| Water pollution poses a serious problem not only in China but around the world. Water resource is characterized by extreme shortage and uneven distribution in China. Diffuse pollution from soil erosion leads to surface water pollution, which restricts sustainable development of social-economy. For dealing with soil erosion and diffuse pollution emerged in water source areas of the Middle Route Project under the South-to-North Water Transfer Scheme, the study presented in this paper was undertaken based on landscape features including topography, soil, climate, pattern and composition of land use. According to the ideas of integrated eco-environment study, information technologies such as remote sensing and geographic information system were combined with reconnaissance field surveys, fuzzy decision theory, SWAT model prediction, landscape feature analysis and PLSR (partial least square regression) approach for studying soil erosion, sediment yield and water chemistry from multi-level perspectives across water source areas. The specific contents of this integrated study include importance of the dominating factors affecting soil erosion, spatio-temporal patterns and dynamic changes of soil erosion risk, spatio-temporal characteristics of soil erosion, sediment yield and water chemistry and their responses to landscape features in watersheds. This study can provide useful information for ecological construction, environmental protection, water quality assurance, and sustainable social-economic development in water source areas. The main results and conclusions of the present study are as follows:(1) The Danjiangkou Reservoir Area is the core region of ecological security and water quality assurance in water source areas, which was therefore chosen as one of the case study areas. Based on subdivided Erosion Response Units (ERUs), a fuzzy decision tree approach for rapid evaluation and mapping of monthly soil erosion risk across broad areas has been developed in this study. An optimal fuzzy decision tree was determined to classify monthly soil erosion risk into five levels, including very low, low, medium, high and very high. The most important factor impacting on soil erosion is mean monthly precipitation. Soil erosion risk is at a level of low or medium when the level of mean monthly precipitation is relatively low, no matter what degree the slope, soil erodibility and vegetation coverage are. However, when mean monthly precipitation is relatively high, soil erosion risk is influenced by more complex integrated effects from the slope, soil erodibility and vegetation coverage.(2) According to produced monthly soil erosion risk maps with five levels derived from the results of the fuzzy decision tree, high and very high soil erosion risk in the DRA is mainly concentrated in June to August, of which July and August show the highest erosion risk covering the largest area (greater than80%), followed by June which has a proportion of65%. November to the following March is dominated by low erosion risk which accounts for more than90%of the area while the medium risk level is dominant (greater than79%) in April, May, September and October. Besides, large tracts of farmland, sparse grasslands and wastelands distributed on steep slopes, which show a relatively high soil erosion risk in most rainy months. With a validated accuracy of76%, the efficiency of the presented method suggests it is worth attempting in other analogous broad area regions.(3) The Upper Du River watershed is the largest tributary of the Yangtze River and an erosion-prone area in water source areas, which was also chosen as one of the case study areas. The annual soil erosion and sediment yield distributions for the years1978,1987,1999and2007were simulated with the calibrated and validated SWAT model, which shows that the most intensively eroded sub-basins were situated in the northern part of the study area. The watershed-averaged soil erosion rates for the years1978,1987,1999, and2007were9.47,10.40,14.14, and7.64t/ha/yr, respectively. The maximum sub-basin loads of soil erosion in1978,1987,1999, and2007occurred in sub-basins8,8,34, and34, respectively. The watershed-averaged sediment yields for the years1978,1987,1999, and2007were3.72,5.36,7.30,3.69t/ha/yr, respectively. The sediment yield of the individual sub-basins varied significantly. The maximum sediment yields in1978,1987,1999, and2007were located in sub-basins8,6,39, and21, respectively. Soil erosion and sediment yield changed consistent with land use in the study area. (4) The15selected landscape metrics were used to analysis landscape pattern characteristics of soil erosion and sediment yield, which shows that the landscape characteristics of the107sub-basins in the analysis varied widely. Especially, the mean patch size (AREA_MN), patch density (PD), Shannon’s diversity index (SHDI), edge density (ED), Mean Euclidian nearest-neighbor distance (ENN_MN) and largest patch index (LPI) shows greater variances than other measures. Partial least square regression (PLSR) was used to explore the relationship between soil erosion, sediment yield, sediment delivery ratio and landscape pattern, respectively. The results show that Shannon’s diversity index (SHDI), Aggregation index (AI), Largest patch index (LPI), Contagion (CONTAG) and Patch cohesion index (COHESION) were the master factors controlling soil erosion and sediment yield. Greater interspersion and higher patch numbers of land cover types may significantly accelerate soil erosion and increase sediment export.(5) Nine typical tributaries in the Danjiangkou reservoir were chosen as the case study areas for characterizing the spatio-temporal patterns of water chemistry, which shows that the dissolved oxygen content was highest in Bai river, Taocha and Xun yang, while the content of potassium permanganate index and total phosphorus were relatively high in Shending river and Zhangwan. Compared with other watersheds, the content of ammonia nitrogen and petroleum in Shending river were highest, while the difference of arsenic content was not obvious. From2006to2009, water chemistry characteristics changed consistent with that in2005. The contents of potassium permanganate index and ammonia nitrogen were extremely high in Shengding river, which indicated that water quality in shending river was relatively poor.(6) Analysis of watershed characteristics for all the tributaries demonstrated that the proportion of urban area, forest, grassland and farmland, and the slope, watershed area and soil organic matter shows greater variances than other variables. LPI, CONTAG, LSI, SHDI and SIDI show greatest variances than other landscape metrics. Dissolved Oxygen was mainly controlled by the four morphometric variables, while hypsometric integral, proportion of urban area, soil organic matter, total nitrogen, and COHESION were the master factors of potassium permanganate index. The master factors of ammonia nitrogen and total phosphorus were almost the same with potassium permanganate index except watershed area. Arsenic was mainly controlled by watershed area, soil organic matter, LPI and LSI, while petroleum was mainly controlled by hypsometric integral, the proportion of urban area, soil organic matter, total nitrogen and COHESION. Summarily, watershed area, hypsometric integral, the proportion of urban area, soil organic matter, total nitrogen and COHESION determine the situation of water chemistry in the tributaries. |
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