MANTIS student Ahmed Omar recently defended his dissertation proposal, titled “Modeling Groundwater and Streamflow Dynamics across Heterogeneous and Structurally Complex Aquifers in Central Texas: A Remote Sensing and AI Approach.” His research addresses the challenges of managing hydrologically connected surface-water and groundwater systems within Texas’s divided regulatory framework. The proposed study integrates remote sensing, machine learning, deep learning, GIS, and explainable artificial intelligence to identify controls on groundwater levels, reconstruct missing groundwater observations, and improve groundwater and streamflow forecasting. The research will also examine how large-scale climate patterns influence streamflow and groundwater dynamics in the karst-influenced Blanco River Basin.