PhD on Hydrological model-data interaction and machine learning for headwater catchment analyses

The Hydrogeology research group at the Department of Environmental Sciences of the University of Basel is offering a fully funded PhD position within the international ANR–SNSF project FutureFlow.

Headwater catchments form the uppermost parts of river networks and represent a substantial fraction of the European hydrological system. Although relatively small, they play a critical role in controlling water resources and sustaining downstream ecosystems. Their functioning is largely governed by the aquifers they host, which regulate water storage and release to streams, sustaining flows during dry periods and buffering climatic variability.
Despite their importance, headwater systems remain poorly understood and difficult to predict, due to complex interactions between geology, topography, and climate, and limited observational data. In the context of increasing droughts and pressure on water resources, this lack of understanding limits our ability to anticipate future changes and design management strategies. Addressing these challenges requires new modelling approaches capable of representing groundwater processes across large and diverse catchments.
The FutureFlow project proposes to transfer concepts from software engineering-such as multi-fidelity modelling and adaptive model selection (model switching)-to hydrology. The objective is to develop flexible and scalable modelling frameworks capable of selecting, combining, and calibrating models of different complexity, to better represent groundwater dynamics and improve predictions at the European scale under climate change.