Spatial analysis of water quality trends in the Han River basin, South Korea

被引:381
作者
Chang, Heejun [1 ]
机构
[1] Portland State Univ, Dept Geog, Portland, OR 97201 USA
基金
美国国家科学基金会;
关键词
water quality; trend; urbanization; land cover; spatial regression; spatial analysis; scale; GIS;
D O I
10.1016/j.watres.2008.04.006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Spatial patterns of water quality trends for 118 sites in the Han River basin of South Korea were examined for eight parameters-temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (TP), and total nitrogen (TN). A non-parametric seasonal Mann-Kendall's test determined the significance of trends for each parameter for each site between 1993 and 2002. There are no significant trends in temperature, but TN concentrations increased for the majority of the monitoring stations. DO, BOD, COD, pH, SS, and TP show increasing or decreasing trends with approximately half of the stations exhibiting no trends. Urban land cover is positively associated with increases in water pollution and included as an important explanatory variable for the variations in all water quality parameters except pH. Topography and soil factors further explain the spatial variations in pH, COD, BOD, and SS. BOD, COD, SS, and TP variations are consistently better explained by 100m buffer scale analysis, but DO are better explained by the whole basin scale analysis. Local water quality management or geology could further explain some variations of water quality. Non-point-source pollution exhibits strong positive spatial autocorrelation as measured by Moran's 1, indicating that the incorporation of spatial dimensions into water quality assessment enhances our understanding of spatial patterns of water quality. The spatial regression models, compared to ordinary least square (OLS) models, always better explain the variations in water quality. This study suggests that spatial analysis of watershed data at different scales should be a vital part of identifying the fundamental spatio-temporal distribution of water quality. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3285 / 3304
页数:20
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