Identification of contamination source in water distribution network based on consumer complaints

A new methodology was proposed for contamination source identification using information provided by consumer complaints from a probabilistic view.Due to the high uncertainties of information derived from users,the objective of the proposed methodology doesn't aim to capture a unique solution,but to minimize the number of possible contamination sources.In the proposed methodology,all the possible pollution nodes are identified through the CSA methodology firstly.And then based on the principle of total probability formula,the probability of each possible contamination node is obtained through a series of calculation.According to magnitude of the probability,the number of possible pollution nodes is minimized.The effectiveness and feasibility of the methodology is demonstrated through an application to a real case of ZJ City.Four scenarios were designed to investigate the influence of different uncertainties on the results in this case.The results show that pollutant concentration,injection duration,the number of consumer complaints nodes used for calculation and the prior probability with which consumers would complaint have no particular effect on the identification of contamination source.Three nodes were selected as the most possible pollution sources in water pipe network of ZJ City which includes more than 3 000 nodes.The results show the potential of the proposed method to identify contamination source through consumer complaints.

Hazard and vulnerability evaluation of water distribution system in cases of contamination intrusion accidents

In this paper, it proposed an index system for hazard and vulnerability evaluations of water distribution networks, based on the simulation of contamination events caused by pollutant injections at different junctions. It attempted to answer the following two questions in the case of contamination events： 1） Which are the most hazardous junctions？ 2） Which are the most vulnerable junctions？ With EPANET toolkit, it simulated the propagation of the contaminant, and calculated the peak concentration of the contaminant and mass delivered at different nodes. According to types of consumers, different weights were assigned to the consumer nodes for assessing the influence of the contaminant on the consumers. Using the method proposed herein, both the hazard index and vulnerability index were calculated for each node in the pipe network. The presented method was therefore applied to the water network of the city of Zhenjiang, which contains two water plants, two booster pump stations with storage tanks. In conclusion, the response time, the relationships between the peak concentration of contami- nant and the total absorption are the most important factors in hazard and vulnerability evaluation of the water distribution network.

Generative adversarial networks for detecting contamination events in water distribution systems using multi-parameter,multi-site water quality monitoring

Contamination events in water distribution networks(WDNs)can have a huge impact on water supply and public health;increasingly,online water quality sensors are deployed for real-time detection of contamination events.Machine learning has been used to integrate multivariate time series water quality data at multiple stations for contamination detection;however,accurate extraction of spatial features in water quality signals remains challenging.This study proposed a contamination detection method based on generative adversarial networks(GANs).The GAN model was constructed to simultaneously consider the spatial correlation between sensor locations and temporal information of water quality indicators.The model consists of two networksda generator and a discriminatordthe outputs of which are used to measure the degree of abnormality of water quality data at each time step,referred to as the anomaly score.Bayesian sequential analysis is used to update the likelihood of event occurrence based on the anomaly scores.Alarms are then generated from the fusion of single-site and multi-site models.The proposed method was tested on a WDN for various contamination events with different characteristics.Results showed high detection performance by the proposed GAN method compared with the minimum volume ellipsoid benchmark method for various contamination amplitudes.Additionally,the GAN method achieved high accuracy for various contamination events with different amplitudes and numbers of anomalous water quality parameters,and water quality data from different sensor stations,highlighting its robustness and potential for practical application to real-time contamination events.

Identification of sources of pollution and contamination in water distribution networks based on pattern recognition

An intrusion of contaminants into the water distribution network (WDN) can occur through storage tanks (via animals, dust-carrying bacteria, and infiltration) and pipes. A sensor network could yield useful observations that help identify the location of the source, the strength, the time of occurrence, and the duration of contamination. This paper proposes a methodology for identifying the contamination sources in a water distribution system, which identifies the key characteristics of contamination, such as location, starting time, and injection rates at different time intervals. Based on simplified hypotheses and associated with a high computational efficiency, the methodology is designed to be a simple and easy-to-use tool for water companies to ensure rapid identification of the contamination sources, The proposed methodology identifies the characteristics of pollution sources by matching the dynamic patterns of the simulated and measured concentrations. The application of this methodology to a literature network and a real WDN are illustrated with the aid of an example. The results showed that if contaminants are transported from the sources to the sensors at intervals, then this method can identify the most possible ones from candidate pollution sources. However, if the contamination data is minimal, a greater number of redundant contamination source nodes will be present. Consequently, more data from different sensors obtained through network monitoring are required to effectively use this method for locating multi-sources of contamination in the WDN.

监测信息深度挖掘的供水管网污染源定位

为实现供水管网污染源及时准确地定位,针对配备在线水质监测设备的供水管网系统,提出一种充分挖掘水质传感器时序信息的贝叶斯方法,用于节点需水量随机波动条件下供水管网污染源定位。该方法采用蒙特卡洛模拟生成随机污染事件,构建各节点污染事件的观测信息概率分布,利用贝叶斯推断,根据传感器报警次序及时间观测信息,实时更新各候选污染节点的后验概率,并根据排序确定可疑污染源位置,同时对比不同传感器信息挖掘程度对定位结果的影响。结果表明,所提出的方法能在水质传感器报警信息累积时不断更新可疑候选节点的污染源后验概率,使候选节点个数降低,污染概率信息熵降低,能有效地识别出污染节点所在区域,且传感器信息挖掘程度越深,污染事件定位的准确率也越高。引入传感器首次报警时间作为辅助信息可以减少候选污染节点个数,降低候选节点污染源概率分布的不确定性,提高定位的准确性。

Characteristics of distribution and transport of petroleum contaminants in fracture-karst water in Zibo Area, Shandong Province, China

Fracture-karst water is an important water resource for the water supply in North China. Petroleum contamination is one of the most problematic types of the groundwater pollution. The characteristics of distribution and transport of the petroleum contaminants in fracture-karst water are different from those in porous water. The flow velocity of fracture-karst water is much faster than the velocity of porous water on an average. Therefore, contaminant transport in fracture-karst water is an absolute advection-dominated problem. The plume of the petroleum contamination may extend to several kilometers from pollution sources. It was not caused by the oil pool floating on the water table but by the oil components dissolved and scattered in groundwater. The distribution of the petroleum contaminants over space are concentrated in the strong conductive zone on the plane. On the vertical section the highest concentration of the oil contaminants appeared in the strata where the contamination sources were located. The concentrations of the oil contaminants in wells changed greatly over time. Therefore, the curves of concentration versus time fluctuated greatly. The reasons are as follows, (a) Fracture-karst water has a very great velocity, (b) Local flow fields which were caused by pumping and stoppage in some wells changed frequently, (c) In fracture-karst aquifer the transport channels are complicated, (d) Residual oil in vadose zone was leached after rainfall. It is of great practical value for the control and remediation of petroleum contamination in fracture-karst aquifer to understand those characteristics.

Metals in sediment/pore water in Chaohu Lake:Distribution,trends and flux

Nine metals, Cd, Cu, Ni, Pb, As, Cr, Zn, Fe, and Mn in sediment and pore water from 57 sampling sites in Chaohu Lake （Anhui Province, China） were analyzed for spatial distribution, temporal trends and diffuse flux in 2010. Metals in the surface sediment were generally the highest in the western lake center and Nanfei-Dianbu River estuary, with another higher area of As, Fe, and Mn occurring in the Qiyang River estuary. Metal contamination assessment using the New York sediment screening criteria showed that the sediment was severely contaminated in 44% of the area with Mn, 20% with Zn, 16% with Fe, 14% with As, and 6% with Cr and Ni. An increasing trend of toxic metals （Cd, Cu, Ni, Pb, As, Cr, Zn） and Mn with depth was shown in the western lake. Compared with metal content data from the sediment survey conducted in 1980s, the metal content of surface sediment in 2010 was 2.0 times that in the 1980s for Cr, Cu, Zn, and As in the western lake, and less than 1.5 times higher for most of the metals in the eastern lake. Among the metals, only Mn and As had a widespread positive diffuse flux from the pore water to overlying water across the whole lake. The estimated flux in the whole lake was on average 3.36 mg/（m2.day） for Mn and 0.08 mg/（m2.day） for As, which indicated a daily increase of 0.93 μg/L for Mn and 0.02 μg/L for As in surface water. The increasing concentration of metals in the sediment and the flux of metals from pore water to overlying water by diffusion and other physical processes should not be ignored for drinking-water sources.

大宝山矿区污染水体中重金属的形态分布及迁移转化

对受广东大宝山矿区矿山废水排放污染的横石河水体中的过滤水、悬浮物和沉积物中重金属的污染分布特征及其迁移转化进行了系统地研究。结果表明:该水体的环境污染是以Cu,Zn,Cd和Pb则为主的多金属复合污染,综合污染指数(PI)为2 23～18 11,重金属Cu,Zn,Cd和Pb的溶解态质量浓度分别达13 82,50 83,0 103和2 91mg L;Cu,Zn,Cd和Pb的溶解态、悬浮态及总量沿河流断面呈相似的空间分布规律,而As则略有不同,但都是沿水流方向逐渐降低的;由于受低pH的影响,水体中As主要以细微颗粒物悬浮态为迁移载体,而Cu,Zn,Cd和Pb则以水溶态为主要迁移方式;沉积物中5种重金属元素都以残渣态为主要存在形态,Cd和Pb的可交换态及Cu和Zn的有机态含量很高,说明这4种元素对环境都有一定的潜在威胁性。

硝基苯类化合物在黄河小浪底至高村河段水体中的分布特征

研究了黄河中下游小浪底-花园口-高村河段表层水、悬浮颗粒物和沉积物中10种硝基苯类有机污染物的含量.结果表明,水样中检测到8种硝基苯类有机污染物,其中孟州一干渠中硝基苯浓度最高,为8.426 8μg.L-1,但都没有超过国家标准(GB3838—2002).伊洛河的悬浮颗粒物中硝基苯类有机物的总浓度达164.382μg.kg-1.洛阳石化沉积物中硝基苯类有机物的总浓度最高,为14.718μg.kg-1.在三相(表层水、悬浮颗粒物和沉积物)中,硝基苯的含量最高.硝基苯类有机物在水、沉积物和悬浮颗粒物中的大体分布趋势为悬浮颗粒物>沉积物>表层水,沉积物中的污染物有再次释放到水体中的趋势.

大宝山矿区水体中重金属的行为研究

广东大宝山矿区矿山废水的排放使周边生态环境遭受了严重的破坏。水体中重金属Cu、Zn、Cd和Pb的溶解态浓度分别达到13.82、50.83、0.103和2.91 mg.L-1。Cu、Zn、Cd和Pb的溶解态和悬浮态含量沿河流主干道断面呈相似的空间分布规律,上游都是沿水流方向降低,下游因吸附于悬浮物中的重金属重新释放略有增加。悬浮物中重金属元素的化学形态提取和扫描电镜能谱分析(SEM/EDAX)表明:4种重金属元素都以残渣态为主要存在形态,其次为可还原态,个别断面的Cd可还原态甚至超过了残渣态的含量,说明该水体这4种元素对环境都有一定的潜在威胁性。

净水工艺中蠕虫的分布规律和污染类型

对珠江地区B水厂净水工艺中蠕虫的分布进行了现场调查,并结合净水工艺特征和检出蠕虫的生活习性等,对其分布规律和污染类型进行了研究。结果表明:B水厂净水工艺中蠕虫优势种属为仙女虫、线虫和摇蚊幼虫。仙女虫虽然有88.4%可被混凝沉淀和砂滤拦截,但进入BAC池后会大量孳生,出水平均密度高达18.94个/m3。各净水单元均对线虫有较好的拦截效果。摇蚊幼虫虽然也能被净水工艺有效拦截,但会在沉淀池大量孳生。从污染类型来看,线虫以原水输入的外源型污染为主,仙女虫和摇蚊幼虫则以二次繁殖引起的内源型污染为主。其中仙女虫污染暴发位置在BAC池,摇蚊幼虫则在沉淀池。净水工艺中蠕虫分布规律和污染类型均与蠕虫生活习性和净水工艺特点相关。

涡河干流水污染时空分布特征与水质动态评价

涡河是淮河流域严重污染的支流之一。对涡河干流主要污染参数NH3-N、BOD5、CODCr、TP、砷、氟化物的监测分析,表明涡河干流水污染具有显著的时空变化特征,污染参数表现为春季最高,秋季最低,由春季向秋季逐渐降低,然后又逐渐升高的"Ⅴ"字型变化规律,且在各采样断面各种污染参数季节变化特征具有较好的一致性。空间分布上表现为上游高、下游低,呈上游向下游逐渐降低的分布态势。模糊综合评价结果表明,涡河干流水污染严重,绝大多数河段全年为V类水质,已失去或大部分失去生活饮水和生产性用水的价值。涡河流域水资源严重污染及其时空分布特征,是流域自然过程与人为活动强干扰耦合作用的结果。

我国地下水质量分布特征浅析

以新一轮《全国地下水资源评价》项目为依托,以几十年地下水化学资料和水文地质资料为基础,对我国地下水质量进行了综合评价,阐述了我国地下水质量分布特征,简要分析了其成因,并提出了预防地下水水质恶化的建议。我国地下水质量总体状况较好,但局部质量低下,区域分布差异很大,是自然地理、地质、水文地质条件、人类活动等因素共同作用的结果。作者认为要想改善地下水质量就要合理开发利用地下水资源,合理布局工农业,并建立和完善地下水质量监测和预警系统。

基于负梯度法的供水管网污染源识别

利用负梯度法研究供水管网突发污染事故时污染源识别问题.首先针对供水管网的污染源识别问题构建最优化问题数学模型,然后用EPANET作为内嵌的水质模拟计算引擎,沿着目标函数的负梯度方向进行问题的最优解搜索,并针对管网算例,对污染源侵入时间、地点和侵入过程进行计算求解.分析差分步长、梯度求解方法等因素对问题求解效率的影响,结果表明采用基于水质模拟的差分法求解梯度向量并以水质公差作为差分步长,具有最好的求解效果.

供水管网大口径管道管垢中污染物分布的径向差异

以管龄为11年的城市主供水管道上的DN300球墨铸铁管为研究对象,采用扫描电镜(SEM)、能谱分析(EDS)、晶体衍射结构分析(XRD)等手段对其径向不同位置的管垢进行了表征,并分析了其各类金属与有机污染物的分布差异.结果表明:管道下部的管垢总量高,平均粒径大.重金属在空间上的分布明显不同,铁、锰、锌、铅、铜和铬在上部的管垢中含量最高,而下部管垢中,铝的含量最高,该分布与管垢中其来源密切相关.管垢中累积了多种的有机污染物,除了微生物代谢形成的烃类物质之外,还累积了藻类的代谢产物及外源有机污染物,不同位置上出现的有机污染物类型也有所差异.该研究结果对将来饮用水管网生物化学安全的研究方法提出了更高的要求,并为管网的饮用水安全保障提供了理论依据.

供水管网突发污染试验模拟及污染源定位研究

以供水管网模拟系统为试验平台,采用多点投加高浓度次氯酸钠溶液模拟污染物扩散的方法进行了试验研究与理论分析.通过实测监测点污染信息,利用改进的模拟-优化反追踪模型进行污染源定位并分析管网拓扑结构等影响因素对模型效率及准确率的影响.研究表明,在影响因素合理表达条件下,可以实现模型的高准确率.

污染物在填埋场底部非饱和土中的一维扩散解析解

为了揭示非饱和状态时污染物在填埋场底部土层中的运移规律,建立了污染物在非饱和土中的扩散模型。模型考虑了零浓度和零通量等下边界条件。在假设土层体积含水量随深度线性分布的基础上,利用分离变量法结合广义正交理论推导了该模型的解析解。解析解计算结果和有限元软件COMSOL Multiphysics 4.2的计算结果符合很好,并可退化到稳态解。100年时非饱和土底端污染物通量为91g/ha/a,是孔隙度0.3时饱和土底端通量(63g/ha/a)的1.4倍,是孔隙度0.6时通量(126g/ha/a)的0.7倍。当土层上下端总体积含水量一定时,同一时刻土层底部污染物相对浓度随顶端含水量增大而减小;土层底部污染物通量变化则很小。本文解析解可用于复杂数值模型的检验,实验数据的拟合和填埋场防渗系统的初步设计等。

基于用户水质投诉信息的供水管网污染源追踪定位

突发性水污染事故事发突然,污染物扩散迅速,对供水管网水质安全危害巨大.在缺乏足够水质监测设备的城市,用户对管网的水质投诉信息可及时反映管网水质情况.根据用户水质投诉的位置信息,利用改进的污染矩阵法查找管网候选污染源节点,再通过概率理论分析各候选污染源节点中是污染源的可能性,最后采用波达法则和数据标准化法两种方法评价最具可能性污染源.该方法的可行性和有效性通过某市管网实例进行了验证.

基于用户水质投诉信息的供水管网污染源的追踪定位

用户对水质异常情况的投诉是反映供水管网整体水质状况的重要信息,但由于投诉信息具有滞后性、非量化等特征,目前尚未有基于这些信息的管网污染源识别方法.基于模式识别理论,提出了一种根据用户投诉信息追踪定位污染源的方法.该方法首先根据投诉节点的位置信息确定污染源候选节点集合,通过水质模拟确定候选节点发生污染后的用户水质投诉顺序,并以此为基础构建模式识别神经网络.考虑到用户投诉信息的特点,采用有噪声的样本对神经网络进行训练,并对不同类型噪声的样本进行测试.结果表明,训练后的神经网络可以有效地识别用户投诉信息模式,进而确定污染物注入位置.

水库突发性污染事故水质影响过程分析

为了有效地控制突发性水污染事故带来的危害,以东北某大型水库为典型研究案例,综合考虑水库水文、气象条件和污染物迁移特征,拟定典型工况,基于已建立的三维水动力和水质耦合模型,模拟分析突发性污染事故发生后库区污染物三维空间分布及随时间变化的特征。结果表明:受入库流量和全年主导风向东北风的影响,总体上污染物随着水流沿西南岸线向坝址方向扩散,且污染物的超标面积逐渐增大;但随着流程的增加,污染物的浓度逐渐减小。通过对水库水质的数值模拟,定量掌握了水库水质实时状态以及污染物空间分布,可以为有关部门制定与实施应急预案提供相关的技术依据。