Department of Geography, Portland State University, Portland, OR 97201, USA.
J Hazard Mater. 2012 Mar 30;209-210:48-58. doi: 10.1016/j.jhazmat.2011.12.068. Epub 2012 Jan 10.
The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants.
运用普通最小二乘法（OLS）和地理加权（GWR）多元回归模型，分析了美国俄勒冈州波特兰都会区和华盛顿州克拉克县的土地覆被、地形、建筑结构与溪流水质之间的关系。分析采用了两种尺度，即流域分段和缓冲区，以局部和全局视角调查了溪流污染物的来源。模型精度（以 R(2) 值衡量）根据所用尺度、季节和回归方法的不同而波动。虽然大部分湿季水质参数与城市土地覆被有关，但大部分干季水质参数与海拔和坡度等地形特征有关。考虑到空间自相关的局部关系，GWR 模型的结果强于 OLS 回归模型。在多元回归模型中，流域分段结果普遍优于分段缓冲区结果，但干季 pH 值和溪流温度参数除外。这表明，虽然河岸带土地覆被确实会对水质产生影响，但需要考虑更远距离的污染源，才能涵盖更大的汇流区。
