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Calculating Water Distribution in Irrigation Channel Networks Using the Beetle Swarm Optimization Algorithm

Authors :
TIAN Guilin
SU Feng
ZOU Hong
LYU Mouchao
SHEN Jixian
QIN Jingtao
FAN Xichao
Source :
Guan'gai paishui xuebao, Vol 41, Iss 7, Pp 96-103 (2022)
Publication Year :
2022
Publisher :
Science Press, 2022.

Abstract

【Objective】 Optimizing water allocation to channel networks in irrigation districts can reduce water waste and help improve water use efficiency. This paper presents the application of a modified beetle swarm optimization algorithm to achieve this goal. 【Method】 The analysis was based on irrigation in 2020 at Dagong irrigation district. Reducing water losses from seepage in the channel network was taken as the optimization objective, and operating duration of each channel and water discharge to the low-order branches were taken as the decision variables. We constructed water distribution in the channel network and solved the optimization using the beetle swarm optimization algorithm. The results were compared with those obtained from the beetle antennae search algorithm and the particle swarm algorithm. 【Result】 The total water distribution calculated from the beetle swarm optimization algorithm is 3 918 500 m3, the total loss from leakage is 228 700 m3, and the total water distribution time is 7.30 d. These are a great improvement compared with those obtained from the beetle antennae search algorithm, and close to the results calculated from the particle swarm algorithm. 【Conclusion】 The modified beetle swarm optimization algorithm is efficient and the results calculated by it meet the requirements for optimal allocation of water resources to channel network in irrigation district. It can be used to improve water management in irrigation districts and other areas.

Details

Language :
Chinese
ISSN :
16723317
Volume :
41
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Guan'gai paishui xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.fea6a71aac14b18a9842b1a3eb9f1c1
Document Type :
article
Full Text :
https://doi.org/10.13522/j.cnki.ggps.2022093