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Performance of landscape composition metrics for predicting water quality in headwater catchments

机译:景观构图度量的性能预测水质散热室水质

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Land use is a predominant threat to the ecological integrity of streams and rivers. Understanding land use-water quality interactions is essential for the development and prioritization of management strategies and, thus, the improvement of water quality. Weighting schemes for land use have recently been employed as methods to advance the predictive power of empirical models, however, their performance has seldom been explored for various water quality parameters. In this work, multiple landscape composition metrics were applied within headwater catchments of Central Europe to investigate how weighting land use with certain combinations of spatial and topographic variables, while implementing alternate distance measures and functions, can influence predictions of water quality. The predictive ability of metrics was evaluated for eleven water quality parameters using linear regression. Results indicate that stream proximity, measured with Euclidean distance, in combination with slope or log-transformed flow accumulation were dominant factors affecting the concentrations of pH, total phosphorus, nitrite and orthophosphate phosphorus, whereas the unweighted land use composition was the most effective predictor of calcium, electrical conductivity, nitrates and total suspended solids. Therefore, both metrics are recommended when examining land use-water quality relationships in small, submontane catchments and should be applied according to individual water quality parameter.
机译:土地使用是对流和河流生态完整性的主要威胁。理解土地利用水质互动对于管理策略的开发和优先级,因此提高水质。最近被聘用的土地利用的加权计划作为推进经验模型的预测力量的方法,但他们的表现很少被探索各种水质参数。在这项工作中,在中欧的下散水集水区内应用了多种景观组合度量,以研究加权土地如何利用空间和地形变量的某些组合,同时实现备用距离测量和功能,可以影响水质的预测。使用线性回归评估了对11个水质参数的预测能力。结果表明,用欧氏距离测量的流邻近,与坡度或对数转化的流量相结合,是影响pH,总磷,亚硝酸盐和正磷酸磷浓度的主要因素,而未加权的土地使用组合物是最有效的预测因子钙,导电性,硝酸盐和总悬浮固体。因此,在检查小型潜水池中的土地利用水质关系时建议使用两项指标,并应根据各个水质参数应用。

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