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Hydrogeology Journal

Erschienen in:

07.05.2018 | Paper

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

verfasst von: Qichen Hao, Jingli Shao, Yali Cui, Qiulan Zhang, Linxian Huang

Erschienen in: Hydrogeology Journal | Ausgabe 5/2018

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Abstract

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities’ operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities’ locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

Vorheriger Artikel Scale effect and value criterion of the permeability of the interlayer staggered zones in the basalt of Jinsha River basin, China

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Titel: Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China
verfasst von: Qichen Hao
Jingli Shao
Yali Cui
Qiulan Zhang
Linxian Huang
Publikationsdatum: 07.05.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Hydrogeology Journal / Ausgabe 5/2018
Print ISSN: 1431-2174
Elektronische ISSN: 1435-0157
DOI: https://doi.org/10.1007/s10040-018-1781-7

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