Advancing predictive understanding of how dominant processes controlling watershed hydro-biogeochemical function operate under a range of hydrologic regimes and vary along stream networks that drain heterogeneous land covers
- Principal Investigator: Eric Pierce
- Annual reports: 2023
Watersheds are complex systems that provide important ecosystem services. These systems supply freshwater resources for energy production, irrigated agriculture, industry, human consumption, and other ecosystem services. The economic and societal importance of watersheds—and their vulnerability to environmental stresses—is exemplified in the southeastern region of the United States.
The southeastern region of the United States, which includes the Tennessee and South Atlantic–Gulf States water resource regions, comprises large areal-extent coastal and inland low-lying areas, elevated plateaus and highlands, numerous high-growth metropolitan areas, and substantial rural expanses. Furthermore, the southeast region is a North American biodiversity hotspot and home to numerous biologically diverse ecosystems.
The Tennessee River Basin in the southeastern United States is the most intensively used freshwater water resource region in the contiguous United States, supporting approximately 4.5 million people with estimated withdrawals of more than 280,000 gallons per day per square mile. Water resources in the Tennessee River Basin and broader southeastern region are vulnerable to changes in land use and land cover and a range of climate-induced disturbances. Projections indicate that the southeastern United States will experience higher temperatures, more extreme heat events, and an intensifying hydrologic cycle with more frequent and severe storm and drought events over time. The impact of these disturbances is exacerbated by existing regional socioeconomic stressors and inequalities.
To address these changes, the Watershed Dynamics and Evolution (WaDE) Science Focus Area (SFA) at the U.S. Department of Energy’s (DOE) Oak Ridge National Laboratory (ORNL) will advance predictive understanding of how dominant processes controlling watershed hydro-biogeochemical function operate under a range of hydrologic regimes and vary along stream networks that drain heterogeneous land covers.
SFA Knowledge Gaps
- Process-Based Understanding of Land Cover Effects on Watershed Function. Researchers do not understand if and how or at what scale land cover influences the generation and export of water and solutes from the landscape to the stream network and how this affects local and emergent hydro-biogeochemical function within the stream network.
- Process-Based Understanding of Hillslope–Catchment Interactions. Researchers do not fully understand what controls upland-stream interactions and how these interactions vary under different hydrologic regimes and land covers.
- Process-Based Understanding of Integrated Measures of Watershed Function. Researchers have an incomplete understanding of how measures of stream function, such as stream metabolism, integrate complex watershed properties that vary in space and time.
- Stream Observational Networks in the United States. Existing observational networks are skewed to higher-order streams and underrepresent low- to mid-order streams.
- Watershed Observational Networks in the United States. The watershed science community has largely focused on end-member systems—forested, agricultural, and highly urbanized—and researchers currently lack sufficient observations in watersheds with heterogeneous land cover.
- Integrated Modeling. Model predictions of watershed function at basin- or continental United States–scales under changing climate scenarios are uncertain because mechanistic understanding of how key processes depend on land cover and hydrologic regimes is incomplete.
Organization and Progression
To advance watershed science, it is necessary to develop a systematic framework that explicitly links local physical–chemical–biological heterogeneity to larger spatial organization. Research efforts over the next 9 years will be on three watersheds, studied in succession, with the goal of systematically translating, applying, and refining the process understanding and modeling capabilities gained from a specific watershed to increasingly disparate systems.
All three watersheds will be of similar mid-order size, with heterogeneous land cover, and located in areas experiencing rapid land cover change within the Tennessee River Basin.
- Phase 1 (FY 2023–2025): Researching Watershed 1
- Phase 2 (FY 2026–2028): Research will focus on Watershed 2
- Phase 3 (FY 2029–2031): Research will focus on Watershed 3
The WaDE SFA is organized around three integrated research themes and a crosscutting modeling activity that together create a multiscale, model–observation–experiment framework to enable hypothesis-driven research addressing the knowledge gaps.
Collectively, this framework will advance a deeper, predictive understanding of the hydro-biogeochemical processes and feedbacks that control solute mobilization and export from headwater catchments with heterogeneous land cover (Theme 1), resultant feedbacks between flow, solute concentrations, and stream function in stream corridors (Theme 2), and the emergent patterns in stream metabolism at network scales (Theme 3).
- Theme 1: Dynamic Headwaters
- Theme 2: Stream Corridor Processes
- Theme 3: Network Function
- Modeling Crosscut: Virtual Watershed
Collaborative Science and Alignment with Grand Challenges
This multidisciplinary, multi-institutional program led by ORNL spans seven partner institutions and takes advantage of expertise in environmental subsurface science, climate change science, biological systems science, ecohydrology, hydrology, computational science, and world-class high-performance computing facilities. The research proposed for the WaDE SFA will directly contribute to three of five grand scientific challenges—integrated water cycle, biogeochemistry, and model-data integration—developed by the Biological and Environmental Research (BER) Program’s Earth and Environmental Systems Sciences Division.