To improve microbial water quality and to prevent waterborne disease outbreaks, knowledge on the fate and transport of contaminants and on the contributions from different faecal sources to the total contamination is essential. The fate and transport of faecal indicators E. coli and enterococci within the Betna River in Bangladesh were simulated using a coupled hydrodynamic and water quality model. The hydrodynamic model for the river was set up, calibrated and validated with water level and discharge in our earlier study. In this study, the hydrodynamic model was further validated using measured water temperature and salinity and coupled with the water quality module. Bacterial load data from various faecal sources were collected and used as input in the water quality model. The model output corresponded very well with the measured E. coli and enterococci concentrations in the river; the Root Mean Square Error and the Nash-Sutcliffe efficiency for Log10-transformed concentrations were found to be 0.23 (Log10CFU/100 ml) and 0.84 for E. coli, and 0.19 (Log10CFU/100 ml) and 0.86 for enterococci, respectively. Then, the sensitivity of the model was tested by removing one process or forcing at a time. These simulations revealed that the microbial decay, the upstream concentrations and the discharge of untreated wastewater were the primary factors controlling the concentrations in the river, while wind and the contribution from the diffuse sources (i.e. urban and agricultural runoff) were unlikely to have a major influence. Finally, the model was applied to investigate the influence of wastewater treatment on the bacteria concentrations. This revealed that wastewater treatment would result in a considerable improvement of the microbial water quality of the Betna River. This paper demonstrates the application of a comprehensive state-of-art model in a river in a data-poor tropical area. The model can potentially be applied to other watersheds and can help in formulating solutions to improve the microbial water quality.

中文翻译：

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河流粪便指示菌动力学建模作为减少粪便污染的基础

为了改善微生物水质和防止水传播疾病的爆发，了解污染物的归宿和运输以及不同粪便来源对总污染的贡献至关重要。使用耦合的水动力和水质模型模拟了孟加拉国 Betna 河内粪便指标大肠杆菌和肠球菌的命运和运输。在我们早期的研究中，河流的水动力模型是根据水位和流量建立、校准和验证的。在这项研究中，使用测量的水温和盐度并结合水质模块进一步验证了水动力模型。收集了来自各种粪便来源的细菌负荷数据，并将其用作水质模型的输入。模型输出与测量的 E 非常吻合。河流中的大肠杆菌和肠球菌浓度；发现 Log10 转化浓度的均方根误差和 Nash-Sutcliffe 效率对于大肠杆菌分别为 0.23 (Log10CFU/100 ml) 和 0.84，对于肠球菌分别为 0.19 (Log10CFU/100 ml) 和 0.86。然后，通过删除一个过程或一次强制来测试模型的敏感性。这些模拟表明，微生物腐烂、上游浓度和未经处理的废水排放是控制河流中浓度的主要因素，而风和扩散源（即城市和农业径流）的贡献不太可能有重大影响。影响。最后，应用该模型研究废水处理对细菌浓度的影响。这表明废水处理将显着改善贝特纳河的微生物水质。本文展示了综合最先进模型在数据贫乏的热带地区河流中的应用。该模型有可能应用于其他流域，并有助于制定改善微生物水质的解决方案。