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Study Research On Optimal Allocation Of Agricultural Water Resources In Dali County Based On Particle Swarm Optimization

Posted on:2020-09-26Degree:MasterType:Thesis
Country:ChinaCandidate:Q ZhangFull Text:PDF
GTID:2370330596979393Subject:Agricultural Soil and Water Engineering
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China's water resources are increasingly in short supply.In order to allow limited water resources to carry on the sustainable and healthy development of agriculture,it is necessary to effectively and rationally allocate agricultural water resources.Based on the review of the research on the optimal allocation of agricultural water resources at home and abroad,based on the actual situation of the research area of Dali County,the paper optimizes the rational allocation of agricultural water resources and the allocation of planting area in Dali County.The basic data are from Dali County.Yearbook,Dali County and other materials,establish an optimal allocation model of agricultural water resources,obtain reasonable planting area of major crops in Dali County,and optimize the allocation of agricultural water resources,and solve the problem of rational allocation of limited agricultural water resources in the irrigation area of Dali County.The problem of crops has achieved the goal of maximizing the economic benefits of agricultural production.The main research contents and conclusions are as follows:(1)The agricultural water demand in Dali County has changed greatly from 1990 to 2013,and the overall trend is increasing.The water demand is in a state of water shortage every year.Among them,the water shortage is the highest in 2007,and the agricultural water shortage is serious.The annual net water demand Both are smaller than the water supply,and there is residual water and water saving space.It is predicted that the agricultural water demand in Dali County in 2020 and 2030 will increase from the average water demand in 1990-2013,and it is still in a water shortage.(2)The agricultural water resources carrying capacity in Dali County is relatively poor.The comprehensive score is basically between 0.29 and 0.34.In 2013,the degree of membership is 0.454.The carrying capacity is in a saturated stage.It is predicted that the water resources will be in saturation stage in 2020 and 2030.Smaller,the future agricultural development should not expand the agricultural planting area on a large scale,and the crop planting structure should be adjusted to improve the utilization rate of agricultural water resources.(3)Optimize the current water resources allocation and planting structure in Dali County,establish an optimization model and solve it.Before and after the optimization,the results show that by rationally arranging agricultural water resources and planting structure in Dali County,the total income of farmers can be improved and passed.The particle swarm optimization algorithm is improved to solve the problem that the algorithm is easy to fall into the local optimal solution and the particle exceeds the constraint range in the optimization process.(4)Considering the discreteness of planting area variables,linear programming,continuous particle swarm optimization and discrete particle swarm optimization are used to optimize the results.The results of different algorithm solutions are compared.The discrete particle swarm optimization algorithm can solve the problem of discreteness of planting area variables.The allocation of crop acreage in the planning year is more applicable and feasible and can be applied to practice.The comprehensive analysis shows that the optimal allocation of agricultural water resources can improve the utilization efficiency of agricultural water resources and increase the economic benefits of agricultural production in Dali County.The research results have certain guiding significance for promoting the optimal allocation of agricultural water resources and realizing sustainable development of agriculture.
Keywords/Search Tags:optimal allocation of water resources, water resources carrying capacity, particle swarm optimization, discrete particle swarm optimization
PDF Full Text Request
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