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2019 | OriginalPaper | Buchkapitel

Using Precipitation and Combined Sewer Overflow Data for Predicting Hygienic Contaminations in Bathing Waters – A Data Analysis

verfasst von : Anna Bachmann-Machnik, Ulrich Dittmer, Annika Schönfeld

Erschienen in: New Trends in Urban Drainage Modelling

Verlag: Springer International Publishing

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Abstract

Rivers and lakes in urbanised areas are increasingly appreciated for their high ecological and recreational value. The demand for bathing sites is growing. However, in many German rivers as the Ruhr River, bathing has been prohibited for decades. At Lake Baldeney, an impounded lake of the Ruhr River, located in a densely populated area in North-Rhine-Westphalia, the first bathing place was opened in 2017. Receiving water from combined sewer overflows during heavy rain events, the hygienic quality of the water body could be affected. Due to that an extensive monitoring programme of quality parameters along the Ruhr River has been carried out during the last years and an early warning system has been established to assure a safe bathing environment at all times in a previous research project. In this article highly resolved precipitation data from six rain gauges, overflow data from four combined sewer overflow (CSO) tanks and one storage sewer as well as flow data from the River Ruhr was analysed together with daily measurements of Escherichia coli (E. coli) and intestinal enterococci (Int. E.) to assess the prediction capacity of hygienic contaminations at the bathing site during three swimming seasons. Data evaluation showed a good predictive capability of precipitation data. Overflow data showed less predictive performance when using overflow information from one tank only, indicating that single overflow events not necessarily lead to hygienic contaminations above critical thresholds.

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Metadaten
Titel
Using Precipitation and Combined Sewer Overflow Data for Predicting Hygienic Contaminations in Bathing Waters – A Data Analysis
verfasst von
Anna Bachmann-Machnik
Ulrich Dittmer
Annika Schönfeld
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-319-99867-1_113