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Int. J. Environ. Res. Public Health 2015, 12(8), 8897-8918; doi:10.3390/ijerph120808897

Surrogate Model Application to the Identification of Optimal Groundwater Exploitation Scheme Based on Regression Kriging Method—A Case Study of Western Jilin Province

1,2
,
1,2,* and 1,2
1
Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
2
College of Environment and Resources, Jilin University, Changchun 130021, China
*
Author to whom correspondence should be addressed.
Academic Editor: Miklas Scholz
Received: 29 June 2015 / Revised: 20 July 2015 / Accepted: 24 July 2015 / Published: 30 July 2015
View Full-Text   |   Download PDF [7412 KB, uploaded 30 July 2015]   |  

Abstract

This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately. View Full-Text
Keywords: western Jilin province; simulation model; LHS; regression kriging method; surrogate model; optimization model western Jilin province; simulation model; LHS; regression kriging method; surrogate model; optimization model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

An, Y.; Lu, W.; Cheng, W. Surrogate Model Application to the Identification of Optimal Groundwater Exploitation Scheme Based on Regression Kriging Method—A Case Study of Western Jilin Province. Int. J. Environ. Res. Public Health 2015, 12, 8897-8918.

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