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霍军军,尚松浩.基于模拟技术及遗传算法的作物灌溉制度优化方法[J].农业工程学报,2007,23(4):23-28.DOI:
基于模拟技术及遗传算法的作物灌溉制度优化方法
投稿时间:2006-03-21  修订日期:2006-06-10
中文关键词:  非充分灌溉  作物水分生产函数  土壤水量平衡  灌溉制度优化  遗传算法
基金项目:国家自然科学基金项目(50579027);国家863计划节水农业重大科技专项(2002AA2Z4311)
作者单位
霍军军 (1981-)湖北钟祥人主要从事水文水资源的研究。北京清华大学水利水电工程系100084 
尚松浩 (1971-)河南叶县人副教授主要从事水文水资源与灌溉排水研究。北京清华大学水利水电工程系100084。Email:shangsh@mail.tsinghua.edu.cn 
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中文摘要:通过土壤水量平衡模型对作物生育期内的土壤含水率及田间腾发过程进行动态模拟,并利用作物水分生产函数的Jensen模型估算作物产量,建立了以灌溉日期为决策变量、最大相对产量为决策目标的灌溉制度优化模型,并采用保留最佳个体的遗传算法求解作物最优灌溉制度。结合山西潇河灌区2003年冬小麦返青后的实际气象状况,用上述模型对冬小麦灌溉制度进行了优化与分析。对动态规划、单纯形搜索法及遗传算法的求解结果进行了比较,表明保留最佳个体的遗传算法能搜索到全局最优解,且结果稳定。不同情况下的灌溉制度优化结果表明抽穗初期是冬小麦的生长关键期,其次是拨节期。随着灌溉水量的增加,最优灌溉制度下的田间腾发量及冬小麦产量也相应增加,但增加幅度逐渐减小。
Huo Junjun,Shang Songhao.Optimization method for crop irrigation scheduling based on simulation technique and genetic algorithms[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2007,23(4):23-28.DOI:
Optimization method for crop irrigation scheduling based on simulation technique and genetic algorithms
Author NameAffiliation
Huo Junjun Department of Hydraulic and Hydropower Engineering, Tsinghua University, Beijing 100084, China 
Shang Songhao Department of Hydraulic and Hydropower Engineering, Tsinghua University, Beijing 100084, China 
Key words:deficient irrigation  crop water-production function  soil water balance  irrigation scheduling optimization  genetic algorithms
Abstract:Based on soil water balance model, soil water content and field evapotranspiration during crop growth stage were simulated dynamically. The crop yield was obtained through Jensen model of crop water-production function. An optimization model for crop irrigation scheduling was established with the irrigation date as the decision variable and the maximal relative yield as the decision objective, and was optimized using elitist-reserved genetic algorithm (GA). The model was used to optimize the irrigation scheduling for winter wheat after greening with the 2003 meteorology data in Xiaohe irrigation area, Shanxi Province. Optimized results with dynamic programming, simplex evolutionary algorithm and GA were analyzed. Result shows that GA is effective in global optimization and results with GA are stable. Irrigation in the early heading stage is the most efficient with irrigation in the shooting stage being the second. Field evapotranspiration and crop yield increase with the irrigation volume, but with decreasing slopes.
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