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Identification of the control factors affecting water quality variation at multi-spatial scales in a headwater watershed

机译:识别影响水质水质水质尺度水质变化的控制因素

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Understanding the effect of landscape characteristics on water quality can provide insight into mitigating water quality impairment. However, there is no consensus about the key controlling factors influencing water quality. This paper examined the combined effects of land use and topography on water quality across multi-scale, and identified the key controlling factors determining water quality variation in the headwater watershed of the Hengxi reservoir in Eastern China. Water quality impairment (WQI), expressed as a composite variable, was established to measure the overall water quality. We used the partial least squares (PLSR) method to explore the combination of landscape metrics and identify the key controlling factors. Results showed that the optimal PLSR model at 50-m, 100-m, and 150-m buffer scales and catchment scale explained 77%, 63%, 60%, and 56% of variability in WQI, respectively. At catchment scale, patch density, the percentage of paddy field, and hypsometric integral were the key controlling factors impacting water quality. At buffer scales, the slope gradient, the percentage of forest land, and topographic wetness index were more effectively determined WQI variation. Thus, the key controlling factors depend on spatial scales. Both spatial scales and corresponding key controlling factors should be considered in the adjustment of land use composition and planning of landscape configuration to better protect water quality.
机译:了解景观特征对水质的影响可以为缓解水质损害提供见解。然而,对于影响水质的关键控制因素,目前尚无共识。本文在多尺度上研究了土地利用和地形对水质的综合影响,并确定了决定中国东部横溪水库水源流域水质变化的关键控制因素。水质损害(WQI)表示为一个复合变量,用于测量总体水质。我们使用偏最小二乘法(PLSR)探索景观指标的组合,并确定关键控制因素。结果表明,50米、100米和150米缓冲尺度和集水区尺度下的最佳PLSR模型分别解释了WQI的77%、63%、60%和56%的变异性。在集水区尺度上,斑块密度、水田面积百分比和高程积分是影响水质的关键控制因素。在缓冲区尺度下,坡度、林地百分比和地形湿度指数更能有效地确定WQI变化。因此,关键控制因素取决于空间尺度。在土地利用结构调整和景观格局规划中,既要考虑空间尺度,又要考虑相应的关键控制因素,以更好地保护水质。

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