Efficient Surrogate Modelling for Sustainable Management of Complex Seawater Intrusion-Impacted Aquifers

This project is a collaboration between the Universities of Sheffield (UK), Texas at El Paso (USA), and South Florida (USA).

CIV Mappin

This project is a collaboration between the Universities of Sheffield (UK), Texas at El Paso (USA), and South Florida (USA), and addresses the sustainable management of water resources in coastal regions with diverse geological, hydro-technical and governance settings under treats of climate change, sea level rise (SLR) and seawater intrusion (SWI). Pressures on water resources in coastal regions are already great and are expected to intensify due to increasing populations, standards of living and impacts from climate change and SLR. We will focus on coastal areas where aquifer over-drafting has caused SWI, thus deteriorating groundwater quality, and where SLR is expected to further reduce availability of fresh groundwater. Solutions to these problems will involve combinations of more efficient pumping schemes, demand reduction, and technological interventions such as desalination. However, determining optimal solutions for these problems poses extreme computational demands. This project will greatly advance the development and application of simulation-optimization by applying deep-learning techniques to the development of computationally efficient, robust, and accurate surrogate models for coastal groundwater systems.



Project Dates

Start Date : 01/10/2019
End Date : 31/05/2024

People Involved

Dr Domenico Bau

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