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Analysis And Forecast Of Irrigation Water Utilization Coefficient In Xianyang Demonstration Area

Posted on:2023-12-25Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y ZhengFull Text:PDF
GTID:2543306776489794Subject:Engineering
Abstract/Summary:PDF Full Text Request
In order to comprehensively evaluate the current situation of agricultural development and water resource utilization efficiency in Xianyang,analyze the current situation and development trend of irrigation water utilization in Xianyang,make the water resources of Xianyang more optimally distributed and rationally utilized,and provide data support and theoretical analysis for the promotion and development of agricultural water-saving technologies and the formulation of agricultural development plans,this paper uses the data of Xianyang Irrigation Water Utilization Coefficient from 2015 to 2020 to conduct the calculation and prediction of The Irrigation Water Utilization Coefficient of Xianyang.In this paper,the irrigation water utilization coefficients of Xianyang in 2018,2019 and2020 and the irrigation water utilization coefficients of irrigation areas of various scales are calculated by means of end-to-end calculation methods;according to the definition and measurement method of irrigation water utilization coefficients,the precipitation,evaporation,soil permeability coefficient,irrigation area scale,irrigation area water source,water-saving irrigation area,irrigation method,water conservancy construction investment,water price and management level of each factor are selected from natural,engineering and human factors,and the influence or theoretical relationship between various factors on irrigation water utilization coefficient is analyzed and discussed.To determine the adaptability of the influence of various factors on Xianyang,to analyze the degree of influence of various factors on the irrigation water utilization coefficient by using multiple linear regression,using the calculation results of the irrigation water utilization coefficient of Xianyang from 2015 to 2020,based on the gray system theory,for the development coefficientαand the initial value(1)(1),the gray Verhulst model and the gray Verhulst improvement model with different optimization combinations were constructed,and the model was used to predict the 2021,2022,Irrigation water utilization coefficient of Xianyang in 2023.The results of the study are as follows:(1)The irrigation water utilization coefficient of Xianyang was calculated.After the calculation of the end-to-end calculation method,the irrigation water utilization coefficients of large,medium and small and pure well irrigation areas in Xianyang in 2018,2019 and 2020were obtained by 0.5506,0.5694,0.6125 and 0.7414,respectively;0.5536,0.5745,0.6302,0.7812;0.5538,0.5778,0.6311,0.7340,respectively;2018,2019,In 2020,the irrigation water utilization coefficients of Xianyang were 0.5814,0.5822 and 0.5831,respectively.The analysis shows that from 2018 to 2020,the agricultural water-saving efficiency of Xianyang will increase year by year,and the irrigation water utilization coefficient of Xianyang will maintain a growth trend.(2)The influencing factors of irrigation water utilization coefficient in Xianyang are revealed.According to the definition,attributes and calculation system of irrigation water utilization coefficient,the main natural,engineering and human influencing factors of irrigation water utilization coefficient are summarized,and the analysis shows that the irrigation water utilization coefficient is positively correlated with precipitation,negatively correlated with evaporation,and negatively correlated with permeability coefficient;the law of irrigation water utilization coefficient of irrigation water utilization in irrigation areas of various scales is large irrigation area<medium-sized irrigation area<small irrigation area<pure well irrigation area;the law of different water sources is the water diversion irrigation area>artesian diversion irrigation area The laws of different irrigation methods are soil channel surface irrigation area<anti-seepage channel ground irrigation area<pipeline surface irrigation area<sprinkler irrigation irrigation area<micro irrigation irrigation area;irrigation water utilization coefficient is positively correlated with water-saving irrigation area,water conservancy construction investment,water price and management level.Taking the irrigation water utilization coefficient as the dependent variable,the annual precipitation,the annual average temperature,the actual irrigation area,the water-saving irrigation area,the farmland irrigation water consumption,the water conservancy construction investment and the water price as the independent variables,the multivariate linear regression analysis shows that the influence of each factor on the irrigation water utilization coefficient is from high to low for the water conservancy construction investment,water-saving irrigation area,water price,annual precipitation,annual average temperature,farmland irrigation water consumption,and actual irrigation area.(3)Simulation and accurate prediction of irrigation water utilization coefficient in Xianyang were realized.According to the calculation results of the irrigation water utilization coefficient in Xianyang from 2015 to 2020,the gray Verhulst model was established based on the grey system theory,and three new gray Verhulst models were obtained by different optimization combinations of the development coefficientαand the initial value(1)(1)in the gray Verhulst model,and it was deduced that the sequence prediction effect on the saturated"S-type"change trend was excellent,and the irrigation water utilization coefficient of Xianyang from 2021 to 2023 was predicted.The prediction results of the three improved models were compared with the predictions of the original model,and the final predictions were:0.5844,0.5857,0.5871,respectively.It shows that the irrigation water utilization coefficient of Xianyang will continue to grow in the future.
Keywords/Search Tags:Xianyang, irrigation water utilization coefficient, End-to-end algorithm, influencing factor analysis, multiple linear regression, prediction, grey Verhulst model
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