GROUNDWATER DEPLETION AND SUSTAINABILITY IN MERCED COUNTY, CALIFORNIA: ANALYZING CURRENT TRENDS SCENARIOS USING GIS TOOLS

Abstract

Merced County, California, located in the drought-prone Central Valley, relies heavily on groundwater to support its agricultural economy. This study estimates groundwater storage at the county level by integrating satellite-based remote sensing data with in situ well observations using geographic information systems (GIS) technology. Key datasets include the Gravity Recovery and Climate Experiment (GRACE) for terrestrial water storage anomalies, the Global Land Data Assimilation System (GLDAS) for soil moisture and snow water equivalent, and the Moderate Resolution Imaging Spectroradiometer (MODIS) for surface water detection. In situ groundwater level measurements from monitoring wells were used to validate and supplement satellite-based estimates. Coarse-resolution global datasets were downscaled using statistical interpolation and resampling methods to produce finer spatial outputs suitable for local analysis. Groundwater storage anomalies were derived by subtracting surface and subsurface components from total water storage. A multi-step processing workflow addressed spatial misalignment, temporal gaps, and scale mismatches across datasets. Results demonstrate that combining remote sensing with in situ data improves the spatial and temporal resolution of groundwater storage estimates. This integrative approach supports local water resource planning by offering scalable methods for tracking groundwater trends in data-limited regions.