Professor in Hydrology and Data Science
Ghent University
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The Department Environment seeks to appoint a full-time ZAP-TT profile in Hydrology and Data Science, with a primary focus on high-quality research and education, complemented by optional contributions to societal engagement. The position aims to strengthen and expand H-CEL’s research heritage, focusing on the development of innovative tools and data-driven methods to improve the monitoring and forecasting of hydrologic states and fluxes. Such advances are essential for ensuring the efficient and sustainable use of water resources in the face of global challenges such as floods, droughts, and increasing water demand.
The envisaged research bridges hydrological process monitoring, process understanding, hydrological and/or land surface modelling, groundwater modelling, machine learning, and (big) data analysis, with a strong focus on the use of Earth Observation (EO) data to quantify Essential Climate Variables (ECVs) relevant to hydrology, such as soil moisture, land evaporation, terrestrial water storage, groundwater, and river discharge. Microwave sensors, in particular, offer unique sensitivity to water and are of crucial importance for observing hydrological processes across scales.
Both satellite and in-situ observations are becoming increasingly abundant and form an essential basis for validating and refining model predictions. Advanced data assimilation techniques are designed to account for uncertainties in both models and observations. When these uncertainties are properly considered, integration of both EO and in-situ data within such techniques enables improved predictions of water availability and hydrologic extremes. Despite major progress over the past decades, important research challenges remain: both satellite and in-situ observations are often limited by spatial and/or temporal resolution, while hydrological and land surface models embed processes defined at different scales. Current models also remain uncertain regarding droughts, as they insufficiently represent groundwater flow and groundwater–surface water interactions. Overcoming these scaling inconsistencies, alongside optimizing process representations, constitutes one of the key future challenges that H-CEL aims to address in developing the next-generation monitoring and forecasting systems. In doing so, H-CEL aims to maintain its primary focus on Earth Observation, with the ambition to consolidate and further strengthen its internationally recognized expertise in the use of EO data for hydrological modelling.
The rapidly growing data landscape opens new frontiers for hydrology. Expanded satellite programs such as ESA’s Sentinel missions and recently-launched or upcoming platforms including BIOMASS, NISAR, ROSE-L, and CIMR will deliver richer and more diverse observations. Leveraging these data through innovative analytical and computational approaches will enhance hydrologic process understanding, model representation, and data assimilation techniques. This process understanding is essential to integrate data in a physically consistent way into models and to support and achieve water management objectives. Ultimately, such integrative approaches will enable more reliable predictions and provide the process understanding needed to design and evaluate measures that foster sustainable and climate-resilient water management at local and regional scales.
The profile is expected to establish a research cluster within H-CEL, which complements the existing clusters on Hydrology and Climate and Hydrology and Water Management. While new directions are encouraged, sufficiently strong connections with ongoing and recently initiated activities within the lab should also be maintained. Given the number of active projects to be (co-)led, experience in project coordination and team leadership is highly valued. To facilitate continuation of ongoing activities, a contribution is expected to the (co-)supervision and coordination of several running projects involving remote sensing of ECVs (more specifically, soil moisture, vegetation water content and snow water equivalent).
The position also involves the (co-)supervision of ongoing PhD and postdoctoral research (currently five PhD candidates and one postdoctoral researcher), and the further development of international collaborations, as well in support of existing partnerships with as well space agencies, universities and research institutes as through the initiation of new research alliances.
The profile will contribute to the teaching provided by the Department of Environment, with responsibilities related to (eco)hydrological processes, hydrological modelling, and remote sensing applications in hydrology. The position also includes the supervision of Master’s and Bachelor’s theses, ensuring that students are actively involved in current research themes and exposed to innovative developments at the interface of hydrology and data science.
Beyond research and teaching, the profile stimulates active participation in institutional and societal engagement. At the institutional level, this involves supporting the operation of the educational programs on environmental management. At the societal level, the profile is encouraged to engage in knowledge transfer and policy-relevant collaboration. This may include contributions to governmental projects or advisory roles in the field of water resources management, especially related to the monitoring and prediction of hydrologic extremes (droughts and floods), and collaboration with space agencies (e.g., ESA) and European institutions (e.g., the European Commission, Copernicus) to provide scientific guidance and recommendations on hydrologic monitoring and prediction, supporting the efficient and sustainable use and management of water resources.