Integrating Unconventional Approaches and Land-Climate Models for Improved Groundwater Recharge Estimation and Uncertainty Analysis in Flanders Under Climate Change

Groundwater quietly keeps our taps running, our crops alive, and our ecosystems thriving worldwide as well as in Flanders, yet its sustainability is threatened by climate change and overuse.

Reliable groundwater recharge estimation (as the main input to this system) is crucial for sustainable management, but conventional models yield conflicting results. This research enhances recharge estimation by integrating unconventional methods, process-based models, data-driven techniques, and land-climate models to improve accuracy and reduce uncertainty. A multi-method framework will compare methodologies across hydrogeological settings in Flanders, combining hydrological models, time-series analysis, remote sensing, and land-climate models.

A key innovation is integrating land-climate models with hydrological models to account for vegetation, evapotranspiration, and land-atmosphere interactions. This study provides improved recharge estimation, uncertainty quantification, and future projections to support sustainable groundwater management in Flanders under changing climate conditions.