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Opportunities in the Hydrologic Sciences (1991)

Chapter: SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS

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Suggested Citation:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." 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:"SCIENTIFIC ISSUES OF DATA COLLECTION, DISTRIBUTION, AND ANALYSIS." National Research Council. 1991. Opportunities in the Hydrologic Sciences. Washington, DC: The National Academies Press. doi: 10.17226/1543.
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~ - Scientific Issues of Data Collection, Distribution, and Analysis Hydrologic processes are highly variable in space and time, and this variability exists at all scales, from centimeters to continental scales, from minutes to years. Data collection over such a range of scales is difficult and expensive, and so hydrologic models usually conceptualize processes based on simple, often homogeneous, approximations of nature. Hence a 2,000- km2 river basin is commonly modeled as a lumped system that responds as a point with average representative properties. Ground water flow is commonly treated as one-dimensional or two~imensional. Rainfall is expressed as a mean over large areas, and as depths over periods of a day. Snowmelt runoff volumes are forecast from averages of snow accumulation at a few index plots. These generalized conceptualizations reflect the normal dearth of data, which lack the temporal and spatial resolution to support more detailed modeling. This forced oversimplification is impeding both scientific understanding and management of resources. In the history of the hydrologic sciences as in other sciences, most of the significant advances have resulted from new measurements, yet to- day there is a schism between data collectors and analysts. The pio- neers of modern hydrology were active observers and measurers, yet now designing and executing data collection programs, as distinct from experiments carried out in a field setting with a specific research question in mind, are too often viewed as mundane or routine. It is therefore difficult for agencies and individuals to be doggedly persis- tent about the continuity of high-quality hydrologic data sets. In the excitement about glamorous scientific and social issues, the scientific community tends to allow data collection programs to erode. 214

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 215 Such programs provide the basis for understanding hydrologic systems and document changes in the regional and global environments. Modeling and data collection are not independent processes. Ide- ally, each drives and directs the other. Better models illuminate the type and quantity of data that are required to test hypotheses. Better data, in turn, permit the development of better and more complete models and new hypotheses. If we accept this synergism, the hydrologic sciences will be well situated for progress, which is needed because recent developments in spatial and temporal models and new data acquisition technology require a rethinking of many of the traditional hydrologic problems. We must, however, reemphasize the value and importance of observational and experimental skills. To address many of the issues described in Chapter 3, we need new observations of hydrologic phenomena. Some of the current uncertainties in our knowledge of the hydrologic cycle require better understanding of hydrologic processes, but progress in the hydrologic sciences will also depend on improved methods for collecting hydrologic data, more complete and better-organized archives of already-available information, and better mechanisms for distribution and exchange of data, particularly in developing countries and in the international arena. This chapter describes some requirements for and characteristics of hydrologic data, assesses the current hydrologic data base, and then discusses some opportunities to improve hydrologic data and their use. NEED FOR COLLECTION OF HYDROLOGIC DATA AND SAMPLES Hydrologic data are needed to measure fluxes and reser- voirs in the hydrologic cycle and to monitor hydrologic change over a variety of temporal and spatial scales. Historically most hydrologic data have been collected] to answer water resources questions rather than scientific ones. Hydrologists use information obtained in laboratories, such as soil particle size, solute concentrations, or electromagnetic spectra, but

216 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES :~:~i~y~nR~o~Lo~G~1c~l~MpL~l~cAT~l~oNs~ OF:~AL~W AlC~M~I~r~Qi~:~:~:~:~ :~ : ~ :~:~:~: ~~:~:::: ~ ~ ~ ~ ~ ~~ ~~ ~~ ~~ 0 :: ~ ~ : ~ ~ ~:~:~ :: ~:~ :~ : ~ ~ :~: :::: : ~~ ~ ~~::~ :~ ~ ~ ~::~: ::: ~ :~: ~ ~ F~ : T:~ :~:~c u~rlng~t 1~e:~spr~l~n~g:~:~montus~ot;;~Ap~r~i~ A l~a~gh~::~J~u~:n~e:.~:~:~The~ ~:net~:~res~u~l~t::~ot~ An - :~:~::4::~::::: ~::~ :::::: :::: ::: :::~:::::~t: ~ ~ ~~ ~~ ~~ ~~ ~ ~~ ~~ ~ ~ ~~. ~n~£reas~e~ ~:~1~n~g~ nodal If::: tem~p~e~r:a:tu~re~wo~u~ tic ~:~:~be~a~ ~~d~ec~re~a~se~:~:~i~n~ stream flow ~:~d~u~r:~i~n~g~ :~ :: ~: :~:~ :~: ~: ~ ~ ~ ~ ~: ~ ~:~: ::~: :~ ~ ~ ~:::~:~::~::~: :~ ~ ~ ~:: ~: ::: ::~: ~: ~ ~ ~ ~ :~:~ :~:~ ::~:~ ~ ~:: ~ ~r:~ ~: ~:: ~-~ ~ :~ ~ ~: ~:~ ~: ~:~:~:: ~ ~ ~ ~ : : ~ ~ ~ ~ ~ : ~ t n e ~ ~ ~ ~ n o ~ r m a ~ : l ~ ~ ~ ~ : ~ s ~ n ~ o w m e I ~ ~ t ~ r u ~ ~ n ~ r ~ ~ : ~ ~ ~ o ~ n ~ t h ~ s ~ ~ ~ ~ ~ o r ~ ~ ~ n e : ~ ~ ~ ~ ~ s p ~ r ! ~ ~ ~ n ~ g ~ ~ ~ ~ ~ a ~ ~ n ~ d ~ ~ ~ s u ~ m ~ m e r . : ~ ~ : ~ ~ T h ~ ~ ; ~ s : : ~ ~ h ~ a n ~ g e ~ ~ ~ · ~: ~::~: :~:~::: ~ ::::~:~:::: ~ ~ :~:~ ~ :~.~:~::: ~ ~:~:~.~ :~: ~ ~:~ :~:~:~ ~:~ ~ ~ ~ n the: rn:ont~h~ly~ :t~m~l~n~g~ o~f~ ~av~a ~ I~ab~le ~streamflow: ~co~u~ld~ ~ d:ra~m~ati~c:a~l l~y ~ ~n-c:re~a:se: :~:~ i ~::: ~I~:~w~i~nter~:~:f:loodi~:ng~la~n:d~ ~:si~gn~ifica~n~tly~decFeas~e:~lthel~l~w~ater~:~a~va~i:labl~e:l~d~u~Fing: :~the~:: c~rit~ical~A~pr~i~l~-th~ug~h-Se~ptem~r~season~ of ~soi~l-m~o;~s~t:ure~repl:e:n~is~h:me~:nt~via . . ~ ~ ~ ~ ~ ~ ~ ~ :. ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~'rr~gat~Qn~.~T~ ~e~:~c~ 1~an~g~:ng~:~:rea~mfl~ow:~:~pat~r~n~$~:~wo~u~1d~affect~existing~1su~£e~:~l:ll~ ~ ~ , ~ ~ ~ ~ ~ ~, ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ : wam~r~:~:~se:rvo~' rs ~w lose~storage~ ~ca~,Dac~ities~ :~were: o~e~sl~g:n~ec :: to~: acco~mmo~c ~am: .:::~ ~ ~ : : ~ ::~: : :: :: ~ :: : ~ :: ~:~: ~: ,~l~storic::~ ~yc ~ro og~'c:: runott~::~pa~erns~. :: :T ~e~:~li~m~paci: :of:~:g~lo:bal:::~c:~t~i~mat:ic~ c~h::a~nge~::~: ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ::r r^~l:lr-~ ~~ t~t~` ~IS potent~~a ~ y :~ve~ ~se~riou~s~.: ~: T 1e~ costs of ~ tak~i~n~g:::: ~ ~ ~~ ~: ~ ~ ~ ~ ~ ~ ::~: ~ ~: ~ ~ ,~ ~: ~:: ~ ~ ~ ~ ~ :~:~ ~ ~- ~ ~:: :~: ~: ~ ~ ~ ~ ~ I I l: I :I::::I~ I l~ lU I I t1 1~L ~ ~. . . 1 l l lO ~ ~ ~ Y ~ ~ e ~: ~ : ~ :: ~ ::: ~ ::: :: :: ~: :: :: :: ::::~:::: : ~ :::: : : ~ : : } : ~ on~: wa=~e:~ reso~u:rce:s~ sy~s e~ms:: : :::: :::: ~: ::::::::: ~:~:~::::: ~:::::: ::: :: :~:::: ::~ :::~ :~ ::: : ::::::~: :: :~:: : ::~:~:: :: ::: ~ ~ :::: :: . ~co~u~nterm~e~as~:w:res~ ~::~a~n~d~ rep:a~i~ri~ng ~d~amagel: co~u:ldl~:h~ave~a ~ ~si~g:n:iti~can~t ::e~ct :~on :~:~ :: ::::::: : ~:: : :~: ~ ::: : : :~: :::: ~ ::::: : : ~ : th:e~::~e~con:om~ies~:~:of individual::: s~te~s::~a~n~d~ofl~:t;~h~e ~l3:n~:ited~::~::~Stat:es~i~ ~ ::~ ~: ~ ~:::~:: ~ ~:~:: ~:~ ~: ~::~::;;~ . ~ ~ . , ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ,J, :: ~ ~ ~ . ~ ~, . : ~ ~ ~:~ 1e ~ key:: ~qu~est~lQn:~: Tor 1~yc £0o~g~:~sts~ ~- - - . . ~ ~ . . . . ~ ~ :St eps ~ ~ ~sn~o~:~lo ::~De ~ ta~:~:en~ ~m:~: t~n~e~ t~a~c~e~ ~::~of:~: . . ~ ~ :~ ~ ~ ~ : ~now ~ ~ecotm~es:~ ~ W:ha:t~ ~i:m~med~i~ate~ ~s~u~c:h~ ~:1 on~g-te~rml~::~u n:certai~n~ty:?~:~ Cer-~ ~ ~:~ . , ~ . . ~ ~ ~ ~ ~ ;: ta~n~l~y ~one: :~a~sw:er::: ~I~ICS: ~n~: :a~:~co~m~m~:l:t~ment:~ ~:to ::~c~ontin~u:~ ~:a~nd to: ~ :::ex~p~a:nd ~: ~progr:ams::of~ca:refu~l:::~s~c::ie~n~tific:l~m~ea~s~u~re~m~en~ts~.l~:~T~h~e:~;~:~:~re:su:llti~ng~l:~lh~ydro:l~:ogic~: :: ::: ::: :~ : :: :::::: :: :::: ~:::: ~ ::: :~ ~ : : ~: :: ~ ~ ~ : ~ ~:~:~ d~ata~l:ba~se$~:~:: wi~l~l~:~en~ab~le~: :hydrol~:ogi~sts~l~:to~stu~dy::~ :and~l~p~red~:~i~:ct~th~e ~ effects~:~of~:~ ,~ ~ , , ~ ~ .~: :~ ~ ~ ~, ~ , ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :::giocal::warm:lng~ anu~ m~a~e :a~pp~:ropriate recommend~at:ion~s::~r~ soc~iaJ p~o:;t:i:cy ::~ : :: ~: ~:~: : : :::: ~ ~::: ::::~:: :::: ~ : ::: ::: ~: ~ : :: ::: ~: ~ ~:~ :::: :: :::: ::: :::: :: ~ :: :::::: ~

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 217 most of their data must be obtained under field conditions. The reason is that, in addition to the elucidation of microscale processes, hydrologists are concerned with processes that have meaning only at the field scale or over long time scales, such as runoff and sediment yield from drainage basins or continental-scale drought. These re- quirements make hydrologic data collection complicated and expen- sive. Despite large financial investments, there remain important questions about hydrologic fluxes and reservoirs that are unlikely to be answered by the incremental growth of instrument networks. Technical and analytical innovations are necessary to overcome the paucity of useful hydrologic data now being collected and collated. To better characterize the hydrologic cycle requires data in several categories, and the choice of what to measure and where and when to measure influences what hydrologic questions we can investigate. 1. We require information about the fluxes and storage of water in its various phases as it moves through the components of the hydro- logic cycle. These include precipitation, snow accumulation and ab- lation, glacier flow and mass balance, discharge in rivers and streams, movement of ground water, and evapotranspiration. Also needed is information about the transport of solutes and sediments as well as the fluxes of energy that drive the hydrologic processes. 2. Hydrologic data are needed to monitor change, or lack of change, in the quantity and quality of water. The major effect of climatic variability on the humans, plants, and animals that inhabit the earth is felt through the hydrology. Similarly, changes in water chemistry cause concern among users of a water resource and can dramatically affect the fish and other biota that live in lakes and streams (Figure 4.1~. Thus we need baseline data, especially in tropical and semiarid areas. 3. In the traditional scientific sense, hydrologic data are needed to test hypotheses and models, and for exploration, to formulate new hypotheses. Hydrologic science can advance as a discipline only if measurement and theory evolve together. Sometimes the mechanisms that govern a complicated hydrologic process are known so poorly that precise data are needed simply to explore the phenomenon; then the next generation of measurements awaits conceptual developments that show which data are essential for testing ideas about how hydrologic phenomena occur. We know only what we measure, and we know what to measure only after some unifying conceptualization of the existing data has pointed the way. Finally, the measurement of hydrologic variables is a scientific endeavor itself. Future progress in hydrologic data collection should result from:

218 o c 3 4> o - I 80 - ~ 40 . _ OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~ 25 ._ 10 , c~~~..o....~.~- ~cl ~ 0 ~ - 5 80 82 84 86 88 ~ 6 Yea r 50 40 ~ ~ ·_ ~ ~,.,~ e Go Lo,.,,. ,, o l 30 80 82 84 86 88 Yea r A: ^~? 0' . . . _ 80 82 84 86 88 Yes r 30 ._ ~ 25 - 0 E 25 o co to' ~ ~ ~ ~ D 80 82 84 86 88 Yea r ..'~'...f~N if o'/~' . . 80 82 84 86 88 Yea r 120 R·~ 0 - ~~ _ 95 cn ~.,,.aC, 4,. o,,.1 ._ ~0 ID A _ 70 . . . 80 82 84 86 88 Yes r 60 . 50 "~i 40 80 82 84 86 88 Yea r 15 . . . . 80 82 84 86 88 Y e a r - O 25 - In.,,. D . ~ ~ ~ ~—o _ 80 82 84 86 88 Yea r FIGURE 4.1 Changes in ionic concentrations in two streams in Shenandoah National Park, Virginia, 1980 to 1988. Units are microequivalents per liter for concentrations and centimeters per year for discharge. SOURCE: Reprinted, by permission, from Ryan et al. (1989). Copyright @) 1989 by the American Geophysical Union. · coordinated experiments where diverse efforts are pooled; · technological advances in such fields as remote sensing, instru- mentation, and information systems; · new forms of analysis such as isotope geochemistry, paleohydrology, and improved models of spatial and temporal processes; and · intensified efforts in design of monitoring networks and exami nation of data quality and compatibility. Need to Collect Data at Varying Scales Hycirologic processes operate over a range of temporal and spatial scales, and important questions exist at time scales from seconds to millennia and space scales from the molecular to the global.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 219 Hydrologic processes operate over a continuum of space and time scales, from those of laboratory experiments to global transport of water and nutrients and from short-lived, transient phenomena to gradual secular variations. Some important questions studied in the laboratory or at scales of a field plot involve interactions between solutes and water or between water vapor, liquid water, and ice. For example: · The rate of elusion of chemical impurities from seasonal snow depends on interactions between solid, liquid, and vapor phases. · The cycling of hydrogen ions plays a critical role in determining the effects of acidic deposition on wild land and agricultural ecosys- tems. The largest components of hydrogen ion cycling are consumption by mineral weathering and production by plant roots. These components are difficult to estimate at field scales because we do not know enough about the kinetics of mineral dissolution reactions and biological release processes at these scales. Errors in estimating annual hydrogen ion consumption and production rates can be as large as the estimated annual input rate from acidic deposition. At the same time, our current knowledge of major fluxes of water in the hydrologic cycle involves large uncertainty. For example: · The mean annual discharge of the Amazon River is about 200,000 m3/s. Typical error estimates for the measurements are 8 to 12 per- cent, i.e., 16,000 to 24,000 m3/s, a rate slightly higher than the mean annual discharge of the Mississippi River. · Data show that sea level is rising slightly, but our investigations into the source of this rise, and the accuracies of our predictions of the future, are hampered because our measurements of the snowfall and iceberg calving from the Antarctic ice sheets do not tell us definitely whether the Antarctic ice volume is growing or shrinking. Thus the proportion of the water attributed to each of the sources causing this rise in sea level is not confirmed. How much comes from Antarctica and Greenland, from thermal expansion of the ocean waters, from shrinking alpine glaciers, and from depleted ground water reservoirs? Data are needed at a variety of scales, and the spatial and tempo- ral scales of available data restrict the questions that can be investigated. As is described in detail later in this chapter, the information is better for some hydrologic fluxes and reservoirs than for others. For most fluxes, however, a fundamental block to progress is our poor knowl- edge of how to interpolate between measurement points and how to extrapolate from few data points. For example:

220 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES · Depths and water equivalences of a snowpack are measured at many snow courses in cold regions, but it is possible to use these data only as crude estimates of the water content of a regional or basin-wide snowpack. · Topographic influences on rainfall, evaporation, and soil moisture are poorly documented at scales varying from individual hillslopes to entire mountain ranges. An additional important issue in the sampling of hydrologic pro- cesses is the structure of the statistical fluctuation that the processes have at different scales of measurement. How do the mean and variance of annual rainfall change as a function of the area over which the estimation takes place? How do the mean and variance of evapo- transpiration depend on the time scale considered? What is the com- bined effect of time and space scales on the statistical properties of hydrologic variables? There is an urgent need to 1. quantitatively characterize the fluctuations of hydrologic vari- ables at different time and space scales; and 2. design data collection programs that will allow the study of theoretical constructs, described in Chapter 3, to structurally link the fluctuations at different scales. Need to Develop Accurate Hydrologic Data Bases to Improve Scientific Understanding Detection of hydrologic change requires a committed, international, long-term effort and requires also that the data meet rigorous standards for accuracy. Synergism between models and data is necessary to de- sign effective data collection efforts to answer scientific questions. Development of scientific theory in the absence of supporting facts does not lead to understanding and can result only in conjecture. The primary sources of facts for the hydrologic sciences are the mea-

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 221 surements that are made of hydrologic and ancillary variables. Most hydrologic data are collected by government agencies for a variety of purposes only one of which is the development of hydrologic un- derstanding. Historically, the major providers of funding for hydro- logic data collection have expected that the resulting data would be useful in setting water policies, developing water resources plans, designing water resources systems, operating the structures that make up such systems, and monitoring the management of water resources. Increased hydrologic understanding can and does contribute to im- proved information for these utilitarian purposes, but the design of hydrologic data networks seldom has as a primary objective the bet- terment of basic hydrologic understanding. Therefore, the data needs of the hydrologic scientist almost certainly will not be fully satisfied by the existing data networks that are supported primarily for operational and accounting purposes. The existing data networks should be viewed by hydrologic scien- tists as opportunities upon which they can build. To optimize these opportunities, it is first necessary to define the characteristics of the data sets that hydrologic scientists need. These characteristics include the variables to be measured and the locations, frequencies, durations, and accuracies of the measurements. They should be derived from knowledge about the hydrologic phenomena to be explored and from the hypotheses to be tested. Allocation of the resources available for data collection must seek complementarily between the scientific and operational data sets. However, the operational networks often change in character because of changing operational demands for data or because of budgetary pressures on the financial sponsors of the data networks. These changes most often are manifested as discontinuities in the time series of measurements, as shifts in the location of the measuring site, or as changes in the accuracy of the data. Thus a full measure of complementarily is an illusive objective but a worthy one that can be approached by adequate communication between research scientists and managers of data collection programs. Important hydrologic changes may be subtle or may be difficult to detect because of large interannual or inter-event variation, and spa- tial and temporal scales of available data restrict the questions that can be investigated. Some important processes are transient short- lived but repeated. Fluxes and reservoirs of water, energy, solutes, and sediment are monitored most intensively over those parts of the world that are humid-temperate, densely populated, and industrialized, but measurement networks are particularly sparse over the oceans and in regions that are subhumid, tropical, at high elevation, or lightly populated.

222 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Need to Collect Long-Term Hydrologic Data Long-term monitoring and the use of paleohydrologic records are fundamental to understanding the role of extreme events in hydrologic systems. The need for long-term measurements is becoming clearer in our investigations of environmental change, including hydrologic change. Some disciplines, such as paleontology and historical geology, have depended for their existence on the availability of data spanning long periods, from 100 million to 2 billion years. Other disciplines that have traditionally focused research over shorter time frames, such as the environmental sciences, now stress the critical importance of long- term records. Despite the increasingly recognized importance of data records of long duration, only a few dedicated research organizations have suc- cessfully maintained high-quality data collection efforts over periods of 50 to 200 years. Furthermore, these organizations have experienced difficulty in committing limited research monies year after year to an activity that is frequently termed "monitoring," often with pejorative overtones. Dams have been built in many areas of the world and the water has been allocated for power generation or irrigation based on only a few years of data, with the too frequent result that the anticipated volumes of water have been available only in years of above-normal runoff. But many scientific questions justify the collection of long- term data. Two general areas for which long-term hydrologic data are specifically needed are discussed briefly in the remainder of this section, but these examples are not meant to be exclusive or exhaus- tive. Understanding Hydrologic Behavior and Hydrologic Change Long-term data are required to understand the basic hydrologic behavior of natural landscape units. In most humid areas, we do not understand well enough the relationships between rainfall, evapo- transpiration, streamflow, and long-lived vegetation such as forests. Research efforts have typically focused on only a short segment dur- ing the life span of forest stands that may exceed a century. Moreover, in areas of low rainfall, where the occurrence of rain exhibits high

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 223 variability over time and space, understanding of such fundamental relationships is even less complete because sufficiently long data records are not yet available to separate the inherent spatial and temporal variability of the processes involved. We do not fully understand, for example, how evaporation and soil moisture are regulated in such situations. The need for long-term data is particularly acute for analyses that focus on hydrologic be- havior at the continental spatial scales and on long time scales. Detection of hydrologic change requires long-term data sets of greater quality and reliability than are normally needed in the investigations of processes. When we measure rainfall for such purposes as flood forecasting, modest changes in the techniques, such as movement or redesign of the gage, do not affect the usefulness of the data for telling us whether to expect a flood on the river. However, when we try to use the same data to identify a long-term trend that is superimposed on the natural year-to-year variability, movement or redesign of the gage may introduce artifacts into the data set, and these may be falsely identified as trends or may disguise hydrologic change. Identifying Extreme Events Identification and analysis of hydrologic extremes, such as floods or droughts, are needed to understand the functioning of human societies as well as natural and managed ecosystems. In most hydrologic processes the extreme events often have the greatest effects on both systems and humans. Because they are infrequent in occurrence, they are poorly represented in all but the longest hydrologic records; only a few data sets contain enough extreme events to allow a precise estimation of their return periods. Moreover, the dynamics of extreme events are hard to measure; stage versus discharge relationships for gaging stations are usually not calibrated for high stages, and scour- ing of the channel during such flows makes extrapolation of rating curves for lower stages prone to error. Flood frequencies and drought recurrences may be well defined for mid-range events, but the tails of the distributions are poorly quantified, both in temporal distribution and magnitude. A series of extreme events may represent just that, a combination of unlikely probabilities, or it can show a change in climate, whereby the events are no longer extreme but merely normal events within a new popu- lation. A good example is provided by analysis of the 1985-1986 drought in the southeastern United States. Estimation of the severity and interval of likely recurrence for this drought was made possible by

224 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES :: W~ER~RESOUR(:ES~IAGEMENT~i~ i ~~ A A ~~ ~ A i ~~:~ ~~ ~~. H:u~nd~reds~of~bi I lilions~ot Eli den l~ars~ha~tei~b~et~:nikested :~s~~nce ~ lain i i I: ~~ ~ ter Or: ~ ~ ~~sta~ em: :~ ~~£~ hi. ~~arI~c ~~::~::~:n::r~l~:VAt~::~WAt~~:~::nro:~:ec~ts id: Jiiam~i.~:~i 1~—irate it ~~:~:i : ~: : : ~ ~ ~ ~ : : ~ ~: ~ ~ , ~: ~ ~ ~ : ~ ~ : ~ If:: : ~ ~ ~ If: : ~ ~ : : :-: i::: ~: ~ :~ i: ~ ~ ~ ~ ~ ~ : ~~: ~ ~ ~ ~ ~ ~ ~ po~r~1~0ns~ ~evees,~c~ ~a~nrte ~i~lmp~~; ~ gatio~ ~—~ i i ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ : ~ ~ ~ w a ~ ~ ~ : t r : ~ a t m e R t : ~ ~ ~ i F , | ~ a n i t S ~ ~ ~ ~ i a ~ r e ~ ~ ~ e ~ p ~ S : . ~ ~ ~ ~ i i ~ ~ t ~ i b e s ~ ~ ~ : r e s e r ~ r ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ :~ ~ :~ ~ ~ i ~ i ~: ~ ~ ~ ~ ::~ h~ave:~been~:~sed,~: ~: are~: rn:ore::~:seinsitiv~e~ to:~ envimn n~n~i~esi~ :~a~ ~id:~t - . ~ ~i~ ain~n~ iiniveStme~ ~t:~i~n: n~eW~ n^e—: ~s ~ on~l~i~sr~al ~tti~ik~ tt~a~bast~i~ :~:~ ~i~:~:vea' s.:~ :~on~:haLs~: ~i~hNi~i~tfu~l aoi~t h~ikimianaa-~: ~:~ ~: In~ourwaterre~sources~ :~ ~ ~ :~ :~: ~: ~ ~ ~ ~ :: ~ ::: :::~:: :~::::::: :::::: :::: ~:~ ~:~ ~ ~i~:I~o~y~a~n~i~m~r~ta~nit~c~haHe~e~ ~ tacesi:~thls~nian~i~:l~ - : C~:I~S:~ffi~ ~: ~ ~ ~impro:ve~how~rs~: vast~nvest~; is~tak~;n~g ~:n1D~accaunt~eco-: i~ :: : ~:~ ::: :~:~: :~.:~::~ ~:~ :::~::~::~ ~:~:~.~:~:: ~:::~ ~::~ ~::~ :~::::~: ~:~::~ ::~::: ~::::~:~::~: ~:~::~:~ ::~::::~::~ :~::~:~:~ ~: ~: ~: ~ no~m~lc: ~env~l~mn~m~ental:~,~ ~a~n~d~sociial i valuies.~i~ l~creases~:~i~n :~a~n~nioal be~nefi~i~i~i~ ~ ~ ~ ~ ~ ~ ~i ~ ~ ~: i~ ~ ~ i~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i ~ ~ ~ ~i~ ~ ~ ~ ~ ~ i~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~i i ~: ~ ~ ~i ~ i~ ~ ~ ::~ ~o~nly~a~i:~few~;percenti~ld ibe~i~wor~ ~ite~n~si~of~b~llil~=si~iof do4~Nia~i~a~coi~ld ~i ~ :: : :~:i::~: ~::~ ~:::~ ~ ~:~::::~ ~::~: ~ ::::~ ~:~:::~ ::~:~:~ ~:~:~:::~ ~:~:~:~ ~:~:~ ~:~:~::: ~:~ :~::: ~:~:~ ~:~:~::~::~:::~:::: ~:~ ~preiserve~e:nv~ir~onmenta~l val~ues~ ~that~i~re~i 3gno~red~ ~6ecades~iago.~i~ H~f-~ ~:~ ~ ~ ~ ~: . ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ , ~ ~ ~ ca ~ Y'~ wate~r~p~ro~c~ ~ave~ ~een ~p a~n:~r,:ec ~::t~O~seirve~: oine~:set~pur~p oses -i:~ut:~i:~ ~::~ operat~d~to se~rw:~ano~er.:~O~n~e e~le~i~:i~s~i~Tenr e~ssee~l~ei:~. ~i ~Origi~:n~al Iy~developied~ ~r~i~:od ~c=oint~ ~ i~: in~p~ro~ites~mele~ir~ic~ :: ~ : ~ :: ::: ::: ~ ::: ~ : ::: ~ : :::: ::: :~ : ~ :~: :::: :: ~:: : ~:: ~ :: : ::~:: :: ::::: : :~: ~ : ~: : ::~ ::: ~ :: :: :: :::: : ~ :::::~: :::: ::::::::: : ::: ::: : ::::::: :: :::: :: ::::: ::::: ~:: :::: :::: :~ ~ : :~:::: ::~:~ : :~ ::: : ::~:: ~::: :~ :::: Dower ~:wit: 1~ ben:ef~i~ts~:~fa~r~:~ar~eater:~t ~:an ~It ~nise~resu ~n~:~t~om ~ll~di~:nt~.~ ~:~i~:~ Th~i~s :~:~:~ren~ce~b~ee~n~:w~h~i~:i~s:~i~ pl~:r~i~a~i - ~:~i~s~a,~u~W c~:~sug- ~ ~ ~ ~ ~ ~ ~ ~ · ~ ~ ~ ~ ~ ~ gests~a~ma~nage~ment~o~ortu~n~i - , ~e~3~il~a~ Y~s~l~n-~:ei ~m~uc l~:t se~p~ ~a~n~nI`~ ~ :: :::: :: ~ :~:::: ::~:: :: :: ~ :::: ~ :::: :: 1:::: ::::: :::~: ::: :~::: ::~:: ::: ::: ~:occurreC~::oe£aGes: ago.:: ~:~ ~:~ ~A~:~m~ajor~dieraT~w~ate:r:~:resources~ agen~cy~ t:h6~U .S. ~B~ureau~of ~Rec~larn:a ~::~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~, ~ ,, ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . :~ ~ ~ ~ ~ ~ ~ :: . .~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ t~iio~n'~:rec=~ogni:z~en~ ~th~iiS~i~ ch~a~l~lenge:~anO~mrm:al~ly~re2~lign~m~sssfon~iaMf~ ~ ~ ~ ~ ~ ~ ~ ~ ~ · ~ ~ ~ ~ ~ ~ ~ ~ ~ T~ ~ ~ ~ ~ ~ ~. ~ ~ ~ ~ ~ T~ ~ ~ ~ ~ ~ ~ ~ T~ ~ ~ ~ ::~: ~t;:o~m~ co~n~str:uct~ oa~ iaina :~towa~m~prove-~ ~mana~mein:it~a~n:~a~at~mn ~iot~i :i ::: : :: ~ : :: ~. ~ ~ ~ :: ~ ~ i: . ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ ~ T~ ~ ~ ~ :~ ~ ~ ~ ~: ~ ~ _ ~ ~ts:~vast~ ~prior~:nv~es - ~em~i~t~ne~:~ il:7~mr~n:~states ~I~ne~n~atioi~n:~S~i~:a:rgest~ii~ :: ~ ~ ~: ~ ~ ~: ~ ~ ~: ~ ~ :: ~ :: ,: ~,~ ~ ~ .~ ~ ~ ~ ~ ~ ~ ,~ - ~: ~ . :~ ~ ~ ~ ~ ~wate:~:~resiolo~ll-c~eS~agelelcy~i~tne~:u~.~.i~i~Amy~i~rpS~or~ng~:J~n~eer~S;~:nais~i~nm~ir ~i~ :::~ ::::~:::: : :~::: :::: :::: :: ~ :::::::::: :::: : ::~::: ::::::~ : : ::~::: : :::~:: ::::~ :: :::~:: :::: ::~::::: :~:: ::::: ~::~: : ~: : ~:~ ~:::: :~:~ :~: ::::~::::: ~ ~ ::: ::: :1: :: ::: :1 :::: :~::: :::: ::::f: :~: ::::: ~: :: ::::~::: ::~: :: r:: :.:: :: :: ::f:. :::: :: .~ : :::: :~::: ::::: l :::::: ~:.: :~.:: .~:: :::~: ~:~:::: ::~. .:::::::::: :::: :::: ::~: :::: ~ ~ ~sucn ~a~:~to.-ma~l~:~s~p,~ou~t~: i~i~m~air.~y:~or~i~:l~ts~:lstr,ict :~an~i~a::lv~lsil~:o~n~rices~ ::~are~ :~fin~d~i~rg~new~n~on~strucitu~ral:~:s:ol~Won~s.~l~nagemebt~carifli~i:~Warise~among~:~ ~ ~ ~ ~ ~ ~ · ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~, ~ ~ . ~ ~ :: . ~ ~ ~ ~ . ~ :~:~ ~co~mnet~ ~u~se~s~ ~ wate~ ~ ~s~c.~i ~as~ ~lirr~lR~atIon~ ~m~uin~c~! Da]~ siU=,hm~~ ~-~i~ :~d~iropow~er~ ~::~:~,=~wer ~cool ing ~ wi~ifNe~prese~rvafion,~ fisl~i - ~:: q~.iW~i~:~ :~ control: ~'no.~ust;rla~l ~u~se~ ~:~:nav~f~gat:l~o~n,~ano recreat~:~.~ ~:~t~l:mm~:~ mana~g;em~ent-~:~:~ ~ ~ , ~ ~ , ~ :~ ::~:of :the :~n:at:ion'~s~ ~water:~ re~sourc~es~ :is:::~:e~ ~key~:~:to ::~reso.iiv~ing::~:se~cai~fli~c~ts.~::~:~:: :::: ::: :::::: ::~ :::: : :: :: ~::: :: :: :: :~::: : :: ~:~:: ~:::: : ::::: :~::::::: :: ~ :: :: :::~: : ::: :~::: ~ :::~::: ~:::::: ::~ ::: ~ ::~: ~ : ~ ~ ~ :::~ ~:i::::: :::: ~ : :~:~:~::~ :: :~: :~ ~better~ i~nform:atior.~:lis~the::i~key~to ~imp~£oved:i~:water ~imarlagem - ~:~ ~ ~ ~ ~:~ ~ j ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ :~ T~he '.n~porta~nce ~ot water: re~soUrces~lnana~g~en'~ent ~was: ~.~::~t~g~h~l~lgh~ted~ ~by~ ~:~ : , :::~ : ::: , :: :: :~: :~ ~, ~, ::~ ~: ~ ~ :~ ~, , :~ :~ ~: ~: ~ :: ~ ~: ~ ~ ~ ~:~ ~: ~:~ ~ ~ the 1:98~8::droL~t~g~h~t. ~Print:~ano~ ~e~l~ectronic ~',neDia~oroug~t~; u~s~ ~cl~ear~ l~m~age~s~ of~: ~: ~ ~ , . ~ ~ ~ ~ ~ :: ~ the consequences o t ~d~rowght~ba~rges ~stranded~on~ sand~ba~:rs~ ~in~ th~e~t\A.isi-~ ~ ~ ::: ~ :~ :: ::: :~ ::: : :~ :: ~ : :::: ~ :: :::: :~ ~ :: ::::::: :::::: : :::: :::::::::: B~ ~ ~ ~ ~ ~ - ~ : ~ ~ . 1 :::~ ~:: ~ ~ ~ :~ ~ ~.: ~1 ~ 1 : ~ :: _~~ :: :: ~ : :~:~ : ::~: ::1:~ ~ :: sissippl Klver empty re~servo'~rs ~ano witnerea.~ corn~Tl~e~tG.s~.~ ~l~e~oro~t~grit~ ::i l I us:trated: d ramatic~al ly ~::~that:~th~e~ ~ avai~l~a:~l iW~l:~of ~water~:: i r~vo~Ives~:~r~i~sk :~a~:nd:~::~ t~hat th~e risk see~ns ~t o be~ increasing.~ ~ ~H~ow~ wil I in~creases in~ :atm~ospheric~ caroon~ U~ox~tUe~al~lu otner Ereenhou~se~aa~ses~chan~e:~ the cl~matet :~ W:~hat:~:~:~: ~ ettects w~ll I such ~ch~ar.ges~h~ave~ on~ou~r~wa~r~ ~r~eso~u~rc~es .li~ ~ bom~e ot the ~ntormat~on nee~nen~ to '~mp,rove:~:wa~ter ~reso~.~r~ces ~mana~ge-~ ~ ~ , . ~ ~ , ~ . ~ , . . ~ , ~ , ~ _ ~mer`.t ~:w' 1~.~ co~me~:~ tro~m~ ~ l~mprovec~ ~ ~a~pp~l~cat'~o:~.?.~o:J:~ex~::s~t~l~n~g~ ~tec~nn:ology~. ~ ~:~:tor: ~::: exa~mple~,~ ~new~d~ata: ~sy~stems~u~sing~ a~ut ~mated~:sur~ce~ :6bservat~ons:)~sa~te~l-:~: :~:Iite c:ommun:ications, :w:eather rada:r ~and:~satell:~ite::i:m~agery~re~beg~inning:: :: : : ~ :: :~ : : :: ,:: ::~ ~:: ~ : : :~ ~ ~: ; ::~:: :::: :: :: :~:::~ :::~: : :::: ::: :: :: ~: :~:: :::~ ::~:

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 1~ ~ ~::~ ::: it: : I::: : : : ::: :::: : ~ : : : : ~ : : : : to Me Used. ~ ~~ Advances fling ~~ computer Technology, especially computer ~1~:~ ~g~aphi~an~d~g~g~ra:p:hi~c i~n:~rm~ation systems ~~and~:;~d~ata~ Abasers:, are bring-: ~ing~n~ew~opp~ortu~n:~;~ties~to~:malce~:~:~beder:decisions~.~ :::::: air: :~:~:~ ~ ::::: ~ I::::: ::~ : : ~ i:: :::: ::~ ~ ~ it: ::: :~ :: :~ : :: : : : ~~:~But~th~e~i~m~porta:nt~i:ntorm~ationreq~uireG ~~torl~mprovec Water resources: ~ ~~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ :: ::~ma~nage~ment~::~must::~a So :~:com~e Caroms: Im~provec sync :ro og~c science.: ~ ata ::: I:: system~s~;~a~r~ costly :a~nd :can be: :justified only when: there is rain adequate ~: ~~ :: ~~ ~ ~ :~ ~ ~ ~~ ~: ~ ~~ :: ~ ~ ~ ~ ~ ~ ~~ ~ :~ ~ ~~ ~ ~ . . . ~ . . . :~::sc~i~er~ce~base~to~assure: that the i:nform~atio:n: will;: bemused swell 1. ~~ Major: ~ . ~ :: ~ : ~~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~:~deral~ta~:~ pro~gra~m~s,~:~s~uch~as~ th~e~s:tream :~gagi~ng program:: of t:h~e~:U~.S. Geological Survey,l~are~ continually: under severe budget pressures:.: Moreover, : It: is: never ~:possi:b~le:~:~to:::~measure ~:a:l~l that: needs:: to;: be: known.:: The :::only::: : li~rn~tiv~::~:i ~~ ~~::~ 4ev~lon ~~ sc i e~n:tific~ ::met:h:~ods: to ~: :~:nf~r :: :wh~at: needs ::::to :be A: ~ i: Known ~:;tro~m~:~wha:t :can ~be: ~measured. ~ i: 225 the availability of high-quality hydrometeorological records main- tained continuously for a site since 1934. An even longer precipitation record, 110 years, was located for a nearby station. Whereas the 1985-1986 drought was the most severe in the 53-year record, the 110-year record revealed five periods of even less rainfall before 1934. This information substantially altered the interpretation and implications of the 1985-1986 drought, showing it to be a much more common event than it was first considered. Need to Collect Data Worldwide to Address Global Hydrologic Issues Useful hydrologic data representing processes at the gIo- bal scale are sparse. Most hydrologic data have been collected with local-scale (or at best national-scale) questions in mind. Although these questions re- main important, hydrologists have begun to recognize subtle hydro- logic effects that have important consequences for human affairs. The uneven distribution of hydrologic monitoring stations around the world makes it difficult to study the simultaneity of trends and the full extent of widespread changes that are suspected to be linked. It is therefore necessary for international scientific agencies to assess the distribution and quality of hydrologic data collection around the world. For those hydrologic variables that translate into recognizable elec-

226 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES tromagnetic features that can be viewed from aircraft or satellites, remote sensing methods must be used to fill in the vast areas between ground-based stations. Because it is not possible with foreseeable technology and resources to monitor hydrology over the entire earth, some important decisions must be made to deploy instruments that will help in answering hydrologic questions of global significance. Data on water quantity flows and storages are usually collected in attempts to define total or partial water budgets for drainage basins. As the size and complexity of drainage basins increase downstream, it becomes increasingly difficult to collate the various data sets- often gathered by different agencies or even different nations into a useful water budget with a clear definition of the various processes of water transfer and their interactions. It is more difficult to recon- struct the influence of, for example, land use changes on the flow and sediment transport of the Mississippi River than it would be to carry out the same task in a small, forested drainage basin in the southern Appalachians. Spatial and Temporal Issues in Hydrologic Problems A funciamental block to progress in using most hydro- logic data is our poor knowledge of how to interpolate between measu remeet pal nts. Some important hydrologic changes may be clifficult to detect because of large interannual or inter-event varia- tion; others are difficult to measure because they involve rare, short-! ived, catastroph ic processes. A fundamental block to progress in using most hydrologic data is our poor knowledge of how to interpolate between measurement points. For example, depths and water equivalences of a snowpack are measured at many snow courses in cold regions, but it is only possible to use these data as crude estimates of the water content of a regional or basin-wide snowpack. Strong spatial gradients caused by topography or vegetation on snowfall, interception, redistribution, and melt are not explicitly modeled in forecasting water supply, runoff rates, and soil-moisture recharge, and in mountainous basins rain gages are of- ten poorly distributed in the higher elevations (Figure 4.2~. Topo-

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 4 4oo Drainage Basin of Eel River at Scotia, CA. 39o 227 ~ ·2 ~ ~W '\18 \9 ~ 1 110 / - . ~1 1 · 3 ·6 1: ~ at;' 16 · _ 17 1 \ 124° 1 23° 1. Scotia 7. Shelter Cove 13. Dos Rio 2. Bridgeville 8. Garberville 14. Covelo 3. Mad River Ranger Stn. 9. Alderpoint 15. Branscomb 4. Honeydew 10. Richardson Grove 16. Willits 5. Miranda Sprengler Ranch 11. Standish Hickey 17. Potter Valley 6. Forest Glen 12. Cummings 18. Lake Pillsbury FIGURE 4.2 Rain gages in the Eel River basin at Scotia, California. (At first glance the rain gages appear to be well distributed, but most are in the river valleys, and so precipitation is not measured in the higher elevations.)

228 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES graphic influences on rainfall, evaporation, and soil moisture are poorly documented at scales varying from individual hillslopes to entire mountain ranges, and there is currently little understanding of the relationship between regional, time-averaged rainfall rates and the frequency and magnitude of storms. Understanding how to interpolate from a few measurement points requires some thorough field studies of the processes responsible for spatial variability and of the relation- ship between long-period averages and hydrologically sigruficant events. Large-scale hydrologic processes such as the coupling between global atmospheric circulation and the North American seasonal snowpack or regional droughts are not well understood or predictable. Under- standing them requires simultaneous measurements of phenomena that have traditionally been within the purview of different disciplines or agencies. There is a need to undertake simultaneous large-scale measurement programs within the context of specific hypotheses about these couplings. Careful design and international cooperation will be necessary to develop such programs in a useful way. Important hydrologic changes may be subtle and difficult to detect because of large interannual or inter-event variation. Recognition of such changes or their absence therefore requires carefully designed, long-term monitoring networks. The paucity of suitably long instrumental records requires the use of historical stratigraphic, botanical, and geochemical records of hydrologic change. The development and quantitative interpretation of these noninstrumental records are in their infancy, but they promise much useful insight into the frequency and magnitude of climatic and hydrologic fluctuations, floods, and sediment yields. Some hydrologic events involve rare, short-lived, catastrophic pro- cesses, such as the influence of the eruption of Mount St. Helens on flooding and sedimentation along the Columbia and Cowlitz river val- leys (Figure 4.3), or the effects of Intense forest fires on runoff and erosion during succeeding wet seasons, or He release of toxic chemicals after ~ndus- ~ial accidents. The probability is low that an instrumental network will be in place to record such an event adequately. Therefore, government agencies and granting agencies need to be able rapidly to mount coordinated field studies to collect data when such transient processes occur. Collection and Archiving of Selected Water Samples The archiving of selected water samples will allow better analysis of chemical and biological changes in aquatic habitats.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 100 ~ ~ 90- 111 LL 80 - 70 — - U) 60- z I 50 - 40 - LL `~ 20 LO In 30 - 10 o 229 Sediment deposited in former scour hole Cowlitz River ~ ~1 WAS _ ~l~4 2 Columbia River 1 1 o 3 ~\~9 ~ Coffin Rock - - FIGURE 4.3 Accumulation of sediment on the Columbia and Cowlitz river beds after the eruption of Mount St. Helens on May 18, 1980. SOURCE: Reprinted from Haeni (1983) courtesy of the U.S. Geological Survey. Hydrologic data needs involve more than requirements for nu- merical information. The archiving and rapid retrieval of samples for future analyses will be needed for the continuing analysis of envi- ronmental conditions in aquatic habitats. For example, an essential feature recommended for the National Science Foundation's Long- Term Ecological Research (LTER) Program is the archiving of chemi- cal and biological samples. Established museums have served historically as repositories for biological materials. Unfortunately, such collections, although usually catalogued and curated well, have been dispropor- tionately directed toward terrestrial organisms, or toward only the terrestrial life stages of aquatic species. Thus special initiatives will be necessary to ensure that appropriate aquatic biological materials are archived and curated, and cryogenically or chemically stabilized water samples from carefully selected sites should be archived for future analysis. If such samples were available today from past decades, they could be used to evaluate changes of chemical parameters in aquatic environments. STATUS OF HYDROLOGIC DATA Knowledge of the distributions in space and time of water, solutes, and sediments is needed for investigation of scientific questions,

230 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES management of water resources, and environmental decision mak- ing. Industrial and agricultural development in temperate regions has led to intensive measurement of hydrologic variables, and envi- ronmental managers have been able to manage resources in such regions, with large errors occurring only occasionally. Many developed nations have extensive, governmentally sponsored programs to monitor the quantity and quality of water resources. Measurements include monitoring of ground water, reservoirs, streamflow, precipitation, and evapotranspiration, and, to a lesser degree, the amount of dissolved and particulate contents in the water. Long-term records are rare, seldom exceeding 50 to 80 years in length, and often the sites at which data are collected have been moved, or the hydrology anthropogenically altered, so that records are not homogeneous. Records from the few long-term stations that have collected data over several centuries and from paleohydrology show substantial changes in hydrologic regimes. Our knowledge of the frequencies of extreme events is usually uncertain. Availability of Hydrologic Measurements Hydrologic data networks are best developed in the hu- mid-temperate, mid-latitude, industrial ized nations. Detection of hydrologic change requires accurate, long- term measurements, and reliable intercomparisons of . . .... ~ v measurements made in different areas or many years apart are crucial. Although most of the developed regions are classified as having a humid-temperate climate, the demands from the population, agriculture, and industry for water of appropriate quality are not always met. In semiarid areas, such as the American Southwest and some metropolitan regions, projections indicate that demand will exceed supply within decades, requiring either conservation measures or more importing of water. In less developed, often tropical regions, data and knowledge of local hydrologic cycles are woefully lacking. The tragic realities of drought prove that precipitation and water supplies are inadequate, but there are few data that could be used to show potential carrying

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 231 capacity even if judicious resource management were to be under- taken. In wetter tropical regions, major land use changes are under way that may alter the hydrologic cycle, and there is little quantitative information to show the natural variation on which the changes will be overlaid. Precipitation and streamflow are two of the most fundamental quantities and are the two most frequently measured. Sufficient data are available in developed regions to estimate mean values for pre- cipitation and surface runoff. However, only rarely are precipitation data comprehensive enough to quantify spatial distributions that are crucial for some applications, such as precise flood forecasting. This is especially true for regions where floods may be produced by un- evenly distributed convective storms. Normal ranges of streamflows are often known for particular drainage basins, but high floods and extremely low flows are measured much less precisely. As humans use more exotic chemicals in industry and everyday activities, the opportunities for these chemicals to enter the hydrologic regime increase greatly. Complete analysis of water for all common and exotic solutes is expensive, but for water used for human consumption and industrial processes, such analysis is becoming more necessary. Contamination of surface water and, even more so, ground water can render resources permanently unusable. More data on solutes are urgently needed to document contamination and to lead to the devel- opment of better preventive measures. Even in developed, more intensely measured regions the data are seldom adequate for reliable forecasting and analysis of water quality. The problems are of a dual nature: the supply of water and its quality are one problem; current and projected use is also uncertain. Recog- nized contamination and loss of resources are increasing at the same time that water use is increasing. Sometimes, data are available to show the probabilities for long-term availability of the water supply and the variation through time. Usually, however, the record is too short to show the range of likely natural variation or too limited spatially for comprehensive hydrologic planning. Fluxes and Reservoirs of Water, Solutes, and Sediment Fluxes and reservoirs of water are measured routinely, but knowlecige of spatial and temporal distribution is not adequate everywhere.

232 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~~ ~~ ~)l~l;OG~1~ 5~1~—E W~ERSH~S~: On ctr0:m~ smoker ~~a~l:~5W~ ~ ~~ ~ ~ ~ ~ ~ . ~ ~ ~ ~: ~ ~ ~ :~: ~ ~ ~ ~~ ~ :: ~ ~ ~ ~: :~ ~ ~ ~ ~ ~ ~ ~ I. ~~ ~ to: en ~sta ~ e~ ::: ~~ ~ ~~am~t ~ ~~ Basins t Its Monad ~~ T: :: i: :: ::: i: ~~: ~ if:: ~::: ~ I: :~ ~ : ~~ ~~ ~T:~ ~ I:: ~~ ~ ~ ~~ ~ ~ Add: ;~ ~~ ~~ Em: ~::comp~rorm~ses:~h adobe made: in: Oral: selection c—~ ding ~~ ~ ~: ~: ~~ ~ ~~ :~ ;. ~ ~ ~ :~ ~~ ~ ~ ~: ~~ ~: . ~ ~~ ~: ~ ~~ ~~ . ~~: ~ ~ ~ ~ ~~ ~~ ~ ~ ~~ ~~: ~~: ~ accom~m~r~m:o^deFate~; 1~ I ~ In ~ 1a Option ~~ acrid Ed, :: :: : ::: :: ::: : :: : : :: ~ ::: : : : :: :: : :: ~~ I: : : :~: Aft: . ~ , ~~ ~~ ~~ ~ ~ ~ ~~ ~~ ~~ ~ ~~ A ~ :~ ~~ ~ ,:I:: 'TV. ~~ ~~ ~~: :~: ~~ ~~ ~~ a: ~:~ ~~:~:~:~ ~~::~:~:~: ::~:::: :::::: ::: : ::::::::: ~::~:~ : i::: ~:~:~ :::::: :::::: ~:~ ~ :~ Hi: ::::~:: i: :: All::: ::~: :: i: ~ ~~ :~ :~: ~~ :~: ::~: ~:~ ~ :::: ~:~:~: ~~:~ ~:~ :: a::: :: ::::: ::::: .~ .: ~ :: ~~:~:~:T E:: Gnaw: ~ range jot 3as':~n at: sizes ~~re~sent~~l~n~ t lie ::~r~etwor <~ em s Tad ~ ~ ~ ~ ~ ~ . ~ ~ ~ . ~ ~ ~ ~ ~ ~~ i ~ ~ ~ ~~ ~ ~ 1 ~ ~ ~ ~~ ~ ~~ t:~ ~ ~ ~ ~ ~~ aft: ~ Ape ~ errs Ad cog—mp~t~ve~ arise Cot w~ c~ata~are~<Q~ecteo. : ~ ~ Aid: ~~ : ~~ ~ :~ ~: ~ ~ ~ ~ Ad: :~ ::: : ~ ~ I: ~ ~ :~: i:: ::: T~ ~ ~ ~ ~ W::: Add: :: ::: i::: ::: :: :~:~:~:Becau~se~s:tream ~~ar~tiW~a~d ~~a:l~vary:: grea~v~h~ basi~p:~ sine ~~ a~ w ith :~:geo log Al: and:~:~c~l~i matol:ogi:ca i~:~stom;~ :direc~ corn pa rl s ons: On-: ~ ~~:~ :: :~: ::::: A::: : :: ::::: i:: :: : ::~: :::: :~::~ ::::: :~:: ~::~::::: ~ : ::::::: :: :~:: ::::: ::~: ~::e:::~:::~:::~ ~~ :: ::~ ::: :::::: :~:re:::~::: :::::::::: ::: :~:: ::t: ::: :~ ::::: :~:::~ :. : ~ not~:~gen~eml~:ly~ne:~ ~m:aue~et~e ~~s~s~ a=~c~nem~l~£oncen-~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~~ ~: ~ ~ ~ ~: ~ ~ ~ ~~: ~~ ~ ~: .~ ~ ~ ~ ~: ~ T:~ ~ ~~ ~ ~ ~ ~ ~ ~: :~ ~ ~ ~ ~ ~: ~~ ~ ~ ~ ~ ~~: ~;ttations:~m~eas~u~red~::~at These stations and th;ose~ot3s~ved~in~ ~~l~ns~u~ ~ ~ :: I:: : :::: ::~::~ :::::: : :::~: :::::: :~: : ::~: I::: : :::: ::: :::::: ::::: 4:::: :~ i::: ::~:~ :~ a:: ~ ~ ~ :~ ~ those range. ~~ ~n u s,~wn'~l:e~e~program~ ~~: ski ~~su:~'n:~t ~~ ~~ ~~ : i: ~ Ida min~ima~Ry delved basins m:~a~;dd~ra~ ~ pi apt ~~ ~ W~ ~~ ~ ~ :~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~~ ~ ~ ~~ ~: ~ T: ~~ ~ ~~ ~::ge~chem~ical,~::and~:eciol~gical~ settings, lbe~more~ti~rnited~tang~ of basin ~ ~~: ::::~: : a: :: : : : : : :~ :~ : :: : : :: : :: : ::: ~ ::~:: : :~:: : :: :: : :: : : : ::: :: : : :::: :: I:: ~ : ::: ::: :::: :::~:: : : ::: : :: ::: : ~ :: ~ s izes~re~esented~i~n~:~;~t~ neth ork mats: and serioos~r~ro:bl~:ern:~ brig ~ ~~::~ ::: i::: ::::: :::: i:: ~:~ :::::~: ~ :~: ::~:: :~::~ ~ ~ I::: :::: :~d:ata~to;~:~de~ne~:ba~sel~:i~ne~n:d~ns~ ~~r~itreams~we~ i n~eneral~.~ : :: ::: :: :: :: : : : ::~ ::: :: :~ i: :~: :::::::: :::::: ::: :::: ::::: :~: ::~: :::~: :~ i:: ~~:Perhaps~::;~u~Itimate~ l:i~mit~on~th~e ~abi:lLi~:~6f ~hyd:ro~to~ti~:~stream~ :::: ::~: :~:::~ :: ~:~::~ :: :~ I:::::::: A::: :~: ::::::: :~::: Add: :::::: :: ::::: :~:::: ::: ::::: ~ hi::: ~ ::~::: a::: ~::~:: :::~: ::::: ::~::~: :~:::: :::~:~: :: i:: : ::~: :: ::: ~ :: ~ ::::~:

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS ::: ::: ::: : ~ I: :: . ~ ~ ~ ~~: 233 ~: ~~ ~~:~w~ith~:~pr~i~sti n~e~:~lwate~r~::q~ual ity~:ste~ms~l~fro~m~:the:~:ubiq wito~u~s~ I tffe~cts~:l~6f~a;i~orn~e~ ~ ~ ~ ~ ~~ ~ ~ ~ ~~ ~ ~ ~: ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~~ ~ ~ :~ ~ :~ ~~ ~ ~~ ~ ~ ~ ~ ~~ ~ :~:~:ii :~:pol l~u~tan~ts~ on ~~th~ei~c~h~emist~ry::;of~re:am~s~.~:l~l:~l n~d~u~str~i:~a:l:~:a~nd~:ag~ric~ultu~:ra~l e~m~i~s-~ :~: ~ I: ~ ~ ~~ ~ ~ ~~ ~~ ~~ ~ ~~ I: ~ ~ ~~:~ ~ : I: ~ :: ~ :: : ~:~ i: I: ~ ~~:~ ~~ I: ~~ :. I: ~ ~~ ~::~: :::: I:: ~ ~si~ons~of~:a~v~a~r~ety;~of:~mia~te::r~a~s ro~tI~ne~:y~:t~ra~ve~hu~nid~md~s~of~:k~l~omete~:~n~:~:~:~ ~:~:t~he~:~:~al:mos~:pl~:re~b~efore~d~o:r~:~wet~d~e~positio~n~lto:~th.e~:~:~s~u~rfa£-e,:~and~,~s~ig:n~if~i- ~:I~:~c~nt:~a~m:o~u~nts~:~of ~~th~is~ma;tte~r~ a~re~l~ultim~atei~v~ca~r~ri~e~d ~~st~re:a~ms~bv~r~u~noff ~ ~~ ~: ~~a:~n~d:~:~:~ro~u~nd~w~ater.~:~::~ ~Kn~ow~l:e:d~ae~ of The:: l~o~n~:~-~ra~n~ne~eftects~::~:ot~ AL ~:~q~u~a~l~i~i:~y:~:~:~n~: ~ ~~::~: ~~:~ :: ~wa~te:~r::~q~u:a~l~ I:ty:~h~as:~:i~n~c:~re~a~sed:~:~a~s~: ~~a~:~re~su~!t~o~t~:~:~resea~rch~:~c:o~nd~u:~cted~over~:~t~h~e~::~ ~:~ ~ ~ :: ~:pa~st~ d e:cad~e~: Two n ~~::~h~e Defects ~~ of Sac ~~d~r~a~i~n~ Ha n~d~:~s~n~ on streams ~ an-d:: As .~ ~~:~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ :~ ~ ~: ~ ~ It:~i~s~ ~not~:s~urp~r~i:s~i~ng,~there~re, :that~some~:of flee: most~:~s:~cces~ul~a~p:p~l;~c:a-~ ~::~tions~ ~~data~:fro~m ~s~m~a~l:l:~,::~u~n~d~evelo:p~e~d watersheds slave Been ::~n~::~m~-easur- ~~ : :~:~i~a~g~th~e~ ~efTe:cts:l~:~su~ifu~r~la:nd~:~n~i~trate~e~m~i~ssi~o~ns~o~n~:~s:tr~e~a~m~ch~e~m~i~stry~*~l~:~Th~e~l:~ ~:~1: valise ~~:of~th~e~se~ ~s:tu~d~ies~:~h::a~s~:~bee~n~n::hd~n~c:ed:l:~b~y~the~:avai:lability~of~yea~rs~:~ ~of~conti n uous~;~d~ata ~ ~on: ~~s:trea~m~ch~e~m istrLy~l~ ~co~i:re:i~ate~wi~h~the~rad:u~a~' ~~:~ :::::::::::::: ~ :~: : :::: :::: ::: :: i: I: :::: ~ :: ::::: I:: ::: ::: :: ~~ ~ ::: ::~:::~:: ~ ~ ~ : :: ~ ~ I: ~ ::::: ~ ~ I: I:: : ~:~ ~ ~~ ~~ ~ ~ ~~ ~ ~ ~ :~ ~:~ :: ~~:~ changes th~at::::~:have~: occurred~::~i~n~:~i~n~d~ustr~la~l and a~g~ricu~l~tu~ra~l~:e~m~l~s~si:l~o~ns:~El~gu~re~ ~~: ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~~: ~ ~ ~ ~ ~ ~~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~~ ~~ :~:~:~:4~.~4~i~1~:~us~t~ra~te~s~:th:e~ca~se~:~fo~r~s~u~fu~:~.:~ ~~; ~~ ~~ ~~ ~~ln~su~:~mm~a~rY~:~m~a::ny ~~hy~d:rol~o~s:ts~h~ave~£on~£l~u:ded~ ~~th~a:t~sa:m~pli~n~g~:~n~::~:u:a-~:~:~:~:~ ~ : :: ~ :: : :::: ~~dev~el~oDe~d~b~a~s~i~n 5 :~d~oe~s::~not :~D~rov~ide~Wa~dI~s~t~i~:n~c~t~sTet~of~:~h:vd~rol~oR~i~c:~:data~:~t~h~at~:~:~:~: ~~: :::~c~a~n:~:~be:~u~sed~:~:~:~o:ne:~:~to~:~:~d~efi~ne~Pri~stLi~ne~:~c~o~n~d::i~tl~o~n~s~.::~:~:~:~l~n~:ste~ad~,~e~se~:~d~a~:~::~: ~~:~:~ ~~rep~res:en~ owner: ~~:e:xt~re~m~e Bin The Wide ;~ra~nge~:~of~:~effec~t~s::~:~t~h~at~h~u~:m~a~n:~:~a~i~vi~tY~:~:~:~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ :~: ~ ~ ~ ~: ~ :~ ~ ~~ ~ ~ : ~ ~ : ~ ~ a s ~ ~ : : : ~ ~ ~ ~ a ~ ~ ~ ~ o : n ~ ~ ~ ~ ~ ~ ~ ~ Y ~ C r o : ~ o ~ : ~ ~ ~ c ~ c a n c ~ i ~ t ~ ~ ~ o ~ : n : ~ s ~ . ~ ~ ~ ~ ~ ~ ~ Knowledge of the fluxes of solutes and sediment is usu- ally poor. Routine measurements of soil moisture are sparse. Rainfall Rainfall is routinely measured throughout the world, but obtaining solid knowledge of its spatial and temporal distribution is hampered by a diversity of observing standards and an erratic pattern of ob- serving networks. Although in some parts of the world rain gages have operated for over two millenia, extensive coverage exists for one to two centuries at best. As with other hydrologic data, coverage is poorest in arid, semiarid, tropical, and highland regions and over the oceans. Like many other hydrologic parameters, rainfall is highly variable in time and space. Thus large-scale fields are difficult to derive from

234 1.5— en- 1.2 UJ , Lo - en ~ ~ ~ 0.6 Li En oh ~ 6 en 0.9 0.3 o OPPORTUNITIES IN THE HYDROLOGIC SCIENCES 68 78. 7j~0 75 I' 72 80,'. 79 . NE 76. 74 73 Y = 0.12 + 0.23E 78 76 I. 77 71 74,/80 6~;3 - SE 68 70 72 l l l Y =0.12 +0.18E 4 5 0 1 2 3 SO2 EMISSIONS, AS SULFUR (9 m~2 yr ) FIGURE 4.4 Average stream yield of sulfate at USGS bench mark stations. Sulfate data are plotted against regional (Northeast, Southeast) sulfur dioxide emissions for the years 1967 to 1980 (two-digit numbers). During the period, both emissions and stream yields of sulfur decreased with time in the Northeast but increased in the Southeast. Both regressions are significant at the 0.01 level. SOURCE: Reprinted, by permission, from Smith and Alexander (1986). Copyright (3 1986 by Macmillan Maga- zines Limited. point gage measurements, many of which are made at unrepresentative sites. Moreover, data on time scales of less than a month are difficult to obtain, although for many studies and applications, data recorded daily or even hourly are necessary. Gage data are also influenced by the characteristics, location, and exposure of the instrument. Gradually, satellite methods to estimate rainfall are being devel- oped to rectify these problems, but so far all are highly empirical and cannot readily be applied to locations other than those where the metals have been tested and calibrated. None provides a high degree of accuracy. Immediately needed improvements are the development of methods to optimally combine satellite, radar, and ground mea- surements with statistical theory to produce large-scale rainfall fields, and the creation of better archives of already existing data.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 235 : ~~ ~ ~ ~ ~ I: ~ I: e · iJ~AJVI ~~ _~ TITUS ~ A: ~~ :::~ : ~ ~ On_ neon: ~ ~ ~ i: : ~:~ of · JO: ~ ~ ~ i: : I: ~~ ~ i: :~: : ~ ~~ ;: I: : ~ ~~ ~ I: ~~ ~ ~1:~892~ Ja:mes ~Churth~began::~teachi n~g~at~the~ Urn i:vers~rty Of Nevada; ~~ :~ ~~ ~ ~~ ~~ ~ ~~ ~ ~~ ~~ ~ ~~ ~~,~ ~ ~~ ~ ~~ ~~: ~ ~~ ~~ ~ ~~ ~ ~~ ~.~ ~ ~ As a~fessDr~Greek~:anu~:~l~in~.~t le~was~:~a~l::so~an~avid~o':utooorsma~n ~~ ~ :~ ~ ~~ ~ ~ ~ ~~ ~~ ~~ ~ ~ :~ ~~ ~ ~ :: ~ ~~ ~ ~~ T~ ~ ~~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~devil,~w~intertime:pscents1nthe~Slerra~Nevada.~-:~ What ~s:ta:rted~out~:as~oure~:~ adventu~re~quickly~became~a~ passion~:~of some::::: ~~ ~ considerable Em i~i - I n me World: of ~ hydra ~ :~ ~ ~: ~~ ~ ~ ~ ~ ~ ~ ~ :: I: ~ ~~ : ~ :~ ~ ~ :~ ~ ~ ~ ~ ~ ~ T~ i: ~ ~ ~~ ~ i; ~ ~~ ~~ I: ~~ ~ I:; ~ ~ ~ i: I; ~ ~~ I: : ~ ~ ~ ~ ~ i:: ~ ~ ~ ~ ~ ~ ~ ~ ~ urchJs~lov.e~the~:~s~nowy~:mou:n~tains~soon~led~tO~ his ~~:~3ending~a~ I; :~ ~ ~ ~ great~dl owe into wintry ~~ldndscapes.~Aware~:~bt~ lists reputation A Ma ~~:~ i; :~ ~ ~ ~ T: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ i: ~ ~ ~ ~ ~ ~ ~ ~ ~ i~ ~ ~ ~ :~ ~ ~: : ~ ~ ~ ~ ~ ~ ~~ ~ i~ ~~ ~ ~~ T~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~ . ~ ~ i: ~ ~ ~ ~ ~ ~ i; :~ ~~powe':~:~as~ ~ ~~ Mama ce~mea~su~rem~ents~e~snow~deposits:~ ~ ~ ~ ~ ~ ~ ~ ~ ~ T~ ~ ~ ~ ~ ~ ~ ~ ~ ~ :: ~ ~ ~ ~ ~ it; ~ ~ ~ ~ :~ i; ~ ~ ~ ~ :: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ I; i; :~ ~ ~ ~ ~~ ~ ~~ :~ ~ ~~ ~: ~~ ~ ~: ~ I; :: ~ ~: :~ ~ ~~ ~ ~~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~~' :~ :~ ~ ~ ~ ~ ~ ~ ~ i. ~ ~ ~ :; ~ ~~ ~ ~ ~ ~~ ~ ~ ~~' ~: ~ :~:; ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~ ~ ~ r is~ot~ t Bell Slew ~lMtl~CO~ ( ~ ~ ~!~:~EMa~C fort ~e~l~r:~oo~ ~~:~ :: I: i: :: :~ ~ ~~ :; ~~ :::: ~ ~ :~ ~ ~ ::; ~ : : :~::~ ~ :~ ~~ :~:~:~ ~ ~ ~~ i: ~ :~ ::~ :: :~ :~ ~~ ~ :: :::: :~ ~ ~ :~: :~: ~ ~:~r~ :~s;~:~W 1~ 1:~:~qVm~ ~ Y~n~tzec A 1~at~:~lUe~;:u:tWetnen:ts~ ~~:~ ~.~ ~~.~ ~~ ~ ~~ :~: ~~ ~: :~ ~~ ~: ~~ ~~ ~~ ~~ ~ ~ ~~ ~~ ~ ~~ ~~ ~~: ~~ :~ ~~ :~ ~ ~~: ~ ~ ~~ ~~ ~~: ~~ ~ ~: ~~ ~~ ~~ ~: ~ ~ ~~;~ ~~: Ad, density, ;~ develooed~ the ~~Mt:~s~now-sa~mal~i~nn~ tub.: ~~ ~~core~:~samDl~es~ ~~ex~leclfom tlie~:~sno:~co~ ~the~:snow~~Natbr~u~~v~a~e~nt should By ~~ ~ A, ~~.~:, ~~ ~~ age, ~~ ~~ ~,~ ~ I; ,~ ~~ ~ ~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~: ~ ~ ~ ~ ~ ~~ ~~ ~ ~ ~ ~ ~ ~~enrane~to I ewe It~ ea u~ivale nets The Snow D e:oos iL: ~ ~~:~ ~:~:~ ~~:~ ~~: ~~:~:~ ~ Yes - se~toAhe~im~tant~e - ~~ - uratt~f~ts ~~snowmel~t~:~:~ ~~ -: ~11( t~:~ ?il~s~el~Qs~ Ditto Bean l:srf~a~seT ~oT~snow~:~:~ ~ ~~ u~ly,~:he~vvas~involv~with~the~:~ i: ~ ~ ~~ ~~ ~ :~ :~ ~ I: :~ ~ ~ ::~:::~ I:: ~~::~ ~ ~~ ~~ ~ :~ :~ ~::~ :: ~ :~ ~~ :: ~ ~: ::::~:~::~::~:~:~::~::~::: ~ ~~:~ :~; i: ~ ::::: :~ ~ :: i:: I: i: ~~ : ~: :~ :~ :~ i: ~ on: others ~stat~exportir g ~hts::~;~:approath~ ~~:c~s~ art he ~:wo:~.~lhe ~e~e~a~He~r~ge~came~in~94~7~en ~~ ~ ~~ ~ :~ :: ~~: ~~ :~ ~: ~ ~~ ~~: ~~ i; ~~ :: ~ ~~: ~ :~ ~ :~ ~ ~ ~ ~: ~ ~ ~ ~ ~: ~ ~~ ~ ~: ~ ~ ~: ~ ~ ~~: ~ ~~ ~ ~ ~ ~~:~ :~: i:~;: ~~ ~ ~ ~ ~ ~~:~ ~ i: ~~ ~: A: ~ ~~ A:: I: ~~ ~: ~' I:: Hi: ~ ~ ~~ Hi: ~ ~ ~~ ~ ::~;: ~ :~ · ~~ :~ ~~ :~ ~-~ ~ :~ :: ~ ~~ ~ ~~ ~ ~ ~ ~: ~ ~ I'm ~ i: ~ ~ ~ ': ~ ~ ~ i~ ~ ~ ~ ~ ~ :. ~ I: ~ ~ ~ ~ ~~:w~ty~l~:a:: m~ly~n~l~s ~~m:e; tnon: s:~me~rta~s~: nigne:st~moun:ta'~ns,~:~ Whose~simw field sfeed 0 t the ~~grea~t~rwer~s.::~:~ :~ ~~ ~~ ~~ I: ~~ ~~ ~ ~::~ :: ~~ ~~ ~~ ~ ; ~ ~~ ~~ ~ ~ ; ~~:~ ~~ ~~ ~ ~ ~~ :~ ~~ ~~ ~~:~:~ ~ ~~ : I:: F~ ~ ~~ ~ ~~ i: ~~ :~ ~ ~ :~: ~ ~ I: ~~ i: ~ of: :~ i: :~ ~ :~ I: ~ i: i: I: I: ~ I:: :~ ~ :: ~: I: at: i: :; ~wa~:m em ~tec~ician . ~~Al~he~route~from ~~pr~fessor~ of: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ it, ~ ~ ~~ ~ ~ ~~ ~~ ~~ ~ ~~ ~~ ~ ~ ~ ~ ~ ~ ~~ ~ ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~~ ~ ~ ;~ ~~ ~? ~ ~ i~ ~~ ~~ ~~ F~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ; ~ ~ ~ ~ ~ ~ ~ ~ ~ i~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~class;~:~i~s~w~ierdi~ - way ~~:well::respe~b6~e~d~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ I: ~ ~ ~ : ~ ~ ~ ~ ~ ? ~ :~ ~~;~ ;, ~~ ~~,~ ~~.~ ~~: ;~ ~~,~ ~~ ~~ ~~.~.~ ~~: ~~,~ ~~: ~:~mt~e~l~f~teinationa ~~Jsksl~on:~ot:~w:~:~an;~l~ce~wnem~:~ne~: ~ :: ::::: : ~ : i: :: I: : : I:: ~~ some~ence~ oVer~the~ra~Pi^~e~i~ld~¢t~c~y. ~~W:h1:le h~rs~methOds ~ may ~~s~m:~i:mitive~i~th~is:~y ~:~remo~:sensirlg~ and Easy i If; ~ ~~ ~~ ~ ~ ~~ i; ~ ~ ~ ~? ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~~ ~~ ~ ~ ~~ ~ ~ ;~ ~~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ ~ ~~ c'om ma` or: ic~ions~:Mt Rose ~ samp ers~ar~ ~:th~ei~r;~mar~y~: deri~va:ti:ves~: are~:sti~l l ~ ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~~ ~ :~ ~ ~ ~ i~ ~ ~ ~ ~ ~ ~ ~ :? ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~:~e~ the I~m~to~ls~of~:snow~and~::i~c;ol lection;~today.~:~ , : ~ :: I: :: ::: :: :~ if:: I: ~ :~: :: : :::: : I: - Snow Accumulation and Ablation Snow accumulates as a seasonal cover before it melts to produce water for runoff and ground water recharge. Data on snow cover are collected by a variety of organizations in different countries for different purposes with little exchange of information. In the past, measurements were made at selected points, but remote sensing may allow large- scale measurements if the technological problems of interpreting mi- crowave signals can be solved. This would allow data collection in remote and difficult environments such as mountainous or arctic re- glmes.

236 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Few stations around the world collect the data needed to analyze the energy balance of a melting snow cover, and many of those that do are experimental and short term. Critical information about prop- erties like albedo is rarely available, and information necessary to drive streamflow-forecasting models is not available except locally. Recent interest in atmospheric deposition and the chemistry of snow cover has stimulated collection of data in some regions, but no consistent data sets are available on regional or global scales. Surface Runoff Surface runoff is measured throughout the world. However, the spatial and temporal distributions of these data are erratic and strongly related to the local level of development. In many developing coun- tries, surface-runoff measurements are spotty in both space and time, whereas most developed countries have reasonably dense data networks that have existed for several decades. In the United States there are more than 10,000 locations at which daily records of surface runoff have been computed and archived for a decade or longer. In addition to the spatial and temporal diversity of surface-runoff data, the accuracy of the data is also variable. Generally, the accuracy of surface-runoff data is better for mid-range flow rates than it is for either high flows (floods) or low flows. Data accuracy also generally deteriorates in extreme environments, such as arid alluvial streams or ice-affected streams in alpine, subarctic, or arctic areas. Soil Moisture The temporary subsurface storage of water in the vadose zone usually coincides with the rooting zone of plants. From the soil, the moisture will either be returned to the atmosphere, temporarily stored in vegetation, or percolated to the saturated zone. Information about soil moisture and its spatial distribution would be of great value in delineating the dynamic nature of hydrologic processes, but except in experimental basins, soil moisture is never measured routinely, and data on its spatial variation are extremely scarce. Soil moisture is hard to measure. Gravimetric measurements in the field are time-consuming, and soil moisture varies markedly over scales of a few meters. Progress in the development of better methods for measuring soil moisture in the top meter of the soil, in areas of both woody and grassland vegetation, is desperately needed. Remote sensing in the microwave wavelengths offers some hope, but the effects of soil, vegetative, and topographic properties need to be worked out.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS Subsurface Water Below the Vadose Zone 237 The basic variable measured in ground water surveys is the water level in observation wells. From these data it is possible to estimate ground water fluxes if information on aquifer properties is available. Various levels of sophistication of analysis are possible, ranging from a simple application of Darcy's law, through flow nets, to use of computer simulation models. It is not possible to estimate fluxes or storage volumes without complementary geological data on properties of the medium. With a sparse data base, there can be considerable uncertainty in these estimates. Rates of ground water recharge or discharge are rarely monitored, although discharge measurements from ground water springs are sometimes made. Most countries maintain regional networks of monitoring wells in principal aquifers used for water supplies. Summaries of well yields and total withdrawals are also available. Although some hydrographic records extend back over 100 years, most data postdate the mid- 1940s. Data density decreases markedly for deeper aquifers. In regions of sparse population or in areas without significant potential for ground water supplies, background data are scarce. On a continental scale, no inventory exists to define the extent and quality of the total volume of subsurface water in storage. Similarly, while fluxes through the ground water reservoir have been characterized for some major aquifer systems (Figure 4.5), no detailed assessment of fluxes is available on a continental scale. Evap~otranspiration In spite of its importance in the hydrologic cycle, there are no routine measurements of evapotranspiration. Although the neces- sary technology has been developed and is available, the instruments still require special expertise to operate and would be costly to deploy in a network of stations for long-term global operation. There is some hope that the anticipated developments in electronics and remote sensing from satellites will bring progress in this area. While a solid data base is lacking, useful information on evapotranspiration can be derived from published maps depicting its approximate long-term average distribution, together with other components of the water balance in different parts of the world. At a larger landscape scale, evapotranspiration estimates based on remotely sensed data in the thermal-infrared region of the electromagnetic spectrum may be possible. There is a need to examine the relationship between thermal-infrared radiation emitted from a plant canopy and

238 FIGURE 4.5 High Plains aquifer. Contours show the water table el- evation for Me aquifer, win ground water flow from the west toward the east. SOURCE: Reprinted, by permission, from Skinner and Porter (1989), Figure 10.9. Copyright (I) 1989 by John Wiley & Sons, Inc. OPPORTUNITIES IN THE HYDROLOGIC SCIENCES r- . 1 . _. _ ~ SOUTH DAKOTA . . . I o o =,~,, ~ i At .. . i .. _ .q i ~ roll IDA - ~ - ~ L_r--~~~ ~ ° KANSAS \i OKLAHOMA _. i x.N \.` ,-—-N. , ~ .\ j~_ Hi. .` .S-' l _._} TEXAS ` \ j - -' .. ~ its temperature structure. If remotely sensed temperatures of forest canopies were combined with existing atmospheric models, then evapotranspiration might be predicted for broad units of the landscape. Methods could be validated for accuracy and temporal resolution through comparisons with site-specific watershed studies where hy- drologic balances are precisely documented. Much of the work in the large-scale, coordinated field experiments such as HAPEX, FIFE, and GEWEX addresses this question of the measurement of evapo- transpiration over the spatial scales of large drainage basins. Fluxes of Energy In spite of the fundamental influence that the processes of surface energy exchange have on the hydrology and climate of the earth, data required to estimate the energy fluxes from the land surface are usually available only for areas where intensive field experiments are under way.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 239 Knowledge of the spatial distribution of energy exchange at the land surface is important if we are to estimate many of the fluxes of interest in the hydrologic cycle. Evaporative fluxes of water in particular are driven by fluxes of energy, which are sometimes easier to mea- sure. Therefore we need information on the exchange of solar and thermal-infrared radiation, latent and sensible heat, and heat flux into or out from the soil or snow. A major influence on the atmospheric circulation and the distribution of precipitation is the distribution of surface heat flux into the atmosphere, whose estimation requires knowledge of the spatial distribution of surface temperature. Radiation One or more components of the radiation balance at the earth's surface are measured at some stations; however, systematic measurements on a global scale are lacking. Satellite measurements can give us rough estimates of solar radiation, however. Although incoming so- lar radiation is a function of the optical properties of the atmosphere, the amount and type of cloudiness, and atmospheric profiles of tem- perature, humidity, and such major radiatively active gases as ozone and carbon dioxide, by far the most important variable is cloud cover. Current programs to map global cloud cover from satellites should fill an important gap in our current knowledge of the earth's radiation balance. Sensible and Latent Heat Exchange Sensible energy flux is not measured in any routine or systematic way, except in special experiments. The information is not much better for latent heat exchange. Except for some data collected in a few experimental settings and at a few lake evaporation stations, there are no reliable routine measurements available of either evaporative flux or the associated energy fluxes. In some countries, including the United States, efforts have been made to measure potential evapo- transpiration by pans or other evaporimeters. Unfortunately, the re- lationship of these measurements to actual evapotranspiration is dif- ficult to assess, because the devices are small, creating local anomalies of energy and humidity conditions, and because they do not incorporate the biophysics of plant behavior. A field tool under development for remote three-dimensional measurements of water vapor fluxes between the surface and atmosphere is a system based on solar-blind Raman light detection and ranging (LIDAR). The technique involves repetitive firing of a short pulse of

240 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES a high-intensity ultraviolet laser into the atmosphere and detection of the returning fluorescence as a function of time, with interpretation of backscatter intensity to determine water vapor concentrations. Recent developments in laser technology, hardware, and software suggest that the LIDAR system could provide a sensitive (5 percent), rapid measurement of water vapor concentration profiles with a spatial resolution of less than 5 m along the laser axis. Successful development of the LIDAR system would provide a quantum advance in estimat- ing relative evapotranspiration in mixed vegetation, complex topog- raphy, and incomplete vegetative cover. It would also bridge the gap between point measurements of evapotranspiration and broad- scale estimates derived from satellite sensors. Surface and Subsurface Data Topography is known to adequate accuracy over most of Europe, Canada, and the United States, but topographic data are not easily available for most of the rest of the world. Land cover is not routinely monitored at scales appropri- ate for hydrologic investigations. Subsurface information on the hydrologic properties of geologic media is generally only available where aquifers have been intensively developecl for water supplies. Topography Examination of hydrologic processes also requires other information about the surface and subsurface of the earth. Among these, perhaps the most important is topography. Elevation and related parameters (slope, aspect, drainage area) exert an important control on surface and subsurface hydrology and ecosystems. Topography influences intercepted radiation, precipitation and runoff movement of sediment, evaporation, soil moisture, and vegetation characteristics.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 241 At a given latitude, the topographic parameters determine the ex- posure of a landscape to weather and sunlight and thus determine its microclimate. Local topography exerts a critical influence on microclimate through its control of the radiation balance, both solar and emitted atmospheric radiation. These in turn affect evapotranspiration, snow ablation, and the movement of soil moisture. Calculation of accurate energy fluxes in mountainous areas requires accurate information on topography, because the high local relief produces a complex array of microclimates and a complex distribution of vegetation. Quantitative modeling of water, nutrient, and sediment transport and of nutrient cycling has been an important activity in hydrologic research. Human activities have affected the cycle of some biologi- cally active substances, especially in aquatic ecosystems. Topogra- phy strongly influences surface and subsurface fluxes of water, but to analyze these accurately requires derivative quantities based on elevation data (local gradient, upslope area). Digital topographic data enable automatic calculation of watershed structure and runoff, but error propagation associated with parameters, based on the first or second derivative of elevation, dictates that original elevation data must be of high quality. Many of the existing topographic data are inadequate, even in the developed parts of the world. Regional and global hydrologic studies require the manipulation of large data sets and therefore require topographic data to be accessed digitally. At present the availability of this type of data is limited. High-resolution digital topography (about 100-m horizontal resolution, showing about the same level of detail as a topographic map at a scale of 1:250,000 or better) exists only for the United States, Australia, and Western Europe. The best global coverage has only 18-km horizontal resolution. In the investigation of global hydrologic problems, an important area of uncertainty is the mass balance of the great ice sheets in Antarctica and Greenland. Elevation changes experienced by ice sheets can be a response to climatic forcing or may be caused by internal instabilities in the ice flow, such as surges. Currently we do not know whether the polar ice sheets are stable, growing, or shrinking. Investigation of such problems depends on topographic data, not the . . . . ,.. . , , ~ _ , clata Wlth tine spatial resolution needed tor accurate calculation ot slopes over individual drainage basins, but more widely spaced elevation measurements accurate to within a few centimeters. Where available, topographic information is usually in the form of topographic maps, consisting of hand- or machine-drawn contours around unevenly distributed spot height measurements. For many parts of the world, coverage is limited, inaccurate, or nonexistent. Mountain belts, deserts, tropical rain forests, and polar areas, all critical

242 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES environments for research on the earth's water balance, lack adequate topographic coverage. Even where topographic maps exist, they may have been generated in a way that limits their usefulness. For example, the distribution of horizontal and vertical control points across a map is usually uneven, and this results in variable accuracy. Land Cover Outside North America and Europe, most data on land cover are compiled from regional or national atlases, and the accuracy of such data is usually not known because human activity changes the surface cover. Extrapolation of measurements and development of models of hydrologic fluxes from field experiments conducted over typical surface covers to the broader region, requires that information on land cover be frequently updated. The influences of vegetation on evapotranspiration into the atmo- sphere and on fluxes of carbon dioxide toward the surface are of special concern. Simulations of atmospheric processes and measure- ments of isotopic concentrations in rainfall show that precipitation over continental areas, and the temperature contrast between continents and oceans, together with associated monsoon circulations, are sensitive to the availability of moisture at the land surface. Under healthy, dense vegetation cover, soil moisture in the root zone is used freely by plants to maintain temperature control by evaporation, in association with leaf respiration and photosynthesis. If soil moisture is depleted, these fluxes are reduced. Today the best example of the need for this kind of information is in the Amazon basin, where some areas are undergoing a rapid transition from forests to clearings. Satellite measurements of forest clearing can be incorporated into large-scale hydrologic models. Subsurface Information Characterization of a ground water reservoir requires data on the extent, thickness, and structure of the geological units at and below the ground surface; on the hydraulic properties of each of the geological units; on the depth to the water table; on the chemical character of dissolved solutes within each unit; and on the areal distribution of ground water recharge. During the last decade, many countries have supported programs to document the hydrology of their principal aquifer systems. This task involves an integration of the geological, hydrologic, and geochemical data as a flow system analysis. A good example of this effort is the Regional Aquifer System Analysis (RASA)

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 243 program of the U.S. Geological Survey. The motivation for much of this work is to provide information that can be used to better manage ground water resources. Such work also provides data useful in identifying aquifers from which society will benefit by using its re- sources to protect and perhaps restore the quality of water that has been contaminated. SOME OPPORTUNITIES TO IMPROVE HYDROLOGIC DATA Coordinated Experiments Hydrologic models and field measurements in a coordi- nated program are neecled to obtain a detailed understanding of the energy and water cycle at scales beyond that of the field plot. Large-scale field experiments, combining satellite and extensive in situ measurements, are a means to verify large-scale hydrologic models and validate spatially ex- tensive observations. The essence of physical science is experimentation. To describe a physical phenomenon requires that it be considered at a given scale- the scale that is available (depending on the data) or a scale that is chosen (depending on the objectives of the study). It is now generally accepted that further progress in the development of the needed parameterizations of land surface fluxes of energy and water in climate dynamics and in hydrology must be based on a new, chosen scale, with comprehensive experiments conducted and field data collected at larger scales than those customary in the past. This recognition has led to cooperation at various national and international levels, resulting in several large-scale field experiments, which are either in progress or in the planning stages, to study the dynamic interactions of the land surface and atmosphere. These multidisciplinary experi- ments can often achieve more than the sum of their separate disciplinary goals if observations are coordinated to achieve a common objective. We refer to such efforts as coordinated experiments.

244 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES The design and execution of coordinated experiments constitute a landmark in hydrology. Several experiments are now being actively planned in the United States and internationally. Studies should be conducted in the future at different locations and under different climatic conditions, to validate existing concepts or to develop new ones that suit changed circumstances. Scientific Development and Achievements Awareness of the importance of experimentation has always ex- isted, but it is only recently that it has become possible to consider experiments at scales that were unthinkable only a decade ago. New opportunities have arisen as a result of developments in low-cost electronic instrumentation, computer technology for handling large data sets, and remote sensing from satellites and aircraft for observations with appropriate spatial scales. One stream of activity has developed from the realization that simulations of the earth's climate using general circulation models (GCMs) are sensitive to evaporation from land surfaces. Thus the idea ripened that pilot experiments are needed at a scale of about 100 km to provide good sets of data together with independent determi- nations of energy and water vapor fluxes near the surface, so that realistic boundary conditions can be put into GCMs. As a result, in the summer of 1986 coordinated observations, known as the Hydrologic- Atmospheric Pilot Experiments Modelisation du Bilan Hydrique (HAPEX-MOBILHY), took place in southwestern France. The experiment was conducted between Toulouse and Bordeaux over an area that measures 100 x 100 km2 and is about 40 percent forestland (the Landes Forest) and about 60 percent open agricultural terrain (Figure 4.6~. Coordinated observations of variables and fluxes in physical state were made by satellite and from aircraft, sounding balloons, and ground stations. (See "Coordinated Field Experiments," Chapter 7, for more detail.) A second line of experimental activity arose within the International Satellite Land Surface Climatology Program (ISLSCP). ISLSCP was organized in response to the need to monitor variables that govern climate and its fluctuations at different regional and global scales. Satellites are eminently suited for this purpose. A first objective of ISLSCP is to develop and use relationships between current satellite measurements and hydrologic and other climatic and biophysical variables at the earth's land surface. A second objective is to validate these measurements and relationships with ground data and also to validate surface parameterization methods for simulation models that describe

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 245 d/ ~ · ~ ~-~ 1° ~ lM CAPTIEUX ~ . BORDEAUX ·) it; ~%%~- ·~ ~ 1. O / o 1°) . ~ _ : , , I ~ ~ · 0~ I' · O. . ~ RENEES UGLY ~: A— ~ - . . . it, [\ NERAC . ~- I . TOULOUSE AUCH . FIGURE 4.6 Location of HAPEX experiment in southwestern France. SOURCE: Re- printed, by permission, from Andre et al. (1986). Copyright @) 1986 by the American Meteorological Society. surface processes ranging from those at the scale of leaves of vegeta- tion up to those at scales appropriate to satellite remote sensing, i.e., 100 to 1,000 m. The First ISLSCP Field Experiment (FIFE) marked the initial phase of an experimental effort envisioned to accomplish these goals. FIFE took place during the summer and autumn of 1987 and 1988 near

246 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 247 Manhattan, Kansas, over an area of about 15 x 15 km2, which included the Konza Prairie Long-Term Ecological Reserve. The experimental area consists of rolling hills with about 50 m of relief between ridges and stream valleys, typically separated by distances of about 1 km. The FIFE study area is roughly representative of a much larger area, since it is surrounded by similar grasslands, which are mainly used for grazing. This area of tall grass prairie covers a strip 50 to 80 km wide that runs from Kansas to Nebraska to Oklahoma. The objectives of ISLSCP and FIFE imposed the need for simultaneous data acquisition and multiscale observation and modeling. As illustrated in Figure 4.7, this was done by acquisition of satellite data, together with si- Satellite 10m-8km Airborne Flux 15km Airborne Radiometry 10m-15km Flux She 10m-1km Canopy, Leaf Physiology 1 cm-1 Om . / I \\ in, FIGURE 4.7 Range of scales addressed in First ISLSCP Field Experiment (FIFE). SOURCE: Courtesy of P. J. Sellers, University of Maryland.

248 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES I~;~;~:~:~:~T~H~E:~ATI~O~NA ~ O M Pi ~~ ~~:~ ~~ ~~ ~~:~-~I~n~e:~c~u~i:r~n~t~state~of~und~ - often teorol~ ~ ~~ If- ~~ ~ ~~ ~: ~~ ~~ ~~ ~ ~ ~~ ~ ~~ ~ ~ ~~ ~~ . ~~: ~ ~~ ~ ~~ ~ :~: ~ ~ ~rece~nt~yea~s~h That a ~~r:~e-:~:~five-d;a~y ~~ou~troo~ki~tor~a~su~n~ny~w~eel~n~d~:~:~ wet:~:p~;:s~ - legato ~~be::~:~And~yet,~ ~ - rtiterm: :~ pm~$lK~n~p~r~i~o:~n~a~n~liswere~ - atlNe~r~:~::~eve~n~ts~::~:~al~Q:ugli~:~:~m~o~re~:~:~:~: Scan sty l~i: ~~:~to~t~:~:b~l:~i~:~a~n:d ~ ersatz ~ar~:~l~ - eq~:;~t~h~is~:e~n~l~:ng~Q~cca~s~:l~o~n~a;~l~t~y~ ~be~d:~e~l~e~s~t~h~at~:~ca~n~:~a~n~d:~:~ :~:d:~o ~:~c~a~s~e~t~g~fl~a~fiQod~s~.~ ~~l~s~s~::~d~ram~ati;:dJ~li~ - c~:~ra~:ns~: May:; ~~nlY~:~i~h~:~, ~ ~~ ~~i~e~p~s~h~t~h~ey~ IS Carried o:~:t~o~u~l~oo~r~a£f~i~v~i~i~=c~ ~~r~:~ ~ ;~:~ ~ :~:~;~:~v:y~i~ rives Nan ~~::~ex~pl a~:l~n~:~th~l~s~ state: ~ ~f~:~a~ if pa id ~ In As: so ~~ id Olin flu n d 4 ;~5y~eratiorial~and~ ReQearch~logy~ ( ~~P~w~;~l;~l~be~a~n~:~;i~m~porta~nt~::~ - t~:th~e~1~9~9~0s.~:~We~h~a~v~e ~~:~im~p~rovre~d~:~ ~ ~~ ~~ ~ ~~ ~.~.~ ~ ~~: ~.~ ~ :~ ~ ~ ~~ ~ :~ ~~ ~~ ~~ ~~ ~~ ~~ ~~ ~ ~~ ~ ~ :~ l ~ ~ ~ b ~ e c a u s e ~ ~ ~ o ~ i ~ r ~ : ~ ~ ~ ~ ~ n ~ ~ ~ ~ ~ ~ ~ s t a n ~ i n ~ g : o b s e r v a e ~ n a ~ I :a~;~:ies,~pg~t - vial ~~:~apa~l~tie~s~are:~e~q - ~~to~t~h~e~k~:~Th~ ~: ~ ~ ~ ~ , ~ i. ~ ~ ~ ~ :~ ~~ ~ ~~ ~: ~ ~ ~ i~ t~.~,: ~~ :~: ~ ~ :: ~ ~~ ~ i, ~ i, ~ ~ ~ - .~.~=~.~ma~co~ntro~:~t~e:~w~eath~e~r~on~:~me~sca~es~ida:ys~:~ I~ ~ ~~ ~ ~ . ~ ~ ~ ... ~ ~ ~~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~ ,~a~v~e~:~sp~at~a~sc~a~ e~s~:~t~ 1o~u~san~c Of c: :o:m~eters~t~ ian~d~l(l the~m:ost~pa~t~i~ '.e 1~a~v~l~o~r~:ls~:we~ ~ ~ '~n~a:~l~e~c ~:~;~ c~u~F~:nt~ :~n~u~me~rica~ ~:~ ~o~d~e~l~s~a~ d~:~comp~ut~er~s~.~:::~ : ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~ ~: ~ ~ ~: ~ ~ ~: ~ ~ ~ ~: ~ ~ ~: ~ :~ ~ ~ ~ ~ ~ ~ :~ ~ ~::~:~:: b~IJ:~t~w~e~:~n~ow~; c~n:ow~th:a~t~:~v~i~:rtu~a I~l~y:~:~ a:~l l~ ~p rec~i~p ir~tati~:o n~:~ :~a~n d~ ~se~ve~re~ :~ : :we~:h~r~:~:~:~:~: ~ ~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~: ~ :~ events~:~:~n~Vo~lve~mesos~cale~p~roce~s~ses ~l~ite~ra~ ~:i n~rmedli^~ i n~s~c:a~e~ ~:~be-~ ~ ~ ~ ~ ~ ~ ~ . :~ ~ ~ . .~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~arge-sca :e~ - ~ ~cyclor,~e$~:~a~nd~ane~w~ages ~a~n~d~s:h:o~r;~-:~ :: :~ ~I:vec ~p ,~e~no~m~e~n~a~s~uc ,:~a~s~t~u~r 3~U ~e~nt:~ec d~i~-es::~ogr~i~n~d~i~v~u~al~c~l~o~u~ds~ :~:~:~wh~i~c~;h:~:~: ~ ~ ~:~:~ ~ ~ ~ ~ ~::~: ~ ~ ~ ~ ~ ~ ~ ~ ~ :~ ~:~: ~ ~ :: ,:: ~ ~-~ ~ ~ ~ ~: ~ ~:~a~re~oTteTn~tte~n~s:~to~::~n~u~nd~red~s~of~ki~om~el:~rs ~:i~::n~:~:~e~xtent~a~nd:~ I~:~fro~m~:h~ou~rs~:~:~ ~:~a ~;~o~r~tw~o~.~: ~O~u~r~£~u ~rre~n~;i se rva~;n~n etwo~rk~i ~ s ~to~d~e~sc~ r~ ~ ~su~c h~ ~e~ve~n~ts: :~u~s~t~;~a ~w~ha~l~e~n~t:~i~to~.~c~aw~h~mo~st~fi~ih~e~ m~esh~:~ '~s~too:~la~r:~e.~:~ . ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~: ~ ~ ~ ~ ~ ~:~ ~B~ut:~a~:re~m~ovI~n~g~:ra~pi~d~l~y:~wa~rcl~u~;n:d~e~;rsta~n~i~nig~su~h~s~yste~m:sl~:~a:n~d~n~ew~ ,. ~ ~ ~ ~o~oserva~tio~a~:a:~ ~:apani~:l:~ltie~s:~a:n~d~m~ore:~:~pow rtu~l :~c~o~p~ute:~s:~:~w:i::~:~g~re~at~ly~ i~m~-: ~ ~ ~ . ~ . ~ ~ ~ :~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~ ~p~v~e~;~p~rea~:l~ell~o:n~, ~l~n~:~:h)~rn~:~g~:a~tl~:y~:;:m~iti:~g~ti~ng~th~:e~: hu~m~an~ ~:~a~n~d~ ~ e:con:~om:~c ~ ~ :~ .~ ~: ~ ~ ~ ~ f ~ , ~ ~ ~ ~ ~ ~ ~: ~ ,~ ~ ~ ~ ~ ~ ~ ~ ~ ~.~ ~ ~. ~ ~. ~ ~ ~ ~ ~ ~ ~mp~ac~l;~:~or~ ~t~ne~se~even~ts~ ~:~n~:~c~o~n~v~l~ct~l~Qn~t:~at~:~m~eso~scaWl~e~:~:we~ath~e:r ~even~ts:: :~::a~re~bot~h~l~co~m:~r~: ~ ~ensibl¢:~and~p~r~i~c~table~i~s~th~e:~ ~c~e:ntra~l~ ~:p~re~m ise:~:~of~the~:~:~:~ :~::Natio~n~al~STOR~M ~Prog~ram~ ~:~: :~l~ji:ye~a~program~of~both~op~era~tio~n~s~a~nd ~ :~ ::::: :: r~:~:h: ~:::: : ::::~:: :::::~::~:~:: :::: : :~:~ : :~:::: : :~:: : ~ : :: :: ~:::: :: ::: :: :: :: : :: :: : :~:::: : :: ~:: :: :~ : I =~=al :~:l:l~:,: ::: ~ : ~ ~:: : : ~ ::: :: :~ : ~ :: ~:: : ~: : :: :: ~ : ~ : ::~:: : ~: ::: :: ~ : : :: ~ :~ ::: ~ :: : ~: ~ ~ : ~ ~ : ~ ~ :: :: ~ ~ ~ : : ~ :::~:~: ~ ~ ~ :~ ~ ~ I n:e~£o~al~s~:~ot~;sT~RM~are t£~: {~1~:~: a~1~v~n~£~" ~f1~::l:nW:-:~. l ~ - ~, ~ ~- ~ ~ ~.~- ~.~ ~-~ ~' :~a~l~u~l:: '~ doy'l~l~l~ce~:t:~nd~am~e~nt~a~l~:~u n~de:rsta~n~di~ng~ ~:of:: : ::: ~ · . :::::, · : t :: :~:: ~ ::: ~ : :::::~: :~:: : ::::::: : ::::~:: : :~: ::::: :: · ::::- : :: :~: :.:: :,: ~. ~ . :~:: :: ~ ~ ~p~rec~:p~i~a:~l~o~n~a~n~ o~t~n~er: ~mesos~cale ~p~roce:s:s~es:~ a~n~d~ ~ t~he i~r:: r ol~e ~ n: the ~ ~h~yd ro- ~ ~ ,: *: ~ ~ ~ ~ :. , ~ ~ . ~ ~ ~ ~: ~: ~og~c ~cyc~e,~ ~a~n~o :~)~ ~m~p:rove ~tn~e:~O-~:~:to~ 4~8~-~h:ou~r~:p:r~ed~ic~tion~:~3~:~ ~r"<i~;~;~ - :~:~a~nu~:~s~e~v:ere:~weal:~he~r.~:~: ~ ~ ~ ~:~:~:~ ~ ~ _ ._ ..~. ~~,~~,=..v~. vr: prec::i:pl:~ar~on ~:~ ~: ~:~To~:~a~c~h~i~e~ve:~th~e~s~goa~l~sr~STOR~M~ bu~i:~lds~:on~:~h~o~ex:t~raord~:i~na~ry;~n~a:tion:al~ ~ : ::: : : :: : : : : : : :: ::: ~:: ::: ::~:::~ :~: : : : ::: ::: : : :~ ~ ~: : :: : : : :: : : ~ : :: ~ ::: ~: : :::::~: :: : :: ::::: :: : ~ ~:: ~ ::~: ~ :: :: ~: : : : : ~ : : :: : : :::~ : : :: : : :~:~ ~;nvestmentTs::~;~n~weather~a;~:~:li~:m~a~tTe~l~in~s~trume~n~ta~t:i~on~ :a~nd~a~ssoci~ated~ in-::~:~: ::~: ~ ~ ~ ~ ~ ~ ~ ~ ~,: ~ . ~ :~: ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~to~rma~tlon ~ch~n~ogy,~ e~a~c~h~sc~h~ed~u~led~: ~r~ deF4~oyment~:~:: and~op~e~ra~t:~io~n~ ~:::~ ~ ~ ~ 1 ~ ~ ~ .: I:~: :: :~::::~ ~::~ ~ . ~ ~ ~ .: ~ ~ ~ .: ~. ~ ~ . ~ ~ ~ ~ . ~ , ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~:~:~::~a~u~rin~:g~:~:~ln~e~: ~ ~Y~us~:~ ~;~t~ne:~:~:~:~m~o~ce~r>~n~zeo~: n~aLt~o~na~l~:~wea~th:e~r~:~:o:bserv~Ing~:~:~sv~ste~n1:~: ~ ~ , ~ .s ~ ~ ~ ~t ~ ~ ~ · ~ ~ - ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ; a ~ n ~ ~ u ~ ~ ~ ~ ~ ~ ~ ~ n e ~ ~ ~ ~ ~ ~ ~ a ~ ~ : : n ~ ~ ~ ~ ~ ~ ~ ~ ~ : s e r v ~ ~ ~ ~ ~ n : : ~ ~ : ~ 3 : y s t e ~ m ~ . ~ ~ ~ ~ : : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : : ~ ~ ~ : ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ : : ~ ~ ~ ~ ~ ~ ~ ~ ; : ~ ~ ~ ~ ~ . ~ ~ ~ ~ ~ ~:: :: ::: ~:: ~:: ~:

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 249 ~~;rharader`:ratlon~ by ~~r~emote~sens~i~n~gt~d~u~ri~n~th~e~ne~xt~d~ec~an~e~.~ multaneous observations from aircraft and at numerous ground sta- tions, and by atmospheric soundings of different types. As international efforts both HAPEX-MOBILHY and FIFE posed severe and formidable problems of logistics and coordination. One of their major accomplishments has been attaining and sharpening experimental technology and expertise for use in planning later experiments. Frontiers and Challenges It is important for future experiments that address the interaction between surface hydrology and the atmosphere to increase the area (

250 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES examined to the regional scale. Possibilities under discussion for the 1990s include a combined experiment with the National Stormscale Operational and Research Meteorology (STORM) Program and an ISLSCP experiment that includes interactions between hYdrolo~v and . , . . . . . , , , , ~ v ~ terrestrial ecology, probably In tne boreal forests ot tne united States and Canada. The STORM program will be primarily a meteorological effort dealing with mesoscale-storm-generating mechanisms, but it should have profound ramifications for hydrology as well. These future ISLSCP experiments are envisioned to involve scales of 200 to 300 km, the grid size of GCMs, and would be best conducted along a gradient of different forest species. Because it will be impossible to measure all relevant variables over such large areas, several experiments of the spatial scale of FIFE will be nested within the larger area. It will be necessary to design experiments to tie together some of the findings of experiments at the level of HAPEX, ISLSCP, and STORM to the continental or even global scale. The Global Energy and Water Cycle Experiment (GEWEX), proposed to begin later, around 1997, should achieve this objective. Remote Sensing Over the next decade, advances in remote sensing the gathering of data by instruments on satellites, aircraft, or the surface to infer properties of the subsurface, surface, and the atmosphere offer the possibility of obtaining frequent hydrologic measurements over wide spatial scales. To achieve the potential benefits of remote sensing, the data must be converted from the raw electromagnetic measurements made by satellites, by aircraft, or at the surface to hydrologic information that is made available to a wide spectrum of hydrologic scientists. The hydrologic sciences, much like the rest of modern earth sci- ence, are starting to examine interactions among the different terres- trial components at all temporal and spatial scales. Such an inclusive perspective requires an integrated data collection program, and remote sensing is an essential component. Instruments currently available

DATA COLLECTION, DISTRIBUTION, ANl) ANALYSIS 251 on satellites, aircraft, or on the surface, along with those planned for the future, will make available measurements obtained throughout the electromagnetic spectrum over a range of spatial and temporal scales. The temporal variations of many hydrologic processes require global coverage every few days, and so satellite instruments with broad swath widths and modest spatial and spectral resolutions are neces- sary. In addition, some hydrologic problems require analysis and interpretation of specific areas and detailed sampling within scenes produced by instruments with lower spatial or spectral resolution. For these applications, data from satellite or aircraft instruments with appropriate higher spatial and, usually, higher spectral resolution are needed. Some processes that are important at the global scale are manifested in surface features with dimensions of tens of meters. Examples include anthropogenic damage to vegetation, which first appears in patches; forest clearing, which dramatically affects evaporation and carbon cycling, and which in the tropics occurs in small, noncontiguous areas; land use change and desertification, where boundaries may move only short distances; alpine snow and ice, where spatial coverage may be small but where large volumes of water are stored; changes in permafrost and buried ice lenses caused by atmo- spheric warming; and changes in the extent of freshwater and saltwater marshes caused by changes in the water table height or sea level. Remote Sensing of Hydrologic Parameters Some important hydrologic variables can be measured by remote sensing. In the visible and near-infrared wavelengths, the source of energy is the sun, and we can measure the solar radiation that is reflected by the surface or scattered by the atmosphere. In the infrared wavelengths, we measure radiation that is emitted by the earth and its atmosphere. In the microwave part of the spectrum, we measure either emitted radiation (passive microwave) or the backscattered response to a signal sent from a satellite or aircraft (active microwave). The visible and near-infrared wavelengths can be used to measure the presence or absence of vegetation; the structure of vegetation, including biomass and leaf density; the stress in vegetation, including moisture content of leaves; soil type; and snow cover and its rate of depletion. For hydrology, the microwave region offers particular advantages, because the signal is integrated over some depth below the land surface, whereas reflectance of solar radiation and emission of thermal infra- red radiation are determined by the characteristics of a much thinner surface layer.

252 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES ~~ ~~;~:~I:QWS:~BAlik~N:: ~~ :~ ~ ~:~f1~q9~_1~q~:~::~ ~~ ~~ ~~ ~~:~ Also ~me~of~u~s:~:~struggl<~ tbroug~h~li~ to find ~::the~right::~ career path,: ~~whiJe~ mbers~take~:a~:~random~step~t~t~s~ets~a~:route~:early. ~~rs~J.~ :~ ~~Ba~tta~ew~;~:~ - :~i~i~:~so~n:~Austria:n~ i mm inrn~nic ~ ~;~rh~i~u=:r1~ Hi cat :: : : : ::~:: :~: ~ : :: :~ :::: :: :: : ::: : :: : :: : i: ~:~r~own~:as~:~ a n~eteoro~iog~ist~bec:ause:~:~an :~Army ~~r~ruiti~r~g:~ ~poster. ~~;~A~I-~ ~ ~~:~ Two - ~~as~a~:~n~h:anica~l~en~g~n~eeri~r~ major dab Passed: At few - r c:~City~fire~departmerit~entrance~ exam~i:n~c~a~se ~~:~:ever~:~ne~l:ed:~ ~:~ :: ::::: :::::: 1 ::: ::: ::: ::: ::~:: ::::::: ::: ::~:: ::: : :: :: :: ::~ : :: ~ :: : ::: ::: :: ::: : :: ::::: : :::: :: :: :: ::: :: :: : i:: ~ : : : :: : Arab <u~p~c~areeC:~it~was~:a~:World~War~l~l:~recr~i~t~n~g~poste~r~:~:thatled~;~:~h~i~m~:~:~ :: ~~in:to:~the~: A:rrny~ - Corps:~av~i:atfon~c~adel~program~:~i~n ~:m~eteoroi~ogy~ ~:~ttan::~was~sei~t~ fort: ~N~e~w:~Yo~rk~::~i~iY~e~rsitv~ to~tra~i~n~in~m`~t~nrnin~v~ ~~:::~ ~ ~~ ~ ~ -I- :::: ~ :~ ~::~ : ::: :: : :~:: :: ~ ~:~ ~:~ ~r~I~n:~ :I n~ne~:~:~u~I~s~ ~:£~I^~ Whet was se~Iected~by~ theist ~Army~as~0ne~ pried ~1~00~weather~ officers ~~ ~~ trained ~ also in radar ~ am; :~~a~rd~Un iversi~ty~3nd~ th6~Ma~ssach~usetts~ ~ lnst~itu~te of ~~ Technology. ~~ LATH is ~wardim~e:~ddties—inuring ~~ground-ba~s~ storm detection ~ and airborne ~weather:~mco~nna~f~ss~an~£~e—set a ~stroag~f~un~tion~ ~ his later~l~if6's~wor~k ~ ~ :~ ~ ~ ~ ~ :~ : ~ ::: ~ : ~ ~ ~ ~ r ~~ ~~ abbe - lid often~c:~redited ~~Ms~ubJ~t~n~ng;~:~givin~g: ham ~ Cant Waybill it'll to! see ~~ poorer ems~with~a~n~n~novat~ive eye. ~~ ~~ ~ ~ ~ ~~ ~ ~ ~ ~ :~ ~ ~ :: ~~ :~ ~ ~ ~ ~~: ~~ ~ ~ ~ ~;~ Attest ye Dwarf ~~ttar~earried~a~ meteorol~ogy~degree ~~frdm~w~Wrk~ Wive~rsit~ He Thea joined iffl~e~U.~ VYeather~ sure.Ar'~ n~nfi~w~:c~c~n=~t^ l n~unaerstorm~ Ret :~at ~~ the~u~n~iv~ers~ity~ ~~ itch ingots ~~;~ where ~~h6~l~ate .~earaed~both~ hi`~rnaster's~ and~ doctoral~degrees.~ The Thunderstorm Project Was the ~~ prot - Germany ~large-scale~ he do experi~mer~s~lollowi~ng~ the War. it inV61~v do the~coordinated~use~ of radar an Extensive Gourd net- ~ ~ ~ I,— ~ ~ ~ ~ ~~ ~ ~ ~~: ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ ~ Nor <~o~meteo~ro~ ogica~l~staitio~n~s'~and~tto~-pe~n~etrating~61 ~B~Iack Widows ~aircraft,~and~ project brow giar~t~leap~lr'~ou~r~u~r'~rstabding of Storm ~::~behav~lor.~:~Baffan~at:hieVed~the~:fi~rstd:efinitive~iderltific:atio~:~ofthe:~coaldscence~:~ : :: ~ ::::: : i:: :~:::~ :: :: :::::: :: ::::::: ::: ~~ ::::: :~:::: :::~:: :: :: ~ r e ~ i p i t a t i o n ~ g r o w t h ~ ~ ~ i ~ r ~ ~ w a r m ~ ~ ~ ~ c 0 n ~ v e c t i v e ~ ~ ~ c 0 ~ f d s . ~ ~ ~ ; ~ ~ A ~ s o ~ ~ d u r i r l g ~ ~ t h i s ~tirtle,~wo~rked w~h~Mhers fonts they amp - l~nudeation~c-um~u~s clouds. ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ T~ ~~ ~ ~ ~~ A mainly theme in h~is~research~s ~ ~~:lar~bac~kscatter~from~h~i~l.~;~H~e~aiso ~ ~~ ~ ~ I. ~ ~ ~ ~ ~ ~~was~a~p~l~onee~r~ ~~ ink ~e~deveiop~m~e4nt Of Dower raw. ~~ Th~rou~horI~t~ :: he; careers ne~s~active ~an~r~g~h~is~Y~a riots interests weather~rn:odifica-~ . ~n,~Doppl~rad~r, ~ arid the~sca~ring p~ropprties~of hydrometers. ~~ aft; :~ ~ A student of l~ar~uageWhe~ s,~e~ll~:ia~r)~,~Spaa:ish:~Fre:nch~;~ G~erm:an~ And: Russian—Balkan ~ washy choice ail ~life- ong~:un~i~versity ~profes;so~r~and~ writer. ; bail East boreal Some 6~ 300ks~ring;~i~his Career ~~ And I literally ~ hundreds of :: ~~ ~ ~ ~: ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~: :? ~~ ~~ ~ ~ ~ ~ pape~rs~a~n~c Arty es. ~ A t ·ou~offe~red~many~h~igh~ positions in government a And ~acad~ia,~he~preferr~ ~ hisses ~sc~1~31a~rly~ ~1 ifestyle.~ the served online :rnany nat~onal~ar~d~te~rn~ational~g~ophysical committees—including the National ~~ ~ Academy~i~of sciences' ~~ Committee on ~~A~ospheric~ Audiences Which ~~ he ~~ ~ ~ ~ ~ ~~ ~ ~ ~ ~ ~ ~ , ~ ~~ ~; C Aired Nod - ~s~a:~0eg~ ~~ the World ~Meteor: - gical~;iO~ani~zabon. - Was Act ~uentia ~ Lain ~~lbundin~g~N~ationil Cent for i~Atmosph~e~lc~Re- ~~;searc:~ 1 ~~ ~~ attari, A way sat ~~hedrt:-~a~scholar,~ Got often indoor ~ the right: for Scientists into God Grown b~tes~w~ithout ~~u~nd~direction ~~ from :~above,~ ~~ believi~pg~that~the~bb~t~scie~e j~is~done~i~n~ ani~unfettered: ~supoortive~atmos~here. : ~ :::: ::: :: ' :: :~ : ~ I: :::::: : ::: ~ : ~ I:: :~ :: ~ ~ ::

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 253 ~~:~:a~sL rye. :: ~ At: :::: I: i: :~ :~::~:: ~ ~ i: ~ ~ ~ ~~ : i: ::: ::: in: i::: ~~ ::~ ~:~ :: i::::::: :::: ~ ::::::

254 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Because clouds do not obscure the microwave signal over much of the wavelength range, remote sensing from aircraft or satellites is possible even when cloud cover is present. Moreover, in the micro- wave frequencies the water molecule is resonant, and the electromagnetic properties of wet substances are much different from those of dry ones. Emitted (passive) or reflected (active) microwave radiation is especially suitable for measurement of rain rate, from ground-based radar; estimation of soil moisture; measurement of hydrogeologic properties, from ground-penetrating radar; and mapping of snow cover. Many categories of hydrologic variables can be measured by remote sensing, because hydrologic processes modify the electromagnetic signal in some portion of the spectrum. However, different hydrologic conditions may cause similar signals, and so continued work is required to achieve unambiguous measurements. We need progress in two categories of problems: · We need to understand better the relationship between proper- ties of the surface and its electromagnetic signature; and · The model between the electromagnetic signature and the physical properties may be complicated, and the inversion of such a model, so that surface properties can be estimated, is often difficult. Future Advances New satellite systems will open uncommon opportunities for hy- drologic research in the coming decade. In the near term, before 1992, these systems include (1) the DMSP Special Sensor Microwave Imager with 12.5- to 25-km resolution, the first launched in June 1987 and later launches scheduled to continue into the 1990s, and (2) the ESA ERS-1 with synthetic aperture radar (SAR) and altimeter, to be launched in 1990. Additionally, NOAA polar-orbiting satellites of the 1990s will have additional channels for the advanced very-high- resolution radiometer (AVHRR) in the near-infrared wavelengths and an advanced microwave sounder. In the longer term, the Earth Observing System (EOS) scheduled for launch in 1998, with its full complement of instruments and the ambitious plans for research across the earth sciences, will allow rapid access to data over global and large regional scales for the purpose of tracking the changing hydrologic cycle. In addition, the Tropical Rainfall Measuring Mission (TRMM) will improve the knowledge of rainfall over important tropical areas of the earth where data are scarce. One important focus of these future missions is the creation of hydrologic data products. A current impediment to the use of remote

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 255 sensing in hydrology is the investment of time necessary to under- stand the characteristics of sensors and the relationship between elec- tromagnetic and hydrologic properties of the surface, along with the cost of data and difficulty of access. Scientists with little previous experience in using remote sensing data are often discouraged by the amount of technical expertise and the sophistication of the computer equipment required to process the data. In the future, hydrologic scientists who understand these kinds of problems must create data products of established quality and reliability, so that other scientists can use these in their models. The hydrologic community should start now to be prepared to use these data products, which will cover large areas of the earth at a frequency of one to a few days, and smaller areas in more detail at intermittent sampling frequencies. Opportunities for Effective Use of Current and Planned Sensors The prospects are promising for remote sensing in hydrology. The sensors designed for future spacecraft missions have excellent char- acteristics for measurement of hydrologic properties. However, data availability and distribution are causes for concern, as are defining and processing suitable data products. Use of remote sensing in hydrology, as in other disciplines, has been hampered because the data are difficult to acquire and analyze, and some data are too expensive. The best scientific results with remote sensing data are usually achieved by analysis of multitemporal as well as multispectral data; therefore data need to be priced so that investigators can analyze many images during a single season and thereby observe both spatial and temporal changes. Two improvements in the current state of hydrologic education and research are required to achieve the potential benefits of remote sensing data. 1. Universities must recognize that students in the diverse array of disciplines that analyze the earth's hydrologic processes will need to be trained in remote sensing, as well as in the conventional sup- porting subjects of physics, chemistry, mathematics, and computer science. Departments that offer courses and degrees in hydrologic science will need to incorporate remote sensing training into their curricula. 2. The hydrologic community will need to agree on the design and distribution of hydrologic information products. The future of hydrologic remote sensing will be enhanced by the wide range of hydrologic information that these data can produce. The instruments that are planned will contribute to science, because

256 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES they can be used to measure many useful surface properties for hy- drologic research, but the contribution will be greater if the data become more widely available in useful products, and if the popula- tion of hydrologists familiar with remote sensing increases. Specific recommendations are the following: 1. The continued availability of data from current sensors is nec- essary for hydrology. Landsat, for example, provides a time series dating back to 1972, and the continued viability of this system in the future must be assured. 2. The continuity between current and future sensors must be ensured, so that the time series created are long enough to interpret hydrologic change. 3. Future sensors appropriate for hydrology need to be designed, constructed, and launched. Each of the facility instruments for the polar platform of NASA's EOS contributes to hydrologic research. 4. Remote sensing data must be distributed soon after acquisition, and data must be available at regular intervals so that both spatial and temporal distributions of hydrologic phenomena can be investigated. 5. Hydrologic data products must be defined and processed from raw remote sensing data, so that the information will be available to a wider variety of scientists instead of being restricted to those with expertise in remote sensing. The definition of the most appropriate hydrologic products and the procedure for selecting the best algorithms will need to be addressed in a systematic way, perhaps by workshops that would bring together an appropriate mix of hydrologists and experts in remote sensing. 6. Hydrologic interpretations from remote sensing must be checked against surface observations. Remote Sensing Below the Surface Research frontiers in remote sensing of subsurface conditions promise important breakthroughs in our capability to map hydrogeologic properties without the need for a dense network of boreholes. Of particular note are techniques based on ground-penetrating radar and tomographic reconstruction. Ground-penetrating radar can provide high-resolution maps of the subsurface stratigraphic profile to depths of tens of meters. Work is under way to determine how a radar profile can be interpreted to characterize the subsurface structure of hydraulic conductivity, the key physical property determining patterns and rates of fluid flux. Using ground-penetrating radar, it may also be possible to delineate plumes of contaminated ground water.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 257 Borehole tomography is similar in concept to the familiar CAT- scan equipment used in medical applications to obtain "pictures" of body organs without surgery. For applications in hydrogeology, multiple cross-hole signals are generated by the movement of a source along one borehole, while receivers record signal arrival at multiple depths in adjacent boreholes. Various source signals are being developed, including seismic, electromagnetic, and hydraulic. The cross-hole signals are processed to reconstruct a picture of hydrostratigraphic properties throughout the region between the source and receiver boreholes. Basic research is needed to better understand the relationship between the recorded signal and the hydrogeologic properties of the subsurface. If the potential of these two methods is realized, they will herald a new era in detailed mapping of subsurface properties relevant to hydrologic processes. Isotope Geochemistry Environmental isotopes can be usec] as tracers to study residence times, mixing ratios, and flow velocities in the hycirologic cycle. Environmental isotopes are a key tool in studying the subsurface component of the hydrologic cycle. Their primary uses include: · identification and differentiation of water masses that have unique mixtures of different isotopes of hydrogen or oxygen in the water molecules; · determination of the extent of mixing of two or more waters; · estimation of residence time in hydrologic systems; and · estimation of flow direction, travel time, and flow velocity. ~ , con The environmental isotopes in most common use today include the stable isotopes deuterium (2H), oxygen-18 (~80), and carbon-13 (TIC), and the radioisotopes tritium (3H), carbon-14 (TIC), and radon (222~. Because the stable isotopes oxygen-18 and deuterium are part of the water molecule and are not significantly affected by chemical interaction with the rock or soil, they provide nearly ideal conservative tracers of water masses. Owing to differences of mass between hydrogen and deuterium, and between oxygen-16 and oxygen-18, one isotope is enriched (fractionated) compared to the other as water changes phase from liquid to vapor to liquid to ice and back. Isotopic frac-

258 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES tionation is a function of temperature, and well-documented effects cause enrichment or depletion of one isotope compared to the other, allowing quantitative evaluation of processes occurring within the hydrologic cycle. For example, winter precipitation is depleted in i8O and 2H compared to summer precipitation. Distinct differences occur in the stable isotopic composition of precipitation with changes in latitude and altitude, and so changes in the trajectory of storm tracks cause changes in the isotopic composition of precipitation. Meteoric water that has experienced evaporative processes is enriched in 2H compared to i8O in comparison to normal seasonal variations observed in precipitation. On a smaller scale, rain that falls in the beginning of a storm is often enriched in i8O and 2H compared to that falling at the end of a storm. Isotope hydrologists can take advantage of these differences in applications such as the following: · determination of the extent of leakage between aquifers; · identification of recharge areas; · determination of recharge rates or water age by counting annual cycles in 2H and i8O moisture in the unsaturated zone; · application of isotope mass balances to determine the extent of interaction between rivers and aquifers; and · investigation of paleoclimatic conditions. Incorporating isotopic data with new advances in geochemical and hydrologic modeling promises considerable potential for gaining new insights into subsurface hydrologic processes and their link to pro- cesses occurring on the land surface. During the period from 1957 to 1963 massive amounts of tritium were introduced into the upper atmosphere from the testing of ther- monuclear weapons. In 1963 and 1964 the tritium content of precipitation reached as much as a thousand times natural background levels and established a unique tracer in ground water systems. Recharge rates have been determined by locating the depth to the 1963 tritium spike. The simple presence of detectable tritium is an indication that a sample contains post-1957 recharge water. Tritium decays with a half-life of 12.3 Years, and dating of shallow around water is possible if the , ~ ~ tritium input to the hydrologic system can be defined (Figure 4.8~. Many other environmental isotopes and transient atmospheric tracers are being studied to investigate their possible applications as dating tools and tags of water masses in hydrologic systems. For dating techniques, research is directed toward the use of chlorine-36, silicon- 32, argon-79, krypton-85, krypton-81, helium-3, helium4, and fluorocarbon compounds. Heavy isotope ratios such as strontium-87/strontium- 86 and uranium-234/uranium-238 can be applied as tracers of water

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 1 ,000 500 100 50 10 5 1 259 OTTAWA PRECIP. 1950 1960 1970 1980 1986 YEAR FIGURE 4.8 Tritium concentrations in precipitation measured at Ottawa, Ontario. SOURCE: Reprinted, by permission, from Robertson and Cherry (1989). Copyright (3 1989 by the American Geophysical Union. masses. Stable isotope ratios of sulfur and nitrogen often show source material and currently are applied to studies of anthropogenic inputs of sulfur and nitrogen into shallow ground water and surface water, such as from acid-rain deposition, agricultural runoff, fossil fuel combustion, and sewage sources. The observed distribution of the decay series of naturally occurring uranium-238 and thorium-232 can be used to derive sorption rates and retardation factors for use in site-specific models of the transport of radioactive or stable elemental waste in saturated geological media. These and other chemical and isotopic tracers hold great potential for opening fruitful avenues of research. Paleahydrology and Long-Term Records Paleohydrologic information can extend the time series of hydrologic data beyond the period of record and thereby give us a better picture of hydrologic trencis and the sta- tistical distribution of phenomena.

260 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES To understand hydrologic processes one must know how the pro- cesses vary through time, from the minutes of a cloudburst and hours of a flash flood through to the variations in precipitation over decades, centuries, millennia, and even longer. Neither means nor variations are necessarily constant over time. Within decades and centuries there can be extreme events, abnormal periods, and even climatic shifts. Detection and quantification of extreme events and climatic shifts are crucial for hydrologic evaluation. Traditional monitoring is useful in many applications, but new methodologies or increased efforts made with established procedures are necessary to produce information about long-term effects of climatic variation on hydrology. A current opportunity to improve hydrologic data is the development of new long-term records of climatic-hydrologic variation. These are useful for process modeling and making predictive or probabilistic estimates that may be beyond the range of recorded events. Impor- tant knowledge can be gained through paleohydrology intensive study of historical documentation and generation of new data using proxy climatic-hydrologic information. Paleohydrology can produce long-term information on means, ex- tremes, trends, and variations of various hydrologic phenomena and probabilities of extreme events. For example, tree-ring analysis has led to reconstruction of records of precipitation, streamflow, drought, temperature, and lake levels. However, there are currently few of these reconstructions. Thus the feasibility has been established, but the extensive application awaits. There is a potential for reconstructing flood records, inundation times, sedimentation rates, ground water recharge, and other important phenomena relating to hydrologic hazards and water resources management. In addition, this type of analysis can identify and date single major events that may have occurred outside the realm of human records. Proxy records may be episodic, such as the identification of a major flood event in fluvial sedimentary deposits, where there may be organic debris for carbon-14 dating. Proxy records can be sequential, such as tree-ring or ice-core data, from which a continuous time series of variation can be recovered. Continuous, accurately dated time series can be used just like measured records to calculate means, variations, extremes, and shifts over time. Another application of these time series is the study of periodicities. Some scientists believe there is a response in climate variation to the 18.6-year lunar-nodal periodicity. One needs almost 60 years of good data to have at least three complete cycles for examining and testing the 18.6-year hypothesis. In most areas of the world such information is unavailable. The proxies that record and represent hydrologic variations are

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 261 biological and geological entities that persist over time and show responses to environmental change. Tree-ring analysis and palynol- ogy are two primary biological methods of deriving paleoclimatic- paleohydrologic records. Tree-ring analysis provides absolutely dated, year-by-year records for the past several centuries and in a few cases for several thousand years. Palynology, the analysis of pollen and spores, provides a longer record but does not give either the resolution or the precise dating of tree-ring analysis. Geological recorders are varves, fluvial deposits and other sedimentary records, geomorphic changes, lake fluctuations, paleosols, ice cores, and geochemical sequences. The dating of most geological recorders is approximate, being based on radiometric, stratigraphic, or other techniques, but the information provided by the geological recorders may cover time spans of thousands to millions of years. Figure 4.9 presents the various paleohydrologic indicators and the time spans and resolutions derivable from them. There are limitations to paleohydrologic indicators. Ice-core sam- pling sites may be the most limited in distribution, and pollen may be the most ubiquitous, although pollen must be deposited coherently by some continuous sedimentary process for best results. Tree-ring sampling opportunities are widely distributed over land masses except for deserts and polar regions, but are particularly plentiful in tropical areas. The geomorphic-geologic sources of information, such as flu- vial flood deposits, are sporadic in distribution, as are paleosols, varved sediments, and paleolimnological opportunities. In areas where proxy paleohydrologic indicators are absent, geochemical indicators, including isotopic analyses, can potentially determine sources, ages, and histo- ries of ground water. Long-term records can be developed also by the study of ancient documents that have only recently been appreciated for their scientific value. Improvements in travel and communication are increasing the awareness of documentation relevant to climatic or hydrologic variation. From records of shipping transit times and sea-ice conditions to descriptions of famine and even reports of tax yields, one can glean information about effects of climate. These types of analyses require that linguists and historians be involved in the study of hydrology. Caution is called for when utilizing such reconstructions, because the analogs on which proxies are based are often incomplete in criti- cal secondary responses. Consistency checks should be made of the reconstructed data such as by using them in models that test the water balance, the timing of extremes, and so forth. Humans now may be on the threshold of causing climatic change, with attendant disturbances to the hydrologic cycle. Some of these modeled and projected shifts have analogs in the past. Precise knowledge

262 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES TEMPORAL RESOLUTION ANNUAL BANDS ~ RADIOMETRIC 0-2 % ERROR ORBITAL TUNING - 5-10 % ERROR 2-3000 YEAR ERROR SOURCES OF ~ PALEOCLIMATIC ~ ~ ~ HISTORICAL DATA / _ — CORALS ICE CORE VARVES . GLACIER MOVEMENT ~ ~<ECOTONE MOVEMENT OCEAN SEDIMENTS ~ VARVES , ~ ~ ~ 1 1o6 105 104 1,000 100 10 1 TEMPORAL COVERAGE (log years ago) FIGURE 4.9 Paleohydrologic indicators and their time spans and resolutions. SOURCE: Modified from Bernabo (1978) courtesy of the U.S. Department of Commerce. Of the analogous conditions aids in planning for future eventualities. The measured records do not extend back to these conditions, but through examination of the different types of climatically sensitive organisms or cyclical phenomena that have left measurable responses to climate, we can identify major past events and develop time series that are proxies for measured climate variations. Global patterns of warmer or colder and wetter or drier regions can be ascertained through

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 263 study of biological and sedimentological indicators. Global circula- tion models, which can be run forward in time to produce estimates of future variations, can also be set back in time to enable comparisons with proxy data. Such exercises should validate the model mechanisms and concepts and also estimate potential changes in the global hydrologic cycle. The extent of the normally recorded information is too limited in time and space for such validation. As a contributing discipline, paleohydrology should be considered still in its early stage. Reconstructions have been published for streamflow of specific rivers in the southwestern and eastern United States and in Argentina based on tree-ring analysis. This technique has also produced multicentury drought histories for certain regions along with calculations of return times for severe drought, at scales of ma- jor drainage basins. However, there are many key hydrologic uncertainties and data gaps throughout the world where tree-ring analysis and

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DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 265 other proxy studies could be applied. Sometimes they provide infor- mation where there are no instrumental records even today, for ex- ample, in coral reefs and ice cores. To execute the application requires interdisciplinary science. There must be expertise in the particular proxy area e.g., palynology, dendrochronology, sedimentology and expertise in hydrology itself to develop sensible and significant results. Although it has been used successfully in many areas of the world, there are now more opportunities than accomplishments in paleo- hydrology. Data Accessibility and Management Advances in the hydrologic sciences depend on how well investigators can integrate reliable, ~arge-scale, ~ong-term data sets. Storms, floods, and droughts are natural events that can be mea- sured just once, whereas laboratory experiments can be repeated. Instruments used in hydrology must be reliable and operated such that data captured are of known standards and precision. On rivers, measured stage data must be transformed to discharge. The stage-discharge relationships, commonly called rating curves, typically must be extrapolated to extreme stage values and may require adjustment as new "agings at the extremes become available. This adjustment may apply retrospectively for rating curves that have been used for many years, and so a data archive should store original stage mea- surements and rating curves separately, to allow this retrospective examination and adjustment. The data sets required to answer many of the open research ques- tions in hydrology will be complex. Inevitably, many scientists from a variety of disciplines and backgrounds will be involved in data collection and analysis, over a significant period of time. How can diverse investigators and investigations produce compatible data sets, assure their quality, and confidently assemble them for larger, indeed public, use and access? Creating effective data systems for assembling and distributing scientific data sets is not trivial and depends heavily on the personal efforts of active scientists. If the data systems are constructed within the scientific community by scientists themselves, rather than by independent data "experts," there will be many scientific opportunities as well as technical and political challenges.

266 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Data Management in the First ISLSCP Field Experiment The First ISLSCP Field Experiment has wrestled with these issues. FIFE was not designed exclusively as a hydrologic experiment, but it included collecting a comprehensive set of hydrologic and related data sets for a 15 x 15 km2 experimental site in central Kansas. The studies of some 30 cooperating principal investigators were actively supported by a data system built by participating staff scientists at NASA's Goddard Space Flight Center. The immediate goals of the data system were to capture and preserve the data and distribute them as rapidly as possible. After the conclusion of the field sampling, the system was converted into an open, widely available archive. The technical elements of data distribution were easily supported: magnetic media via mail for large volumes and an on-line access via electronic networks for browsing and routine data extraction. Equally important, however, was a user support staff. Technical and scientifically competent people were required to simplify access, prepare adequate documentation, and teach novice users about both the system and the data. Assessing data quality can be difficult enough for a single investi- gator working with his own data. The problem is compounded when the data are required quickly by cooperating investigators and distributed through a data system to people who may be unfamiliar with the technical details (or difficulty) of the measurement. The FIFE solution was to use the data system as the focus for a cooperative assessment of data quality. Data Storage and Access Optical disks and compact disks have become an attractive alternative to traditional magnetic tape or disk storage media, because they offer the capacity and security necessary for hydrologic archives, and because multiple copies of large archives can be made cheaply. For example, the entire daily stream gaging record of all gaging stations for one year is stored on optical disks for such countries as the United States and New Zealand. The need to publish expensive yearbooks of data disappears. Issues to Resolve The evolving requirements characteristic of active research demand a data system with real-time adaptability. This can be achieved by a scientifically involved data system team that puts a priority on service.

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 267 This is no small effort: it requires direction on a day-to-day basis by active scientists. In particular, for large projects, the role of a project information scientist must be recognized as critical and must be re- warded appropriately. In addition to personnel issues, there are several political aspects. Three legal categories of data can be defined: data that are acquired

268 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES from public sources with no distribution restrictions, data that are collected by publicly funded principal investigators, and data that are acquired with public funds from private sources, corporations, or individuals with specific legal rights to restrict their distribution. The FIFE approach was to recognize a data collection and analysis phase in which data sets were exchanged and revised and their quality controlled, but during which general access was restricted. The experience suggests that the more direct control scientists have over the data system, the better it will serve science. In particular, direct control makes possible rapid adaptive responses to the unexpected opportu- nities that can develop in any experiment. A control data base can be a tool and focal point for cooperatively assembling and checking the data sets. Advances in computer technology make it possible to link such a data base electronically to field sites and investigator laboratories, where a common set of hardware and software tools can be inexpensively supported. These would allow each scientist to create his or her portion of the data base, in near real time. Challenges in Measuring Water Quality Public concern with pollution of water resources, as well as its effects on human health and the environment, is widespread and occasionally intense. Investigations of water quality must be designed accorcl- ing to sound scientific principles. In response to public concern, many studies are being conducted to monitor and assess the amount and distribution of pollutants entering the hydrologic cycle. If these studies are to be useful to understand the causes of observed conditions, and thus provide a foundation for cost-effective amelioration of water quality problems, they must address scientific principles as well as practical ones. Water Quality Monitoring and Assessment Data for water quality monitoring and assessment may be divided into three types:

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 269 · data collected to characterize ambient concentrations in lakes, rivers, and ground water; · data collected to monitor effluents; and · data collected to monitor water quality for a specific use. The remaining discussion focuses on ambient water quality data. However, managers of data collection programs for all three types of data need to become more aware of ways that data from individual programs can be made more useful for addressing issues that are beyond the immediate program objectives. These include: · the need to collect important ancillary data, to place the water quality data in the context of the natural and cultural setting; · the need to carefully document sample collection and labora- tory analysis procedures; and · the need to archive the raw data in easy-to-access computer files. Scientific Issues and Challenges Past experience shows that water quality data collected for utilitarian purposes are either difficult or impossible to use for scientific purposes. It is seldom appreciated that science-oriented designs not only contribute to advancing science but also significantly improve the process of attaining many practical goals. Water quality is threatened by thousands of potentially harmful substances. Developing effective evaluations of water quality for so many chemicals is an imposing challenge, requiring continued devel- opment of screening techniques and broad-spectrum analytical pro- cedures. We also need better ways to link contaminant selection to the physical-chemical properties of different substances, to the behavior of different substances in surface and ground water, sediments, and plant and animal tissues, to chemical usage estimates, and to the relative health and ecological risks associated with different pollutants. A related issue has been the failure of traditional monitoring pro- grams to identify emerging water-quality problems, possibly because of the lack of a significant link between these programs and scientific inquiry. For example, most water quality sampling in the United States has been targeted exclusively at substances for which regulations already exist, leading to a focus of effort on selected constituents— priority pollutants that occur infrequently, and often to a disregard for more important contaminants. Future data collection programs need to provide explicit flexibility to enable adjusting to changing environmental concerns and incorporating

270 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES exploratory aspects into the design. Frequent interpretation of data also is required to identify emerging issues; the data should not be simply collected and archived for future analysis. The integration of biological measurements with physical and chemical measurements also can significantly strengthen the utility of a data collection pro- gram to help identify emerging problems. For example, biological properties may be more sensitive to water quality than are chemical or physical measurements. Too often chemical and biological mea- surements are considered competitive rather than complementary as- pects of water quality characterization. The design of water quality monitoring and assessment programs usually does not reflect consideration of the issue of scales. Yet the scale of focus will constrain the issues that can be addressed, for example, in providing information on non-point-source contamina- tion. Simple use of highly intensive area sampling will not produce significant results within the limits set by realistic funding and the human resources available. Instead, innovative designs must be developed that fully use the existing understanding of the physical, chemical, and biological processes that determine water quality. A major deficiency in environmental data collection programs has been the inadequate development of information useful for defining long-term trends in water quality. Part of the problem is simply that data collection programs are too easily abandoned when funding problems occur or in the excitement of responding to newer, more glamorous social or scientific issues. A greater commitment to continuity is needed. Moreover, a key challenge is to carefully balance long-term consistency with inevitable changes in hydrologic knowledge, the technology available for field and laboratory measurements, and the types of contaminants extant. To the extent possible, long-term pro- grams should rely on repetition of measurement, but they must also document carefully the criteria for site selection, the characteristics of sampled sites, and the methods of data collection and analysis. When changes in measurement techniques occur, the old and new techniques should be applied in tandem as long as is necessary to determine the relationships between them. Interrelationships among components of the hydrologic cycle must also be considered. Understanding of the connections among the atmosphere, surface water, and ground water needs to be incorporated into the design of environmental monitoring programs for these dif- ferent media. For example, atmospheric cycling can be critical to the transport of major and trace constituents of terrestrial waters. So in some circumstances, a basic understanding of atmospheric processes

DATA COLLECTION, DISTRIBUTION, AND ANALYSIS 271 and appropriate atmospheric monitoring may lead to more effective collection of data describing water quality. Use of Biological Methods in Water Quality Analysis Biological information can complement chemical analysis to improve the measurement of water quality. Physical and chemical properties of water may vary rapidly, and intermittent or infrequent "grab" samples may give misleading indi- cations of prevailing water quality. The native biota may be better indicators of water quality and human effects because of their prolonged exposure, integrated response, and differing sensitivity to all the varying conditions of their environment. Indeed, organisms provide the only direct measure from which ecologically significant impacts can be deduced. All levels of biological organization molecular, cellular, tissue, organ, individual, population, and community have been used or proposed for use in water quality interpretation. The methods may or may not identify a particular cause of change, but a measurable biological response may help to identify physical or chemical tests that should be used in the search for a cause or causes. The first biological methods used in connection with water quality assessment were based on the observed presence or absence of species. Characteristic native species were used to demarcate zones of decreasing concentration downstream from a point of heavy organic loading. Particular species were thought to show the pollution condition in each zone. However, the supposed indicator species also occurred in unpolluted environments, and the zonation varied with the type and intensity of pollution and other hydrologic properties. Further work on human effects resulted in methods based on analysis of assemblages of species. The relative dominance of tolerant and intolerant species or of functional feeding groups in a biotic community is sensitive to water quality. These methods are successful when enough ecological knowledge exists about the species used, as is the case for most fish (although fish may be impractical to sample). They are less success- ful when the ecological requirements of the species are poorly known, as is usually true for algae and benthic invertebrates. In the absence of detailed information for the species of interest, effective ecological methods are available based on resemblance between biotic commu-

272 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES nities in hydrologically similar streams, with and without human impacts. The selection of suitable reference streams is crucial to the success of this approach. The occurrence of one type of effect, sewage contamination, has traditionally been determined using as tracers microorganisms indigenous to the gut of humans and other warm-blooded animals. Bacterial density in laboratory cultures inoculated with water samples is inter- preted to show the degree of fecal contamination and the potential occurrence of associated human pathogens. Escherichia cold is replac- ing fecal coliform and fecal streptococcus in these tests as a more specific indicator of human effects. The sensitivity of organisms to target contaminants or the concen- tration of contaminants in living tissue can be used to detect the spatial distribution or biological availability of contaminants. The method samples native species or introduced, caged species. It is limited by differences in sensitivity or in uptake of contaminants among species, by lack of suitable widely distributed sentinel species in continental waters, and by effects of enclosure on caged organ- isms. Laboratory bioassays using sensitive organisms are performed to determine biological effects of specific environmental characteristics. Responses, usually from short-term tests, are measured as bioaccumulation or as changes in behavior or physiology. Although test conditions are standardized, thus far the results cannot be extrapolated to other test conditions or species. In particular, bioassay results do not directly provide adequate information about an effect on the long-term structure and functioning of ecosystems. Limitations of single-species bioassays have led to the use of laboratory or field-emplaced microcosms to determine the effects or the fate of contaminants. The sizes of such microcosms range from less than a liter to many cubic meters. Microcosms contain important components and exhibit important processes of natural ecosystems. They simplify environmental variability while exhibiting multispecies phenomena under controlled and replicable conditions. The results obtained from experimental microcosms are empirical analogues of whole-ecosystem functioning but require great care in broad extrapolation to the field. Methods based on levels of organization below the individual level are applied in the field or laboratory to detect, quantify, or determine possible human effects. Techniques based on enzymes, antibodies, tissue cultures, and gene probes are being used or actively developed. The degree of sensitivity and specificity possible with these methods suggests that their use in water quality analysis will increase. Clearly, biological data can supplement physical and chemical data

D~ COLE DlS~lBU~^ ~~D APSIS 2~ to provide more holistic understanding of Me Coning and of the natural evolutionary bends of hydrologic system as emu as human effects on such systems To accomplish this in detain major advances are needed for determining the hydrologic implications of ecological results Also needed are improvements aimed at increasing the sen- si~iV, subdue ~ ~~ of biological methods Ed at decrease costs and analytical bme. To date, only for indicator bacteria have procedures been adequately st~dard~ed Ed ~ result made accessible in water quality data banks. Other biological data relevant to water quality assessment are scattered and are based on diverse methods of sampling and analyst. Standardized methods Would enhance the sciendRc value of biological ~krmabon by providing a refile baseline fir making Choral Ed spatial co~adso=. Proved cocoon of ecological results and their significance is also needed' in forms useful to other scientists and to the public. Biology can furnish uncommon insights for hydrologic science, in- ~ghts not achievable solely Tom a Edge of physics and chewy. For example, organisms are involved in the transport and cycling of elements in water and sediments. Organisms are targets of scientific Earl to preserve rare Ed Educed species. Pop~abo~ of orgasms are ~tendonaDy added by management programs and u~nhonaDy affected by natural and anthropogenic environmental effects These and other issues often require studies on large spatial and temporal scales. Saw sages Cold be ~o~ora~d Ho national Ed ~temabonal mater quality monitoring systems to provide the means to evaluate Ed Prove Completely developed but potendaNy valuable biological methods for understanding the organization and functioning of hy- drologic systems. SOURCES AND SUGGESTED READING Andre, ~ Cal ~ P. Goutorbe, and A. Perrier. 1986. HAPEX-~OBILHY: A hydrologic atmospheric experiment for me study of water budget and evaporation flux at the climatic scale. BulL Am. ~eteorol Sac. 67:138-144. Baumgarmer, A., and E. ReicheL 1975. The World Water Balance. Elsevier, Amsterdam, 179 pp. Bernabo, C. 1978. Proxy Data: Natured Records of Past Climates. NOAA Environmental Data Service ReporL U.S. Department of Commerce, Washington, D.C. Earth System Sciences Committee, NASA Advisory Council. 1988. Earn System ScF ence: A Closer View. National Aeronautics and Space Administration, Washing- ton, D.C. EOS Science Steering Committee. 1987. Earn Observing System. Vol. IL From Pattem to Processes: The Strategy of the Earth Observing System. National Aeronautics and Space Administration, Washington, D.C., 140 pp

274 OPPORTUNITIES IN THE HYDROLOGIC SCIENCES Haeni, P. 1983. Sediment deposition in the Columbia and Lower Cowlitz rivers, Wash- ington-Oregon, caused by the May 18, 1980, eruption of Mount St. Helens. U.S. Geological Survey Circular 850-K, 21 pp. Kinter, J. L., and J. Shukla. 1990. The global hydrologic and energy cycles: Suggestions for studies in the pre-global energy and water cycle experiment (GEWEX) period. Bull. Am. Meteorol. Soc. 71(2):181-189. Krishnaswami, S., W. C. Graustein, J. F. Dowd, and K. K. Turekian. 1982. Radium, thorium and radioactive lead isotopes in groundwaters: Application to the in situ determination of adsorption-desorption rate constants and retardation factors. Water Resour. Res. 18(6):1663-1675. Robertson, W. D., and J. A. Cherry. 1989. Tritium as an indicator of recharge and dispersion in a ground water system in central Ontario. Water Resour. Res. 25:1097-1109. Ryan, P. F., G. M. Hornberger, B. J. Cosby, J. N. Galloway, J. R. Webb, and E. B. Rastetter. 1989. Changes in the chemical composition of stream water in two catchments in the Shenandoah National Park, Virginia, in response to atmo- spheric deposition of sulfur. Water Resour. Res. 25:2091-2099. Skinner, B. J., and S. C. Porter. 1989. Physical Geology. John Wiley & Sons, New York. Smith, R. A., and R. B. Alexander. 1986. Correlations between stream sulphate and regional SO2 emissions. Nature 322:722-724. Stockton, C. W., and G. J. Jacoby. 1976. Long-term surface water supply and streamflow trends in the upper Colorado River basin. Lake Powell Research Project Bulletin Number 18. University of California, Los Angeles. U.S. Committee for an International Geosphere-Biosphere Program. 1986. Global Change in the Geosphere-Biosphere: Initial Priorities for an IGBP. National Academy Press, Washington, D.C.

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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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