CBET-EPSRC: Efficient Surrogate Modeling for Sustainable Management of Complex Seawater Intrusion-Impacted Aquifers
Lead Research Organisation:
University of Sheffield
Department Name: Civil and Structural Engineering
Abstract
The overarching goal of the proposed research is the sustainable management of water resources in coastal regions with diverse geological, hydro-technical and governance settings. 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 sea level rise (SLR). We will focus on coastal areas where aquifer over-drafting has caused seawater intrusion (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 (SO) by developing computationally efficient, robust, and accurate surrogate models for coastal groundwater systems.
The limited literature on SO and surrogate modeling in SWI problems has focused on simplified hydrogeological settings and mathematical representations of management strategies. However, realistic SWI problems involve hydrogeological complexities, including discrete lithological facies, faults and fractures, saltwater-freshwater mixing zone dynamics, and surface-water groundwater interactions, as well as nonlinear objective functions and continuous and discrete decision variables to represent a wide range of engineering components. We hypothesize that these hydrogeologic and management features determine the building of accurate and efficient surrogates; and accurate surrogate SO models for SWI problems can be at least an order of magnitude faster than full-scale models. The reduced computational cost allows to investigate a broader range of SLR and climate change impacts and a wider range of management responses to these impacts. The innovative aspects of this research are: (a) development of a systematic approach for building robust surrogates by testing against full-scale SO models on simple to complex problems; (b) assessment of tradeoffs between surrogate model accuracy and computational efficiency across a range of hydrogeologic and management settings; (c) identification of robust management schemes for managing coastal groundwater resources in three "end-member" case study aquifers; and (d) collaboration with water management agencies to develop useful scenarios, optimization frameworks, and model output. The three test aquifers (Santa Barbara, California; Biscayne, Florida; and San Salvador Island, The Bahamas) have diverse hydrogeologic and management characteristics and well-calibrated groundwater flow models. The project objectives are: (a) develop SO-SWI-SLR test problems to provide robust evaluation of model surrogates; (b) formulate management objectives and constraints based on management of the test case aquifers, and identify scenarios relevant to the test cases; (c) program, train, and evaluate the performance of "data-driven" and "model-driven" surrogates to identify optimal management schemes for the test case aquifers, a range of SLR rates, climatology, and groundwater demand scenarios. This work will build on our US-UK group's complementary experience simulating SLR and climate impacts on SWI and in developing SO models for other groundwater problems.
The limited literature on SO and surrogate modeling in SWI problems has focused on simplified hydrogeological settings and mathematical representations of management strategies. However, realistic SWI problems involve hydrogeological complexities, including discrete lithological facies, faults and fractures, saltwater-freshwater mixing zone dynamics, and surface-water groundwater interactions, as well as nonlinear objective functions and continuous and discrete decision variables to represent a wide range of engineering components. We hypothesize that these hydrogeologic and management features determine the building of accurate and efficient surrogates; and accurate surrogate SO models for SWI problems can be at least an order of magnitude faster than full-scale models. The reduced computational cost allows to investigate a broader range of SLR and climate change impacts and a wider range of management responses to these impacts. The innovative aspects of this research are: (a) development of a systematic approach for building robust surrogates by testing against full-scale SO models on simple to complex problems; (b) assessment of tradeoffs between surrogate model accuracy and computational efficiency across a range of hydrogeologic and management settings; (c) identification of robust management schemes for managing coastal groundwater resources in three "end-member" case study aquifers; and (d) collaboration with water management agencies to develop useful scenarios, optimization frameworks, and model output. The three test aquifers (Santa Barbara, California; Biscayne, Florida; and San Salvador Island, The Bahamas) have diverse hydrogeologic and management characteristics and well-calibrated groundwater flow models. The project objectives are: (a) develop SO-SWI-SLR test problems to provide robust evaluation of model surrogates; (b) formulate management objectives and constraints based on management of the test case aquifers, and identify scenarios relevant to the test cases; (c) program, train, and evaluate the performance of "data-driven" and "model-driven" surrogates to identify optimal management schemes for the test case aquifers, a range of SLR rates, climatology, and groundwater demand scenarios. This work will build on our US-UK group's complementary experience simulating SLR and climate impacts on SWI and in developing SO models for other groundwater problems.
Planned Impact
This work will contribute to solving the critical sustainability problem of water management in stressed coastal regions subject to uncertain SLR scenarios; and advance surrogate modeling for ultra-dimensional and highly nonlinear systems that can be applied to a wide range of engineering problems; and collaborative interactions with decision-makers and stakeholders leading to improved science communication and science-driven policy. Project results will be disseminated by publications in peer-reviewed engineering journals, presentations at scientific conferences and meetings involving coastal water resources policymakers, administrators and stakeholders. The project collaborators are internationally known for their research contributions to groundwater modelling and monitoring, optimization applied to surface and groundwater management. This will strengthen both UK and US's leaderships in the areas of simulation-optimization applications to water management.
People |
ORCID iD |
Domenico Bau (Principal Investigator) |
Publications
Yu W
(2023)
Investigating the Impact of Seawater Intrusion on the Operation Cost of Groundwater Supply in Island Aquifers
in Water Resources Research
Yu W.
Investigating the impact of seawater intrusion on the operation cost of groundwater supply in island aquifers
in Water Resources Research
BaĆ¹ D
(2022)
Land subsidence surrogate models for normally consolidated sedimentary basins
in Geomechanics for Energy and the Environment
Description | University of Texas at El Paso |
Organisation | University of Texas, El Paso |
Country | United States |
Sector | Academic/University |
PI Contribution | This is a collaborative project between the University of Texas at El Paso, USA, and the University of Sheffield, UK. The US PI is Dr Alex S Mayer, whereas the UK PI is Dr Domenico Bau. |
Collaborator Contribution | The overarching goal of this research is the sustainable management of water resources in coastal regions with diverse geological, hydro-technical and governance settings. 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 sea level rise (SLR). We will focus on coastal areas where aquifer over-drafting has caused seawater intrusion (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 (SO) by developing computationally efficient, robust, and accurate surrogate models for coastal groundwater systems. |
Impact | collaborative research |
Start Year | 2020 |
Description | Conference Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | title: 'Comparison of off-line and on-line trained Gaussian process models for island groundwater management' authors: Weijiang Yu, Domenico Bau, Mayer Alex, Yipeng Zhang, Lauren Mancewicz, Mohammadali Geranmehr session selected: 'Advancing the State-of-the-Science of Water Resources Modeling - Community Development at the Intersection of Domain, Data, and Computer Sciences' |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.agu.org/FIHM |
Description | Univ of Shefield - Dept of Civil and Environmental Engineering - PGR Conference 2021 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Poster Title: Studying the impact of seawater intrusion (SWI) on the cost of groundwater supply in island aquifers Authors: Weijiang Yu, Domenico Baù, Alex S. Mayer, Yipeng Zhang, Lauren Mancewicz |
Year(s) Of Engagement Activity | 2021 |