| Summary: | 碩士 === 朝陽大學 === 營建工程系碩士班 === 87 === Recently, the water pollution has become a serious problem because of the out of controlled development around the lakes and the reservoirs. Traditionally, water quality sampling in such a wide catchment area is time-consuming, expensive, and can only be executed in couples of points. Due to these limitations, the reliability of results from on-site sampling will be reduced. In this study, we introduce how to use the satellite remote sensing techniques to solve these problems.
The common trophic status indices are the OECD single variable index and the multivariable Carlson index. Since the eutrophication involves certain complex conditions in the water, the trophic status defined by the single variable index will cause a conflict by its different results from the three eutrophic criteria in chlorophyll, total phosphorus, and Secchi depth. The multivariable index can offer a synthetic assessment for eutrophication. However, it seems unsuitable to classity entrophic status by strict criterion for imprecise water variation. Fuzzy set theory provides a means for representing the complexity and uncertainty of eutrophic classification.
The first purpose of this study is to integrate remote sensing data into a suitable regression model to transform the satellite image data to the in-situ water quality eutrophic parameters. The second purpose is to assess the water quality status using the fuzzy synthetic evaluation. We compared the results from traditional standards and the fuzzy synthetic evaluation to provide a proper consult for decision-makers. Both of the regression model and the water quality assessment are deduced from the Te-Chi Reservoir and the Fei-Tsui Reservoir in Taiwan. At the end of this paper, we can determine water quality eutrophication status and correspond varying status with different colors. All of the operations are proceeded in GIS software ERDAS IMAGINE, and the eutrophication distribution is shown in a colorful geographic map.
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