An Optimized Water Distribution Model of Irrigation District Based on the Genetic Backtracking Search Algorithm

Abstract

Improving irrigation efficiency in order to balance water supply and demand has become an urgent need for social development in the northwest of China. In this paper, we propose an irrigation water distribution model based on the genetic backtracking search algorithm (GBSA). This algorithm is composed of two main modules, the vector evaluation genetic algorithm (VEGA) and the backtracking search algorithm (BSA). We applied the GBSA model in the Xijun irrigation district of Heihe River Basin. The VEGA module was first used to optimize water distribution in the irrigation district, and ensure a uniform flow rate and a minimum hydraulic loss in the main canal. Moreover, the advantage of BSA module in rapid water distribution was utilized to further improve the overall water distribution velocity of the GBSA model. To evaluate the performance of the GBSA, both the grey relational analysis and the TOPSIS method were used to comprehensively evaluate its various indicators. The results show that the GBSA can meet the water distribution requirements of the whole canal irrigation system, maintaining uniform flow rate, minimizing unused water and water distribution time to optimize irrigation water distribution. At the same time, the GBSA has better performance compared to other existing methods for irrigation water distribution.

Keywords

• Irrigation water distribution
• vector evaluation genetic algorithm (VEGA)
• backtracking search algorithm (BSA)
• genetic backtracking search algorithm (GBSA)
• grey relational analysis (GRA)
• TOPSIS method