The overall state of surface water and groundwater systems in the Great Lakes Basin (GLB) remains insufficiently understood to accurately predict water storage and flow across the region. A USGS assessment of GLB science needs (Carl et al. 2021) concluded that limited groundwater quantity and quality information is available to support water-resource management, and that groundwater’s role in the Great Lakes system is largely unknown. Climate change is increasing hydrologic variability, while demands for water for drinking, agriculture, and industry continue to grow. Improving estimates of water storage and movement from the land to the coasts is therefore essential. As part of a broader effort to develop an integrated surface-groundwater hydrologic model for the GLB, this work focuses on monitoring inundation and groundwater dynamics using satellite remote sensing. We present a novel approach for measuring inundation and estimating groundwater level fluctuations across the basin every 12 days using synthetic aperture radar (SAR) observations. Surface water and wetland extent derived from Sentinel-1 SAR growing-season data (April–October, 2016–2025) are mapped and combined with high-resolution LiDAR elevation models in a wetland connectivity framework to infer groundwater elevations. The resulting surface water, inundation and elevation datasets are openly available through a web viewer to support coastal monitoring and GLB hydrologic model development and calibration.
