Agricultural water allocation with climate change based on gray wolf optimization in a semi-arid region of China

PeerJ

article

Zhidong Wang¹  Xining Zhao¹  Jinglei Wang³  Ni Song³  Qisheng Han³ 

[1] College of Water Resources and Architectural Engineering, Northwest A & F University;Institute of Soil and Water Conservation, Northwest A&F University;Farmland Irrigation Research Institute of Chinese Academy of Agriculture Sciences/Key Laboratory of Crop Water Use and Regulation, Ministry of Agriculture and Rural affairs

关键词: Semi-arid land;    Climate scenarios;    Allocation of land and water resources;    Multi-objective programming;    Grey wolf optimization;    Analytic hierarchy process;   

DOI  :  10.7717/peerj.14577

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

BackgroundWe quantified and evaluated the allocation of soil and water resources in the Aksu River Basin to measure the consequences of climate change on an agricultural irrigation system.MethodsWe first simulated future climate scenarios in the Aksu River Basin by using a statistical downscaling model (SDSM). We then formulated the optimal allocation scheme of agricultural water as a multiobjective optimization problem and obtained the Pareto optimal solution using the multi-objective grey wolf optimizer (MOGWO). Finally, optimal allocations of water and land resources in the basin at different times were obtained using an analytic hierarchy process (AHP).Results(1) The SDSM is able to simulate future climate change scenarios in the Aksu River Basin. Evapotranspiration (ET0) will increase significantly with variation as will the amount of available water albeit slightly. (2) To alleviate water pressure, the area of cropland should be reduced by 127.5 km2 under RCP4.5 and 377.2 km2 under RCP8.5 scenarios. (3) To be sustainable, the allocation ratio of forest land and water body should increase to 39% of the total water resource in the Aksu River Basin by 2050.

【 授权许可】

CC BY