Water resources are essential provisioning services in Hawaii. Because of its unique location and geology, water issues in Hawaii are tightly connected with climate and geology. In view of increasing climate variability and extreme weather events such as flooding and drought, a meteo-hydrological model is needed to advance our understanding of the water cycle and better predict and manage future availability of water resources. This fellowship will establish collaboration between the university and national research laboratory to address water issues that contribute to both economic (e.g., resources and food production) and security (e.g., flood and drought prediction and assessment) in the state. This proposal will support an early-career female minority faculty on tenure-track to establish a new research direction in meteo-hydrological modeling, and will support a female Ph.D. student for training integral to her dissertation project at the UHM. The established meteo-hydrological model will become a new skill set and tool for PI Tsang to collaborate with researchers within and outside of the university and tackle statewide food, water, and energy issues. Both university and the state of Hawaii will benefit from having a large scale meteo-hydrological model and the capacity to tackle the statewide economic, agricultural, environmental challenges.
This NSF EPSCoR RII Track-4 fellowship will support training opportunities for PI Tsang in meteo-hydrological modeling skills and initiate a new and long-term collaboration between the University of Hawaii at Manoa (UHM) and the National Center for Atmospheric Research (NCAR), at Boulder, CO. This project will expand PI Tsang's current research by allowing her to incorporate advanced atmospheric model information to study complex hydrological systems in Hawaii. By working with the experienced Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro) development team at NCAR, PI Tsang will be able to establish a next-generation hydrological model for the state of Hawaii. During the fellowship, this collaboration aims to 1) incorporate finer resolution meteorological data to the model and 2) improve the representation of groundwater contribution to baseflow in the model. This model, WRF-Hydro-Hawaii, will have the capacity to couple weather information from climate models to provide higher spatial and temporal resolution in describing the hydrological responses, such as streamflow and flood forecasting, in Hawaii. The WRF-Hydro-Hawaii model will also be configured to run on the High Performance Computing (HPC) cluster at UHM. PI Tsang's research group will continue the model development, contribute improved modules to the WRF-Hydro modeling community, and apply WRF-Hydro-Hawaii beyond flood forecasting to include water availability for food production and issues on natural resources and environmental management. The newly developed modules of refined rainfall-pattern representation and groundwater-surface water interaction will contribute to the improvement of WRF-Hydro that applies to other tropical islands and continental systems.
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.
