In Chapter 2, the committee identified a broad suite of water science and resources challenges and questions that are key for making significant advancements to address national and global water issues. These 10 questions are highly important and addressing them would be valuable for the nation. A subset of these questions, however, has been determined by the committee to have the highest potential not only to address the critical water science and resources challenges but also to advance the U.S. Geological Survey’s (USGS’s) strategic science priorities and those of its partners (see Statement of Task 3, Box 1.1).
To identify which questions among the 10 described in Chapter 2 would best achieve these goals, the committee developed a rubric to highlight the questions with the (1) highest scientific importance, (2) relevance to pressing societal needs, (3) alignment with USGS strategic directions, and (4) opportunities for collaborations among the Water Mission Area (WMA) and its partners, including other USGS mission areas (see Appendix A for a discussion of other mission areas), other federal agencies, and state and local partners. When the rubric (see Appendix D) was applied to the questions in Chapter 2, five questions arose that met these qualifications to the highest degree. Although the committee offers these five questions as the top priorities, it encourages USGS to address the other questions as resources permit.
In addition, WMA asked the committee to consider tools and approaches WMA may employ for observing, understanding, predicting, and delivering water science. These technological innovations—sensors, new modeling
approaches, data visualization, and citizen science—are discussed below, as they set the context for how to address these high-priority questions.
New space- and ground-based sensors have the ability to advance observations and analysis of water resources. Space-based sensors for global-scale observations of water stocks have made great advances (Lettenmaier et al., 2015), but technical challenges exist with respect to measuring and monitoring water quality. Integrated, multiagency initiatives (e.g., 3D-Nation1) that use tools such as high-resolution lidar are expected to provide seamless topographic and bathymetric elevation coverage across the nation. Drone-based platforms will advance monitoring of water quantity, quality, and ecosystem health. In the near term, nutrient monitoring using probes are likely to remain expensive, and the reliability of electrochemical electrodes and “lab-on-a-chip” sensors are not yet known in long-term deployments (Banna et al., 2014). In the near future, the application of sensors capable of continuously detecting and measuring organic (e.g., pesticides, emerging contaminants) and inorganic micropollutants (e.g., certain metals) remains technologically infeasible at environmentally relevant levels. Microsensors, however, remain an area of research and development that shows great promise, and the technology will continue to develop, improve, and become more affordable. The miniaturization of mass spectrometers may enable field deployments that can be tailored to detect specific contaminants at environmental levels (e.g., Snyder et al., 2015), while developments in environmental DNA (eDNA) analysis may revolutionize monitoring of ecosystem health and resilience.
Big Data and New Modeling Approaches
While the recent past has seen unprecedented growth in computing capacity, enabling models with high resolution and process fidelity at all scales, the future will depend on the treatment of extremely large-volume datasets (i.e., “big data”). Data from multiple sources and locations, including both biophysical and human-system information, will be assimilated into models on a near real-time basis; and models developed by experts in individual domains will be integrated, requiring attention to common data protocols and interoperability—the ability for different data systems
1 See https://my.usgs.gov/confluence/display/3DNationStudy/3D+Nation+Requirements+ and+Benefits+Study; accessed September 17, 2018.
and software to communicate (Kingdon et al., 2014). Technologies such as cloud computing (discussed in the next section) and the “Internet of Things” will continue to advance and will need to be incorporated as part of water modeling platforms (Granell et al., 2016). The field of data analytics, which uses algorithms to find correlations not previously considered within datasets, will also be a critical area of future improvement.
These developments will support improved scientific understanding, development of improved water models, and interdisciplinary model integration. Remotely sensed information on surface-water levels, soil moisture, vegetation status, snow and ice, and groundwater storage could provide new data products that will enhance model capability and improve both short-term forecasts and longer-term projections of change. Models with national coverage running at multiple spatial and temporal scales that integrate weather, surface water, and groundwater hydrology might provide the framework for delivery of these and other new data products. Such models will allow cross-site interpolation and synthesis to provide hydrologic information at any desired location and scale. These models will also support integration of a suite of other components essential to the USGS water missions, such as human impacts, climate change, ecosystems, water quality, and human health (Patterson et al., 2017).
Improved coupled modeling of the natural-human water system will need to include infrastructure, operational management, and human values and preferences. Models that incorporate decision-support systems will be able to assist natural resources managers and policymakers to inform management and policy decisions, especially if they are user driven, co-developed, and “fit-for-purpose.” Projections of future human impacts and risk are inevitably associated with large uncertainties; therefore, there is a need to develop a framework for decision-making under uncertainty.
Cloud Computing and Data Visualization
There is a strong need to improve access to water resources data, computational tools, and presentation. In the near future, such access will largely take place through mobile devices, social media, Web-based tools, and intuitive visualizations, but opportunities also exist to employ augmented and virtual reality. Options already exist to deliver time-sensitive, broadly useful data through social media, such as the Twitter feed on USGS’s Texas Water Dashboard that shows streamgages in flood stage2 and the USGS FloodWatch app for mobile devices. These types of outreach could be greatly expanded.
Web-based cloud services, which offer the multiple advantages of
ready public access to big data and open-source tools to easily manipulate and visualize data, avoid the need for major investment in technological resources, expertise, and proprietary software. Such an approach enhances opportunities for broader public engagement and actionable science. USGS is currently in the early phase of developing cloud-computing services through its Cloud Hosting Solutions enterprise. At the present time, the USGS cloud enterprise is intended for USGS Water Science Centers and mission programs.3 Future efforts will need to expand in order to facilitate public access to cloud solutions. Cloud-based decision-support tools provided in easily accessible formats could be used to allow interested citizens and professional managers to investigate the consequences of different scenarios (e.g., flooding) within their areas of concern.
Historically, USGS scientists and technicians were among the only groups in the nation with the training and qualifications to collect consistent, accurate, and unbiased water resources data, and USGS water programs were well supported in federal budgets. Now, more than half of WMA funding comes directly from state and local sources (see Appendix A for more discussion), and many state, local, and academic institutions have developed water resources research and monitoring capabilities that rival or even surpass the resources available to USGS personnel.
Although there are a wide variety and quantity of data currently being collected by agencies outside USGS, barriers exist to integrating these data into national databases due to long-established USGS “gold standard” protocols (Crilley, personal communication4). WMA has not only recognized these issues, but has begun to respond by providing cost-sharing to local stakeholders and establishing uniform data protocols through programs such as the National Ground-Water Monitoring Network and the National Water-Use Science Project (see Appendix A). Such data outsourcing, for which USGS serves as a national data repository and manager, rather than the main data collector, is likely to continue and expand in the future.
3 See https://my.usgs.gov/confluence/pages/viewpage.action?pageId=568560396; accessed September 17, 2018.
4 Communication during committee’s open session in San Diego, California, on November 30, 2017, with Dianna Crilley, Associate Director for Data, USGS California Water Science Center.
The past decade has seen a huge growth in citizen science, when the public engages in data collection and analysis using sensors, computers, and mobile devices. These crowdsourcing science examples are an outgrowth of established citizen science programs, such as the Audubon Bird Surveys, with more recent versions examining where earthquakes were felt,5 collecting information about marine debris,6 measuring precipitation,7 analyzing data from the Hubble Space Telescope,8 and exploring underwater imagery.9 Nascent efforts to use citizen science to improve streamflow data already are underway and the ability to make ever more sophisticated measurements is very likely to proceed apace over the next 25 years. In partnership with USGS, CrowdHydrology10 uses crowdsourced observations of stage-height data at numerous sites in 15 states, while Stream Tracker, a National Aeronautics and Space Administration (NASA)-funded citizen science project, documents intermittent stream flow.11 The National Water Quality Monitoring Council, also in partnership with USGS, provides information to organizations interested in establishing citizen science monitoring programs.12
The opportunity for citizen scientists to fill data gaps and supplement existing data networks through collection of basic water-quality measurements or water sampling for later analysis will continue to grow. Such citizen science data could provide crucial information to feed into water-quality databases and could be used to corroborate predictive water-quality models. The challenge, however, is how to make sure that the data quality is adequately understood, verified, and documented. The role for citizen analysis is likely to keep expanding in the future and change as technology evolves.
As previously mentioned, critical water resource challenges for the coming decades are unlikely to fundamentally differ from existing challenges. Looking forward 25 years, disruptive changes (e.g., technological innovations mentioned above) and the continued development of physical
6 See, for example, http://depts.washington.edu/coasst/what/vision.html; accessed September 17, 2018.
8 See http://hubblesite.org/get_involved/citizen_science; accessed September 17, 2018.
scientists, social scientists, and engineers who can utilize these advances and collaborate with one another across disciplines will allow for novel approaches that can transform WMA. The priority questions discussed below, and their attendant recommendations, should be read in this context. Many of the topics discussed in the next section are already part of ongoing USGS programs. Nevertheless, the committee believes it is worth noting that there is a clear need for a forward-looking USGS to adopt a more flexible and nimble strategy to enable rapid changes in data, technology, and workforce expertise.
1. What is the quality and quantity of atmospheric, surface, and subsurface water, and how do these vary spatially and temporally?
To effectively manage water resources and to provide clean and safe water for all, there is a critical need for reliable, comprehensive data on the quantity and quality of the nation’s surface water and groundwater resources. WMA is tasked with collecting water quantity, movement, distribution, and quality data, which are archived in the National Water Information System. A central element of this program is to deliver the data that the United States needs to manage and protect surface water and groundwater resources and minimize water-related risks. WMA also plays an essential role in providing information that is of great use for other USGS mission areas, federal agencies, and state and local partners. For example, studies at USGS Northern Prairie Wildlife Research Center (within the Ecosystems Mission Area) rely on hydrologic data collected by WMA scientists, which have resulted in many successful collaborations (e.g., McKenna et al., 2017; Levy et al., 2018, and references therein; Mushet et al., 2018). The upcoming NASA Surface Water and Ocean Topography (SWOT) Mission will be dependent on USGS streamgage data, which is used to ground-truth satellite measurements and calibrate stream discharge models (Pavelsky et al., 2014; Solander et al., 2016). Collaborative efforts with the private sector may also become important.
While USGS excels in the collection of high-quality water-resources data, current needs for water data are unprecedented, and current technologies have raised the bar for water-data delivery and interpretation. Therefore, a re-evaluation of the National Water Information System’s strategic goals and capabilities is needed to ensure that WMA is nimbler in response to environmental change; this includes monitoring relevant components of the hydrological cycle as well as the interactions among them. Analysis of these observations leads to operational decisions ranging from the federal to the local level, such as determining river flows or groundwater withdrawals (McNabb, 2017). However, because no set protocol exists with respect
to data measurement and reporting, there are issues with interagency data sharing and cooperation; these issues could be minimized by having different agencies agree on standard formats for measuring and reporting data. The Water Quality Portal, sponsored by USGS, the U.S. Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council, exemplifies cooperation among federal agencies, state agencies, and citizen groups. The portal serves data collected for many diverse purposes by more than 400 state, federal, tribal, and local agencies. Another example is the Advisory Committee on Water Information.13 As the lead agency, USGS can advocate for uniform standards, guidelines, and procedures for the collection, analysis, management, and dissemination of water information.
With all the pressures on the water environment, USGS will need to re-evaluate its current capabilities in the context of new opportunities that may not necessarily always meet the agency’s current strict guidelines with respect to data collection, data quality, and evaluation. These new platforms include big data–driven model assimilation and integration, new applications of social media, and expansion of citizen science (discussed in a previous section). Not all of these uses necessarily need the “gold standard” of data collection that USGS is known to deliver, which may provide an opportunity for USGS to assess the level of quality that could be needed for different uses (i.e., “fit-for-purpose”). Innovative approaches will expand spatial and temporal monitoring frequency and enhance the capability to deliver data that meet specific user needs. USGS could also consider a training role, bringing together stakeholders to coordinate methodologies to promote data consistency across USGS scientists and stakeholder groups. USGS is a natural fit to prioritize the ever-increasing demands for all types of water quantity, quality, and use data.
Recommendation 1.1: Enhance data collection, include citizen science, and develop Web-based analytical tools.
To enable the nation to meet future water resources challenges, WMA should (1) strategically enhance the temporal and spatial collection of water quantity, quality, and water-use data using robust, innovative technologies to develop readily accessible “fit-for-purpose” information; (2) further infuse citizen science into USGS data-collection activities to augment traditional monitoring networks; and (3) develop innovative, intuitive Web-based data analysis and visualization tools for the nation to better understand the status and trends of its water resources.
Recommendation 1.2: Coordinate with agencies and organizations on data delivery.
As part of the national effort to deliver water quantity and quality data and information, WMA should coordinate with other agencies and relevant organizations to co-develop accessible, open, and codified data formats, protocols, interoperability, and software tools. This will allow integration across data streams and encourage synthesis of multiple observations in order to detect trends, patterns, and changes in water quantity and quality.
Venues that USGS might explore for fostering coordination of activities related to the provision of data needed to address key water resources challenges in coming decades include the Advisory Committee on Water Information, which has played a coordinating role in some instances, and the National Ground-Water Monitoring Network (see Appendix A), which leverages data from state and local cooperators and supports local data collection and open data formats.
2. How do human activities affect water quantity and quality?
Assessing the role of human activities in water quality and quantity is key to understanding and managing water now and in the future. Human-induced changes to the land and water environment include replumbing of the hydrologic cycle through water withdrawals and diversions; changes in infiltration resulting from impervious surfaces in urban areas, which influence runoff and contaminant delivery; changes in water, nutrient, and sediment delivery from agricultural land use; and alterations to water quality through the release of nutrients, pathogens, and deleterious substances to groundwater and surface water. USGS has a role to play in not only basic water monitoring, but also in assessing and predicting the role of human and natural stressors on water quality and quantity (Van Metre et al., 2017). Continuity in its surface water and groundwater quantity and quality monitoring programs will enable USGS to elucidate trends in water movement, storage, abundance, and quality as human activity continues to alter the hydrologic cycle. These programs will provide the basis for implementing the necessary modeling to project anticipated changes.
A major challenge for USGS to address this question for the entire nation will be to manage the streamgage and observation well networks so that changes from anthropogenic activity can be captured. There are opportunities for USGS to optimize its current water monitoring efforts and employ new technologies and methods to both better observe changes to water resources and fill existing data gaps. For example, the USGS National Water-Quality Assessment Project (NAWQA) has included a focus on
human-impacted watersheds (NRC, 2012d). USGS also hosts the National Ground-Water Monitoring Network Data Portal, which provides access to groundwater data from multiple, distributed databases. In the future, it will be beneficial to periodically reassess and optimize monitoring locations and sampling frequencies to capture changes due to human activities.
USGS could bridge data gaps in the observation network through collaborative efforts with other federal and state agencies. For example, cooperation between USGS and the U.S. Army Corps of Engineers (USACE) occurs on a wide range of topics, from snowpack assessments to flood mitigation efforts. USGS also collaborates with several federal agencies—including EPA, the National Oceanic and Atmospheric Administration (NOAA), USACE, and the U.S. Department of Agriculture (USDA)—to monitor drought conditions in the United States. Opportunities exist where data shared between USGS and other agencies can be utilized to observe trends in human activity that could affect water resources. In addition, tools used to predict land-use change or plans for anticipated water infrastructure can be used to help guide USGS regarding new locations for additional water measurements.
USGS could provide leadership in developing predictive models to assess future water quantity and quality conditions under different land- and water-use scenarios. A regional-scale predictive model of future groundwater storage, recharge, discharge, and human withdrawals, under plausible future agricultural, conservation, and climate scenarios, can offer a forward-looking vision on the water security of the region and food security of the nation. USGS has the expertise to lead such future assessments, and through its regional Water Science Centers (e.g., Lauffenburger et al., 2018) can develop a set of predictive models for regions under future significant water sustainability stress.
USGS is also poised to contribute significantly to understanding human impacts on water quality. Past and current monitoring efforts through NAWQA were the first to detect emerging contaminants in both aquifers and surface waters (Kolpin et al., 2002), and USGS analytical capabilities make it particularly well suited to detect the effects of human activity on aquatic ecosystems. For example, feminization of male fish by estrogenic compounds was first reported by the USGS Ecosystems Mission Area (Blazer et al., 2007) and collaborations with WMA through NAWQA have detected the presence of other pharmaceuticals in fish tissue (Schultz et al., 2010). Given the critical human impacts on water resources, maintaining and strengthening collaboration between WMA and other USGS mission areas will be important, as will collaborations with local, state, federal, and transboundary agencies. USGS modeling to understand and predict stressors on water quality, such as the SPARROW (Spatially Referenced Regression On Watershed attributes) model for the Mississippi River Basin
Recommendation 2.1: Increase focus on the relationships between human activities and water.
WMA should prioritize investigations of the relationships between human activities and changes in surface water and groundwater quantity, quality, and water-related hazards through a careful synthesis of observations and coupled natural-human systems models forced by climate and socioeconomic factors.
3. How can water accounting be done more effectively and comprehensively to provide data on water availability and use?
USGS currently faces challenges with respect to water accounting. The SECURE Water Act of 2009 (42 U.S.C. § 10361) had specific mandates that included providing a more accurate assessment of U.S. water resources, determining the quantity and quality of water available for beneficial use, and identifying long-term trends in water availability. WMA produces 5-year water-use circulars14 (e.g., Hutson et al., 2004; Kenny et al., 2009; Maupin et al., 2014; Dieter et al., 2018) that provide critical documentation in support of the Act. USGS collects county-scale water withdrawal data for these summaries, organized by specific use (e.g., livestock, golf courses, aquaculture) as well as water sources (e.g., groundwater, surface water, saline sources, total).
However, USGS has not tracked consumptive use since 1995; data gaps exist within several water-use categories (e.g., industrial, livestock, mining) and withdrawals are based on estimates. In addition, the 5-year reports are often significantly delayed (e.g., the most recent 2015 data assessment was released in 2018 [Dieter et al., 2018]). The current water-use program does not appear to have a systematic approach to evaluating the accuracy of water-use data.
The current dependence on state and local partners to collect most water-use data has led to inconsistent data collection and, in some cases, to significant data gaps. Water-use reporting is mostly in response to state regulations (which vary across the nation), and USGS does not have authority to mandate the collection of these data. Some states do not collect such data, while others may not have the ability to share it with the federal government. For example, some local water users may feel that their water consumption is a proprietary issue. This does not, however, make coordination and communication between USGS, as a national reporting agency, and the states, as data collectors, any less essential.
New methods are in use or development to aid in the estimates of water withdrawals. For example, data from space-based Earth observation platforms can model water withdrawals based on land use, evapotranspiration, and precipitation (van Eekelen et al., 2015). Satellite-based measurements can be used in conjunction with water-use data to provide assessments of existing and future available water stocks (Solander et al., 2017). These new tools, in conjunction with new consumption models, can enable USGS to refine water use estimates in the future.
Understanding the extent and patterns of anthropogenic water withdrawals is critical toward assessing available and future water stocks and their impact on aquatic and watershed ecosystems (Vörösmarty et al., 2000, 2010; Gleick, 2003a,b). USGS’s efforts to quantify water usage are an essential function to assess both current and future water needs for human use and ecosystem function. Integrating resources management with remote sensing is important in efforts to fill data gaps and bridge the nexus among water, energy, and food (Sanders and Masri, 2016). Understanding how humans influence the water cycle through withdrawals to support energy and food production, industrialized activities, and domestic consumption will have significant consequences with increasing population, climate change, and globalization.
When coupled with climate change effects, factors such as population dynamics, the nature of human-built water infrastructure, and decisions about water management and use will affect total water demand and availability. Improvements to current water-accounting practices will be needed to determine how much consumptive water is permanently lost to the hydrologic system for a specific region. Furthermore, withdrawal values based on estimates will need to be corroborated by other methods such as remote sensing.
To better manage the nation’s water resources, models that predict water usage will need to be refined in a manner that integrates “on the ground” assessments with data derived from remote sensing. A combination of improved models and better-constrained datasets could lead to policies that are better able to mitigate the impact of human water withdrawals and consumptive use on sensitive watersheds that may not be able to sustain development and growth in the future. USGS will need to collaborate closely with other federal agencies and states to collect, analyze, and integrate critical data.
Recommendation 3.1: Develop a robust water accounting system.
WMA should conduct studies to understand how to best and most efficiently execute water accounting and how to assess and present uncertainty in the reported data. Water accounting should go beyond
measurement of the resource itself to consider the biophysical and societal constraints on water use and should include estimates of consumptive versus non-consumptive water use.
Recommendation 3.2: Collaborate with agencies and organizations on water-data standards and categories of use.
As part of the national effort to collect water-use data and information, WMA should collaborate with other agencies and relevant organizations to co-develop standards, protocols, and clear definitions for categories of water use, and should adhere to common format standards across states, counties, and watersheds.
4. How does changing climate affect water quality, quantity, and reliability, as well as water-related hazards and extreme events?
Natural and human-caused climate change will strongly influence the hydrologic cycle and freshwater resources (IPCC, 2013; USGCRP, 2017). Such effects can now be observed in a wide range of systems, including changing evaporative demand associated with rising temperatures, dramatic changes in snow and ice, alterations in precipitation including the frequency of extreme events, and rising sea levels (Bates et al., 2008; NRC, 2012b,c; Georgakakos et al., 2014; Haddeland et al., 2014; Jiménez Cisneros et al., 2014).
WMA has fundamentally contributed to observing changes with its extensive, long-term monitoring of the nation’s surface water and groundwater quantity and quality. This long-term monitoring has provided the observational basis for scientists (including those within USGS) to detect trends in water resources and frequency of water-related hazards and to make correct attributions for these changes, and for practitioners to design infrastructures to mitigate and adapt to the change. WMA is also collaborating with other federal agencies to develop predictive models (e.g., the National Water Model; see Box 2.1) from local to national scales.
Looking ahead, USGS is well positioned to play a leadership role in monitoring, detecting, understanding, and predicting climate-driven water quantity and quality changes and delivering such knowledge to the end users and the public. WMA needs to strategically monitor indicators of water quality and quantity at locations and timescales that will most likely be affected by climate change in the coming decades and to use this information in developing and refining integrated models that can be used to project potential hydrologic impacts of a changing climate.
USGS is a leader in synthesis activities to search for patterns and trends in climate change, as well as their underlying causes. To further improve understanding in the future, WMA could recommend critical water quality
and quantity indicators that need to be more closely monitored and processes that need to be represented in predictive models. The USGS Powell Center for Analysis and Synthesis15 is well positioned to solicit and support synthesis activities that can be co-led by USGS and academic scientists.
To enable stronger predictive capabilities, WMA can continue to develop integrative models that consider surface water and groundwater processes simultaneously. Such models can treat water quantity and quality as co-evolving entities. Given the challenge of modeling large areas while maintaining sufficient detail for local decision-making, models might nest small-scale simulations in larger spatial contexts to provide meaningful information to managers from the watershed to the national level. Future modeling efforts might also integrate human and climate forcing and strategically use extensive USGS observations through parameter estimation, data assimilation and model validation and benchmarking. At the national level, WMA can collaborate with other federal agencies through projects such as the National Water Model (see Box 2.1) by contributing expertise in process representation and by providing a national hydrogeologic framework that supplies subsurface parameters such as porosity and permeability of the soils and sediments.
To deliver this information, WMA needs to advance its work on interactive visualizations that show patterns and trends of the hydrologic effects of climate and land-use change from the national to the local level.
Recommendation 4.1: Ensure that monitoring networks provide adequate information to assess changing conditions.
USGS should periodically assess the state of surface water and groundwater monitoring networks to ensure that these networks can provide data for hydrologic impact analyses as environmental conditions change due to climate, agriculture and other land uses, and urbanization.
5. How can long-term water-related risk management be improved?
Environmental change and societal decisions alter the nation’s vulnerability to hydrologic risk. Hazards such as floods, droughts, and waterborne contaminants are driven by changes in climate, land cover, hydrology, and biogeochemistry and are increasingly affected by how humans manage land-use and water resources. A need exists to improve the scientific understanding of how humans interact with the environment and how those interactions affect water resources and risks. USACE and the U.S. Bureau of Reclamation have oversight of the construction of engineered approaches to long-term hydrological risk (e.g., infrastructure such as dams and levees),
the Federal Emergency Management Agency (FEMA) has oversight over response to immediate risks, and EPA regulates water quality. USGS produces the data and tools that inform the actions of those agencies, such as producing models and software for predicting surface water and groundwater flows, assessing water quality, and collecting data on and calculating recurrence statistics for extreme events. These scientific tools also assist in state and local decision-making.
Models that integrate across human and natural systems will be needed to improve the understanding and prediction of long-term, multi-decade environmental and societal impacts. They can also inform policy and management decisions while accounting for deep uncertainty in human decision-making. Interdisciplinary research to fully understand and predict linkages among surface water and groundwater, water quantity and quality, and natural and human systems is needed (Wheater and Gober, 2015). These models can be used to inform risk-management actions, such as informing communities of changing risks of floods and pollution, supporting the management of complex water resources systems, and predicting how land-use change may affect the climate and how extreme events will influence the global economy.
Given the complex interactions and feedbacks in the natural-human water system, better prediction and risk management will need both new observational data and integration of models across disciplines. Managing long-term water-related risks in the face of environmental and societal change will require improved understanding of observed historical change. Models can play a key role in the diagnosis of the complex interactions (whether societal policy, human actions, or environmental change) that underlie the past. USGS should lead an effort that develops improved process-based understanding of water and associated nutrient and contaminant movement as a function of environmental change and that quantifies outcomes at a range of spatial and temporal scales. Improving long-term water-related risk management will also require better understanding of the likely effects of climate change on extreme events (e.g., Polade et al., 2017) due to their impacts on regional hydrological systems. Models are also needed that consider both the physical system and the human-economic constraints on the system to fully understand risks of shortages in water availability.
Prediction of future hydrologic risks will be based on simulation and evaluation of potential outcomes from environmental scenarios within social and economic constraints. Building capacity for reliable long-term prediction and risk management requires developing a validated understanding of complex socio-hydrological systems, developing models to simulate these systems, and exploring a range of alternative future scenarios. The work will need to leverage new data streams and computational technologies and adapt to changes as they occur over the next several decades.
USGS can lead this effort through improving the prediction of surface-water and groundwater systems and developing new capabilities for integration of models to predict the complex interactions that underlie water-related risks from future change.
Recommendation 5.1: Focus on long-term prediction and risk assessment of extreme water conditions.
WMA should prioritize activities that address long-term prediction and risk related to hydrologic causes such as floods, droughts, and waterborne contaminants. WMA should seek to understand how climate change, land-cover and land-use change, and other biophysical and socio-economic factors affect the nation’s water resources, including water quantity and quality, extreme events, and other hydrologic hazards. USGS should further develop integrative models that can help predict future hydrologic conditions under these changing climate conditions. These activities will require integrative studies with other USGS mission areas and should include resource managers, decision-makers, and social scientists.
Integrated, coupled system models are necessary to better understand the complex water systems—whether natural components, human impacts, or evolving states such as changing climate and environmental conditions. Integrated models that incorporate appropriate temporal and spatial scales will improve understanding of water quantity, water quality, and the linkages and feedbacks among hydrologic components.
Recommendation 6: Develop multiscale, integrated, dynamic models that encompass the full water cycle.
WMA should prioritize multiscale and integrated modeling efforts that dynamically couple above- and below-ground hydrologic stores and fluxes, water quantities and qualities, and natural and human drivers and interactions, and utilize diverse observations ranging from ground-based sensing to Earth observations from airborne and space-borne platforms.
Given the growing importance of water resources challenges to lives and livelihoods, economic development, and environmental health, and the increasing costs of water-related disasters, there is a strong argument
that water-related agencies should continue to work together, and even strengthen their ties. Opportunities exist for WMA to provide scientific support to other agencies within the U.S. Department of the Interior in areas such as potable water reuse, desalination, and water use and disposal associated with unconventional hydrocarbon extraction. The U.S. Bureau of Reclamation’s WaterSMART program is a prime example of how WMA can collaborate and provide support to advance the science associated with water conservation. Collaboration has always been a strong suit of WMA; yet, it is critical to continue and expand these collaborations and partnerships as resources become more limited. One of the areas ripe for collaboration is integrated modeling—WMA could draw on the expertise of other USGS mission areas, which hold some of the core data (e.g., modern geologic maps) that are needed for such integrative efforts.
Recommendation 7: Collaborate as appropriate both within and outside of USGS, including agencies and the private sector.
Given that water resources challenges are inherently interdisciplinary, WMA should continue to build and maintain strong collaborations. WMA should maintain and strengthen ties with other USGS mission areas to maximize the impact of its work on observing, understanding, predicting, and delivering water data and issues. WMA should maintain and strengthen ties with other federal and state agencies, and as appropriate, international agencies (especially regarding transboundary water issues) to meet these water resources challenges. WMA should also evaluate and, where deemed advantageous, engage in private-sector collaborations to develop new data sources and platforms, and in the dissemination of data and information, models, and other products.
In 2015, USGS produced a Bureau Workforce Plan, in which it outlined some broad needs for the future.
Moving into the future, it is paramount to maintain USGS scientific capability and reputation and provide skilled and innovative science support. . . . [T]here are key skill sets and capabilities that while currently found in the USGS, will be increasingly needed in the future. There will be increasing demand for multidiscipline syntheses and landscape-level science, which will require capabilities such as mapping, geospatial data integration, remote sensing, predictive modeling, scenario development, forecasting, simulation, and decision support. . . . The USGS will also need a workforce that can adapt to new technology and respond quickly, in both quantity and expertise, to changes in science and management priorities. (USGS, 2015, p. 1)
Given the priority questions above, the committee emphatically endorses the aims outlined in that USGS report.
The modern WMA workforce will need to reflect the priorities of emerging and future science questions and technologies. In addition to WMA’s current workforce strengths in hydrology and water science, a highly trained workforce with expertise in data and computational science (including big data, data analytics, and data delivery and visualization); modeling; remote sensing; disciplines such as climate science, hydrology, geochemistry, and ecosystem science; and interdisciplinary fields such as hydroclimatology and hydrochemistry will be needed. The future workforce will need to be nimble, inter- or multi-disciplinary, collaborative, and adaptive.
Recommendation 8: Build a workforce who are ready to take on new water challenges.
WMA should align its current and future workforce to meet critical strategic needs, specifically building capacity for improved water monitoring; coupled natural-human systems modeling; and data analysis, analytics, visualization, and delivery using reliable, accurate, robust, and innovative methods.
The committee was charged to identify the nation’s highest-priority water science and resource challenges over the next 25 years. The committee is cognizant of the proverb “it is difficult to make predictions, especially about the future,” but believes that there are clear trends that lend support to these views of future water challenges. The global population will grow by 2 billion by 2040 and will place additional demands on natural resources. This growth in population will be realized during a time of economic advances in the developing world, which will likely amplify demands. Global temperatures will continue to increase over the next 25 years, and climate change will continue its course. The world population living in urban areas will grow to about 60 percent by 2040. All these changes will add to the water resources challenges identified above, with concomitant needs for new data, information, analyses, and science to address the challenges.
USGS has been the premier federal agency for water resources since its establishment in 1879 and continues to be so. The committee envisions that WMA will adapt in the future to deliver the necessary data and science to enable the country to manage its water resources effectively and
to deal with hazards. The five high-priority questions identified above can provide a framework to help guide the evolution of WMA, so that USGS can effectively address the water science and resources challenges that will face the nation over the next 25 years.