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

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

University of Basel ranks among the world’s one hundred best universities and boasts a top‑ten place among German‑speaking universities.

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 Future Flow.

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 Future Flow 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.

This project will advance multi‑fidelity modelling approaches tailored to headwater systems and deliver new insights into groundwater‑surface water interactions. A key challenge for hydrological headwater catchment analyses lies in characterising and predicting their hydrological functioning, and this is fundamentally related to the fact that the majority of them are unmonitored and their hydraulic parameters unknown. The objective of this PhD project is to bridge this gap and develop data‑driven, machine‑learning‑based approaches to identify the governing hydraulic parameters of headwater catchments, hind‑ and forecast their stream and groundwater outflows, and to understand their susceptibility to extreme hydrometeorological conditions based on storyline approaches.

• Contribute to the development of the multi‑fidelity modelling platform Hydro Mod Py ,
• Implement machine‑learning based approaches to estimate hydraulic properties across the headwater catchments of Europe,
• Evaluate hydrological validation approaches for headwater catchment properties identification,
• Implement hybrid‑modeling approaches to hind‑ and forecast the hydrological behaviour of ungauged headwater catchments using climate storylines

The outcomes of this project will support both the scientific community and practitioners by improving the assessment and prediction of hydrological responses to climate change.

• MSc in Hydrology, Hydrogeology, Data/Computer Science or a related field,
• Strong interest in environmental data analysis and/or numerical modelling,
• Proficiency in Python programming,
• Fluency and excellent writing skills in English, with a strong interest in scientific and public communication.

The project brings together a consortium of leading European institutions, including the University of Neuchâtel, University of Rennes 1, CNRS, BRGM, ENS Paris, Eawag and the University of Basel. The successful candidate will be part of a cohort of 4 PhD students, 2 research engineers, and 7 principal investigators, working collaboratively across partner institutions. The project will be supervised by Prof.

Oliver S. Schilling
, Head of the Hydrogeology Research group at the University of Basel, and co‑supervised by Prof. Clément Roques
, Université de Neuchâtel. The position is based at the…