Accessible probabilistic modeling of wellhead protection areas for small and medium-sized water supplies

Groundwater supplies nearly half of the global population with drinking water but faces increasing contamination risks. Delineating Wellhead Protection Areas (WHPAs) is essential for safeguarding groundwater quality, yet uncertainty in subsurface parameters complicates this process. Here we present a practical probabilistic workflow combining Monte Carlo simulation with the Analytic Element Method, implemented within an open-source Python framework. This method generates an ensemble of capture-zone realizations by incorporating parameter uncertainties through repeated simulations, with results visualized via GIS tools and summarized as percentile-based WHPA envelopes. Applied to a Swedish aquifer case study, the approach aligns well with deterministic numerical models while better capturing variability. In rural and semi-rural settings, the workflow can serve as a first screening step by showing how uncertainty changes the extent of the WHPA and which surrounding land uses may be affected under different precautionary delineations. By making uncertainty-aware WHPA delineation accessible to small and medium-sized water suppliers with limited resources, this method supports improved groundwater protection and aligns with emerging legislative requirements for risk-based water source management.