Adaptive Management of Coastal Aquifers Using Entropy-Set Pair Analysis–Based Three-Dimensional Sequential Monitoring Network Design
Publication: Journal of Hydrologic Engineering
Volume 24, Issue 3
Abstract
A three-dimensional compliance monitoring network design methodology is presented to develop an adaptive and sequentially modified management policy that intends to improve optimal and justifiable use of groundwater resources in coastal aquifers. In the first step, an ensemble metamodel-based multiobjective prescriptive model is developed using a coupled simulation-optimization approach to derive a set of Pareto optimal groundwater extraction strategies. Prediction uncertainty of metamodels is addressed by utilizing a weighted average ensemble using set pair analysis. In the second step, a monitoring network is designed for evaluating the compliance of the implemented strategies with the prescribed management goals due to possible uncertainties associated with field-scale application of the proposed management policy. Optimal monitoring locations are obtained by maximizing Shannon’s entropy between the saltwater concentrations at the selected potential locations. Performance of the proposed three-dimensional sequential compliance monitoring network design is assessed for an illustrative multilayered coastal aquifer study area. The performance evaluations show that sequential improvements of optimal management strategy is possible by using saltwater concentrations measured at the proposed optimal compliance monitoring locations. Therefore, the salinity concentration data collected at the designed compliance monitoring wells can be used to collect feedback information in terms of salinity concentrations. This feedback information can be applied to improve the initially prescribed optimal groundwater extraction patterns while keeping the original management goal intact.
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Journal of Hydrologic Engineering
Volume 24 • Issue 3 • March 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: May 1, 2018
Accepted: Oct 9, 2018
Published online: Dec 31, 2018
Published in print: Mar 1, 2019
Discussion open until: May 31, 2019
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