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Optimal Allocation Of Water Resources In Shihezi City Under The Strictest Water Resources Management System

Posted on:2022-08-24Degree:MasterType:Thesis
Country:ChinaCandidate:F WuFull Text:PDF
GTID:2480306548988439Subject:Master of Engineering
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Under the background of the strictest water resources management system,with the accelerating process of urbanization,accompanied by the rapid development of new industrialization,agricultural modernization and industrial informatization,the shortage of water resources in Shihezi city is gradually aggravating,and the overall utilization efficiency of water resources is low,water shortage and water waste coexist.It is urgent to study the optimal allocation of water resources in Shihezi city.Starting from the research background and significance of the optimal allocation of water resources,this paper comprehensively expounds the research status of the three research contents involved in this paper at home and abroad,and clarifies the research ideas.The main research contents and conclusions are as follows:(1)From the three aspects of water resources,social economy and ecological environment,12 indexes are selected to construct the evaluation index system of water resources carrying capacity in Shihezi City,and the evaluation grade standard is formulated.The weight is determined by fuzzy analytic hierarchy process(FAHP),and the water resources carrying capacity is evaluated,the development trend is diagnosed and the factors affecting the water resources carrying capacity are identified by combining fuzzy set pair analysis and five element subtraction set pair potential.The results show that the evaluation grade of water resources carrying capacity in Shihezi city is grade II,and the overall development trend is balanced development.There are five main factors affecting the water resources carrying capacity in the study area.It is necessary to further tap the water-saving potential from the vulnerability factors affecting the water resources carrying capacity in the study area,so as to provide the basis for the optimal allocation of water resources.(2)In this paper,an improved grey model,index analysis method and index prediction method are constructed.Before forecasting the water demand of Shihezi City,the applicability of each method is analyzed,and the index prediction method is discarded.The forecasting results of gray model and index analysis method indicate that the change trend of regional water demand is increasing year by year,and the water demand of Shihezi City will continue to show an upward trend for a long time in the future.There is a gap between the forecasting results and the total water consumption control indexes of the "Three Red Lines".The forecasting results of gray model are closer to those of the "Three Red Lines".The existing water resources in Shihezi City are unreasonably allocated,so it is urgent to optimize the allocation of water resources.(3)In this paper,a multi-objective optimal allocation model of water resources under the constraint of "three red lines" is established,and the multi-objective optimization problem is transformed into a single-objective optimization problem by means of fuzzy AHP.An improved particle swarm optimization algorithm is constructed,and its astringency and global optimization are determined by test function.It is found that both of them are improved.The optimal allocation model is solved by algorithm,and the optimal allocation scheme of water resources in 2025 and2030 is obtained,and the effect of the allocation scheme is evaluated.The results show that the optimal allocation scheme of water resources reasonably restrains water demand and can maximize the comprehensive benefits of society,environment and economy.The effectiveness of the allocation scheme is verified by the results of effectiveness evaluation.The allocation results can provide reliable scientific basis for regional water resource planning and dispatching.
Keywords/Search Tags:Shihezi City, Assessment of water resources carrying capacity, Forecast of urban water demand, Optimal allocation of water resources
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