Yang Huicai, Wang Guoqiang, Yang Yan, Xue Baolin, Wu Binbin
College of Water Sciences, Beijing Normal University, Beijing 100875, China.
United Faculty of Agriculture, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan.
ScientificWorldJournal. 2014;2014:526240. doi: 10.1155/2014/526240. Epub 2014 Apr 7.
In recent years, land use upstream of the Three Gorges Reservoir (TGR) has changed significantly because of the TGR project. In this study, the Soil and Water Assessment Tool (SWAT) model was examined for its ability to assess relationships between land use changes and nonpoint pollutant indexes upstream of the TGR. Results indicated that the SWAT model, calibrated with the adjusted parameters, could successfully reproduce the nonpoint indexes at the water quality monitoring sites in the two rivers. The different land use change types were shown to be sensitive to nonpoint pollutants in the study area. The land use change type from upland to water was the strongest influence on changes in total nitrogen and total phosphorus. An empirical regression equation between nonpoint indexes and different land use change types was developed for the study area by partial least squares regression (PLSR) as follows: Y = b 0 + ∑ i=1 (m) b i X i. This regression equation was useful for evaluating the influence of land use change types on changes in nonpoint pollutants over a long time period. The results from this study may be useful for the TGR management and may help to reduce nonpoint pollutant loads into downstream water bodies.
近年来，由于三峡工程，三峡水库上游的土地利用发生了显著变化。在本研究中，对土壤和水资源评估工具（SWAT）模型评估三峡水库上游土地利用变化与面源污染物指标之间关系的能力进行了检验。结果表明，经调整参数校准后的SWAT模型能够成功再现两条河流中水质监测点的面源指标。研究区域内不同的土地利用变化类型对面源污染物敏感。从旱地到水体的土地利用变化类型对总氮和总磷变化的影响最大。通过偏最小二乘回归（PLSR）为研究区域建立了面源指标与不同土地利用变化类型之间的经验回归方程，如下所示：Y = b 0 + ∑ i=1 (m) b i X i 。该回归方程有助于评估长期土地利用变化类型对面源污染物变化的影响。本研究结果可能对三峡水库管理有用，并可能有助于减少向下游水体排放的面源污染物负荷。
