One of the ways to reduce the risk of contaminated water consumption is to optimally locate the quality sensors. These sensors warn users in the case of contamination detection. Analyzing the actual conditions of the contamination which enters the network is faced with many uncertainties. These uncertainties include the dose of contamination, time and location of its entry which have received less attention. Also, the uncertainty in the nodes' water demand causes changes in the distribution and contamination diffusion within the network. The main impetus of the present study is to determine the optimal quality sensor locations in the water distribution network in order to reduce the damage caused by contaminated water consumption prior to the contamination event detection. For this purpose, a parameter is defined as the maximum possible damage for calculating which the vulnerability and importance of the nodes have been considered in addition to the uncertainties in the location and time of the contamination entry. The importance of each node differs from that of other ones. Ranking the importance of the nodes is influenced by both land use and covered population ratio. In this study, six scenarios are defined for the contamination event in the water distribution network. These scenarios consider the effects of varying pollutant dose and the contamination input from nodes which are prone to its entry. Also, the NSGA-II has been utilized in order to minimize the damage with minimum number of sensors. The proposed model is evaluated on a real network in Iran. The results indicate that adding only one or two contamination warning sensors to the proposed locations can lead to the decreasing damage caused by the contaminated water consumption from 54 to 82%. According to the proposed method, the best answer for scenarios 1–6 was obtained for 7, 6, 6, 2, 2 and 2 sensors, respectively. The results showed that the slope of the pollution rate diagram does not change much from 6 sensors upwards in the first three scenarios, and from 4 sensors upwards in the second three scenarios. In scenarios 1–3, with 7, 6 and 6 sensors, respectively, in different nodes, the best placement is for 203–224 equivalent attack population, and in scenarios 4–6, with sensors in nodes 4 and 43, the best placement is for 225–279 equivalent attack population.

降低污染水消耗风险的方法之一是优化定位质量传感器。这些传感器在检测到污染时向用户发出警告。分析进入网络的污染的实际情况面临着许多不确定性。这些不确定性包括受到较少关注的污染剂量、时间和进入地点。此外，节点用水需求的不确定性导致网络内分布和污染扩散的变化。本研究的主要推动力是确定配水网络中的最佳质量传感器位置，以在污染事件检测之前减少污染水消耗造成的损害。以此目的，一个参数被定义为计算的最大可能损害，除了污染进入的位置和时间的不确定性之外，还考虑了节点的脆弱性和重要性。每个节点的重要性与其他节点不同。对节点的重要性进行排序受土地利用和覆盖人口比率的影响。在这项研究中，为配水网络中的污染事件定义了六种情景。这些情景考虑了不同污染物剂量的影响以及来自易于进入的节点的污染输入。此外，NSGA-II 已被用于以最少数量的传感器将损坏降至最低。所提出的模型在伊朗的真实网络上进行了评估。结果表明，在建议的位置仅添加一个或两个污染警告传感器可以将污染水消耗造成的损害从 54% 减少到 82%。根据所提出的方法，分别针对 7、6、6、2、2 和 2 个传感器获得了场景 1-6 的最佳答案。结果表明，污染率图的斜率在前三种情况下从 6 个传感器向上变化不大，在后三种情况下从 4 个传感器向上变化不大。在场景 1-3 中，传感器分别位于不同节点的 7、6 和 6 个传感器，最佳放置位置是 203-224 个等效攻击群体，而在场景 4-6 中，传感器分别位于节点 4 和 43 中，最佳放置位置适用于 225–279 等效攻击人群。