Résumé
Analyzing the spatio-temporal dynamics of groundwaters is crucial for a better understanding of the global hydrological and biogeochemical cycles, especially with climate change and the intensification of human activities. However, monitoring groundwaters is still complicated due to the lack of in situ data and the weak spatial coverage of these sites. Remote sensing is a good opportunity to address this problem. The method to study water level maps of the groundwater table is based on the use of a dense network of virtual stations produced using radar altimetry and surface water extent obtained by multispectral imagery. The interpolation of these two datasets allows us to produce minimum water level maps associated with the groundwater lebel base at a spatial resolution of 500 m from 2000 to 2022. First results show a link between groundwater anomalies and cumulative rainfall.