60 https://www.uni-bremen.de/en/umweltgeophysik/forschung/projekte/hydrogeoml Project HydroGeoML en University of Bremen Thu, 18 Jun 2026 15:47:32 +0200 Thu, 18 Jun 2026 15:47:32 +0200 University of Bremen content-654277 Fri, 06 Mar 2026 14:01:31 +0100 https://www.uni-bremen.de/en/umweltgeophysik/forschung/projekte/hydrogeoml#c654277 <p>Groundwater is a vital source of fresh water, heavily stressed by overuse and climate change. Accurately estimating groundwater recharge is crucial but difficult. This project presents a novel hydrogeophysical approach that combines geoelectrical monitoring, hydrological modeling, and machine learning:</p> <p>Key points of the project:</p> <ul> <li><strong>Problem:</strong> Increasing stress on groundwater resources and high uncertainty in groundwater recharge estimation.</li> <li><strong>Solution:</strong> Development of a hydrogeophysical approach based on geoelectrical monitoring, hydrological modeling, and machine learning.</li> <li><strong>Methods:</strong> <ul> <li>Development of a hydrogeophysical inversion approach to estimate hydraulic conductivity and spatially resolved recharge rates.</li> <li>Investigation of machine learning approaches for efficient estimation of hydraulic conductivities.</li> <li>Application of optimized survey techniques to improve spatial resolution.</li> </ul> </li> <li><strong>Validation:</strong> The approaches will be tested and evaluated using synthetic models, laboratory experiments, and real field data.</li> <li><strong>Goal:</strong> Provision of spatially resolved, accurate estimates of groundwater recharge rates to improve the management of groundwater recharge facilities.</li> </ul> <p>This project aims to develop innovative methods to support the management and optimization of groundwater resources through more precise information on groundwater recharge.</p> Content