摘要
[目的]寻求符合哈密市经济发展现实需要的可持续发展的水资源配置方案。[方法]以哈密市为研究区域,以经济效益最优为目标,以水资源为约束条件采用粒子群优化算法(PSO)建立耕地用水优化配置模型,获得哈密市不同农作物类型的适宜种植面积,确定农业用水总量与产出效益,使用DEA模型中的C 2R模型分别对优化前后的哈密市农业用水效率进行评价。[结果]PSO优化预测2025年耕地总面积为70635 hm^(2),总效益达29.02亿元,比2015-2019年最高效益(2017年25.88亿元)提升了12.13%;优化预测的2025年耕地单位面积效益达4.11万元,比2015-2019年最高单位面积效益(2019年2.73万元)提升了50.50%;DEA分析的C 2R模型打分结果表明,粒子群优化后的结果更为优秀。[结论]优化后的方案在满足哈密市工业用水需求的同时又能提升哈密市农业用水的效益,该优化结果可为哈密市未来农业水资源的分配与利用提供科学依据。
[Objective]To seek a sustainable water resource allocation plan that meets the actual needs of economic development in Hami City.[Method]Taking Hami City as the research area,taking the optimal economic benefits as the goal,and taking water resources as constraints,the particle swarm optimization(PSO)was used to establish an optimal allocation model of cultivated land water,to obtain suitable planting areas for different crop types in Hami City,to determine the total amount of agricultural water use and output benefits,and the C 2R model in the DEA model was used to evaluate the agricultural water efficiency before and after optimization in Hami City.[Result]After optimization of PSO,it was predicted that the total cultivated land area in 2025 would be 70635 hm^(2),and the total benefit would reach 2.902 billion yuan,which was 12.13%higher than the highest benefit from 2015 to 2019(2.588 billion yuan in 2017).The optimally predicted benefit per unit area of cultivated land in 2025 would reach 41,100 yuan,which was 50.50%higher than the highest benefit per unit area from 2015 to 2019(27,300 yuan in 2019).The scoring results of the C 2R model analyzed by DEA showed that the results of particle swarm optimization were better.[Conclusion]The optimized scheme can not only meet the industrial water demand in Hami City,but also improve the efficiency of agricultural water use in Hami City.The optimized results can provide a scientific basis for the future distribution and utilization of agricultural water resources in Hami City.
作者
皮青兰
张永福
PI Qing-lan;ZHANG Yong-fu(College of Resources and Environment Science,Xinjiang University,Urumqi,Xinjiang 830046;Key Laboratory of Oasis Ecology of Ministry Education,Xinjiang University,Urumqi,Xinjiang 830046)
出处
《安徽农业科学》
CAS
2021年第16期70-74,共5页
Journal of Anhui Agricultural Sciences
关键词
种植结构优化
水资源约束
粒子群优化算法
DEA模型
哈密市
Planting structure optimization
Water resource constraints
Particle swarm optimization(PSO)
DEA model
Hami City