• Title of article

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

  • Author/Authors

    Heejun Chang، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    20
  • From page
    3285
  • To page
    3304
  • Abstract
    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-Kendallʹs 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 100 m 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 Moranʹs I, 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.
  • Keywords
    Water qualityTrendUrbanizationLand coverSpatial regressionSpatial analysisScaleGIS
  • Journal title
    Water Research
  • Serial Year
    2008
  • Journal title
    Water Research
  • Record number

    765002