Optimizing the conjunctive surface and subsurface operations of a multi-lake system

Yu Wen Chen, Hone-Jay Chu, Liang Cheng Chang, Yi Chuan Fu

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial lake is considered a new water resources alternative in Taiwan in recent years. Kao-ping Artificial Lake is an example and it is a lake system with five artificial ponds. The groundwater level surrounding the lake is higher than those in the surrounding areas. Therefore, the determination of available water from the system is more complex than those for reservoir operations. This research considers the effects of the water supplied by the lake, the water stored in the lake, and the exchange between the lake and groundwater system in the operations of the Kao-ping Artificial Lake. The research develops an optimal conjunctive model for the Kao-ping Artificial Lake. However, if a numerical model is used to simulate the behavior of Kao-ping Artificial Lake operations, it will increase the computational burden. In order to solve the problem, a Back Propagation Neural Network (BPN) trained by simulation results for MODFLOW 96 and LAK2 is applied to represent the nonlinear dynamic relationship between the lake and the unconfined aquifer. Secondly, the water to be provided by the system at each time step is determined by an optimal rule curve found by a Genetic Algorithm (GA). Results of this study indicate that the conjunctive use model can significantly increase the water supply reliability. In addition, the model also provides an optimal groundwater recharge strategy. The model is shown to be able to reduce the magnitude of the water shortage and increase the resilience of the operating rule curve and is therefore believed to be a promising tool in Kao-ping Artificial Lake's future operations.

Original languageEnglish
Pages (from-to)295-306
Number of pages12
JournalJournal of the Chinese Institute of Civil and Hydraulic Engineering
Volume21
Issue number3
Publication statusPublished - 2009 Sep

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering

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