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Updated 12 October, 2003
A Plan for a New Science Initiative
The uncertainties in assessing the effects of global-scale perturbations on the climate system are due primarily to an inadequate understanding of the hydrological cycle -- the cycling of water in the oceans, atmosphere, and biosphere. Overcoming this problem necessitates new ways of regarding a field traditionally divided amongst several disciplines, as well as new instrumentation and methods of data collection. (Chahine, 1992)
There is growing consensus that now is the time to rise to the challenge Cahine put forward eight years ago. The Committee on Global Change Research recognized the need to consider the global water cycle as one of the critical themes for research in the coming decade (NRC, 1998). Similarly, the NRC Committee on Hydrologic Science (NRC, 1999a) noted the central role of water in the working of the Earth's climate system and argued convincingly for an expanded research program to learn how this system works.
The unprecedented abilities we now have to make new observations, visualize data, and construct models of water cycle processes all point to the substantial and significant scientific progress that can be made in the coming decade. Conceptual advances also offer new opportunities for rapid scientific advancement, for example, in hydrometeorology and ecohydrology.
The agencies of the U.S. Global Change Research Program (USGCRP) all have successful programs related to the water cycle. Many of them are directed at needs specific to the agency's mission. All fulfill critical needs and should be continued. Our vision is for a coordinated effort that expands the overall scope of the collected work on the water cycle. We argue that, despite differing cultures and missions, USGCRP agencies, along with the scientific community in general, and the public at large would all greatly benefit from a much improved knowledge base on the water cycle at long time and large spatial scales.
Thus, as an overarching principle, we believe the initial focus of the water cycle science initiative should be on (1) seasonal to interannual and longer time scales, and (2) regional to global spatial scales. We believe these emphases are most appropriate to the climate (vs weather) charge of the USGCRP, and to our own charge from the USGCRP to develop a global water cycle science plan. Determining priorities in this light also has strong scientific and practical justification. Arguably, scientific and societal challenges are greatest at these scales and potential scientific rewards are commensurately large.
Additionally, a critical applications gap exists in the availability of useful scientific knowledge for water managers and other stakeholders on these space-time scales. Knowledge about hydrologic fluctuations with durations of decades to centuries is important because the lifetimes of our water resource systems and of the effects of water resource decision making are of comparable duration. We emphasize that improved understanding of water cycle processes at these greater time and space scales has critical implications for water management and ecosystem protection at scales relevant to local decision making.
As explained in Chapter 1 and is evident throughout this report, the Water Cycle Study Group has sought to ascertain, in the most basic terms, the science needed to (1) determine whether the global water cycle is accelerating, (2) enhance our ability to make useful predictions, and (3) develop information that would mitigate the effects of water cycle calamities. These three issues form pillars on which a science plan can be well based. The scientific elements needed have been covered in the previous three chapters. Here we present a plan that embeds science elements related to chosen time and space scales into an overall “systems -- framework to address the pillar initiatives.
We see three primary challenges for research efforts. The first is to deliver more comprehensive data and information of enhanced resolution and increased precision in a timely way. Successfully meeting this challenge will require integrating data from new sensors with data from existing networks, and selective expansion of existing observation networks. Techniques borrowed from neighboring disciplines, for example, those using stable isotopes, must be embraced. In addition to collecting new data, existing long-term records must be archived and preserved carefully, and observations must be continued indefinitely at sites with long-term, high-quality records, so that patterns of temporal variability, including long-term, low-frequency fluctuations, can be defined and studied.
Studies of hydrologic proxy variables, such as tree rings, varves and other sedimentary deposits, and archaeological relics, must be undertaken to extend the length of long instrumental records. The databases of proxy records must be coordinated and integrated with instrumental databases. It is absolutely essential that this challenge be met for two reasons. Major advances in the environmental sciences almost always follow on the heels of new observations (including “proxy -- observations) and new instruments with increased resolution. Research on the water cycle is no exception. Additionally, users of water cycle research often need data and information themselves and not only predictions from models.
The second major challenge is to determine how predictable the water cycle is for the temporal and spatial scales of interest. Ascertaining the likely limits of predictability will lead to improved prediction, because efforts can be concentrated on more predictable components of the water cycle. Progress in promising areas will be the most cost-effective and rapid. At the same time, less predictable or inherently unpredictable processes must be estimated insofar as possible and their limits of predictability assessed so we can better appreciate the scope and magnitude of “unanticipated changes. --
The third challenge follows directly from the challenges above -- improving our ability to predict water cycle components. To improve predictions, a comprehensive program that includes observations, process experiments, and numerical modeling will be needed, and predictability studies will be needed to guide development efforts.
The research plan should be implemented within a systems framework, in which data, process research, and modeling are all integrated with active feedback from users of the research (Figure 5.1). Seasonal and longer lead-time predictions of tropical sea surface temperature and its effects on climate variability in other parts of the globe have been provided to the public. Better knowledge of the relations of soil moisture and other land surface processes with atmospheric phenomena will enhance predictions' accuracy. Different sectors have made use of such information with varying degrees of effectiveness. By considering users' needs in the way predictions are made and observations presented, the information can be made significantly more useful.
The proposed integrated plan is not simply a summary of all the initiatives enumerated under the three individual science questions. It must integrate across the science questions if the needed achievement that we envision is to be realized. The strategy cannot be seen as a simple tree where various “ornaments -- of specific research needs and findings, however meritorious on their own, are placed. Some cross-cutting associations are easily appreciated -- for example, ocean-land-atmosphere models have a prominent role in addressing science questions 1 (Chapter 2) and 2 (Chapter 3). Other work will require cross-disciplinary links that have been made only weakly in the past, such as the application of data assimilation techniques (Chapter 2) to models and observations relating to nitrogen transport from large watersheds to coastal oceans (Chapter 4). In addition to outlining how integration might be done, the plan presented in this chapter was developed with full recognition that priorities must be identified so that resources can be allocated accordingly.
Elements of an integrated water cycle science initiative form part of a systems model (Figure 5.1), with the initial priority focus on climate time-space scales. Major issues within the initiative fall under improving our observational capabilities, assessing predictability (expectations that are reasonable based on science), and developing improved, significant predictions, using the best methods available to deliver information to users. Figure 5.2 illustrates these interactions. Within this framework, we propose three pillar initiatives, with the elements of the science plan based on these initiatives drawing on individual science elements discussed in Chapters 2, 3, and 4. (Appendix D presents tables showing the links between pillar initiative science elements and earlier report chapters.)
Pillar Initiative 1. Determine whether the global water cycle is accelerating and to what degree human activities are responsible.
The frequency of extreme hydrological events -- an environmental feature that affects all aspects of human society and enterprise -- varies over decadal and longer time scales. There is evidence that the global hydrologic cycle may be accelerating, leading to an increase in the frequency of extreme weather events. This acceleration, if it is truly occurring, may be the result of human activities (including, among other things, increasing the concentrations of greenhouse gases in the atmosphere and altering the landscape of the planet through changes in land cover and land use). Determining whether the water cycle is accelerating, and if so, how much the acceleration owes to human activities, requires a focused effort on modeling changes in the global water cycle on climate time scales, and on supporting observations, process studies, and budget studies.
Key elements in addressing this pillar initiative are better understanding of the processes governing space-time distributions of regional and global precipitation, atmospheric water vapor, cloud processes, snow and ice dynamics, and global ocean fluxes. Efforts to improve process understanding must be founded on better observations of pertinent state variables, field experiments, and improvements in coupled atmosphere-land-ocean models. This research initiative encompasses a number of specific research priorities:
Water Vapor and Wind Measurements. Innovative measurements of water vapor should be incorporated into standard measurement systems. Along with water vapor observations, improved measures of wind (wind profilers) should be deployed so that water vapor fluxes and moisture convergence can be better estimated from observations and analyses. Field campaigns should be carried out over relevant global regions to characterize water vapor and cloud distribution, especially in the upper troposphere. In addition to using state-of-the-art water vapor measurements, these experiments should be carried out in conjunction with mesoscale, regional, and global climate modeling.
Cloud Data. Unique new observations provided globally by experimental satellite missions such as TRMM, Cloudsat, and PICASSO/CENA will provide new insights into cloud microphysics and three-dimensional structure. These observations are needed, together with a coordinated system for processing existing, archived cloud data, to understand cloud ensemble properties and upper tropospheric moisture distributions.
Precipitation Data and Analyses. Current precipitation data sets need to be extended in space and time to maximize the value of existing historical observation records. New high-resolution gridded precipitation analyses will be critical for better large-scale understanding of the global hydrologic cycle. Precipitation data covering the entire globe at sufficiently high resolution to capture diurnal variability and spatial inhomogeneities will improve understanding of water cycle exchanges and prediction at all scales. Support is imperative for the Global Precipitation Mission (GPM), which currently promises to provide three-hourly, global, four-kilometer precipitation coverage.
Intensive field campaigns are needed to define precipitation predictability. The campaigns should include a combination of boundary layer observations, aircraft observations during precipitation events, upward-looking surface measurements, synoptic-scale information, and coordinated satellite observations. The field experiments should be accompanied by advanced numerical experiments designed to untangle some of the uncertainties in current modeling schemes. These experiments will provide better parameterizations for larger scale (e.g., global) models.
Snow Water Equivalent. Improved seasonally and regionally specific algorithms should be developed for extracting snow water equivalent (SWE) from microwave brightness temperatures. In support of these remote-sensing efforts, an initiative should develop a research-quality data set on the climatology of snow properties, initially over North America and eventually globally, integrating in situ, microwave, and visible snow measurements. Efforts should be made to supplement the current network of snow depth observations from selected manual climate-observing stations in the United States with weekly measurements of SWE.
Global Ocean and Ice Sheet Observations. Enhanced global ocean and ice sheet observations are needed, combining satellite remote sensing and long-term deployment of arrays of ocean buoys or subsurface floats, to help document, model, and eventually predict the life cycle of global climate variability modes. Such efforts, while not the sole province of the water cycle research, must be closely coordinated, as they have strong implications for improved understanding of the global water cycle. A global ocean surface flux monitoring program is critically needed, to obtain for the first time an estimate of the freshwater flux from atmosphere to ocean (through precipitation) and from the oceans to the atmosphere (through evaporation).
These components of the global water cycle remain a major source of uncertainty in attempts to characterize water fluxes between reservoirs and to predict variations in these fluxes at seasonal time scales. A set of coordinated field, remote sensing, and modeling experiments should be carried out to better understand the role of regional anomalies in the global transport of water, in particular, the persistent deviations in global moisture transport that lead to extreme droughts and large area flooding.
Nested Modeling and Computing Capabilities. Nested regional climate models can provide a means of bridging the spatial scales of atmospheric, land-surface and subsurface processes. A systematic approach to model design and development is needed that will permit determining the scales at which predictive information should be exchanged within a nested modeling approach. This research will be heavily computational, requiring enhancements to available national computing capabilities. Computer visualization must be developed to enhance our understanding of hydrologic systems and allow researchers to transfer model results more readily to the user community.
Better geographical information systems using information on such input parameters as elevation, vegetation type, soil type, land use, land cover, river reaches, and hydrologic unit boundaries -- at finer spatial and temporal scales -- should be developed, along with the distributed hydrologic models that such information would enable. Fellowship and exchange programs should be developed to foster the involvement of scientists at all levels (including students) in developing and improving coupled land-atmosphere models.
Water Budgets. A continuing effort to use observations to close water budgets is critical. New data sets geared specifically for budget studies are needed. Because analysis budgets are the main link between models and observations, they should be rigorously tested against all observations, especially those hydrometeorological observations developed to cover broad space and time scales. New continental and global hydrometeorological data sets will be required to support these activities. These data sets include gridded (or equivalent) observations of streamflow over continental domains, and gridded high-resolution precipitation data. Expanded budget studies covering snow accumulation, melt, runoff, and evaporation of snow in continental regions should also be undertaken to understand how snow contributes to the water cycle.
Pillar Initiative 2. Determine the deeper scientific understanding needed to substantially reduce the losses and costs associated with water cycle calamities such as droughts, floods, and coastal disruptions.
By better understanding the hydrological cycle and its relationship to meteorological, climatological, biological, and other phenomena, we can increase our skill in predicting regional water supply and hydrologic and biogeochemical anomalies at seasonal and longer time scales. This prediction capability will permit resource management and disaster planning and mitigation measures to minimize associated economic losses.
Key elements for addressing this pillar are improving model predictive skill by testing models with better observations; explicitly addressing conceptual model and parameter uncertainties; and comparing different computer codes using data from carefully designed field experiments. Specific research priorities under this initiative include the following:
Surface Networks, Sensors, and OSS. Observations via surface networks and sensors must be ongoing and improved. The spatial and temporal resolution of precipitation measurements should be improved. The accuracy of NEXRAD and satellite estimates is ultimately limited by the gauge observations used in their calibration. The gauge network thus remains the backbone of the precipitation observation system, especially for climatological applications. Current precipitation data sets need to be extended in space and time to maximize the value of existing historical observation records. A regional-scale network of sites should be developed at which surface meteorological variables, soil moisture, and groundwater levels will be measured.
A network of in situ monitoring stations near mouths of major U.S. rivers should be emplaced to couple water fluxes with fluxes of dissolved and suspended material, in particular, to link water, nitrogen, and carbon cycles. International partners should be encouraged to establish comparable networks to obtain global scale measurements. A powerful method for determining the gaps in observations is observing system simulation (OSS). OSS uses a predictive model, a set of measurements that are either already operational or are prospective, and a data assimilation system that optimally combines observations and model output. OSS methods have not been widely used for land surface simulation, but they have important implications for the design of both surface and satellite observing systems.
Satellite Observations. Satellite observations are needed for hydrological variables not yet remotely sensed, and for which technology development may be required. New satellite observation methods promise to better define variations in subsurface moisture storage. NASA's post-2002 plans should be encouraged for an experimental soil moisture demonstration mission, aiming for about 10-km spatial resolution and a 2- to 3-day repeat cycle. The antenna technology to support such a mission needs to be pursued.
Improved estimates of water contained in seasonal snowpacks should be developed. NASA's post-2002 plans for an exploratory cold seasons/regions process observing mission, aiming for higher resolution, global estimates of snow water storage, should be carried forward. A global capability should be advanced to estimate, in near -- real time, the discharge of major rivers at their mouths and at key points within the continents; these goals would be achieved by NASA's proposed Hydrologic Altimetry Satellite (HYDRA-SAT) mission.
Land-Ocean-Atmosphere Interactions. Field campaigns and intensive observation programs to better understand interactions among land, ocean, and atmosphere are needed to isolate the effects of fast and slow processes in the hydrological cycle. Enhanced field campaigns should take place over multiple years to observe large-scale surface conditions, surface fluxes, and atmospheric variables. These large-scale observations would be supplemented with simultaneous observations of the slower components of the land system, such as groundwater levels.
Nested basin studies should be conducted in three to five river systems that exhibit different land cover, levels of human disturbance, and regulation, to characterize and improve understanding of linked water, C, and N transport and transformation processes. Studies on both terrestrial and aquatic ecosystems should be part of the program. Basins should be selected over a range of bio-hydro-climatic conditions (water-limited, energy-limited, and nutrient-limited systems) so that models can be adequately pushed and tested.
Coupled Land-Atmosphere Models. The development of coupled land-atmosphere models should be accelerated through the better use of data assimilation techniques. One existing vehicle for this development is the new U.S. multiagency initiative known as Land Data Assimilation System, or LDAS. LDAS should be supported and expanded to include data representing snowpack and high-latitude glaciers. Studies should examine whether two-way land-atmosphere coupling or climate modulation by local hydrologic processes results in predictability that can be exploited through coupled modeling. For seasonal and longer lead prediction of water fluxes, a modeling strategy must be developed to minimize the propagation of uncertainty among the components of such predictive models.
Data at high spatial and temporal resolution will be required to link global, coupled ocean-atmosphere models to an integrated system model that can produce predictions and associated uncertainty estimates suitable for use in water resources management decisions. Computational resources and observational data to initialize and verify the models should be supported. Process models should be developed of coupled water, carbon, and nitrogen transport and transformation in aquatic ecosystems and terrestrial water cycle components (e.g., in soil and groundwater) that can be tested against data from integrated databases and results of field studies. Model development and testing will also require focused, small-scale experimental studies to elucidate processes.
Quantifying Fluxes among Reservoirs. Quantifying fluxes among atmospheric, surface, and subsurface reservoirs must be a priority. Measurements should include surface water fluxes, water content, pressure, and temperature in the unsaturated zone, and water levels and temperatures in the saturated zone. Geophysical measurements using electromagnetic induction or ground-penetrating radar should be used to interpolate and extrapolate information between monitoring locations. Data on environmental tracers such as chloride, tritium, tritium/helium, and chlorofluorocarbons should be measured in the unsaturated or saturated zones to date the water for recharge estimation and to evaluate flow mechanisms. A national network of groundwater monitoring wells for both water level and water chemistry is essential for groundwater recharge characterization and the identification of long-term trends due to pumping, drought, and land use change.
Coordinating Science and Water Resource Management. A knowledge transfer initiative should be designed to integrate users needs into the development of the research agenda and to ensure that research results are provided in a form useful for users. Estimates should be developed of the natural variability of surface hydrological processes that can be incorporated into water resource systems design and management, with reduced dependence on historical observations. Ensemble forecast products for operating water resource systems should be produced, with a primary focus on reservoir systems (or, in some cases, free-flowing rivers), but with implications for groundwater in systems that conjunctively use surface water and groundwater.
Addressing Water-Related Disasters. Ocean-land-atmosphere interactions are critically important in understanding how water-cycle calamities may arise. A substantial effort must be made to better understand the phenomena that give rise to major departures in the behavior of centers of deep tropical convection, and therefore lead to persistent anomalies in global circulation, moisture transport, and thus large area droughts and floods. Enhanced global ocean observations and coordinated field campaigns should be used to study changes in heat and water fluxes between the surface and the global atmosphere that directly impact the global water cycle and continental hydrologic processes.
Pillar Initiative 3. Develop scientifically based capacity to predict the effects of changes in land use, land cover, and cryospheric processes on the cycling of water and associated geochemical constituents.
An important hypothesis has been advanced about human impacts on water resources, namely, that changes in land and water use (through, e.g., irrigated agriculture, deforestation, and urbanization) are increasing rates of water cycling through terrestrial reservoirs, altering storage in these reservoirs, and making water resources increasingly vulnerable to extreme events. Cryospheric processes, which can be considered ephemeral changes in land cover, are critically important to water resource issues; for example, snowmelt is the primary source of runoff in the western United States. Cryospheric processes also have important effects on the cycling of water and energy between land and atmosphere.
Comprehensive data sets should be assembled to evaluate the relationships between land cover change and the surface water cycle. This activity should draw on existing efforts to characterize land cover changes using satellite and other data sources, but would be linked to information about the land surface water cycle in both managed and natural environments. A program of enhanced, sustained observations of key state variables should evaluate statistical relationships and physically based models for land cover and water movement at the land surface. Numerical modeling should evaluate water resource susceptibility to climate variability and land use and land cover changes and to changes in processes related to snow and ice dynamics. Specific research priorities under this initiative include the following:
Surface Flux Networks. Existing surface flux networks to measure water, energy, carbon, and nitrogen fluxes should be expanded to include more sites and to obtain a complete suite of measurements on surface heat, radiative fluxes, and hydrologic state variables (including soil moisture) sufficient to close the local energy balance. A rotating sub-network should be implemented to expand the range of land cover types and hydroclimatic conditions represented. Evaporation over the ocean also needs to be monitored regularly rather than as part of limited field experiments. Evaporation should be simulated correctly for specific sites over land and ocean. The USGS stream-gauging program should be strengthened in areas critical to estimating water and biogeochemical transport within and from continents. Strategic augmentation of existing streamflow and water quality monitoring stations should be planned to help estimate the movement of C and N as well as nutrients and other dissolved and suspended constituents, with particular focus on rivers draining into estuaries that have experienced hazardous algal blooms in the past decade. Advanced technology should be imported and new sensors developed to improve in situ monitoring of water flows and concentrations of dissolved and suspended constituents. The detectors developed would be useful in a wide range of routine water quality studies and should include sediment monitoring.
Land Hydrology Validation Sites. A set of global land hydrology validation sites should be established, at which continuing observations of surface moisture and energy fluxes would be collected, along with data on subsurface moisture (in both saturated and unsaturated zones). The data should be collected over closed catchments large enough to allow closure of the surface water budget. These continuing observations should be supplemented by periodic rotating field campaigns, which would integrate surface, aircraft, and satellite observations.
Cold Seasons Research. A cold seasons initiative should be implemented, including (1) retrospective data analysis over a range of spatial scales -- subcontinental, continental, and global; (2) model experiments to help isolate linkages among components of the energy and water cycles; and (3) field experiments. The last would cover spatial scales relating not only to cold season process effects on moisture storage at the land surface, but also to larger scale, land-atmosphere interactions. These interactions would be associated with the roles, for instance, of snow presence/absence on albedo, frozen surface processes on land-atmosphere turbulent energy transfer, and riverine runoff on the circulation of large water bodies like the Arctic Ocean.
Larger Scale Experiments. Large- and basin-scale experiments should be carried out to effectively improve model representations of the relevant processes, to estimate model parameters, and to validate model simulations and predictions. The experiments should evaluate fluxes between hydrologic reservoirs, as through evapotranspiration, recharge, and surface water -- groundwater interactions in watersheds with different land cover types. The studies should be integrated with related work to characterize and improve understanding of linked water, C, and N transport and transformation processes, and should be incorporated in process models of coupled water, carbon, and nitrogen transport and transformation in aquatic ecosystems and terrestrial components of the hydrologic cycle.
Model Testing Facilities. Model testing facilities should be established at existing weather and climate prediction centers (like NCEP), which would be charged with facilitating model evaluation and the transfer of methods from the general research to the operational modeling community and vice versa. These facilities should promote standardized flux couplers and interfaces, standardized archiving, and other technical innovations (like visualization and parallel software structures) that would enhance the ability to use the facilities' models and data streams for model development.
Water Cycle Science and Mathematics. A new program is needed in the science and mathematics of water cycle predictability to guide applications of atmospheric and hydrologic theories over a broad range of space and time scales. Climate predictions on seasonal and longer time scales must be made within a probabilistic framework that takes into account the uncertainty of initial and boundary conditions, as well as the inherent characteristics of the distribution of possible states that may ensue from the given initial state. Research is required to place current ad hoc methods of producing ensemble model predictions on a firmer theoretical basis.
Modeling Vegetation. The past successes of including vegetation functional controls on surface water and energy balances over meteorological time scales should be followed with efforts to handle the vegetation's slower, structural responses to changes in climate and land use. Because these changes in vegetation (notably, structure, density, and species distribution) affect water cycling, they must be dynamically included in models to accurately understand and predict water cycle behavior over the longer time scales in which vegetation change. Analysis of the pathways (carbon, water, and energy exchange) through which a changing climate interacts with a dynamic biosphere will support model development that integrates atmospheric forcing, land surface mass and energy fluxes, and vegetation dynamics.
Emerging methods show promise for rapid improvements in predicting water cycle variability over the critical seasonal to interannual and longer time scales, and regional to continental space scales. These new methods include observations of variables that define the global water cycle, continual advances in modeling capabilities, and developments in the theory used to describe coupled processes involving nonlinear feedbacks. The application of new measurement technologies and modeling methods to water cycle processes will permit greatly enhanced applications of science to a myriad of societal problems related to water resources. Advances in water cycle predictive capabilities can also be used to inform decisions on land management and management of chemicals such as fertilizers.
Water cycle science must proceed along three complementary tracks -- observation, modeling, and process studies. Program elements in these general areas form the backbone of the integrated science plan. Another integral element of this plan is a formal and visible knowledge transfer program, one that fosters participatory, interactive research involving researchers, decision makers, resource users, educators, and others.
The management of water resources in the United States requires a fully integrated knowledge base derived from a broad mix of disciplines including not only the natural sciences but also the fields of law, economics, sociology, and political science. The approach taken in this study has identified a number of issues based on current state of scientific knowledge and has recommended actions to address these issues through science initiatives and knowledge transfer. However, as new water problems emerge and a more integrated view of management and science evolves, opportunities will certainly arise for climate and hydrologic information to benefit society through more holistic approaches to these problems. To address these future opportunities fully, plans should be developed for a wide-ranging integrated program, encompassing research on social, legal, economic, and political issues, as well as issues in the natural sciences.