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Testing and sensitivity of a simple method for predicting urban pollutant loads

机译:一种简单的预测城市污染物负荷的方法的测试和敏感性

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This paper tests a simple two-parameter regression model, based on rainfall intensity, for calculating event loads of total suspended solids, total phosphorus, and total nitrogen from urban catchments. It also examines the sensitivity of the model to its two parameters and to the rainfall time step. This was done by using large data sets collected at six urban catchments in temperate Melbourne. It was found that the two-parameter model typically explains approximately 90% of the variation in event loads at a site. The model also predicts the within-event behavior of pollutants when the flow lag time is taken into account, with R~2 correlations greater than 0.6 in most cases for both loads and concentrations at a six minute time step. Despite its acknowledged correlation with flow, rainfall intensity over short time steps is shown to be the primary driver of pollutant mobilization, and provides a practical means of predicting pollutant loads by using readily available data.
机译:本文基于降雨强度测试了一个简单的两参数回归模型,用于计算城市集水区中的总悬浮固体,总磷和总氮的事件负荷。它还检查了模型对其两个参数和降雨时间步长的敏感性。这是通过使用在温带墨尔本的六个城市集水区收集的大数据集完成的。发现两参数模型通常可以解释现场事件负载的大约90%的变化。该模型还预测了当考虑到流量滞后时间时污染物的事件内行为,在大多数情况下,对于负荷和浓度,在六分钟的时间步长处,R〜2的相关性在大多数情况下都大于0.6。尽管其与流量之间存在公认的相关性,但短时间步长的降雨强度被证明是污染物动员的主要驱动力,并提供了使用现有数据来预测污染物负荷的实用方法。

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