Abstract: Groundwater supports over one-third of the global population and provides 42% of the agricultural water supply. In mountain-valley aquifer systems, where mountains supply more than 50% of downstream water, intensifying droughts threaten the long-term sustainability of valley-fill aquifers. However, characterizing groundwater recharge in high-elevation critical zones remains challenging due to complex hydrogeology and a lack of subsurface observations. To address these challenges, combining data-driven approaches with process-based hydrologic modeling is essential. In this talk, I address several central bottlenecks in large-scale hydrologic modeling—data scarcity, reconciling observations across disparate spatial and temporal scales, and high computational demands—and demonstrate how computer science can bridge these
gaps.
Bio: Dr. Hoori Ajami is a Professor of Groundwater Hydrology in the Department of Environmental Sciences at the University of California, Riverside. Her research focuses on characterizing surface water–groundwater–atmospheric interactions in mountain-valley aquifer systems, developing computationally efficient hydrologic models, and applying remote sensing and isotopic data to characterize the hydrologic cycle. She received her Ph.D. in Hydrology from the University of Arizona and was a postdoctoral fellow at the University of New South Wales, Australia, prior to joining UCR.
Abstract: Groundwater supports over one-third of the global population and provides 42% of the agricultural water supply. In mountain-valley aquifer systems, where mountains supply more than 50% of downstream water, intensifying droughts threaten the long-term sustainability of valley-fill aquifers. However, characterizing groundwater recharge in high-elevation critical zones remains challenging due to complex hydrogeology and a lack of subsurface observations. To address these challenges, combining data-driven approaches with process-based hydrologic modeling is essential. In this talk, I address several central bottlenecks in large-scale hydrologic modeling—data scarcity, reconciling observations across disparate spatial and temporal scales, and high computational demands—and demonstrate how computer science can bridge these
gaps.
Bio: Dr. Hoori Ajami is a Professor of Groundwater Hydrology in the Department of Environmental Sciences at the University of California, Riverside. Her research focuses on characterizing surface water–groundwater–atmospheric interactions in mountain-valley aquifer systems, developing computationally efficient hydrologic models, and applying remote sensing and isotopic data to characterize the hydrologic cycle. She received her Ph.D. in Hydrology from the University of Arizona and was a postdoctoral fellow at the University of New South Wales, Australia, prior to joining UCR.