Multivariate adaptive regression spline ensembles for management of multilayered coastal aquifers

Roy, Dilip Kumar, and Datta, Bithin (2017) Multivariate adaptive regression spline ensembles for management of multilayered coastal aquifers. Journal of Hydrologic Engineering, 22 (9).

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Abstract

Application of multivariate adaptive regression spline ensembles (En-MARS) in a coupled simulation-optimization methodology to derive multiple-objective optimal groundwater extraction strategies for a multilayered coastal aquifer system is demonstrated. Two conflicting objectives of groundwater extraction strategies are solved using a controlled elitist multiobjective genetic algorithm. A three-dimensional density-dependent coupled flow and salt-transport numerical simulation model is used to generate the training patterns of groundwater extraction strategies and resulting saltwater concentrations. Prediction capability of En-MARS is compared with that of the best multivariate adaptive regression spline (MARS) model in the ensemble. En-MARS is then linked externally within the optimization algorithm to develop the management model. The optimal solutions obtained from the En-MARS models are verified by running the numerical simulation model. The results indicate that MARS-based ensemble modeling approach is able to provide reliable solutions for a multilayered coastal aquifer management problem. The adaptive nature of MARS models and use of ensembles and parallel processing results in a computationally efficient, accurate, and reliable methodology for coastal aquifer management that also incorporates uncertainties in modeling. (C) 2017 American Society of Civil Engineers.

Item ID: 50401
Item Type: Article (Research - C1)
ISSN: 1943-5584
Keywords: coastal aquifer, linked simulation-optimization, multivariate adaptive regression spline, ensemble, parallel computing
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A version of this publication was included as Chapter 7 of the following PhD thesis: Roy, Dilip Kumar (2018) Development of a sustainable groundwater management strategy and sequential compliance monitoring to control saltwater intrusion in coastal aquifers. PhD thesis, James Cook University, which is available Open Access in ResearchOnline@JCU. Please see the Related URLs for access.

Date Deposited: 20 Sep 2017 08:37
FoR Codes: 09 ENGINEERING > 0905 Civil Engineering > 090509 Water Resources Engineering @ 100%
SEO Codes: 96 ENVIRONMENT > 9609 Land and Water Management > 960999 Land and Water Management of Environments not elsewhere classified @ 100%
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