EPSCoR Research Fellows: NSF: Enhancing Water Budget Simulations across CONUS: Modeling Vegetation Uptake of Rock Moisture
- Institution
- Regents of the University of Idaho, ID
- Principal investigator
- Meng Zhao
- Funding
- $300K
- Duration
- 2025–2027
Moonbase score
Still being scored
Abstract
Accurate water resource predictions are critical for the nation’s water security, especially during extreme events. Today, communities are experiencing increasingly frequent floods and droughts, heat waves, and wildfires, all of which will impact vegetation behaviors and drive land use/cover changes. As such, predicting the resulting impacts on water budget components is fundamental to enhancing the nation’s preparedness for water-related hazards and water scarcity under a changing climate. However, virtually all land models ignore a substantial volume of plant-available water stored in unsaturated, weathered bedrock. This oversight can lead to biased predictions of ecosystem water consumption and downstream water budget components, jeopardizing the nation’s water-food-energy security. The research objective of this proposed project will be to directly address this knowledge gap by implementing an innovative approach within the Community Land Model Version 5 (CLM5) to represent vegetation's uptake of rock moisture and subsequently evaluate its impact on water budget simulations across the continental U.S. (CONUS). This fellowship will enable the PI to establish a mentor-mentee relationship with Dr. Sean Swenson, a prominent hydrologist and core developer of CLM5, and to receive specialized training and access to state-of-the-art land modeling equipment at the National Center for Atmospheric Research (NCAR). Specifically, the PI proposes that modeling plant access to rock moisture will refine simulations of water budget dynamics. To investigate this hypothesis, the PI will visit NCAR for two summers, where Dr. Swenson will mentor the PI in advanced techniques for modifying land models, focusing on CLM5—a leading-edge land model widely used to study the role of land in climate and weather. To enable vegetation water uptake from the weathered bedrock layer, this fellowship project will truncate the root profile by the position of the unweathered bedrock, which will stimulate root growth into the hydrologically active bedrock layer and account for the ability of the vegetation to extract water stored in weathered bedrock. The team will run the original CLM5 and the rock moisture configuration with the same forcing data. Then, they will compare the performance of the two models, assessed by their accuracy in simulating observations of evapotranspiration and streamflow, as well as their responses to climatic extremes. This collaborative endeavor will advance the understanding of land-atmosphere interactions and improve the predictive capabilities of land models, ultimately contributing to more accurate assessments of water availability and environmental resilience across the CONUS. The broader impacts of this fellowship will be further extended through installing CLM5 on Idaho’s supercomputer, organizing a workshop for academic professionals and students, and crafting a hands-on CLM5 course. Together, these efforts will enhance Idaho’s hydroclimate modeling infrastructure, enhance research capabilities, empower STEM researchers and students, and elevate Idaho’s standing in national research endeavors. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
LOADING MOONBASE SCORE
Questions for Regents of the University of Idaho
Answered by the team behind this research.
No questions yet. Sign in to ask the first one
Related grants
Same institution, same topic, scored first.
- NSF · Regents of the University of Idaho52
EPSCoR Research Fellows: NSF: Heterogeneous Integration of Wide Bandgap Semiconductor Chips for High Temperature Applications
Feng Li · $300K · 2025–2026
- NSF · Regents of the University of Idaho43
FET: EAGER: Physics-Informed AI-Models for Efficient Computation of Stochastic Electromagnetic Fields in Realistic 3D Nano-Scale Optical Interconnects
Ata Zadehgol · $300K · 2024–2026
- NSF · Regents of the University of Idaho41
Collaborative Research: RII FEC: Transforming wastes Into Economic Assets for Sustainability, Resilience, and Prosperity by a Novel Negative Emission Technology
Armando G Mcdonald · $1.0M · 2024–2028