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评估降雨对合流制污水溢流特征的影响:柏林案例研究。

The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study.

机构信息

Grupo de Investigación Ciencia e Ingeniería del Agua y el Ambiente, Facultad de Ingeniería, Pontificia Universidad Javeriana, Edificio J.G. Maldonado, S.J., Carrera 7 No. 40-62, Bogotá, Colombia.

Berliner Wasserbetriebe, Netz- und Anlagenbau, Neue Jüdenstrasse 1, 10864 Berlin, Germany.

出版信息

Water Sci Technol. 2013;68(12):2683-90. doi: 10.2166/wst.2013.524.

Abstract

The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

摘要

本研究旨在通过多元统计方法和对德国柏林主要合流污水溢流(CSO)出口的在线测量,探讨降雨量变量与CSO 水质/水量特征之间的关系。典型相关分析结果表明,最大和平均降雨量强度是描述 CSO 水量和污染物负荷的最具影响力的变量,而降雨事件的持续时间和雨深似乎是描述 CSO 污染物浓度的最具影响力的变量。偏最小二乘(PLS)回归模型的分析证实了典型相关的发现,并强调了降雨对 CSO 特征的三个主要影响:(i)CSO 水量特征主要受最大降雨量强度的影响,(ii)CSO 污染物浓度主要与降雨持续时间有关,(iii)污染物负荷似乎主要受降雨前的干旱天气持续时间的影响。PLS 模型的预测质量相当低(R²<0.6),但结果可用于定性探讨降雨对 CSO 特征的影响。

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