Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm

Abstract

This study develops a production well management model for the conjunctive management of water resources in semi-arid areas. The management model integrates a large-scale pressurized water distribution system and a three-dimensional groundwater model under an optimization framework. The well pump operations optimization problem is formulated as a Boolean integer nonlinear programming (BINLP) problem to optimize the periodic 24-h pump on/off operations over a 1-week operation horizon. The management model considers multiple objectives and is solved by a parallel genetic algorithm (PGA) to overcome the difficulty of solving the BINLP problem. The PGA significantly reduces computation time for a case study in Chandler, Arizona. The Chandler water distribution model is built based on EPANET, and the Chandler three-dimension groundwater model is developed using MODFLOW. The high performance computing (HPC) of the genetic algorithm makes it possible to obtain 24-h real-time operations in the 7-day forecast model. The tank reliability, resilience, and vulnerability (R-R-V) are evaluated to infer the system reliability. The Pareto curve provides compromise solutions between the two competing objectives of energy reduction and pressure violation reduction.

Analytical solutions for minimization of energy use for groundwater pumping

“…Loáiciga and Leipnik [2000] and Loáiciga [2004] incorporated energy use into an expression for the net revenue of the sale of groundwater. Field applications have included those by Rastogi [1989] to an aquifer in northern California, by Theodossiou [2004] to an unconfined aquifer underlying the Kokkinohoria area in southern Cyprus, and by Tsai et al [2009], who solved a multiobjective problem that included a term minimizing energy for an aquifer underlying Chandler, Arizona.…”

Evolutionary Testing of Hydraulic Simulator Functionality

“…GAs have repeatedly been used to advantage in a variety of water planning and management problems, including optimal design (Milan 2010;Reca et al 2008), conjunctive management (Tsai et al 2009), leakage reduction (Nazif et al 2010), etc. When using a GA in the solution of an optimization problem, one has to choose its type and chromosome representation best matched to the problem, define its objective function, and specify its termination condition.…”

Contrastive analysis of three parallel modes in multi-dimensional dynamic programming and its application in cascade reservoirs operation

“…Therefore, we have to put the emphasis on the second approach that is to reduce the computational time of DP by using advanced computer technology. In recent years, the rising popularity of multi-core processors provides the necessary hardware for the implementation of parallel computing, and the CROO problem not only contains a large amount of calculations, but also has a certain degree of parallelism which is conducive to the implementation of parallel computing (Chen et al, 2008(Chen et al, , 2009Carter and Matthews, 2008;Tsai et al, 2009;Pinto et al, 2013). So, it has become an inevitable trend to improve the computational efficiency of DP by combining parallel processing technology (Zheng et al, 2013;Bruno et al, 2013;Zhan et al, 2013).…”