Water and Environmental Engineering Group, Department of Civil Engineering, Institute for Marine Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU) in Ålesund, Larsgårdsvegen 2, 6009 Ålesund, Norway.
Water and Environmental Engineering Group, Department of Civil Engineering, Institute for Marine Operations and Civil Engineering, Norwegian University of Science and Technology (NTNU) in Ålesund, Larsgårdsvegen 2, 6009 Ålesund, Norway.
Sci Total Environ. 2019 Apr 10;660:306-320. doi: 10.1016/j.scitotenv.2018.12.460. Epub 2019 Jan 4.
Formulating effective management intervention measures for water supply systems requires investigation of potential long-term impacts. This study applies an integrated multiple regression, random forest regression, and quantitative microbial risk assessment (QMRA) modelling approach to assess the effect of climate-driven precipitation on pathogen infection risks in three drinking water treatment plants (WTPs) in Norway. Pathogen removal efficacies of treatment steps were calculated using process models. The results indicate that while the WTPs investigated generally meet the current water safety guidelines, risks of Norovirus and Cryptosporidium infection may be of concern in the future. The pathogen infections attributable to current projections of average precipitation in the study locations may be low. However, the pathogen increases in the drinking water sources due to the occurrence of extreme precipitation events in the catchments could substantially increase the risks of pathogen infections. In addition, without optimal operation of the UV disinfection steps in the WTPs, both the present and potential future infection risks could be high. Therefore, the QMRA models demonstrated the need for improved optimization of key treatment steps in the WTPs, as well as implementation of stringent regulations in protecting raw water sources in the country. The variety of models applied and the pathogen: E. coli used in the study introduce some uncertainties in the results, thus, management decisions that will be based on the results should consider these limitations. Nevertheless, the integration of predictive models with QMRA as applied in this study could be a useful method for climate impact assessment in the water supply industry.
制定有效的供水系统管理干预措施需要调查潜在的长期影响。本研究应用综合多元回归、随机森林回归和定量微生物风险评估（QMRA）模型方法，评估气候驱动降水对挪威三个饮用水处理厂（WTP）中病原体感染风险的影响。使用过程模型计算处理步骤的病原体去除效率。结果表明，尽管研究中调查的 WTP 通常符合当前的水安全指南，但未来可能需要关注诺如病毒和隐孢子虫感染的风险。归因于研究地点当前平均降水预测的病原体感染风险可能较低。然而，由于集水区发生极端降水事件，饮用水源中病原体的增加可能会大大增加病原体感染的风险。此外，如果 WTP 中的紫外线消毒步骤不能得到最佳运行，当前和潜在未来的感染风险都可能很高。因此，QMRA 模型表明需要改进 WTP 中关键处理步骤的优化，并在全国范围内实施严格的保护原水水源的法规。所应用的模型种类和研究中使用的病原体：大肠杆菌在结果中引入了一些不确定性，因此，基于结果做出的管理决策应考虑到这些限制。尽管如此，本研究中应用的预测模型与 QMRA 的集成可以成为供水行业气候影响评估的一种有用方法。
