Water Resources Research Act Program

Details for Project ID 2021NM004G

Closing the Supply-Demand Gap for Sustainable Water-use Under Climate Change: Impacts using Remote Sensing and Artificial Intelligence

Institute: New Mexico
USGS Grant Number:
Year Established: 2021 Start Date: 2021-09-01 End Date: 2024-08-31
Total Federal Funds: $249,979 Total Non-Federal Funds: $249,979

Principal Investigators: Hatim M. E. Geli

Abstract: The arid to semi-arid region in southern New Mexico (NM) where the Rio Grande Project (RGP) is located normally experiences limited water supply condition. The RGP is an interstate transboundary project that connects NM, Texas, Mexico through water releases and allocation agreements. These normally dry conditions have been exacerbated with recent prolonged and persistent drought conditions that is expected to only worsen due to projected climate change impacts. Water demand in the RGP is driven by the socioeconomic and livelihood needs of its community that heavily relies on agricultural production systems and the interconnected surface-groundwater hydrological systems. Based on the recent past drought events and the projected climate change impacts, the gap between supply and demand is only expected to widen. Focusing on the agricultural production system, there is a need to identify water and land management practices that can effectively enhance the sustainability of the water resources systems in the region and address the question of when and where these practices need to be applied. The proposed research will provide improved estimates of the water balance components of the RGP using an existing hydrological model that has already been calibrated for the RGP – the MF-OWHM coupled with remotely sensing ET product; couple this hydrological model with crop growth model to provide prediction of crop yield and water requirements for future climate projections until 2074; develop and evaluate the responses of this coupled model due to different water and land management scenarios using artificial intelligence; and constrain the identified scenario with a socioeconomic model that will be develop as part of the proposed research activities. We expect to provide a water supply-demand assessment framework that can be used farmers, water managers, and decision makers to identify regionally effective management practices.