Abstract Understanding changes in water quality over time and landscape and anthropogenic factors affecting them are of paramount importance to human and ecosystem health. We analyzed the seasonal trends of total nitrogen, total phosphorus, chemical oxygen demand, and total suspended solid (SS) in the Han River Basin (HRB) of South Korea using the Mann-Kendall test. We explored the effects of anthropogenic (land cover and population) and natural factors (topography and soil) on the trends by using Moran’s Eigenvector based spatial filtering regressions at four different spatial scales. Water quality of the HRB generally improved from the early 1990s to 2016 with decreasing summer nutrient and winter SS concentrations. Water quality trends were spatially autocorrelated with distinct spatial variations within the basin. Some stations close to the Seoul metropolitan area, however, still exhibited poor water quality conditions. Approximately 20–70 percent of spatial variation of different water quality trends were explained by some combination of current agricultural land cover, forest land cover, % area covered by water, change in those land covers and slope variations. The 100 m buffer and one-kilometer upstream scale analyses generally showed higher explanatory power than the sub-watershed scale analyses, while the effect of seasons differed for different parameters. The significant factors in each regression model typically differed among different scales but not among different seasons of the same scale. The spatial filtering approach removed the residual spatial autocorrelation and thus significantly increased the explanatory power of water quality trend models.

中文翻译：

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影响韩国大河流域水质趋势空间格局的景观和人为因素

摘要 了解水质随时间和景观的变化以及影响它们的人为因素对人类和生态系统健康至关重要。我们使用 Mann-Kendall 检验分析了韩国汉河流域 (HRB) 的总氮、总磷、化学需氧量和总悬浮固体 (SS) 的季节性趋势。我们通过在四个不同空间尺度上使用基于 Moran 特征向量的空间过滤回归，探讨了人为因素（土地覆盖和人口）和自然因素（地形和土壤）对趋势的影响。从 1990 年代初期到 2016 年，随着夏季养分和冬季 SS 浓度的降低，HRB 的水质总体上有所改善。水质趋势在空间上与流域内不同的空间变化有关。然而，靠近首尔市区的一些车站的水质仍然很差。不同水质趋势的大约 20-70% 的空间变化是由当前农业土地覆盖、林地覆盖、水覆盖面积百分比、这些土地覆盖的变化和坡度变化的某种组合来解释的。100 m 缓冲区和 1 公里上游尺度分析通常比子流域尺度分析显示出更高的解释力，而季节对不同参数的影响不同。每个回归模型中的显着因子通常在不同尺度之间存在差异，但在同一尺度的不同季节之间不存在差异。