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Dynamic Evaluation Of Water Resources Carrying Capacity Based On Water Resources Monitoring System

Posted on:2020-02-10Degree:MasterType:Thesis
Country:ChinaCandidate:C L LiuFull Text:PDF
GTID:2370330575498620Subject:Hydraulic engineering
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With the rapid development of modern information technology and Internet technology,people's production and lifestyle has gradually changing.The level of information construction in various industries has become one of the indicators to measure the level of economic and social development of the country and region.The rational development and utilization of water resources is an important guarantee for a country and a region to achieve sustainable development.Water resources carrying capacity is an important indicator reflecting the sustainable development and utilization of regional water resources.The traditional evaluation methods of water resources carrying capacity are mostly ex post evaluation.There are shortcomings in scientificalness,timeliness and operability.There is an urgent need to adapt to the needs of the new era.Based on the establishment of a scientific and perfect water resources monitoring system,the dynamic analysis and evaluation of water resources carrying capacity using information technology achievements are of great practical significance for the sustainable development and utilization of regional water resources.(1)On the basis of summarizing the experience of water resources information construction at home and abroad,this paper puts forward a real-time water resources monitoring system consisting of water quantity real-time monitoring system,water quality monitoring system of water function area and hydro meteorological monitoring system.This paper expounds the system requirements,system structure and function realization,and puts forward suggestions and plans for establishing a complete and unified water resources monitoring system in the region.(2)The characteristics of water resources monitoring data are analyzed and excavated,and the processing of abnomial values of water resources monitoring data is studied.This paper defines the concept of abnormal value of water resources monitoring data,puts forward the methods of using median method to identify intuitionistic abnormal value,empirical mode decomposition(EMD)to identify non-intuitionistic abnormal value,and uses piecewise polynomial curve fitting method,moving average method and grey system model to correct the abnormal value of monitoring data,which improves the reliability and accuracy of water resources monitoring data.The monitoring data of a water plant in Huzhou City are taken as an example for analysis and research.(3)In this paper,the evaluation system of regional water resources oonitoring capacity is established.According to the two aspects of water quantity and water quality monitoring,11 representative evaluation indicators are selected,and Huzhou District of Zhejiang Province is selected as the research area.The evaluation index values and corresponding evaluation criteria are determined according to the regional situation.On the basis of analyzing the characteristics of the evaluation model,the fuzzy set pair evaluation model is used to evaluate the current monitoring capacity of water resources in Huzhou City.(4)The application of regional water resources monitoring system is discussed from the aspects of data statistics,analysis and evaluation and information sharing.Taking Huzhou City as the research area,the dynamic evaluation model of water resources carrying capacity based on water resources monitoring system is constructed.The evaluation period of January to August 2018 is selected,and the sensitivity analysis method is used.Combined with the actual monitoring capacity of water resources in Huzhou City,the evaluation indexes are selected,and the single index evaluation and comprehensive evaluation are carried out respectively.The dynamic warning mechanism of water resources carrying status in Huzhou city is established.
Keywords/Search Tags:water resources monitoring, abnormal data, dynamic assessment of bearing condition, fuzzy set pair model, empirical mode decomposition
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