Inverse problem and hydrogeophysical data integration


Frédéric Nguyen, Urban and Environmental Engineering, University of Liège, Belgium
Thomas Hermans, Department of Geology, Ghent University, Belgium
Peter Bayer, Institute of new Energy Systems (InES), Technische Hochschule Ingolstadt, Germany

Featured Speakers

Walter Illman, University of Waterloo, Canada
Marijke Huysman, Vrije Universiteit Brussel, Belgium
Troels Norvin Vilhelmsen, Aarhus University, Denmark


Our understanding of complex groundwater systems including the vadose zone and our ability to predict their evolution is fundamental to a variety of disciplines relevant for society, ranging from groundwater resources and environmental issues to sustainable energy use. Hydrogeophysics includes in addition to hydraulic, geological or soil data, geophysical data with a greater spatial coverage providing indirect information on the subsurface. Recent developments in measuring technologies allow collecting more detailed information over a wider area and greater temporal resolution. This pushes forward our ability to understand complex groundwater systems such as those involving seawater intrusion, geothermal systems, or biogeochemical systems, vital for researchers and decision makers.

Nevertheless, the integration of such data for predictive purposes can be tackled with different computational methods. The latter may include improved subsurface conceptualization and calibration using tomographic images or large-scale data, and automated inverse modeling/parameter estimation through sequential, joint, and coupled approaches following a deterministic or stochastic framework. Other key challenges reside on uncertainty analysis, rock physics, multi-phase flow and model complexity.

We welcome contributions addressing new developments or advances in hydrogeophysical data or images integration and inverse problems, conceptualization, or parameter space reduction, prediction focused approaches, and uncertainty analysis.

We also invite contributions showing applications in real-world case studies, or case studies that highlight the challenges and the demand of future research directions, in particular for complex systems.

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