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The Study On The Optimization Of Surface Water Environmental Monitoring Network Of Chaohu Lake

Posted on:2013-05-12Degree:MasterType:Thesis
Country:ChinaCandidate:J WangFull Text:PDF
GTID:2231330377460992Subject:Environmental Engineering
Abstract/Summary:PDF Full Text Request
The optimization of surface water monitoring network is a key link ofenvironmental monitoring quality assurance system, and the reasonable monitoringsites can obtain the spatial representative data. In the past years, the environmentalmonitoring sites for Chaohu Lake were built with the condition of lacking therelative material. As a result, it leads to the construction of excessive unnecessarymonitoring sites. As the population increases and industrial development, it isnecessary to adjust and optimize the previous monitoring network which is morescientific and representative.Firstly,by using monitoring data from2005to2009five-year andmathematical statistics theory, we analyzed the yearly water quality correlationbetween the existing28monitoring sections and its neighbors. It can be found thatthe annual water quality is very unstable in some monitoring sections,and manyneighboring water qualities have the extremely remarkable correlations, whichreflect the redundant construction of monitoring sections. Then we cluster the28sections by using the fuzzy clustering analysis in SPSS software. Afterconsideration of the hydrology,meteorological,source of pollution layout andenvironmental management factors and so on, we finally determine the21monitoring sections.Finaly,we proved the optimized section group can replace theoptimization section group. Chaohu Lake monitoring sites were optimized with thesame methods as the rivers aroud Chaohu Lake used. The total number of optimizedsites is eight,after canceled7unreasonable points and added three new points.The optimization of monitoring network can provide timely and efficientinformation support for water environment management and decision-making.
Keywords/Search Tags:Chaohu Lake, moitoring sections, monitoring sites, Rational analysis, cluster analysis, SPSS software, optimal adjustment
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