| Unbalanced precipitation and seriously deteriorated quality of river water determine the most important role that reservoirs played as the drinking water resource in Zhejiang Province in China. Protection of reservoirs water became an urgent task relating to the province's drinking water security and sustainable economic development. Recently, with the process of economic development and urbanization, a number of reservoirs have been confronted with the problem of water eutrophication and quality deterioration. Thus, it is quite necessary to carry out the researches on reservoir water quality and watershed ecological environment for better protecting the reservoir water. This study evaluates the reservoir water environment from aspects of reservoir water quality, eutrophication status, land use change of watershed and ecological security of reservoir environment, by integrating remote sensing, GIS as well as data mining technology. The main objectives and results are as follows:Firstly, the changes in water quality levels and eutrophication status of30large/medium-sized drinking reservoirs in Zhejiang Province from2001to2013were analyzed. It is concluded that the water quality of these reservoirs declined in general during this period, In2001, all these estimated reservoirs reached class ? standard for drinking water quality, while there were10reservoirs that were not up to class ? standard in2013. Generally, the eutrophication status of these reservoirs exhibited the transformation from oligotrophic to eutrophic, with significance in water eutrophication during our estimated period. The results of qualitative analysis to the reservoirs water with TM images (2010) were consistent with the changes of water quality. It is shown that as the decline of water quality levels, the DN value of band1and band4exhibited a rising trend.Based on TM images and the water monitoring data of Qiandao Lake, this study adopted traditional statistical regression model and RBF artificial neural network model to simulate and predict chlorophyll a, transparency, total nitrogen and total phosphorus of the reservoirs water, In the regression model, take the high water period as an example, it is concluded that logarithmic model with parameter of (b3+b4)/b2was the best inverse model for chlorophyll a with remote sensing, exponential function model with parameter of bl/b4was the best inverse model for transparency, exponential function model with parameter of b1*b4and exponential function model with parameter of (bl+b2+b3)/b4were the best inverse model respectively for total nitrogen and total phosphorus In the RBF artificial neural network model, it used Cfs (Correlation-based Feature Selection) technology to select the optimal dataset of remote sensing parameters, and with this optimal dataset as variables to simulate and predict indicators of water quality. Through comparison between the accuracies of these two models, it is concluded that the RBF artificial neural network model was estimated to have better performance.According to analysis of the land use change in the reservoir watershed in the year of1995,2000,2005and2010, it revealed that built-up land increased significantly, water bodies increased slightly, forest area was balanced and cultivated land decreased during this15-year period. Reservoir watersheds that experiencing relatively rapid expansion in built-up lands were observed in the northern and eastern coastal regions of Zhejiang Province, while reservoir watersheds that experiencing relatively slow built-up lands were observed in southwestern Zhejiang Province. Built-up lands occupation mainly occurred in flat areas with low altitude. Population and economy were estimated as two main driving factors of built-up land expansion for the strong correlation between population/GDP and the area of built-up lands. Total industrial output played lighter role compared with population and GDP. The Influence of population in2010visibly decreased compared with1995,2000and2005, but the effects of GDP and total industrial output has increased significantly. Population is detected as the most important driving factors of cultivated land decrease. However, low correlation appeared between area of cultivated land and GDP, and no obvious correlation was detected between total industrial output and area of cultivated land. The comparison between the proportions of the cultivated land/construction land and the level of reservoir water quality showed that with the declined water quality level, the average proportion of construction land in reservoir watershed presented a trend of increase.We adopted CART decision tree method to predict the water quality of reservoirs in Zhejiang Province by selecting16parameters including land use, socio-economic indicators, reservoir characteristics and climate as the independent variables and the water quality level of73drinking reservoirs of2010as the dependent variables. The classification accuracy of the model reached94.23%. After validation with the test dataset, the accuracy of the model reached80.95%. The CART rules revealed that human factors, including industrial wastewater emissions, industrial output, GDP, population density and land use, were the main factors in determining the quality level of reservoir water in Zhejiang province. The analysis of the importance of parameters showed that industrial wastewater emission was the most important factor causing water quality change.Finally, we used the PSR framework to evaluate and analyze the ecological environmental security of30large reservoir watersheds in Zhejiang Province from1995to2010by integrating RS, GIS, fuzzy analytic hierarchy process (FAHP) and set pair theory. The results showed that the ecological environment security of the reservoir watersheds had decreased in general from1995to2010. The pressure and status sub-indices mainly contributed to the decrease, while the response sub-index had a slight increase. For the spatial distribution, the security level of southwest is higher than the northeast in general. And regions where significant decreased security occurred were mainly concentrated in the central and northeast areas of Zhejiang Province. |
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