A Multi-Objective Hierarchical Model for Irrigation Scheduling in the Complex Canal System

Shanshan Guo, Fan Zhang, Chenglong Zhang, Chunjiang An, Sufen Wang and Ping Guo
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Shanshan Guo: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
Fan Zhang: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
Chenglong Zhang: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
Chunjiang An: Department of Building, Civil and Environmental Engineering, Concordia University, Montréal, QC H3G 1M8, Canada
Sufen Wang: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
Ping Guo: Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China

Sustainability, 2018, vol. 11, issue 1, 1-15

Abstract: Due to population growth, environmental pollution and climate change, the lack of water resources has become a critical factor which threatens sustainable agricultural development. Reasonable irrigation scheduling strategies can reduce the waste of water and enhance agricultural water-use efficiency. In the present study, the decomposition-coordination theory was adopted to analyze the hierarchical canal system. A novel nonlinear multi-level multi-objective optimization model for complex canal systems was established, taking account of the multiple demands from decision makers and realistic factors of canal operation. An interactive method of the technique for order preference using similarity algorithm and genetic algorithm was proposed to solve the developed model. The developed model was successfully applied for the operational strategy making of a canal system located in the arid area of northwest China. The results indicated that the optimization model could help shorten the operational duration by two days, achieve about 26% reduction of irrigation water consumption, and improve the efficiency of water delivery from 0.566 to 0.687. That will be very favorable for the promotion of the agricultural water productivity, the relief of water shortage crisis and the sustainable development of agriculture. The outcomes can provide a wide range of support for decision making and make irrigation decision-making more scientific and systematic.

Keywords: irrigation scheduling; multilevel multi-objective programming; decomposition-coordination theory; TOPSIS; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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