Bertels Daan, De Meester Joke, Dirckx Geert, Willems Patrick
KU Leuven, Department of Civil Engineering, Hydraulics and Geotechnics Section, Kasteelpark Arenberg 40 - box 2448, Leuven 3001, Belgium.
KU Leuven, Department of Civil Engineering, Hydraulics and Geotechnics Section, Kasteelpark Arenberg 40 - box 2448, Leuven 3001, Belgium.
Water Res. 2023 Oct 1;244:120498. doi: 10.1016/j.watres.2023.120498. Epub 2023 Aug 18.
Combined sewer overflows (CSOs) can have a severe negative, local impact on surface water systems. To assure good ecological surface water quality and drinking water production that meets the demands, the impact of sewer system overflows on the surrounding water bodies for current and future climate conditions needs to be assessed. Typically, integrated, detailed hydrological and hydrodynamic water quantity and quality models are used for this purpose, but often data and computational resource requirements limit their applicability. Therefore, an alternative computationally efficient, integrated water quantity and quality model of sewer systems and their receiving surface waters is proposed to assess the impact of CSOs on surface water quality in a sparsely observed area. A conceptual model approach to estimate CSO discharges is combined with an empirical model for estimating CSO pollutant concentrations based on waste water treatment plant influent observations. Both methods are compared with observations and independent results of established reference methods as to evaluate their performance. The methodology is demonstrated by modelling the current impact of CSOs on the water abstraction area of a major drinking water production centre in Flanders, Belgium. It is concluded that the proposed conceptual models achieve similar results for daily WWTP effluent and CSO frequency, whereby the accumulated CSO volume is similar to more detailed full hydrodynamic models. Further, the estimated pollutant concentrations correspond with another dataset based on high resolution sampled overflows. As a result, the proposed computational efficient method can give insights in the impact of CSOs on the water quality at a catchment level and can be used for planning monitoring campaigns or performing analyses of e.g. the current and future water availability for a data scarce areas.
合流制下水道溢流（CSO）会对地表水系统产生严重的负面局部影响。为确保良好的生态地表水水质以及符合需求的饮用水生产，需要评估下水道系统溢流在当前和未来气候条件下对周边水体的影响。通常，为此目的会使用综合、详细的水文和水动力水量及水质模型，但数据和计算资源需求往往限制了它们的适用性。因此，本文提出了一种计算效率高的下水道系统及其受纳地表水的综合水量和水质模型，以评估CSO在观测数据稀少地区对地表水水质的影响。一种估算CSO排放量的概念模型方法与一种基于污水处理厂进水观测数据估算CSO污染物浓度的经验模型相结合。将这两种方法与观测数据以及既定参考方法的独立结果进行比较，以评估它们的性能。通过对CSO对比利时弗拉芒地区一个主要饮用水生产中心取水区域的当前影响进行建模，展示了该方法。研究得出结论，所提出的概念模型在每日污水处理厂出水和CSO频率方面取得了相似的结果，累积CSO体积与更详细的完整水动力模型相似。此外，估算的污染物浓度与基于高分辨率采样溢流的另一个数据集相符。结果，所提出的计算效率高的方法能够深入了解CSO对集水区水质的影响，可用于规划监测活动或对数据稀缺地区的当前和未来水资源可用性等进行分析。
