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Optimal Research Of Wells Layout And Water Allocation In Well-Canal Irrigation District

Posted on:2021-12-08Degree:MasterType:Thesis
Country:ChinaCandidate:T MaFull Text:PDF
GTID:2480306104489074Subject:Hydraulic engineering
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Scientific allocation research of agriculture water in well-canal irrigation area plays a vital role in improving Water-Energy-Food nexus and promoting sustainable development of irrigation area,has been one of the hotspots in the field of optimal allocation of water resources.However,due to the lack of scientific planning and reasonable utilization of wells in well-canal irrigation area,the water table in some areas has been critically reduced,further causing problems such as low pumping efficiency,cost surges and wells discard,and due to the unreasonable allocation of water resources,it's difficult to achieve efficient use of water resources in irrigation areas.In this paper,Cele Oasis in Xinjiang province was chosen as study area,focus on the two types of problems of the unreasonable utilization of wells spatial layout and surface water and groundwater allocation in the oasis well-canal irrigation area,combined with the system engineering theory and ideology of mathematical programming,the corresponding mathematical optimization model was proposed.Finally,the applicability of models is comprehensively evaluated through analysis of results and discussion.The main research contents and results of this paper are as follows:(1)Establish optimization model of wells layout in oasis well-canal irrigation area.The SOS(Special Ordered Sets)tool sets was introduced to deal with the nonlinear functions related to the well layout,and the relevant constraints were transformed through reasonable assumptions and the introduction of integer variables.Finally,the model was constructed as a Mixed Integer Linear Programming Model(MILP).The model comprehensively considers the short and long-term economic costs of the operation of the wells in the irrigation area,and uses the mathematics solver Gurobi to solve the problem with the minimum the implicit cost and the explicit cost of the well operation as optimization goals,two types of well layouts and pumping flow optimization schemes are obtained.Furthermore,the applicability of the model is further verified by comparison with the pumping scene before optimization and analysis and discussion of evaluation indicators.(2)Establish optimization allocation model of surface water and groundwater in oasis well-canal irrigation area.Based on the well layout optimization model,factors such as the uncertainty of surface water inflow in the irrigation area were comprehensively considered,the model was eventually constructed as a Chance Constrained-Mixed Integer Linear Programming Model.On the basis of the two types of well layout schemes set according to the different economic cost considerations in the optimization model of the well layout,the adjustment expectations of agricultural water prices are added to the two types of schemes respectively and form the short-term and long-term planning scenarios.In addition,according to the different runoff frequency,five types of sub-scenes from high water year to low water year are added respectively.After solving the model,the surface water and groundwater allocation schemes with the irrigation area as the spatial scale and the month within the crop growing season as the time scale under different scenarios were obtained.Through the analysis and discussion of a series of results such as the optimization results of the benefits and costs of irrigation districts,the optimal allocation of water resources in various periods,the spatial distribution of the proportion of surface water allocation,and the optimal irrigation water volume of crops,the law of water resources allocation between different scenarios was summarized.At the same time,the applicability of the model itself is further verified.
Keywords/Search Tags:Water Resource Allocation, Well-canal Irrigation Area, Well Layout Optimization Method, Mixed Integer Linear Programming Model(MILP), Chance Constrained Programming(CCP)
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