One of our high impact activity (HIA) involved studying the use of machine learning (ML) algorithms for downscaling remotely sensed Earth observation data. In a world increasingly affected by climate change, there's a pressing requirement for high-resolution, continuous hydrological data to facilitate sustainable water management and predict water-related trends. The Gravity Recovery and Climate Experiment (GRACE) mission, since its launch in 2002 and its successor, GRACE-FO, has indeed transformed hydrological monitoring. By measuring the variations in Earth's gravity field, it provides crucial data on terrestrial water storage (TWS). Despite limitations in spatial and temporal resolutions, GRACE has proven invaluable in studying changes in groundwater storage and aiding in formulating long-term water management strategies.
Key issues threatening the MRVA include:
• Since the late 1920s, water levels decreased by nearly half of its thickness
• Led to reductions in the baseflow of streams connected to the aquifer
• Formation of cones of depression in some areas, altering groundwater flow and potentially causing up-coning of brackish water
• Increased chloride concentrations in the aquifer, affecting water quality
