Drinking water quality monitoring in real time is of utmost importance to ensure public health. Although water utilities, following the related legislative framework, monitor drinking water quality through samplings, the likelihood of detecting contaminants in consumers’ taps is low, depending on the scale of the monitoring programme. Additionally, even if the monitoring frequency is high, there is a time delay since sampling and analysis processes take some time. The selection of suitable locations for the installation of online water quality sensors is a hard task for a water utility due to the complexity of the water distribution system, the limitations of certain network junctions which are not easily accessible, and the computational burden involved. This topic has been extensively studied in recent years and sophisticated methods have been developed using optimization techniques. However, small water utilities do not have the means to implement such tools. This paper applies a methodology to identify the suitable junctions for the installation of online water quality sensors based on different objectives and under demand-driven conditions. This paper utilizes the hydraulic simulation model of a standard network to set up the water quality simulation model. A thorough analysis of various contamination scenarios takes place with different injection nodes and at different starting injection times for 24 h. The latter relates to the contaminant’s spread due to varying water demand. After a thorough analysis of 816 scenarios, a prioritized list of the most suitable nodes for the installation of the sensors is available for each optimization objective. Comparing the prioritized list of nodes achieved from each single or multi-objective function, the detection probability is almost the same. The analysis revealed that, due to varying water demand conditions, the ranking of the proposed nodes suitable for the installation of water quality monitoring sensors differs. Thus, varying hourly water demand should be part of analyses seeking to get reliable results.

中文翻译：

---

需求驱动条件下基于不同标准的小型供水管网中适合放置水质传感器的位置的识别

实时监测饮用水质量对于确保公众健康至关重要。尽管自来水公司遵循相关的立法框架，通过采样监测饮用水质量，但根据监测计划的规模，检测到消费者水龙头中污染物的可能性很低。此外，即使监测频率很高，也存在时间延迟，因为采样和分析过程需要一些时间。由于配水系统的复杂性、某些难以接近的网络连接点的限制以及所涉及的计算负担，选择合适的位置安装在线水质传感器对于自来水公司来说是一项艰巨的任务。近年来，该主题得到了广泛的研究，并使用优化技术开发了复杂的方法。然而，小型供水公司没有实施此类工具的手段。本文应用一种方法，根据不同的目标和需求驱动的条件，确定安装在线水质传感器的合适接头。本文利用标准管网的水力仿真模型建立水质仿真模型。使用不同的注射节点和不同的开始注射时间 24 小时对各种污染情况进行彻底分析。后者与由于不同的需水量而导致的污染物扩散有关。经过对816个场景的深入分析，每个优化目标都有一个最适合安装传感器的节点的优先列表。比较从每个单目标或多目标函数获得的节点优先级列表，检测概率几乎相同。分析表明，由于需水条件的不同，适合安装水质监测传感器的拟建节点排名不同。因此，改变每小时的需水量应该是寻求获得可靠结果的分析的一部分。适合安装水质监测传感器的拟议节点的排名不同。因此，改变每小时的需水量应该是寻求获得可靠结果的分析的一部分。适合安装水质监测传感器的拟议节点的排名不同。因此，改变每小时的需水量应该是寻求获得可靠结果的分析的一部分。