:l~ 119~33 : : : : ~ t ~ ~ ~ The day when German~Jews were boycotted. ~Three~lweekslJater~W§l~r~;~hwarz:~ 1~ ~ ~ ~ :~ ~ ~ 1: arrivedl~at H:aifa. Palestine. and began: l~fel::anew asilM~;c~hael :E~n:nri~ 1~;::~ Evenari became a lecturer at the Jerusal~em~Univers~ity but~soor~lwas ~fi~ghtingl~l in leanly with the ~ Jewish Brigade Back home in 1~945~,~he~ worked w~ith~l~lcol~-~i~ I exudes t establish t he Botany Department ~ the~Heb~rew~ I Universe fast I :~o~ne~6f~11~1 the world's most famous centersl~for ~~ecology.~Fo~r~ rr~ore~tha~n~50~ars~1he~ 1 ~ , ~ ~~ devel~opedhis~ideasin~;~ecol~ogy,~seeking~to~exptai~nplant~establ~ishment,~pe~r-~ . . . ~ ~ ~ ~ mance, ~ survive , an c Istrl Caution. ~ ~ ~ ~~ ~ ~~ ~ : : Because of this~work, Evenari became intrigued withers th~e~ch~alle~n~ge~of~desert~ farming, and there he m~ade~his~most~important contributions to hydrology. this studies of historical runoff~llfarming~under extremel~dese~ cond~itions~l~were~a~n~ . . . , ~ :: ~ ~ ~ ~ . ~ . ~~ . ~ : ~ A: ~ : outstanc ring anc n'~ ~ y or~g~na contr' 3ution.~ ~ Doug 1 extensive 1Istor:~£a ~~::re-~: ~ ~ ~ '. ~ ~ ~ ~ -. ~: ~ ~ ~ searc 1, arduous rie: c wor <, ant ~aeria surveys Gel cone uc Alec t flat a tours ring ~~ /~ ~ ~ ~ :: . . ~~: ~ ~ ~~ ~ . ~ ~ ~ ~ : i empire once existec leased on runorr cIrecteo tr om extender mountain~catcn~ment~ areas onto fields. He worked Ditto reconstruct~such~ a~rm~,~A¢d~at~experimental~ farm,: and today its~g~reenl fields are An oasis kiln the yellow landscape The Negev~Desert,lland~ a unique opportunity~l~for researchers from around~the~woild. ,~ , ~ ~ , ~ , :, it, ~ ~: ~ ~ ~ : ~/'tnout irrigation, ::runolT farming provec:capao~'e ~Q~sup~,~rtlng~pastures~ veg: ~~ ~ ~ ~ r . ~ ~ · ~ ~ :~ e::: : ~::.~~ id: ~ : :::: :::::: A: :: I: ·:::: :: at::::::: r. ~::::~::~ :~ :: etaoles, ano fruit trees. Altnougn we acre sty tar tromp a fug understanding ~~ ~~ ~ ., :, . . , . ~ . . .. . . . . . . . . . Erie compilcatea lnterrelationsnl~p: w~ltnlr'~: Desert ecosystems, ~ inks work Was Significant step~toward~6egin~ning~1~to~ und~erstandi~the~ integratio~n~6f~the~desert~ ecosystem':s biological,: geologi£al,~meteorologica~l, ~and~::~:hyd~roblogical~l~atures. . , , ~ ~ . ~ . , ~ . ~ ~ . . ~ ~ ~ ~ ~ ~ ~ ~ M~lcnael Evenarl received many honors during nils long, productive lifer bother his scientific work~and for~.~his humanitarian Contributions. ~~ llde~was~ ~~a~ t h:ou~nhtful mange with Ma d:eeolinterest in the :fate:: of h::umankind I :~:~n:~receiv:in~:~:~th~ ~~:~ ~:i: ::: : ::: ~ :::: prestigious Internationai~l~Balz~an Prize Thin 1988, which honors deserving cultural and humanitarian work, Evenari gave an~accentance speech that caoturedl~i~ some of his special Nits. He explained: that while we s:ee~the~eve~r-increas-: ing advancement of Science And technology as progress, we must ~nc~t~forget~ , , , , . , · ~ . ,- . ~ . ~ _. . teats tne blessings or ~~scl~entitic Covey are ~ not ~wl~tnout~ a Pricer ~~: Here ~ lisle scarcely an invention that man has not turned into A lethal weapons or an :: : : : : : : : instrument of ecological destruction. The ethical behavior of:~man~kind~ha~s~not~ kept pace with technical development. ~~ ~~Mankin~dl~i~has~become its own Worst enemy. but tvenar~: Implored us to channel our wav of late to reform our ~: educational value system,~and to image it our primary goal to en~ucate~ano practice the ethical values given In the oi:0 Land New ~Testaments~ann Lathe ::~ :teachings of:~:Buddah::. i: :~:

SOME CRITICAL AND EMERGING AREAS > I_ o Q a: G LO A l l l l l ecotone location , 1 \ , \ ~ / / \ I / / species a \ ' / / dominates 5( - /'\ \ /~\ \ /'\ \ LATITUDE species b \ dominates \ 175 FIGURE 3.25 Hypothetical relationship of net primary productivity and latitude for two competing vegetation types. SOURCE: Reprinted, by permission, from Arris and Eagleson (1989~. Copyright (a) 1989 by Ralph M. Parsons Laboratory, Massachusetts Institute of Technology. the soil moisture supply. This amounts to maximization of soil mois- ture for given climate and soil. Are these hypotheses valid? Are others preferred? Their verifica- tion would establish equations of state for equilibrium vegetation communities, thereby contributing significantly to solving such practical problems as optimal irrigation strategies, soil rebuilding, revegetation, estimation of effective mesoscale soil properties, recognition of changing climate, and many more. Once the appropriate equations of state are determined, the rates of change from one state to another can be addressed. This is of considerable concern in planning for and coping with the effects of climate change on soil-vegetation systems. Microbial Transformations of Ground Water Contaminants What is the nature of the feedback processes that occur between biochemical processes and the various physical transport mechanisms? Subsurface microbiology and biotransformation of organic contami- nants offer scientific and engineering challenges. Investigations that integrate both laboratory and field opportunities to make measure-

176 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~~:~ ~~:~:~CHARI:ES~:~R:~HU~R~S:H ~~ ~~ ~~:~:~ :: : i:: ::: : i:: :: ~:~895~-~1~ 9Wi~:: ~ ~~ ~~ The ~~\Ve~s~ Ewe ~~Of~l~g~1 1~p~1~r~the ~~establ~'shme~nt~of National ~~ ~ ~ :~ ~ ~ ~ ~ ~: ~ ~ ~: ~ ~ ~ ~~: ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~~ ~~ ~~ ~ ~ ~: ~ ~~ ~ ~ ~ ~ ~ ~re~i~n~th64~ ~E~a~s(~pri~mar~l~y~to~pr~re~st~a:6d ~~ where rest~r~c~es~i~n h~3Aw~f~rc~::~ ~n:~:v~if,~hl~tr~m~ ~~ :~+P~ti~m~ Little was Own About t~inMl~u~ence~l~rests~o~n~water~t~ld~ing~ ~~a~nd~reg~lat~ion~streamflow~. I~h~;re~ ~~n~s~;~ss~ue~was~at~ ash 1~! In ~l; 926~whe~n ~~C11aH~e~s~H~u~rs~,~ ~~a~n~e~i~st,~i~oi~ned ~e~ve-man~e ~~newI~y~ettabl i~sh~ed~A~ppal~a- ~~ ~~::~ ~c~h~:a~n~ Forest :~Ex~p~e~r~i men tin Sat I o n .~ ~1~ :H~e~p i o n ee reads ~ fir esea rc:h ~~ An eco bogy ~~ a d ~ ~ it: ~~ ~: ~ ~: ~~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ :~ ~ ~ ~ :~ ~ ~ ~ ~forest~h~l - ~~a~nd~m~a~ny~of~the~basic~prt~n~c~iples~of~lwi~ld~la~n~d~hydrol~-~ ~i~a~nd~:w~a~r~h~ed~ma~nagernerit ~ar~e~irectly~;~attri~buta~blb Nisi n~nova- ~tive~thi~n~ki~n~g~a~nd~ag~siv~qrch~le~aders~h~ip. ~~;~ ~: ~AnAnvekl~b~l~lli4~il~ewe4~a~B~.~S.~from~the~Universiiy~ of ~r~i~ an~d i~Ph~:D .~ from~the~ U~n~i~ve~rs'ty~ ~of ~Mi n~nesota~.~ ~T~he~fi~rs~t ~goal ~hi~s~resea~ Nc~h~was ~to ;defi rie~the~ c~haratteridtics~the~soil~ water~a~nd ~climate~d~aba ~ed~ agri£ultur~1~ ~1a~n~d. ~ He ;foresaw ~t~ ~d foNr~en~on~r~heds to~ prov~ide~cont'~n~u~ous~ ~me~asu~mme~nts~ of ~e~ci~p~it~on,~ g~ro~urid~wate r Jevels~, ~and~strea~mf~low.~: ~ B~y ~1~9~32~:iH~u~4h~ ~had~ ~studiecl~t~Y~arious~ needs~th~e~m~ounta~in~and~Pied; ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ a~bad p~d a comprehe~n~sive~ s~s~of ~wat~r - ~¢ ~and~ ~a~n ap~p~roach~s~vi~ng~em .~ ~1~ con- dJ~ ~Nt~ ~l~p~u r~po~se~4 f the~streandlow~an~d~e-rosion~st~ i~n ~ its~ _ ~ ~ p—~ ~ n d e r l y i n g t h e ~ ~ ~ ~ r e l a t i ~ o n ~ ~ ~ ~ o f ; - est~a~nd ~c ?ve::r~ to~e~s~upl>ly and~distrib: udon~of~et~logi~ca~l~ :4a~)~He~d~ne~e~d~for~an ~;ntbrdisci'~i:~n~a~ry;~a~pproach~ =~ - w~:atil~'zed~=ar~il~furid~s~ ~t(:e~9.30s (the~ia ~l~t~servation :~:~:~!~p~ ~he:~:::~rk~t~r~ts~Ad~:m~l~n~s~trat~l:~o~r!,~:~a~no~so~:~o~n~J~to~:;~comp:lete~ly~:t:n~-~ h ~tycle :on ~ uniero(ls~watershed :~ - : was~t ~t~n ~re,~a~:nt~i n~i~ntell~ect,~.a~hd~c~om~ptetel~y~into~l~era~nt~of:~ ~b~urea~£rati~c~ob~cles~:~to~1 ~ce.~ ~ D4r~ng ~:~the~l~ate~1i~93~a~nd ~early~ ~i~ :~:~ ~ ~1 ~94~ Hu~rsh's~:wor~k~i:n :~£01 1~abo::r~tion~ w~th~: :~ot~h~er :~ outs~:nct~i ng:::~ h~c rolo-: ~:~ ~ ~ ~ ~ ~ ~ ~ ~, ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ , ~ _ :~. ~ ~ ~ ~ ~ ~:~ :: ~. ~gists,~ ~I~;ke~ ~E :~.~.~ ~Brater ~a~n~d~M~ ~ ~D~.~Hoov~ert:~s~ha~ped~cu~rre~nt~concepts ~jof ~:~:~: streamftow~ge~tion~ion~forest~la~nd~anc ~:~:quan~i~j~:mar~y~ efl~of ~:~ ~ii~for~est rernoval~on strea~fl - ~and~ wal:er~qudl~.~j~H~e ~deve~loped ithei fi~rs~t ~ ~ j~ ~si i~c~cess~l ~infiluameter~ and~stLIdidd~ ~wa~ter~ move~m~ent ~th~rough~ the ~ ~soii I i~ ~p~ild.~Although~a~st-rong ~ad~voc~ate; ~the~sc~ientific ~ me~od~i~H~u~rs~h~was~ ~ ~:~:~ :::: ::: :::~: : :::: :: ~: ~:: :: ~ :~ : :~ :~ : ::: :: :::~:: ::: ~ : : :: ::: :: : ~:equal Iy~ adep t and~s~uccessf~ul ~j~;n~ng~ ~so>lutio~n~s:ito~i~very~pr~a~ctical ~q~ue5~;0n~s~.~He~wa~s~pe~rh~aps~proEide5~0f~is~resear~0nnaturaliz~ation~0f~ h~ighway~ ~r~adba~n lci~ to~ ~control~erosion . i~ ~ ~ : :~: ::: ~: : ~ ~: ~ ~ : ~ :~:~ 1 n~te~r~v~ear:s.~:~:H~u::r~s:h~:~coin~ti~nu~ed~:~h~is~ atl~voc:a~cY~ fo~r ~m~a~i~n~te~n~a~n:ce~:~and~: :;~: : ~ :: ~: : :: : :: :: : :: ~i~mpro~ve~ment~ of ~ ~en~v~iro~n~men~td~l ~q~u~al ity as ~a s £~i~en:t~ist-sch~o:~l:ar ~ a:nd~ con:~-: ~s~ul~d~i~ni~the~ United~State~s~a~nd~al3road,~in~cl~ing~1jance,~Ja~pa~n,~Turkey~,~ ~ancl~ Kenya.~n~ ~] 953~, ~h~e~receive:~ the~presfi~giou~s ~;~Nash~conse~ryation~ : ::~: ~::: ~:: : :~: ~ ~ : :: :: :: ~ ::: :::~: ~ ::: :::: ~ ::::~ ::::

SOME CRITICAL AND EMERGING AREAS 177 IHI~i:s;~:c~on~tr~f:b~u~ti;~ons~to~lth~e ~~h~y~diro~log~i~c~ Sciences l~a~:d~ocum~ente~d:~ :~in~; ~~ ~ Over 1~ ~:p~u~b-~l~catio~n~s~. ~:~ ::rerh~aps: ~t~e~gre~a~test ~trl~u~te~to As ~g~e~nl~u~s~:~l~:s:~ that: ~~ ~~ ~ ~ ~: ~~ ~: ~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~1~ fits Rework <: ~~ Basil ~stooc ~ At Gel test Of trimmed ire ~r~seatc~h~ plan he co~ncerv$d~ In :~ ~ ~~ ~ s,~ ~1 :_ lye ail: anc ~ amok ~em~entec Milan ~ ~~ : u~ oec~a~me~:~a~n~l~n~e~r~n~at~l~on~a~ ~~ Renown i: ~ :~:~:~h~vd~ro~l~c,~i~c: :: ~l~a~bo~rato~rv~d~r~;~n~:~:~h~t~:s~acti-ve~c~a~reer~a~n~d~ ~~:~i~h~l~ittl~e~ change In ~~ ~~ 1~ concepts ~~co~nti:n~ued as ha ~world~lea~de~r~ in~h~yd~ro~lQg~i~c~researc~h:~r:~5~0:;~ye~a~rs~.~ ~ ~~ ~ If: ~ :: ~~W~E~T~L~A~1~DS~: ~~ KIDNEYS LOFTY THE LANDSCAPE ~~ ~ : ~~ ~:WetI~a~nds~ provide some of theist Important ecosysmrns~ on Hearth. - ~ At Global scal~e,:~wetla~nd~s~:re~p~f:es~e~n~a~bo~u~6~:::~pe~r~c~e~n~t~:~o~f~th~e~:~tota~1~1~a~nd~:~:~: :~:~: surface ~~ra~nai~n~: From ~1~ ~7~ ~~:~e~rc~e~n~t~i~n~ ~~l:~h~e~s~u~bt~ro~i~ca~l~ Onto About 2~:~ ~~ ~~ Hi: ~ ~ ~~ percent Hi: in the ~~ pod a~r~z~o no.::: Wetland s~:~:p~e~r~r~m:~ several: I: va~l~u~a beef u~n~c~t~i o nits ~~:~ ~:~ls~e~rv~i~n~g~lla~s~:~:~s~o~-rc~es,:ll~s~i~n~k~s~,~l~a~n~d~ll~t~ra~n~s~r~m~ersl~l~of~c~h~em~ical~s~a~ndbiological I: Variety of flora and Buns. His~tori~ca~l:ly, wetlands have been the; center- ~ Spice of ~~cul~ura!~ and Economic: ~dev~e~lq~pme~nt,~::~ ~~i~nc~lw~d~i~n~g~ ~~d~om~e~st~i~c~:~:~we~t-~:~ :: ~:::~:~:~ ~a~n~c ~s~:~s~u~c~ 1~:~a~s~:~ri~ce~padd~i~es~f~wh~ic~h~:~s~u~p~port~a~m~aj~o~r~seg~m~en~t~of~t~h~e~wQ~rI~d~;~'s~ i~p~opula~t~i~o~n.: ~ For~centuries, pe~atlands, salt ~m~arsh~e~s,~an~d~ ~mangrove~ foFes$s:~ ~:~ :~ ~h~a~ve~ ~a~l~l~ ~p~ro~Y~i~ded~tood~ ~a~n~d~t~l~b~er :ess~e~nt~i~a~l~t¢~ ~m~a~n~n~.~ ~ ~:;: ~:~ ~ ~:~ ~:~:~ ~ ~ ~:~:~: ~: :~ ~: ~: ~H~yd~rolo~g~ic::~p~ro~c~elsses: ~a:re::~:c~l:o~s~e~l:~y~ :: ~l~i~n~kedl~: Iw~ith~ ~c~h~e~m~ic~:l a~nd~ ~:~p~h~y~si~c~a:l aspects of wet~lands,~ which~i~n turn~ a~ct bi~otic ~function~s~ a~nd ~su~bsequent~ ~:~ ~ fe~ed~b~a~ck~ ~:t:h~at~:~:~:~m~aY: a:~te~r~ ~w~ll~a:n~d ~:~h~y:d~ro~l~o~y.~ :~ ~FI~Yd~ro~a~i~c~;proce~sses~;~d;~-: ~::~ ~ ~rectly :~ i ~nf~llu~enc:e~ :~spe~cies composition~and~ric~h~n~e~ss,~ pri~ma~ri Iy~pr~od~c:t;ion~, ~1 :~ ~ ~ ~ ~ ~ ~ ~ ~ , ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ organ'~ :~m:at~r::: :tu~r~n~ove~r: ~ an~d~ t~h~el:~c~yc~li~n~g:~ ~of~:~ ~n~u~tr:;~e~n~: ~ i~n~:~l:he~w~et~la~n~d~s~ ~ ~ - ,~ ~: ~ : :,;:~ ,;~ . ~,~ ~ :: :~ :~: ~, :~ ~:: .~ ~ : ~: ~ ~ ~:~ ~:~:~: .::~ ~ :~ ~ ~ ~ ~ ~ ~: ~ ~:~:~:~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ ~. ~ .~. ~ ~ ~ ~ .~ ~ ~ ~. ~ _. ~ ~ . . ~. ~ ~. . . ~ -. .. ~ ~ ~ ~ ~ ~ ~ ~T~h~e~se~ ~ ~h~i~h~l:~y~ ~ ~p~rod~t~i~v~e~e~cos~ys~m~s~;~ ~a~re~:~freq~ue~o;~t~y~;~s~u~bi~e~ed~to~a~n~a~n:- ~ ~nua~l~ ~f~l~oodl pe~r~iod:* ~ ~Th~e~a~mp~l~it~u~de and: ~gula~rity~ ~of ~fl~oodi~n~g ~am of ~ ~utmost I ~ ~ ~ ~ i ~ m ~ ~ p o : r t a ~ n ~ c e ~ ~ I ; i n : I ~ t h ~ e : s ~ e I ~ f I ~ u ~ ~ c t ~ u : a ~ t ~ i I n ~ g ~ ~ ~ s ~ y ~ s ~ e m : s I ~ I ~ ~ ~ ~ ~ w ~ h ~ ~ e ~ e ~ ~ ~ I c ~ o m ~ m ~ u ~ n ~ ~ i t i ~ ~ ~ s : - ~ a i r e I a d J ~ ~ ~ s ~ t e d r . : :~ ~to~t 1-e~|~ ~se~-of:~seasona ~ var~a;tio~ns~ I n ~water eve~ ~s. ~ ~ne~ ~rearran~ge~me~nt~ ~ot~: ~: ~:~hvd~ro:l:oR:'c=::: Da~tter:n~s~::~thro~:h~:..:~hu~m~a.~ i~i n~rve~n~ti.~n~wi l~l~ ~ res~u~lt:~:i~n :~:~l~a~re:e-s~c~ale~ : :: :~ec~olo:gica~ I cha~n~ge~s :~ ~w:h~o~se:~ ::~co~n~se~q:ue~n:c~s~:~c:a~n;n:ot~:~b~e~:~we~l~:l;~:~::~u no~e~rs:tood~ :~:~o:r:~ :~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ : ~ ~ predic~tedl~:a~t~:~our:lprese~n~t:;ll~evel: ~ofl~ u~nd-e:rsta~n~din~g~.~l ~ ~ ~ ~ ~ ~ : ~::: ~ ~i ~T~here ~i:~s a~n~ l~l r~ent ~n~ee~d f~r i:accel~e:rated:: ires~e:a~rc~hli::~:o~nii~wetl~::a~n~d~s: ~be~c~aiu:se: ::: :1:~ ::~f~:~:th~ ~tr`?~m~n~fi:~:~:~:fi~V~l~n~m~n~t: n~r~:~:res ~these:~ ~ec~3s~v~m~ t:a~c~e ~-~ ~ A~I- 1~ ~ th~o-u~g~h~::efforts~ ~:~to :~ protect wellands ~ hav~e increased~ ~ they con~ti~n~u~a~ lto~l~be~:~:~:~:~ ~ , : : ~ a i t e r e ~ d : ~ t h ~ ~ r o ~ ~ h d ~ ~ - r a i : n a £ ~ e . ~ : : ~ d r ~ d ~ ~ i ~ n ~ ~ £ ~ , ~ ~ ~ ~ : ~ i ~ ~ m ~ ~ D o ~ u ~ n d ~ m e ~ n t , ~ : I t : h e : r ~ ~ m ~ a ~ i ~ I ~ a n : d ~ ~ ~ n ~ u t r i e ~ n ~ t ~ : ~ ~ ~ ~ ~ ~ a~d:d~i t~o n~S:r~:~:~ :~ t~i~l~l~:n~:~:~: ~a~n~d ~:: co~n~ve~rsi~o:n~::: ~to~ ~ ~ag~r~c~u~l~tu~re .~:~1~ h~e~ :~v~al~ue~ ~a~n-~t~h~e ~ ~ ~ i::;: ~ m~a~n~a~g~em~e~n~ii of w~et~l:antl~s~ ~i~n~ ~thei r ~natural Istate h~inge on :~ bas~ic hyd~rol:og-ic~ ~:~:: ~:::s~t~u~d::ies~.: ::~::

178 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES meets in contaminated aquifers are just beginning. The quantifica- tion of microbial effects on subsurface transport processes and the feedback mechanism of these processes on microbial ecology as well are still in their initial stages of development. An example of such a feedback starts with a decrease in soil per- meability caused by ion-exchange reactions (which brings about clay dispersion) or microbial action (which produces pore clogging by mucilaginous organics). In either case, the decrease in permeability decreases water fluxes. This, in turn, reduces the rate and extent of the original ion-exchange reactions or microbial activities. Will a steady state eventually be created? Or will transport stop entirely? Answers to these questions are of considerable interest in connection with soil formation, ore deposition, and pollutant migration, to name but a few applications. Microbial populations can strongly influence rates of transport and the transformation of synthetic organic compounds. The dynamics of this phenomenon are not yet well understood, especially at the field scale. Nevertheless, it is clear that they are annually dependent on the growth mechanisms of the microbe colonies, which are them- selves linked to complex hydrologic and geochemical interactions. There is a need to develop basic understanding of this complex system, including the relationships among its parameterizations at different scales of observation. HYDROLOGY AND CHEMICAL PROCESSES Introduction Chemical processes in the hydrosphere determine the composition of natural waters, control rates of chemical weathering and the geo- chemical cycles of most elements, and influence the chemistry of both the earth's crust and its atmosphere. Trace atmospheric gases emanate in large part from aquatic and wetland systems, influencing climate and hence the hydrologic cycle itself. Finally, the chemical composition of the water, as much as its quantity, determines its ability to support life. Chemical and biological processes in water are tightly intertwined, influencing each other and determining not only the "quality" of the water but also the nature of life on the planet. Understanding the interactions of chemical and hydrologic pro- cesses by which the chemistry of the earth's waters and atmosphere is shaped is no longer a matter of purely academic concern. Today, the very ability of our planet to sustain a stable environment for life is challenged by human interventions, chemical and hydrologic, on a

SOME CRITICAL AND EMERGING AREAS 179 global scale. The dramatic effect of these chemicals on the water quality of streams can be seen in Figure 3.26, which shows a nearly tenfold increase in the flux of chloride during the last century for the Rhine River. Hydrologists, chemists, and biologists face the challenging task of understanding earth processes that inseparably involve concepts from each discipline. In addition to demanding interdisciplinary synthesis, the frontier questions of environmental chemistry require additional emphases within the traditional disciplines themselves. Hydrologists will need to focus more on the actual pathways and residence times of indi- vidual water parcels in different environmental compartments. A1- though many traditional problems in hydrology (e.g., large-scale water balances, flood forecasting, and ground water resource evaluation) do not require such knowledge, chemical considerations demand knowledge of water flow paths and hydraulic residence times. Knowing where a parcel of water has been, and for how long, often is the key to understanding its chemical evolution. Recognition and incorporation of hydrology into conceptual mod- els of natural water chemistry will require environmental chemists to advance the state of existing chemical kinetic models. Historically, the dominant paradigm of aquatic chemistry the study of chemical 350 kg/s Cl 300 o us 250 c: I LL o X 200 150 100 50 o 1 l or far I I I I I I 1890 1910 1930 1950 1970 1990 YEAR · I ~ FIGURE 3.26 Changing chloride flux in the Rhine River at the border of The Nether- lands and Germany. SOURCE: Personal communication from T. S. Uiterkamp, 1985 Annual Report of the Cooperating Rhine and Meuse Drinking Water Companies.

180 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES processes in natural waters has been that of chemical equilibrium. Because most reactions were considered very fast (e.g., acid-base re- actions over microseconds) or very slow (e.g., geological alteration of minerals over millennia) compared to human time scales, the historic focus has been on (pseudo) equilibrium presumably achieved among the many components of aquatic systems over periods of hours to years. This convenient paradigm must now be reconciled with the realization that the time scales of many important chemical processes are in fact within the range of pertinent hydrologic residence times. Some reactions that were thought to be fast have turned out to take hours; some otherwise slow reactions are in fact accelerated by unforeseen catalytic, photochemical, or biochemical mechanisms. In summary, the extent of chemical reaction in environmental wa- ter is determined by the chemical rates of reaction relative to the hydrologic residence times, and these quantities can be of similar magnitude. The need for new environmental syntheses, drawing upon and expanding the scope of both hydrology and chemistry, is abun- dantly clear. Some Frontier Topics Effects of Acid Rain The 1980s saw a rise of public awareness that industrial society is beginning to influence the earth's chemistry on a regional and global scale. The "acid rain" issue is a dramatic example. Surface water acidity and associated toxicity to fish have led the public's list of concerns. More recently, concern has also grown about the nutrient effects of nitric acid deposition and possible resulting eutrophication of natural waters (e.g., EDF, 1988~. Understanding hydrology is central to understanding and predicting acid rain effects. At every step along the pathway of water, from the formation of precipitation to the eventual discharge to the oceans, crucial and challenging questions remain. Precipitation Chemistry Although a broad understanding of the factors that determine the chemical composition of rain and other atmospheric deposition exists, the available data base limits the development of truly quantitative approaches. Research using rainfall composition data as tracers of the hydrologic cycle offers opportunities to understand better the

SOME CRITICAL AND EMERGING AREAS 181 relationship between rainfall composition and the chemistry of soils, surface water, and ground water. What are the mechan isms whereby atmospheric po} ~ ut- ants are incorporated into rain? Rain is not pure, distilled water. Both rain and snow contain a wide range of dissolved and suspended materials, both organic and inorganic. However, it has only been during the last two decades that analytical facilities have been capable of demonstrating the great variety and range in concentration of substances included in precipitation. Gases, liquid droplets, and particulates are released into the atmosphere from natural and anthropogenic sources on the land surface. These emissions differ widely in composition from place to place and with time. Doing atmospheric transport, gases and particles interact physically and chemically under the influence of radiation, temperature, and humidity, yielding new compounds. At any particular site, the com- position of the atmosphere will reflect several factors, including the direction of the wind, the character of the sources, the extent of mix- ing from multiple sources, and the chemical reactions that have occurred. When snow forms in the atmosphere, it can incorporate particles and gases, some of which are soluble in water. During descent, if temperatures are high enough, the snow will change to rain. Rain selectively scavenges both gases and particles from the air as it falls, and becomes enriched in these materials to a degree that will vary with rainfall intensity, chemistry of the dissolved material, and history of the air mass. If snow instead accumulates on the ground, it will serve as a substrate for dry deposition from the atmosphere, and, upon melting, will dissolve a part of these deposits. Recognition of acid rain as a problem in Europe and North America has indeed greatly stimulated interest in the chemistry of atmospheric deposition. This interest creates opportunities not only for solving practical problems, but also for advancing understanding of the basic chemical processes. There has been a major increase in research on the sources and transport of the chemicals removed from the atmo- sphere by rainfall, as well as investigations of the mechanisms whereby atmospheric pollutants are incorporated into rain and snow. That research, however, has not yet produced quantitative models with which the composition of wet deposition can be predicted on the basis of the factors noted above.

182 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES thy ~~ ~~ ~~ ~~ ~ ~~ ' ~~ ~~: ~ ~ ~~ ~~ ~~ ~~' :~:~:~::~: ~ :: ~~:f~d~D~may~h~ave~ ¢r~the~:~n~aturai~ro-~ ~:~ 'if ~ ~ ~~ ~ .: ~~ ~ ~ ~~ ~ ~~ :~ ~~ ~~ .~ ~~ ~ ~ ~~ ~ ~~ ~~ ~ ~~ ~~:~ ~.:~.

SOME CRITICAL AND EMERGING AREAS 183 Snowpack Chemistry What are the measurement techniques and modeling schemes necessary to better understand the spatial and temporal distribution of the rates of chemical release from snow throughout a catchment? Snowflakes may form around microscopic pollutant particles in the atmosphere. Once they have served to initiate the condensation process, these particles become encased in the growing ice crystal. As the snowflakes fall, they may scavenge pollutants from the atmo- sphere. Once they form a snow cover, they generally receive a continuous input of pollutants by dry deposition. The strengths of these inputs can be so great that, in some locations, it is possible to tell the direc- tion of air movement by the color of the snow: Saharan dust reaches the snow-covered Alps, and the Scottish mountains can be tinted black from coal burning in England. As the seasonal snow cover thickens with the included impurities,

184 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES the snow undergoes continuous metamorphism (Figure 3.27), which has been hypothesized to move the impurities to crystal surfaces. This phenomenon is believed to occur because of the continuous grain growth that takes place in snow and the constant exchange of ice mass from grain to grain as water vapor moves down the temperature gradient in dry snow. As ice crystals grow, they should reject almost all solute impurities; thus snow grains undergo purification from the onset of melt. The availability of impurities on the grain surfaces contributes to "acid shock," which is observed commonly now but was first identi- fied as a major problem only in 1978 (Iohannessen and Hendriksen, 1978~. The initial fraction of meltwater causes the sudden removal of a large fraction of the acid-producing solutes that have accumulated in snow over the winter months. This causes a sudden surge of polluted meltwater as a direct result of the concentration of impurities on the grain surfaces during the metamorphism described above. Events during winter such as midseason melt can concentrate impurities near the bottom of snow cover to produce more rapid removal. Thus the events during any particular winter can have a considerable effect on the details of an acid flush. Large variations In the chemical contamination of snow occur vertically over the scale of the thickness of snow cover and laterally over the regional scale. Many data, gathered under demanding conditions, are necessary to provide a clear picture of the level of contamination and the mobility of the contaminants. 0y0°~ 0 . ~ ~ 0 0 ~ ~ O O FIGURE 3.27 Snowflakes are destroyed rapidly by metamorphism. In the process, contaminants, such as acids, are redistributed and concentrated in a complex fashion. SOURCE: Reprinted from Bader et al. (1939) courtesy of U.S. Snow, Ice, and Perma- frost Research Establishment.

SOME CRITICAL AND EMERGING AREAS 185 Because of the wide range of weather patterns in different areas and in different years, all of the possibilities are not well understood, and the consequences of increasing acid deposition in areas that are now relatively acid-free are not yet predictable. These uncertainties arise in part because of large variations that occur in snow accumulation and melt rate, even in small alpine catchments. The spatial and tem- poral distribution of the rates of chemical release from snow throughout a catchment must be evaluated. This evaluation will require data on the initial distribution of chemicals and their elusion from the snow- pack in response to melt and metamorphism. Changes in elevation and in aspect produce such large changes in energy budget factors (such as solar radiation) that different parts of a catchment often melt out during different parts of a season. The effect of the acidic meltwater also varies spatially over a watershed (e.g., poor buffering in relatively unweathered zones and the release of trace metals from soils). Even if meltwater penetration into lakes produces little effect (for example, if the lakes are well stratified), the resulting flush of acidic meltwater down their outlet streams may not be acceptable. Fate of Acid Deposition in the Soil Environment What is the relative importance of different flow paths and residence times to the chemistry of subsurface water? Although rain and meltwater may in part enter a stream directly, in many areas most of the water enters the soil environment prior to emerging as streamflow. Subsurface flow pathways bring water into contact with several effective agents of chemical change. Quantitative ignorance of these pathways is a major obstacle to understanding the chemistry of the water when it re-emerges as streamflow. Weathering, microbial transformations, production of humic materials, and plant uptake profoundly influence subsurface water chemistry; yet, models of each are in their infancy. Moreover, their relative importance is governed as much by hydrologic flow paths as by purely chemical and biological factors. Figure 3.28 diagrams the interrelated physicochemical phenomena that combine to control acidity in the soil water (the soil solution). In addition to rain and melted snow, the physical inputs can include fog and dry deposition (particles and acidic gases such as sulfur dioxide and nitric acid vapor). Deposition comes both from direct atmospheric

186 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Dryfall | | Wetfall MEL Organic H+(aq) Matters Soil Solution Bio-uptake OWL gnterflow ~ = 1 CO2(9) ~ ~;;;, | Polymers | Mineral Weathering FIGURE 3.28 Some physicochemical factors controlling the acidity of water in soils. The close interaction of both chemical and hydrologic processes is involved in the ultimate determination of soil water chemistry. SOURCE: Reprinted, by permission, from Sposito (1989b). Copyright @ 1989 by Oxford University Press. inputs and from throughfall below the vegetation canopy, and mea- surements must be made on time scales that are relevant to the run- off cycle and on space scales that reflect catchment physiography. These same considerations apply to acid-exporting processes (e.g., volatilization, eolian transport, and streamflow). The important chemical phenomena that influence the acidity in the soil water are (1) acid-base reactions involving carbonic acid, soil humus, and mineral weathering products (e.g., aluminum-hydroxy polymers); (2) ion-exchange and mineral weathering reactions; (3) vegetational uptake and release of ions; and (4) microbiologically mediated processes (such as nitrate immobilization and sulfate reduction). Although carbon dioxide concentrations in the soil atmosphere exceed those in the open atmosphere by more than 1 order of magnitude, and soil humus is the single most important repository of acidity in soil, almost no quantitative, catchment-scale data exist on soil carbon dioxide characteristics, on the rates of production and decomposition of humus, and on humus-mediated effects on soil acidity. Mineral weathering rates, typically investigated in the field through geochemical mass balance techniques, range over at least an order of magnitude for catchments in the United States, and their functional relationship to microscale chemical kinetics and mechanisms is es- sentially unknown. Extrapolation of the existing data base to unstudied catchments is not possible, particularly in light of the oversimplified models used to interpret geochemical mass balance data (e.g., idealized

SOME CRITICAL AND EMERGING AREAS 187 mineralogy, constant reaction stoichiometries, and constant rates of transformation). Biological processes important to the regulation of acidity in soils include nutrient uptake and release and the microbial mediation of chemical reactions. The soil environment near plant roots can become either acidified or more alkaline, depending on the overall nutrient uptake and release characteristics of the plant. Fluctuations in soil pH near roots of as much as two pH units have been observed. These processes are not well characterized, especially at the catchment scale. Similarly, the effect of microbial populations on chemical reactions that consume or produce acidity is not known on the catchment scale. Further, the implications of the perennial but gradually changing nature of forest biota have not been worked out. Perhaps most importantly of all, the flow paths and residence times of water in this complex subsurface environment are not known, de- spite the overriding importance of knowing in which soil layers or microhabitats, and for how long, the soil water resides. This knowl- edge gap is especially evident in current acid-rain-effect models, which are deemed important to the eventual formulation of national acid rain regulatory policy. In such models, for lack of knowledge the water flow paths are represented arbitrarily or are omitted entirely (i.e., a whole catchment may be treated as if it were a fully mixed vessel of soil particles and water). There is a pressing need for closer integration of hydrology with environmental chemistry, as well as for advances in the tools used to map out water flow pathways in the soil environment. Contaminant Fate and Transport The frontier issues in ground water and soil water contaminant fate and transport share much with the issues of subsurface acid deposition effects described earlier. Usually, however, the chemicals of concern issue from point sources. Many are toxic, and the hydrogeologic setting is often that of an economically valued aquifer used for water supply. One important frontier area encompasses the problems of heterogeneity at several scales. Others involve the complexity of interaction between reactive solutes and soil or aquifer solids, the possible transport of very small particles (colloids), and the effects of microbial communities on both contaminant fate and subsurface per- meability. These frontier problems are discussed in more detail in a previous section, "Hydrology and the Earth's Crust." They bear reiteration as

188 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES a set of issues that is of particular relevance to current concerns about hazardous waste in the environment. Added to these issues is the critical role of the biogeochemical cycles that couple terrestrial eco- systems to subsurface runoff flow paths. The mechanisms, mass transfer rates, and mass storage capacities in these flow paths and cycles vary with the chemical element concerned and exhibit significant spatial and temporal variability within and among catchments. Their key importance to water quality management derives from the natural pathways of detoxification they can provide for potentially hazardous chemical compounds deposited on land. Better knowledge of the flow paths of water under differing water loading rates, of the chemical character of the labile pool of a compound in soils, and of the factors influencing bioturnover rate are necessary before we can predict the quality of receiving waters to be managed for beneficial human use. Sediments also play an important and incompletely understood role in the behavior of chemicals in surface waters. Sediments range widely in grain size, mineralogy, surface area, organic matter content, extent of chemical reactivity, and rate of reaction with surface water solutes. Some move in suspension, whereas others are transported slowly over the streambed or are temporarily immobile in stream bottom deposits. Sediments may control the concentration of a solute dissolved in water or may have little effect on water quality, depending on sediment reactivity, the extent of sediment-water contact, and the chemical characteristics of the solute. For example, hydrous oxides of iron and manganese in sediments bind toxic metals (e.g., lead). Solid organic matter can react strongly, not only with organic solutes, but also with inorganic ions. Clay minerals, with their small size and large surface areas, serve commonly as substrates for deposits of various substances (e.g., iron and manganese oxides, as well as organic mat- ter). Such deposition greatly enhances the availability of these oxides and organic materials for subsequent reaction with dissolved surface water solutes. Clay minerals themselves carry adsorbed ions that can be exchanged with other ions in solution, thereby affecting water quality. Thus one must understand sediment-solution interactions in order to understand the chemistry of surface waters. What is the relative rate of transport of various sizes of polluted aggregates and grains in stream waters, and how long are such particles stored at various locations before moving on in the channel system ?

SOME CRITICAL AND EMERGING AREAS How much transfer of adsorbed materials from one grain to another occurs during streambecl storage, with cliffer- ing interbed flow and dissolved oxygen availability? 189 The degree of affinity between a solute and sediments can vary greatly, depending on the nature of the solute and the characteristics of the sediment. Some solutes, including many toxic metals, like mercury, can be adsorbed very strongly by sediments. Others, like sodium, are held weakly. Changing either the concentration or the chemical form of the adsorbing solute, or altering the composition of a surface water, can alter radically the affinity with which a solute is held. Thus, if clean water flushes a polluted stream, some release of pollutants from the sediments will occur even though the pollutants are adsorbed strongly. If the stream discharge also increases, the bed sediments may be disturbed, allowing resuspension of interstitial fine particles into the water column and migration of coarser particles as bed load. Alternatively, if labile organic matter and sediments containing toxic metals bound in iron and manganese coatings are deposited together on the bed under quiescent conditions, an oxygen-depleted, reducing environment can develop, causing dissolution of the iron and manganese oxides and release of these metals into the stream water. Organic pollutants can also be changed during storage in the bed, and, when the next stream rise occurs, they may be transported in an altered chemical form. Sediments derived from commonly occurring landforms can be expected to contain fine-grained aggregates ranging from silt size up to boulder size. Chemical reactions between these aggregates and solutes are influenced not only by the transport of reacting solutes to the exterior surface of the aggregate (film diffusion) and the reaction time (often very short), but also by the time needed for the participating ions to diffuse into and out of the aggregates (particle diffusion). This means that a surface water system can develop a significant "memory"; therefore a common simplifying assumption, that adsorbed solutes are transported almost entirely in dispersed fine-grained sediments, can be very wrong. The importance of sediments in concentrating chemical elements from solution is also recognized. When aquatic organisms ingest polluted sediments, the pollutants can become incorporated into tissues, and, as smaller organisms are consumed by larger organisms along the food chain, the pollutants can be concentrated to the point where human beings, the ultimate consumers, can be harmed. These and

190 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES many other issues remain to be addressed before a thorough under- standing can be achieved of how specific solids and solutes interact and move through surface water systems. There are many opportunities to gain an improved basic knowledge of the operation of natural water systems while contributing to solving a major problem for an industrial society that of water quality. Global Chemical Cycles What are the feedback links that control the interaction between the hydrologic cycle and the global chemical cycles of crucial elements, such as carbon and nitrogen? Several elements have biogeochemical cycles that are important at the planetary scale and are linked to the habitability of the planet as well as to the distribution and productivity of its ecosystems. The geochemistry of carbon provides a clear example of the im- portance of global elemental cycles in hydrology. As greenhouse gases in the stratosphere, carbon dioxide and methane are of great interest to climatologists and hydrologists. Carbon dioxide is also the dominant natural acid in the hydrosphere, and its concentration in water influences the weathering of minerals. In addition, fixation of carbon dioxide by photosynthesis and its regeneration by respira- tion are among the very principles of life on the earth. Thus major processes in the atmosphere, hydrosphere, lithosphere, and biosphere are linked, influencing each other through the geochemical cycle of carbon. Ultimately, our general circulation models of the atmosphere will have to be interfaced not only with ocean circulation models (more physics), but also with geochemical models of the cycles of key elements such as carbon (chemistry). Nitrogen is a second element whose cycling is intimately linked to hydrology and whose movement and transformation profoundly influence life on the earth. Biologically available nitrogen (e.g., nitrogen as ammonium or nitrate) is a major required nutrient for all life. Its availability is believed by many to limit the production of the oceans as well as of many terrestrial systems; its excess can initiate eutrophication and ecosystem degradation (as in the Chesapeake Bay). In its gaseous forms, nitrogen as nitrogen dioxide is an ingredient in the production of photochemical smog and health-threatening ground-level ozone, and nitrogen as nitrous oxide both attacks the stratospheric ozone shield and contributes to the greenhouse effect.

SOME CRITICAL AND EMERGING AREAS 191 The major biological transformations of nitrogen occur in, or are closely tied to, soil water and surface water systems. The hydrologic cycle transports biologically available nitrogen, as well as determines conditions toxic or anoxic, long or short water residence times, moist or dry) that control the transformations. As with carbon, the global cycles of this element are intimately linked with hydrology. Several of the radiatively active gases implicated in global climate change are produced in anoxic systems whose existence hinges on the extent of water saturation. Our present ability to predict the response of this hydrologic-chemical-biological system to perturbations is almost nil. An example is the problem of methane release from wetlands. Methane gas follows water vapor and carbon dioxide in importance as a greenhouse gas. Like carbon dioxide, its presence In the a~anosphere is growing, its concentration increasing at a rate of about 1.7 percent per year (Figure 3.29~. Major sources are believed to include combustion, 350 340 - o 330 By IL O 320 o CM C' 310 300 . Art ~ 1 1 1 1955 1960 1965 1970 YEAR 1975 1980 1985 1.61 1.62 - z o 1.58 ~ z Ad o 1.52 IN C: 1.50 FIGURE 3.29 Worldwide concentrations of tropospheric carbon dioxide (CO2), sampled from 1958 through 1984 at the Mauna Loa Observatory, Hawaii, and of methane (CH4), derived from simultaneous Northern and Southern Hemisphere samples of surface air from 1978 through 1984. Units of measurement are parts per million, by volume. Methane and carbon dioxide are both important greenhouse gases, and both are intrinsic in biospheric processes. SOURCE: Carbon dioxide data courtesy of C. D. Keeling, Scripps Institution of Oceanography; methane data courtesy of D. R. Blake, NASA/ National Space Technology Laboratories, and F. S. Rowland, University of California at Irvine (UCAR, 1985). Published by University Corporation for Atmospheric Re- search, Boulder, Colorado.

192 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES fossil deposits, the rumen of cattle, and wet ecosystems such as rice paddies and natural wetlands. In wetlands, methane is produced in waterlogged environments but in close proximity to the atmosphere, thus facilitating release to the air. The complexity of methane pro- duction and release by wetlands is illustrated by Figure 3.30. Vegetation and waterlogged sediment together provide oxygen-depleted condi- tions that permit the generation of methane by microbes. The same sediment controls the export of methane (which can occur by dispersion, convection, and bubbling), in part by harboring methane-consuming microbes near the surface. ~ ' ~ ~ ,~- CO2 Fixation V. Atmospheric Release ~- UNSATURATED ZONE A ~ - a_ Vl. ~ (yes 111. Diffusion Plant-Mediated l CH4 Export _ ~ IV. Oxidation to CO2 SATURATED ZONE o f o o o o o o o 11. Ebullition (rapid) Diffusion, Convection, and Dispersion (slow) So o o by= 1. Methanogenesis FIGURE 3.30 Processes involved in methane evolution from northern peatlands. Methane produced by bacteria (I) may be transported toward the surface by several physical processes (II). Methane reaching the unsaturated zone faces competing fates of reoxidation (IV) or physical transport (III) to the free atmosphere (V); plants (VI) may also trans- port methane upward. Hydrology directly affects each step of the process.

SOME CRITICAL AND EMERGING AREAS 193 _ :: ::::~:: :: : ::::: A: If: ::: ::~: ~ ::::: :: ::~ :~ ::::: ::::: :::: i: :: :: :~: ::~ ~ :~: ~ i:: ::::~: ::::::: ~ ~ ::::: :: ~ : ~ :: :::~::: i:: ::::: :::: :: ::: ::~ :~::::: ::: ::: ~ :~ :: :::: : ::::: i: ::~ ::: :~ ~ : :::: :: :~ : i: : :::: : ::: : ::: ~~ :: ~ : :: :: ::::: ~ :: :~: : : :: :: :~:::~:: ::::~: : ::::: ::::: : :: :: ::: : ::: : :: ::: :::::::: ::::::: :: :: ::: :: :::::: : ::: ~ : ~ ::~: :::: :: :~: :::: : :: : : ::: : : i: : : ::: : ::: :::: : :: : :: :: : :: :::::::: ::::: ::::: :::::: ~ :::::: :~: : :: i:: :: :::::: ~ ::~: :: i: ~ : ::::: : : ::: ~ : ::: :::: :~ ::: :: :: :: : : ~ :: :: ::: :::: :: :: :: ~:~:::::~:~: :::: ~:~:~:~ aft: :~: ~~: :::: ~ ~~ ~~ : ::::::: :~ :: ::::: ::: ::: :~: :: ~:~ ~ :~^R:~:~T~:::~: ~~ ~ A~:~::~I: ::C:~:: :: ~ :: i:: :~ : ::: ~ :: :: . ::: ~ : ~ : : i: ~ ~ : : ~ .~ - i % ~ i: ., : :~:~% ~ :: ~ :~: ~ : i: ~ ~ ~ ~ i: : :: ~ :: ~~ ~~ i: :: ~ : ~ i: ~ : :: ~ : ~ : : ~ ~ :~ ~ : ~ : :: : ~ : : : : : ::: ::: :~ :: :: :~: ~~: : ~ :~::::: ::: ~ ~ :: ::: :: ::: : ~ ~ :: ~~~ ::~_ :, t~ ~~: :~: : :~ ~: i: ~ :~ ~ :~ i: : : : :: : :: i: ~ ~ ~ ~ :~ ~ :~: ::: ::~ i:: ::: ::: :: ::~: :~:: ::: : ~ ::~ : :::: i: : :~::: :~:: :: :~ :~ ::: : i: i::: : :: A: :: Hi:: ::: ~ ~ ~ :~ : :: :: :::: ::: : :: : : :: ~ : ~~ :: :: ~ ~ ~ If, :: :: . i:, :~:: _~ ~ : ~ .: ~ ~ :. :: ~ ~ , ~ , ~ ~ ~ : . . . ~~ ~~ ' .O~e:ll~ M. 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194 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Hydrologic activity profoundly influences each step of the overall process. Water movement determines both convective and disper- sive methane movement. Water table height controls the proportion of organic sediment that is saturated, anoxic, and methane-producing, relative to the upper, unsaturated, methane-consuming layer. Small (tens of centimeters) changes in water table height can shift a wet- land from a methane-evolving to a methane-consuming system. Po- tentially sensitive feedback links may thus exist, perhaps on a global scale, whereby methane evolution helps drive climate change, which in turn, via hydrologic effects, alters methane evolution. To understand such a complex system will require the full integra- tion of chemical, hydrologic, and biological disciplines. This frontier task has not yet been seriously undertaken and is one of several important challenges facing the field of hydrology in the next decades. HYDROLOGY AND APPLIED MATHEMATICS Introduction Experimentation/observation and theorization are the two pillars on which much of modern science and technology rest. Mathematics provides the fundamental logical framework for developing systematic and logically consistent theories of physical phenomena. The early attempts at a quantitative understanding of hydrologic phenomena were directed toward laboratory experimentation of individual pro- cesses, for example, water movement over land, in channels, and into and beneath the surface, and their mathematical characterizations. These efforts led to a fairly comprehensive laboratory-based understanding of many individual components of the hydrologic cycle. At larger space and time scales, controlled experimentation be- comes more difficult, and at the largest scales, all but impossible. Then nature itself has to be treated as a laboratory for taking observations of the natural phenomena. However, in a natural laboratory it is impractical to isolate and investigate individual effects on a given phenomenon. So one must frequently be content to observe the physical phenomenon at hand rather than all the individual processes that govern that phenomenon. Owing to the highly nonlinear nature of hydrologic processes, and their mutual interactions, typical observa- tions in space and time show a high degree of variability over a very wide range of space and time scales. A major challenge currently facing hydrologic science is to uncover the physical message of ob- servations at space and time scales other than the laboratory scale

SOME CRITICAL AND EMERGING AREAS 195 and develop logically consistent and testable mathematical theories of hydrologic phenomena. Specifically, theoretical studies are undertaken for identifying and formulating general mathematical constructs and providing testable theories for the purposes of (1) providing theoretical interpretations and explanations of empirically observed regularities and structures, (2) unifying disjoint empirical relationships and/or processes across scales, (3) discovering hidden order in physical phenomena, e.g., symmetries, and invariance across scales, that specific models must obey, (4) providing guidelines for new measurements and experimentation for testing general, but important, mathematical hypotheses, and (5) providing qualitative theoretical insights to help in understanding the key features of a physical phenomenon and in making predictions. Recent advances in the mathematics of probability and stochastic processes and in nonlinear equations and numerical methods and major growth in computing capabilities and in remote sensing technology all point toward new and exciting opportunities in the development of hydrologic theories over a broad range of space and time scales. In this section, some of the emerging new directions in theoretical investigations of hydrologic phenomena are described to illustrate the ideas and objectives listed above. Some Frontier Topics Scaling and' Multiscaling Invariance in Spatial Variability of Hydrologic Processes "This paper is an invitation for the reader to solve the problems of pure and applied geometry involved in its approach to the notion of length and shape rather than an attempt of the author to answer the questions by himself." So reads the abstract to the classic paper by Hugo Steinhaus (1954) entitled "Length, Shape, and Area." The problems of "pure and applied geometry" that had captured the attention of one of this century's most eminent mathematicians centered on a hydrology problem. Specifically, Steinhaus sought to determine a practical means of assigning "length" to rivers described by maps drawn at different scales under the full recognition of the fact that rivers have no intrinsic length scale. A contemporary statement of this problem would begin with the recognition that the river is a naturally occurring "fractal," or exemplifies the "paradox of length," in the words of Steinhaus, and then ask how theoretically meaningful measurements of such structures can be had. The problem has a

196 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES depth that makes the invitation no less important to hydrologic inter- ests today than it was some 35 years ago. So how does one contend with the "issues of scale" that are so pervasive in hydrologic phenomena? For the river problem, Steinhaus offered a probabilistic method that continues to hold the promise of a foundation for revolutionary new approaches to measurement. An- other perspective is illustrated by the related work of Albert Einstein (1926) in his classic paper entitled "The Cause of the Formation of Meanders in the Courses of Rivers and of the So-called Bear's Law." This work holds the fundamental view that, in spite of the fractal paradox of length, there are scales on which regularity may be both measured and physically explained. This view is explored by Einstein in his qualitative physical explanation of the cause of formation of meanders and of the observation that meander frequency decreases with an increase in river cross section. The interplay between probability, physics, and geometry is by now deeply rooted in hydrologic theories and practice. While stochastic approaches to the analysis of average properties of single rivers are prominent in the work done by Luna B. Leopold, Walter B. Langbein, and others in hydrology in the 1950s and 1960s, the search for the next step is at the very frontier of contemporary science and mathematics (Leopold and Langbein, 1962~. And as one moves from the case of single rivers to that of the multichanneled branching networks found in river basins, the interplay becomes all the more exciting. What are the scaling and multiscaling properties of three- dimensional drainage networks? In his paper entitled "Erosional Development of Streams and Their Drainage Basins: Hydrophysical Approach to Qualitative Morphology," Robert E. Horton (1945) devised an ordering scheme for encoding and measuring the degree of complexity of bifurcations in river networks that displayed observable patterns of pronounced regularity. These observations influenced in no small way the developments of quantitative- empirical geomorphology over the next two decades. However, it was not until the late 1960s that Horton's observations were interpreted statistically by R. L. Shreve in a series of theoretical papers. The manner of the statistical interpretation leads once again to unresolved issues of deep physical, mathematical, and practical importance. For example, Leopold recognized the simple utility of Horton's law of stream numbers for estimating total lengths of rivers from maps; based

SOME CRITICAL AND EMERGING AREAS 197 on a simple geometric progression uncovered by Horton, the esti- mated total length of rivers in the United States is roughly 2 million to 3 million miles (Leopold, 1962~. However, the accuracy of such an estimate is largely unknown. Problems pertaining to rigorously es- tablishing laws of averages and the determination of error bars (cen- tral limit problems) for such estimates represent new mathematical territory that evidently holds significant new results for both hydrology and probability theory. Moreover, the extensions of the statistical theory to hydraulic-geometric quantities, such as river slopes, widths, depths, flows, and sediments, in networks involve the very essence of the scale issues embedded in the works of Steinhaus and Einstein. Scaling methods have been and continue to be developed and ex- plored in physical-statistical theories to describe properties of matter at phase transition, turbulence in the atmosphere, unstable biological populations, the Hurst effect in river flow statistics, and so on. An example that conveys the depth of such approaches is furnished by the following modern approach to the classical problem of Holtsmark. Specifically, one considers a random suspension of electrical charges in the atmosphere and asks for the probability distribution of the force exerted on a unit charge located at a fixed point in three-dimen- sional space. Now, doubling, tripling, and so on, the density p (charge per unit volume) corresponds to resealing the length ~ by an inverse cube root of two, three, and so on. If the Coulomb inverse square force law of classical physics is assumed, then the probability distribution of force at a given scale of ~ units is standardized under resealing by t2/3. The statistical scaling exponent 2/3 combines the physics of inverse square law with the geometry of space dimension. If the locations of the charges are taken to be statistically independent, then the probability distribution of the force is uniquely determined by the exponent 2/3. Such is the potential for modern scaling methods in physical theories. The search for an invariance property across scales as a basic hidden order in hydrologic phenomena, to guide development of specific models and new efforts in measurements, is one of the main themes of hydrologic science. Modern approaches to problems in hydrology are moving toward scaling theories as much out of pragmatic necessity as out of pure scientific curiosity and rigor. This is true whether one looks at current theoretical efforts dealing with water in the atmosphere, on the surface, or beneath the ground. The pragmatic reason is that hydrologic un- derstanding and predictions are needed over a broad range of scales, ranging from 100 m to 10,000 km in space and from a few minutes to many years in time. Over such a range, measurements are hard to make and hard to follow because of noise and nonlinearity. Therefore

198 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES it is all the more important to make theoretically meaningful obser- vations on such natural systems that are subject to the paradox of measurement. The purely scientific reason happens to be the same one. If the spatial and/or temporal variabilities embody a fundamental hidden order that manifests itself across a wide range of scales as an invariance property, then it must be formulated mathematically and tested empirically, for the presence of such a property must be obeyed by more specific mathematical models. Recent investigations of the scaling properties of river networks have provided new theoretical insights into the widely known empirical feature that, on the average, rivers drained by larger drainage basins have flatter slopes than those drained by smaller basins. Specifically, the empirical mathematical relationship characterizing this feature has been shown to follow as a consequence of the simple scaling invariance property of river slopes in a channel network (see the earlier discussion in this chapter's section titled "Hydrology and Landforms"~. The first-order predictions of the theory based on simple scaling are remarkably close to empirical observations, but data quite clearly suggest the need for generalizations. A promising avenue, called multiscaling, is currently being explored for such generalizations. While simple scaling properties of stochastic processes have a relatively long tradition in the more advanced mathematical theories, multiscaling processes are only beginning to be understood mathematically, mostly within the context of statistical theories of turbulence. In simple terms, the idea is partly that simple scaling implies a log-log linearity in the plot of any statistical moment versus the scale of measurement together with a linear relation between the order of the moment and the slope of the log-log relationship. Figure 3.31 illustrates this feature schematically. This feature leads to the interpretation that the statistical spatial variability in the physical process does not change with a change in scale; simple scaling processes are therefore said to possess the self-similarity property. However, preliminary empirical analyses of spatial rainfall, river flows, and channel gradients in networks suggest that while the log-log linearity is preserved between the moments and the scales of measurement, the corresponding slopes exhibit a nonlinear concave growth with the order of the moments. In contrast to linear slope behavior in simple scaling, the nonlinear concave growth of slopes shown in Figure 3.31 leads to the interpretation that statis- tical spatial variability in such processes increases with a decrease in spatial scale. In this case the scaling behavior is determined by a spectrum of exponents, as opposed to a single exponent in simple scaling; hence the term "multiscaling." Determination of these exponents in terms of measurable physical and geometrical parameters of river

SOME CRITICAL AND EMERGING AREAS En z llJ o 4 ~ - CO .3 I LO O .2 LL o En .1 199 - '~ Linear Slope Growth in Simple Scaling, - Non-linear Slope Growth in Multi- Scaling~ - 1 1 1 ~ 1 1 1 2 3 4 5 6 7 8 ORDER OF THE STATISTICAL MOMENTS 1 FIGURE 3.31 A schematic display of the difference between scaling and multiscaling behavior of empirical data. basins is a problem of great significance. Multiscaling seems to arise in those physical systems that are governed by highly nonlinear dynamics. Clearly, tests of a multiscaling invariance property will require new, more extensive measurements than are generally available at present. On the application side, such theories will guide hydrologic predictions for river basins under sparse data sets, and due to an- thropogenic changes, as well as aid in the development of fundamen- tal mathematical models of the hydrologic phenomena. Stochastic-Dynamical Analysis of Hydrologic Time Series An important task in hydrology or in any other branch of natural science, for that matter is to reconstitute from the data the principal features of the underlying physical system and to make predictions about its future evolution. Now, a typical time series pertaining to hydrologic data displays considerable complexity, without any obvi- ous periodicity and with random-looking excursions of the relevant variables from their average level. A question of primary concern, therefore, is how to decipher the message of such a time series and thus understand the role of systematic effects and randomness from a physical perspective.

200 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES When confronted with a complicated, erratic succession of events, the first issue that comes to mind is that the phenomenon of interest is blurred by the presence of a great number of variables and poorly known parameters, whose inevitable presence is hiding some funda- mentally simple underlying regularities. Traditional statistical methods provide useful algorithms for extracting the relevant signal from what is believed to be parasitic, random noise. Nevertheless, the traditional statistical analyses are not always telling the whole story, and it is important to adopt complementary approaches that are based on a more dynamical view of the hydrologic phenomena. The importance of a dynamical approach stems from recent devel- opments in physical and mathematical sciences. These developments show that the stable and reproducible motions that dominated science for centuries do not always symbolize our physical world. Experiments on quite ordinary physicochemical systems at the laboratory scale and the study of simple mathematical models have revealed the existence of instabilities that amplify small effects and drive the system from arbitrarily closed initial states to many possible alternate future states. These nonlinear phenomena are sources of intrinsically generated complex behavior and unpredictability, in the sense that many outcomes of the evolution now become possible. Although these evolutions are governed by a well-defined set of deterministic laws, they exhibit an aperiodic random-looking behavior, called deterministic chaos. Clearly, for such phenomena it becomes meaningless to eliminate the variability and to keep only the mean as being the most representative part of the behavior. Historically, one of the most compelling early arguments demonstrating the presence of chaotic behavior in nonlinear phenomena came from the geosciences. In the now-classic work of meteorologist Edward Lorenz (1963), the existence of deterministic chaos was shown numerically on a simplified model of the phenomenon of thermal convection. Figure 3.32 depicts a typical scenario of the way the solutions X of a nonlinear dynamical system behave when a parameter ~ built into it is varied. At the values Hi, \2' \3, . . ., of the parameter, usually referred to as bifurcation points, new branches of solution are gener- ated. These bifurcation cascades often culminate in deterministic chaos. In general, they produce a multiplicity of simultaneously available states, known as attractors. Which of these states in the attractor is actually chosen depends on the initial conditions. This high degree of sensitivity to initial conditions confers a markedly random character on the system, since the initial conditions are history-dependent and may be modified by the fluctuations or by external perturbations. In actual fact, therefore, the dynamics of a multistable nonlinear system

SOME CRITICAL AND EMERGING AREAS X o J o oh 201 - . ,.-i- fit;.'' - /Y— - j (b) I 1 ,~ 1 ~ , \1 \2 !... -] chaos . _ Parameter ~ FIGURE 3.32 Typical bifurcation diagram of a nonlinear dynamical system. exhibit an aperiodic succession of intermittent jumps between coex- isting attractors. This view is reminiscent of a great number of natural processes. For instance, it has been used recently to model the prin- cipal features of the abrupt climatic changes associated with Quater- nary glaciations. As is illustrated below, it should also prove useful in understanding the dynamical aspects of hydrologic time series, on time scales of the order of centuries, such as the abrupt changes in the succession of humid and dry periods in the regime of annual precipitation. Can the dynamics of multistable nonlinear systems suggest new physical insights into the patterns of annual rainfall time series? Will these insights bring a greater potential for drought prediction? Let us choose the onset of drought in the western Sahel as a case study (Demaree and Nicolis, 1990~. Figure 3.33 depicts a typical time series record. Statistical analysis shows that such a record is nonstationary and that a more or less well-defined transition occurs between plateaus. This transition in the example in Figure 3.33 occurred in the mid- 1960s. Actually, an examination of the historical record of the Sahel

202 3.0 2.2 o 1.3 tar CL 0.5 IIJ N - ~ ~.3 o z -1.2 . -2.0 I I 1 1 1 1 1 1900 1913 1925 1938 1950 1963 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES it 1975 1988 2000 YEAR FIGURE 3.33 Normalized rainfall departures, in standard deviations, at the Kaedi station (Mauritania) for the period from 1904 to 1988. SOURCE: Reprinted, by permission, from Demaree and Nicolis (1990). Copyright (3 1990 by the Royal Meteorological Society. region shows that such abrupt changes of rainfall prevailed over sev- eral centuries in the past. Following the ideas of the dynamical sys- tems approach explained above, one may wish to stipulate that the annual precipitation time series is a bistable nonlinear dynamical system possessing two stable states, one of quasi-normal rainfall and the other of low rainfall. However, once the system lands in either of these states, it is still subjected to variability arising principally from two sources. The first one includes the imbalances that inevitably exist between such internally generated processes as transport and radiative mechanisms, and the second source arises owing to distur- bances of an external origin, such as the sea surface temperature anomalies. These phenomena are perceived by the dynamics as a stochastic forcing, and the evolution of such a stochastic-dynamical system can be expressed in a generic form as dt = f(X, ~ ~ + F(t)

SOME CRITICAL AND EMERGING AREAS 203 (the time rate of change of X equals the nonlinear dynamics plus the stochastic forcing). Here X denotes the variable to be predicted, and f is the nonlinear dynamical part of the evolution, which includes the effects of feedback, of radiation, and so on, and also depends on a parameter \. The term F(t) represents a stochastic forcing. In the simplest form, F(t) is gen- erally assumed to have no correlations and to have a normal prob- ability law. It is called the Gaussian white noise. The principal features of the evolution predicted by the above equation may be summarized as follows. Suppose that the system starts in one of its two stable attractors. If the strength of the stochastic forc- ing F(t) is small, then during a long period of time the system will perform a small-scale jittery motion around a level corresponding to this attractor. But sooner or later, there is bound to be a fluctuation capable of overcoming the "barrier" separating this state from the second available state. When this happens, the system finds itself in another attractor in a very short time interval. Subsequently, it will again undergo a small-scale random motion around this new state until a new fluctuation drives it back to the previous state, or to a third one if such is available. This intermittent evolution looks very much like the record of Figure 3.33. More generally, it provides us with an archetype for understanding other hydrologic processes beyond our specific example, for instance, river flows that seem to exhibit abrupt transitions. Of course, a more quantitative view requires that the function f(X, \) and the noise strength F(t) be known. A minimal model of f should involve nonlinearities giving rise to stable states whose number and characteristics are identical to those of the plateaus found from the statistical analysis of the record. Having chosen the dominant nonlinearity, one can actually determine most of the model parameters from the data. An interesting question pertains to the residence times, that is, the time the system spends in a given attractor state or, alternatively, to the transition times between attractors. It would obviously be quite interesting to predict such times, since this would be equivalent to predicting the duration of an ongoing drought or to forecasting a forthcoming one. The theory of stochastic processes allows one to make statistical predictions of these times for the systems described by the above equation. Applied to the Sahel record shown in Figure 3.33, this type of an analysis predicts that the mean transition time from the dry state is much larger than the time from the more humid state. The theory also predicts an appreciable dispersion around these mean values.

204 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES In conclusion, dynamical systems theory suggests new techniques of data analysis. It also allows us to formulate the key questions pertaining to the dynamical behavior of complex hydrologic phe- nomena from a novel point of view. New physical insights and pre- dictive capabilities will emerge from such analyses in the future. Nonlinear Dynamics and Predictability of Hydrologic Phenomena Weather and climate processes of hydrologic interest, such as rainfall, exhibit a complex and highly variable structure in time and space. The general approach for making predictions of these processes, as, for example, for real-time flash flood forecasting, has been to use nonlinear deterministic equations governing atmospheric dynamics and to solve these equations numerically using high-speed computers. This is called numerical weather forecasting. Within the last two decades the complexity of numerical models has grown commensurately with the capacity and speed of computers. However, despite substantial progress in short-term weather forecasting, the reliability of forecasts has not increased much. Recent developments in the theory of dynamical systems show that many nonlinear deterministic phenomena are sources of intrinsically generated complex behavior and unpredictability. As explained earlier in this section, solutions of many nonlinear dynamical systems can take any one of many possible states called attractors. Which of these alternate states is chosen by the system depends on the initial conditions. This high degree of sensitivity to initial conditions confers a markedly random-looking character to the evolutions governed by purely deterministic dynamical equations. Ordinarily, in mathematical modeling or in laboratory experiments, the state (physical) variables are known in advance, and one deals with a well-defined set of evolution laws for these variables. However, this full information is seldom available for a natural system. Rather, only an observed time series of a climatic variable, say, rainfall rate, is available at one or several locations in space. Recent advances in dynamical systems theory have been instrumental in the development of new techniques to provide important qualitative information about process dynamics from the observed time series at one or several locations in space. They do not depend on specific model assumptions and details of the nonlinear dynamics. Therefore an important problem is to learn more about the underlying dynamics of weather and climate processes, independent of any modeling, from the observed time se- ries, and to find to what extent they are predictable.

SOME CRITICAL AND EMERGING AREAS Are there strange attractors in hydrologic time series? What are the limits of preclictability of hydrologic phenomena? 205 Suppose that but), k = 0, 1, . . ., r- 1, are the state variables actually taking part in the dynamics. The mathematical space in which these variables take values is called the phase space. Xk's are assumed to sat- isfy a set of first-order nonlinear equations whose form is unknown, but which, given a set of initial data Xk(0), produce the full details of the evolution. By successive differentiation in time, this set of r equations can be reduced to a single, highly nonlinear, rth order equation for any one of these variables. For example, instead of but), k = 0,1, . . ., r- 1, one can take Apt) and its (r- 1) successive derivatives to be the r state variables spanning the full phase space. Now, the most impor- tant point to notice is that both Xo~t) and its (r -1) derivatives can be deduced from a single observed time series, Xo~t~), Xo~t2), . . ., Xottn), where to is the initial time, /` = t2 - to = t3 - t2 = . . . = In - to_ is the sampling time, and n is the total number of observations. So, in principle, an observed time series contains sufficient information about the multi- dimensional character of the system's dynamics. Important scientific issues, such as the extent of the predictability of a natural system, depend on the nature of the trajectories of the dynamical system in phase space, i.e., the "geometry" of the phase space. In order to identify this geometry from observed time series data, one typically wants an estimate of the minimum number r of variables that captures the essential features of the long-term evolu- tion of the climatic or weather system. This number also denotes the dimension of the phase space. In addition, one wants to test for the possible existence of an attractor in the phase space that represents this evolution. In a dissipative dynamical system like rainfall, the attractor occu- pies only a reduced portion of the phase space and therefore has a lower dimension than that of the phase space. One might visualize this scenario with the example of a simple pendulum. Its trajectories lie in a two-dimensional phase space, defined by an angle ~ with the vertical direction and the angular velocity d8/dt. If the pendulum loses energy to friction, then the trajectories gradually spiral inward toward a point that represents the state of no motion. In this case, the attractor is a zero-dimensional point. If the energy supplied to the pendulum exactly balances the energy dissipated by friction, then a steady state is reached in the form of a repeating loop in the phase space. In this

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SOME CRITICAL AND EMERGING AREAS case, the attractor is a one-dimens space and is called a limit cycle. 207 tonal closed curve in the phase Trajectories of many natural systems like rainfall do not converge with time either to a point or to a limit cycle. Even though the attractor has a dimension smaller than that of the phase space, the trajectories do not cross themselves, do not repeat themselves, and contain every possible frequency in a broadband spectrum. To fulfill these conditions, the attractor has to have some strange geometrical attributes. For example, its dimension turns out to be a fraction rather than a positive integer and therefore is known as a fractal. It is called a strange attractor. The existence of a strange attractor means that trajectories, which are initially close, ultimately diverge into completely different paths. Therefore, beyond this time, predictability is no longer possible. The limits of predictability are set by the rate of divergence of the trajec- tories from the initial conditions close to one another. This rate of divergence is measured by the so-called Lyapunov exponents. The inverse of the largest positive Lyapunov exponent gives the time limit of predictability. The calculation of these exponents is an area of active research. Applications of these techniques of phase space reconstruction from time series are beginning to appear in the literature. Some recent examples include the identification of chaotic attractors governing the weather over Western Europe, the climate dynamics of Quaternary glaciations, and the mesoscale dynamics of certain extratropical storms in the United States. These techniques hold the potential to enhance understanding of different dynamic scenarios in diverse hydrologic processes, e.g., river flows, sediment flows, and rainfall, which is necessary both for developing physical descriptions of these processes and for making predictions. SOURCES AND SUGGESTED READING Hydrology and the Earth's Crust Back, W., and R. A. Freeze. 1983. Chemical Hydrogeology. Benchmark Papers in Geol- ogy. Vol. 73. Hutchinson Ross, Stroudsburg, Pa., 413 pp. Back, W., J. S. Rosensheir, and P. R. Seaber. 1988. Hydrogeology. Geology of North America. Geological Society of America, 524 pp. Bethke, C. M., W. J. Harrison, C. Upson, and S. Altaner. 1988. Supercomputer analysis of sedimentary basins. Science 239:261-267. Biggar, J. W., and D. R. Nielsen. 1976. Spatial variability of the leaching characteristics of a field soil. Water Resour. Res. 12(1):78-84. Blot, M. A. 1941. General theory of three-dimensional consolidation. J. Appl. Phys. 12:155-164.

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SOME CRITICAL AND EMERGING AREAS 209 Gagliano, S. M., K. J. Meyer-Arendt, and K. M. Wicker. 1981. Land loss in the Missis- sippi River deltaic plain. Gulf Coast Association of Geological Societies, Trans. 31:295-330. Horton, R. E. 1945. Erosional development of streams and their drainage basins: hydro- physical approach to quantitative morphology. Geol. Soc. Am. Bull. 56:275-370. Keown, M. P., E. A. Dardeau, Jr., and E. M. Causey. 1986. Historic trends in the sediment flow regime of the Mississippi River. Water Resour. Res. 22:1555-1564. Kirkby, M. J. 1976. Tests of the random network model and its application to basin hydrology. Earth Surface Processes 1:197-212. Kirkby, M. J. 1985. A two-dimensional simulation model for slope and stream evolu- tion. Pp. 203-222 in Hillslope Processes. A. D. Abrahams, ed. Allen & Unwin, London. Meade, R. H., and R. S. Parker. 1985. Sediment in rivers of the United States. Pp. 49- 60 in National Water Summary 1984. U.S. Geological Survey Water Supply Paper 2275. Potter, P. E. 1978. The origin and significance of big modern rivers. J. Geol. 86:13-33. Rodriguez-Iturbe, I., and J. B. Valdes. 1979. The geomorphological structure of hydro- logic response. Water Resour. Res. 15(6):1435-1444. Schumm, S. A., and R. W. Lichty. 1963. Channel widening and floodplain construction along Cimarron River in Southwestern Kansas. Pp. 71-88 in U.S. Geological Survey Professional Paper 352-D. Selby, M. J. 1982. Hillslope Materials and Processes. Oxford University Press, London. 264 pp. Shreve, R. L. 1966. Statistical law of stream numbers. J. Geol. 74:17-37. Smith, T. R., and F. P. Bretherton. 1972. Stability and the conservation of mass in drainage basin evolution. Water Resour. Res. 8~6):1506-1529. Trimble, S. W. 1977. The fallacy of stream equilibrium in contemporary denudation studies. Am. J. Sci. 277:876-887. Wells, J. T. Subsidence, sea-level rise, and wetland loss in the Lower Mississippi River Delta. In Sea-level Rise and Coastal Subsidence: Problems and Strategies. J. D. Milliman and S. Sabhasri, eds. John Wiley & Sons, New York, in press. Wells, J. T., and J. M. Coleman. 1987. Wetland loss and the subdelta life cycle. Estua- rine, Coastal and Shelf Science 25:111-125. Willgoose, G. R., R. L. Bras, and I. Rodriguez-Iturbe. 1989. A physically based channel network and catchment evolution model. Report No. 322. Ralph Parsons Labo- ratory, Department of Civil Engineering, Massachusetts Institute of Technology, 464 pp. Hydrology and Climatic Processes Anthes, R. A., J. J. Cahir, A. B. Fraser, and H. A. Panofsky. 1981. The Atmosphere. Third Ed. Charles E. Merrill, Columbus, Ohio, 531 pp. Bolin, B., B. Doos, J. Jager, and R. Warrick, eds. 1986. The Greenhouse Effect, Climatic Change, and Ecosystems. John Wiley & Sons, New York, 541 pp. Budyko, M. I. 1974. Climate and Life. Academic Press, New York, 508 pp. Callendar, G. S. 1938. The artificial production of carbon dioxide and its influence on temperature. Q. J. R. Meteorol. Soc. 64:223-240. Charney, J. G. 1975. Dynamics of deserts and drought in the Sahel. Q. J. R. Meteorol. Soc. 101:193-202. Dewey, K. F., and R. Heim. 1981. Satellite Observations of Variations in Northern Hemisphere Snow Cover. NOAA Technical Report NESS 87. U.S. Department of Commerce, Washington, D.C.

210 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Dey, B., and O. S. R. U. Branu Kumar. 1983. Himalayan winter snow cover area and summer monsoon rainfall over India. J. Geophys. Res. 88:5471-5474. Dozier, R. J., S. R. Schneider, and D. F. McGinnis, Jr. 1981. Effect of grain size and snow pack water equivalence on visible and near-infrared satellite observations of snow. Water Resour. Res. 17(4):1213-1221. Glantz, M., ed. 1988. Societal Responses to Regional Climatic Change: Forecasting by Analogy. Westview Press, Boulder, Colo., 428 pp. Hansen, J., G. Russell, D. Rind, P. Stone, A. Lacis, S. Lebedeff, R. Ruedy, and L. Travis. 1983. Efficient three-dimensional global models for climate studies: Models I and II. Mon. Weather Rev. 111:609-662. Henderson-Sellers, A., and K. McGuffie. 1987. A Climate Modeling Primer. John Wiley & Sons, New York, 217 pp. Kondratyev, K. Ya. 1969. Radiation in the Atmosphere. Academic Press, New York. Koster, R. D., P. S. Eagleson, and W. S. Broecker. 1988. Tracer Water Transport and Subgrid Precipitation Variation with Atmospheric General Circulation Models. Report 317. Ralph M. Parsons Laboratory, Department of Civil Engineering, Massachusetts Institute of Technology. March. L'vovich, M. I., and S. P. Ovtchinnikov. 1964. Physical-Geographical Atlas of the World (in Russian). Academy of Sciences, USSR, and Department of Geodesy and Geography, State Geodetic Commission, Moscow. Manabe, S., and J. L. Holloway, Jr. 1975. The seasonal variation of the hydrologic cycle as simulated by a global model of the atmosphere. J. Geophys. Res. 80(12):1617- 1649. Meter, M. F. 1990. Greenhouse effect: reduced rise in sea level. Nature 343:115-116. Namias, J. 1978. Multiple causes of the North American abnormal winter, 1976-1977. Mon. Weather Rev. 106(3):279-295. National Research Council. 1988. Toward an Understanding of Global Change. Na- tional Academy Press, Washington, D.C., 213 pp. Nicholson, S. E. 1989. African drought: characteristics, causal theories and global tele- connections. Pp. 79-100 in Understanding Climate Change. A. Berger, R. E. Dickinson, and J. W. Kidson, eds. American Geophysical Union, Washington, D.C. Richardson, L. F. 1965. 1922 Weather Prediction by Numerical Process. Cambridge University Press, New York, 236 pp. (Reprinted by Dover, Mineola, N.Y.) Schneider, S. H. 1987. Climate modeling. Sci. Am. 256(5):72-80. Seligman, G. 1936. Snow Structure and Ski Fields. Macmillan, London. Sellers, W. D. 1965. Physical Climatology. The University of Chicago Press, Chicago, 272 pp. Street-Perrott, A., M. Beran, and R. Ratcliffe, eds. 1983. Variations in the Global Water Budget. D. Reidel, Dordrecht/Boston, 518 pp. Wallace J. M., and P. V. Hobbs. 1977. Atmospheric Science: An Introductory Survey. Academic Press, New York. Walsh, J. E. 1984. Snow cover and atmospheric variability. Am. Sci. 72:50-57. Warren, S. G. 1982. Optical properties of snow. Rev. Geophys. Space Phys. 20(1):67-89. Washington, W. M., and C. L. Parkinson. 1986. An Introduction to Three-dimensional Climate Modeling. University Science Books, Mill Valley, Calif. 422 pp. Hydrology and Weather Processes Anthes, R. A., J. J. Cahir, A. B. Fraser, and H. A. Panofsky. 1981. The Atmosphere. Third Ed. Charles E. Merrill, Columbus, Ohio, 531 pp. Bolin, B., B. Doos, J. Jager, and R. Warrick, eds. 1986. The Greenhouse Effect, Climatic Change, and Ecosystems. John Wiley & Sons, New York, 541 pp.

SOME CRITICAL AND EMERGING AREAS 211 Byers, H. R., and R. R. graham, Jr. 1949. The Thunderstorm. U.S. Government Printing Office, Washington, D.C., 287 pp. Chappell, C. F. 1987. Quasi-stationary convective events. Pp. 289-310 in Mesoscale Meteorology and Forecasting. Peter Ray, ed. American Meteorological Society, Boston. Eagleson, P. S., N. M. Fennessey, W. Qinliang, and I. Rodriguez-Iturbe. 1987. J. Geophys. Res. 92(D8):9661-9678. Glantz, M., ed. 1988. Societal Responses to Regional Climatic Change: Forecasting by Analogy. Westview Press, Boulder, Colo., 428 pp. Leary, C. A., and R. A. Houze, Jr. 1979. The structure and evolution of convection in a tropical cloud cluster. J. Atmos. Sci. 36:437-457. Newton, C. W. 1950. Structure and mechanism of the prefrontal squall line. J. Meteorol. 7:210-222. Palmer, C. A. 1952. Reviews of modern meteorology 5 Tropical meteorology. Q. J. R. Meteorol. Soc. 78:126-163. Schneider, S. H. 1987. Climate modeling. Sci. Am. 256(5):72-80. Washington, W. M., and C. L. Parkinson. 1986. An Introduction to Three-dimensional Climate Modeling. University Science Books, Mill Valley, Calif. 422 pp. Waymire, E., V. K. Gupta, and I. Rodriguez-Iturbe. 1984. A spectral theory of rainfall intensity at the meso-p scale. Water Resour. Res. 20(10):1453-1465. Hydrology and Surficial Processes Bowen, I. S. 1926. The ratio of heat losses by conduction and by evaporation from any water surface. Phys. Rev. 27:779-787. Brutsaert, W. 1982. Evaporation into the Atmosphere: Theory, History, and Applica- tions. D. Reidel, Dordrecht/Boston, 299 pp. Buckingham, E. 1907. Studies on the movement of soil moisture. Bureau of Soils Bulle- tin No. 38. U.S. Department of Agriculture, Washington, D.C., 61 pp. Dane, J. H., and A. Klute. 1977. Salt effects on the hydraulic properties of a swelling soil. Soil Sci. Soc. Am. J. 41(6):1043-1049. Dozier, J. 1989. Spectral signature of Alpine snow cover from the Landsat Thematic Mapper. Remote Sensing Environ. 28:9-22. Dunne, T., and R. D. Black. 1970. An experimental investigation of runoff prediction in permeable soils. Water Resour. Res. 6(2):478-490. Eagleson, P. S. 1970. Dynamic Hydrology. McGraw-Hill, New York, 462 pp. Eagleson, P. S., ed. 1982. Land Surface Processes in Atmospheric General Circulation Models. Cambridge University Press, New York, 560 pp. Harbeck, G. E., Jr. 1962. A practical field technique for measuring reservoir evaporation utilizing mass-transfer theory. Pp. 101-105 in U.S. Geological Survey Professional Paper 272-E. Hewlett, J. D., and A. R. Hibbert. 1967. Factors affecting the response of small water- sheds to precipitation in humid areas. Pp. 275-290 in Forest Hydrology. W. E. Sopper and H. W. Lull, eds. Pergamon, London. Horton, R. E. 1933. The role of infiltration in the hydrologic cycle. Trans. AGU 14:446-460. Hursh, C. R., and E. F. grater. 1941. Separating storm hydrographs from small drainage areas in surface and subsurface flow. Trans. AGU 22:863-871. Kirkby, M. J., ed. 1978. Hillslope Hydrology. John Wiley & Sons, New York, 389 pp. Nielsen, D. R., J. W. Biggar, and K. T. Erh. 1973. Spatial variability of field measured soil water properties. Hilgardia 42:215-259.

212 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Pearce, A. J., M. K. Stewart, and M. G. Sklask. 1986. Storm runoff generation in humid headwater catchments. 1. Where does the water come from? Water Resour. Res. 22:1263-1272. Penman, H. L. 1948. Natural evaporation from open water, bare soil, and grass. Proc. R. Soc. London, Ser. A 139:120-146. Sutton, O. G. 1953. Micrometeorology. McGraw-Hill, New York, 333 pp. Sverdrup, H. U. 1937. On the evaporation from the oceans. J. Mar. Res. 1:3-14. Sverdrup, H. U. 1946. The humidity gradient over the sea surface. J. Meteorol. 3:1-8. Hydrology and Living Communities Arris, L. L., and P. S. Eagleson. 1989. A physiological explanation for vegetation eco- tones in eastern North America. Report No. 323. Ralph M. Parsons Laboratory, Department of Civil Engineering, Massachusetts Institute of Technology. Eagleson, P. S. 1982. Ecological optimality in water-limited natural soil-vegetation systems 1. Theory and hypothesis. Water Resour. Res. 18(2):325-340. Eagleson, P. S., and R. I. Segarra. 1985. Water-limited equilibrium of savanna vegeta- tion systems. Water Resour. Res. 21(10):1483-1493. Eyre, S. R. 1968. Vegetation and Soils: A World Picture. 2nd Ed. Edward Arnold, London. Little, E. L. 1971. Atlas of United States Trees. Vol. 1. Conifers and Important Hard- woods. U.S. Department of Agriculture Misc. Pub. 1141. U.S. Government Print- ing Office, Washington, D.C. L'vovich, M. I. 1979. World Water Resources and Their Future. (Translated from the Russian). R. L. Nace, ed. American Geophysical Union, Washington, D.C. Rosenzweig, M. L. 1968. Net primary production of terrestrial communities: prediction from climatological data. Am. Nat. 102:67-74. Walter, H. 1973. Vegetation of the Earth. Heidelberg Science Library. Vol. 15. Springer- Verlag, Heidelberg. Whittaker, R. H. 1975. Communities and Ecosystems. Second Ed. Macmillan, New York. Hydrology and Chemical Processes Bader, H., R. Haefeli, E. Bucher, J. Neher, O. Eckel, Ch. Thams, and P. Niggli. 1939. Der Schnee und seine Metamorphose (Snow and Its Metamorphism). Translation 14. U.S. Snow, Ice, and Permafrost Research Establishment, Wilmette, Ill. Berner, E. K., and R. A. Berner. 1987. The Global Water Cycle: Geochemistry and Environment. Prentice-Hall, Englewood Cliffs, N.J. Environmental Defense Fund (EDF). 1988. Polluted Coastal Waters: The Role of Acid Rain. EDF, Washington, D.C. Garrels, R. M., and C. L. Christ. 1965. Solutions, Minerals, and Equilibria. Harper & Row, New York, 450 pp. Garrels, R. M., and F. T. Mackenzie. 1971. Evolution of Sedimentary Rocks. W. W. Norton, New York, 397 pp. Harriss, R. C., D. I. Sebacher, and F. P. Day. 1982. Methane flux in the Great Dismal Swamp. Nature 297 (5368):673-674. Jenny, H. 1980. The Soil Resource: Origin and Behavior. Springer-Verlag, New York. Johannessen, M., and A. Hendriksen. 1978. Chemistry of snowmelt: changes in con- centration during melting. Water Resour. Res. 14:615-619. Kennedy, I. R. 1986. Acid Soil and Acid Rain. John Wiley & Sons, New York.

SOME CRITICAL AND EMERGING AREAS 213 McCormick, J., and J. Tinker, eds. 1985. Acid Earth: The Global Threat of Acid Pollu- tion. Earthscan, London and Washington. Sposito, G., ed. 1989a. The Environmental Chemistry of Aluminum. CRC Press, Boca Raton, Fla. Sposito, G. 1989b. The Chemistry of Soils. Oxford University Press, New York. University Corporation for Atmospheric Research (UCAR). 1985. Opportunities for Research at the Atmosphere/Biosphere Interface. UCAR, Boulder, Colo. Hydrology and Applied Mathematics Demaree, G. R., and C. Nicolis. 1990. Onset of Sahelian drought viewed as a fluctuation induced transition. Q. J. R. Meteorol. Soc. 116:221-238. Einstein, A. 1926. The cause of the formation of meanders in the courses of rivers and of the so-called Bear's law. Naturwissenschaften, Vol. 14. Gupta, V. K., and E. Waymire. 1990. Multiscaling properties of spatial rainfall and river flow distributions. J. Geophys. Res. 95(D3):1999-2010. Horton, R.1945. Erosional development of streams and their drainage basins: Hydrophysical approach to quantitative morphology. Geol. Soc. Am. Bull. 56:275-370. Leopold, L. B. 1962. Rivers. Am. Sci. 50(4):511-537. Leopold, L. B., and W. Langbein. 1962. The concept of entropy in landscape evolution. U.S. Geological Survey Professional Paper 500-A. Lorenz, E. N. 1963. Deterministic nonperiodic flow. J. Atmos. Sci. 20:131-141. Nicolis, C., and G. Nicolis, eds. 1987. Irreversible Phenomena and Dynamical Systems Analysis in Geosciences. D. Reidel, Dordrecht. Rodriguez-Iturbe, I., B. Febres-Power, M. B. Sharifi, and K. P. Georgakakos. 1989. Chaos in rainfall. Water Resour. Res. 25(7):1667-1676. Shreve, R. L. 1966. Statistical law of stream numbers. J. Geol. 74:17-37. Steinhaus, H. 1954. Length, shape, and area. Colloq. Math. 3:1-13.

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Hydrology--the science of water--is central to our understanding of the global environment and its many problems. Opportunities in the Hydrologic Sciences explains how the science of water historically has played second fiddle to its applications and how we now must turn to the hydrologic sciences to solve some of the emerging problems. This first book of its kind presents a blueprint for establishing hydrologic science among the geosciences.

Informative and well-illustrated chapters explore what we know about the forces that drive the global water system, highlighting promising research topics in hydrology's major subfields. The book offers specific recommendations for improving hydrologic education, from kindergarten through graduate school. In addition, a chapter on the basics of the science is interesting for the scientist and understandable to the lay reader.

This readable volume is enhanced by a series of brief biographical sketches of past leaders in the field and fascinating vignettes on important applied problems, from the relevance of hydrology to radioactive waste disposal to the study of ancient water flows on Mars.

The volume concludes with a report on current research funding and an outline of strategies for scientists and professional societies to advance the field.

Opportunities in the Hydrologic Sciences is indispensable to policymakers in science and education, research managers in geoscience programs, researchers, educators, graduate students, and future hydrologists.

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