Evaluating pipe failure risk in water distribution networks using GIS fuzzy overlay, ROC curves and machine learning logistic regression

Special Issue on the Battle of Background Leakage Assessment for Water Networks

Increases in the growth of urban regions along with climate change have contributed to a scarcity in water resources. For arid regions, this problem may be aggravated by inadequate management plans and a lack of proper data collection related to the geographical location of water distribution networks. A possible solution is the use of geographical information system (GIS) as a tool in decision-making process in the field of water distribution management. Coupling external hydraulic calculation models with GIS can further enhance this management tool. The current study used these tools in assessing the performance of a drinking water distribution network of an urban cluster in Tlemcen Algeria. A methodology was developed by coupling GIS to a hydraulic calculation model (Mike Urban). The results showed that it is possible to obtain an alphanumeric description of the pipes, tanks, and all the accessories constituting the network. Design irregularities in the Tlemcen urban cluster’s network were identified. The approach adopted in this work effectively contributes to the management of water distribution networks using GIS.KeywordsGISManagementModelingWater distribution network

Worldwide, water utilities are finding it increasingly difficult to meet the growing water demand. The problem, already acute in view of the urbanization trends, is compounded by the age of the infrastructure: one third of water utilities have 20% or more of their pipelines nearing the end of their useful life. This paper outlines an innovative approach for improving leakage management processes through the adoption of data analytics techniques and hydraulic simulation. More in detail, the aim is to provide analytical leaks localization and correspondent severity estimation in order to reduce time and costs for interventions and rehabilitation while improving asset management. The technical solution has been developed as a set of web services able to interoperate with other technological systems usually adopted by urban water distribution utilities, such as Supervisory Control And Data Acquisition (SCADA) system, Customer Information System (CIS), Geographical Information System (GIS) and Hydraulic Simulation tools. This paper presents some results obtained by the application of the approach to a real case study and also proves how its effectiveness may be improved in a sectorized water distribution network.

The water distribution industry is facing challenges of water leakages in drinking water distribution networks. Mainly high pressure and the deterioration of ageing pipes and fittings cause the increase of the leak, and the consuming water and the number of bursts in the network. This study based on hydraulic and geospatial information system model has been suggested to estimate the probability of leaking for each pipe segment in the selected water distribution network. In this model, the likelihood of leaking is illustrated using pressure, age, length, diameter and slope of the pipe. The system is implemented with GIS tools, WaterGEMS, Google Earth Pro and Minitab software. Google Earth Pro is used to design the pipe network. The hydraulic model creates with WaterGEMS is integrated with ArcGIS. Minitab is used in elaborating the linear regression model, which is proposed to gain the leakage probability. The formed methodology is applied in identifying vulnerability ranges that have been identified for the pipe segments in the water distribution network. For the adducting results, a Geographic Information System (GIS) is used. Using the capabilities of this GIS model, the colour coded map represents the vulnerability ranges of the areas. The gained results can be used in detecting the most leakage areas and control pipeline leakage in the water distribution network. This methodology is developed to provide maximum protection against water leaks in the selected region.KeywordsGeographic information system (GIS)WaterGEMSGoogle earth proMinitab

Visual analytic hierarchical process for in situ identification of leakage risk in urban water distribution network

Reliability analysis of urban water distribution networks (WDNs) has become a prerequisite for allocation of funds for their installment, upgradation and maintenance, etc. Extensive research has been carried out in the field of mechanical and hydraulic reliability. However, another important field that deserves attention is the water quality reliability analysis in a WDN. In the past, a single heavy disinfectant dosage at the treatment plant was considered sufficient to deliver safe drinking water to the consumers. However, with the growing awareness of negative impacts of chemicals on human health, it has become necessary to restrict the maximum disinfectant residual in water. Also, a minimum level of residual disinfectant concentration is to be maintained throughout the WDN to safeguard water from possible contamination. This necessitates boosting of disinfectant in a WDN. Chlorine is the most commonly used disinfectant in urban water supply schemes. Booster chlorination (BC), therefore, has acquired a greater significance in urban WDNs. In the present study, a methodology has been suggested to determine the minimum number of BC stations in a WDN to satisfy the residual chlorine concentration goals at the consumer nodes. The optimal location of BC stations is identified for minimizing the required dosage of chlorine. Thereafter, the reliability analysis of water quality is carried out when the BC stations are subject to failure for a fully operational WDN. The methodology has been illustrated with the help of a hypothetical WDN.

Urban water distribution networks (WDNs) are increasingly vulnerable to diverse disruptions, including pipe leaks/bursts and cyber–physical failures. A critical step in a resilience-based approach against these disruptions is the rapid and reliable identification of failures and their types for the timely implementation of emergency or recovery actions. This study proposes a framework for sensor placement and multiple failure type classification in WDNs. It applies a wrapper-based feature selection (recursive feature elimination) with Random Forest (RF–RFE) to find the best sensor locations and employs an Autoencoder–Random Forest (AE–RF) framework for failure type identification. The framework was tested on the C-town WDN using the failure type scenarios of pipe leakage, cyberattacks, and physical attacks, which were generated using EPANET-CPA and WNTR models. The results showed a higher performance of the framework for single failure events, with accuracy of 0.99 for leakage, 0.98 for cyberattacks, and 0.95 for physical attacks, while the performance for multiple failure classification was lower, but still acceptable, with a performance accuracy of 0.90. The reduced performance was attributed to the model’s difficulty in distinguishing failure types when they produced hydraulically similar consequences. The proposed framework combining sensor placement and multiple failure identification will contribute to advance the existing data-driven approaches and to strengthen urban WDN resilience to conventional and cyber–physical disruptions.

Background and Objective: Urban water distribution networks consider as one of the essential infrastructural facilities and equipment in urban areas. The pipes are one of the primary and essential components of a water distribution network break during operation due to various factors. So, developing models for pipes failure rate prediction can be one of the most crucial tools for managers and stakeholders to the optimal operation of the water distribution network. In the last decade, various studies have performed to predict the failure rate of water distribution pipes using statistical and soft models - each of which has strengths and weaknesses. This study aims to present a new approach based on the development of a hybrid prediction model, considering the capabilities of soft and statistical models, to more accurately predict the water distribution network pipes failure rate compared to statistical and soft models used in previous research. Material and Method: In order to achieve the study goals, 4-year (2015-2018) time duration statistics of Gorgan water distribution network characteristics including diameter, length, age, depth of installation, and the number of pipe failures used to predict future pipes failure rates. To modeling the pipe failure rate of the investigated network, five different models, including three statistical models (linear regression, generalized linear regression, support vector regression) and two soft models (feed-forward neural network, and radial basis function neural network) has studied. Optimal parameters of the models were selected based on appropriate statistical error indicators, including correlation coefficient (R), Mean Square Error (MSE), and Correlation Mean square error Ratio (CMR) for the training and testing data. In order to select the best model from different models to predict the failure rate of network pipes, the values of R and MSE indicators of the above models were calculated in the validation stage and compared with each other. Finally, to predict pipes failure rate more accurately, a new approach is developed based on the hybrid prediction model in which the predicted values of pipe failure rates by statistical and soft computing models considered as independent variables of the best model inputs and the observed values of failure rates as dependent variables of the best model outputs. Results: Comparing the values of R and MSE indicators of each statistical and soft computing model used in this study in the validation phase show that these models cannot predict the pipes' failure rate with reasonable accuracy. Feed forward neural network model with the highest R = 0.69 and the lowest MSE = 0.062 values has the best estimates. Using the new approach developed based on hybrid soft and statistical models, the R index is equal to 0.96, and the MSE index is equal to 0.046. Conclusion: A significant increase in the R index (39%) and decrease in the MSE index (25%) through using the proposed hybrid approach compared to the feed-forward neural network model demonstrates that using the new approach provides perfect accuracy prediction of the pipes failure rate of the water distribution network.

The main objectives of this paper are, designing and balancing of Water Distribution Network (WDN) based on loops hydraulically balanced method as well as using Geographical Information System (GIS) methodology with the contribution of EPANET. GIS methodology is used to ensure WDN’s integrity and skeletonized a proper and functional WDN by using Network Analyst utilizing the geometric network and topology network by hierarchical geo-databases. The problem is to make WDN hydraulically balanced by applying WDN balancing method. For that reason, we have analyzed water flows in each pipe and performed the iterations process on loops in order to make the algebraic summation of head loss“h_f” around any closed loop zero. In case, the summation of pipe flows must be equal to the flow amount entering or leaving the system through each node. At each iteration, reasonable changes occurred at pipes flow until the head loss has become very small or fixed zero as (optimizes correction) by using excel sheet solver. Since this method is confirmed to be effective, simulations were done by using GIS and EPANET water distribution platform. As a result, we accomplished hydraulically balanced WDN. Finally, we have analyzed and simulated hydraulics parameters for the targeted area in Kabul city. Thus, determined successfully the hydraulics state of parameters around the network as a positive result. It is worth mentioning that, Hardy-cross method is being used for approaching more precise optimized correction and consequences concerning hydraulically-balanced and optimal WDN. This method can be done for complex loops WDN as well; the advantage of the method is simple math and self-correction. Managers and engineers who work in the field of water supply this methodology has been recommended as the more advantageous workflow in planning water distribution pattern.

In urban water infrastructure (UWI), information and communication technology (ICT) are presently concentrated on central facilities (e.g., treatment plant) or are installed at main points in the urban drainage or water distribution network, e.g., inlet points of district meter areas (DMA) or combined sewer overflow structures. In this regard, the Internet of Things (IoT) concept as part of smart city development enables a large-scale implementation of measuring equipment and allows the integration of decentralised elements into an overall controlled system. Consequently, reliable and suitable ICT is a key element for the exchange of measurement and control data as well as for the success of these systems. From a water engineering perspective, it is often difficult to choose the right ICT for the intended UWI application. Likewise, from an IoT technology perspective, it is often unclear what kind of UWI applications are feasible, making them difficult to efficiently implement. Aim of this work is to develop a first-decision making tool, which can be used by network operators, researcher, and stakeholders to support supervisory control and data acquisition (SCADA) development and to realise an efficient ICT system in the field of network-based UWI. In contrast to existing recommendations, our approach is based on a comprehensive review of required spatial and temporal resolution of measurement and control data for a wide range of different network-based UWI applications. Subsequently, this enables a targeted coordination with the properties of communication technologies (e.g., data rate, range, and quality of service) and leads to a significantly improved and integrative decision-making tool.Subsequently, we tested the functionality of the framework on two exemplary applications in UWI, namely (1) determining suitable communication technologies for an early warning system for leakage detection and localisation in water distribution networks (e.g., (W)M-Bus for water meters, LoRaWAN for water pressure sensors, and GPRS at inlet points of DMA), and (2) identifying feasible applications for an existing LoRaWAN network (e.g., monitoring micro-climate and automatic irrigation at nature-based solutions). Results from the framework application have been evaluated through a literature review on used communication technologies, and are found to be consistent with real-word applications. As conclusion, different communication technologies are necessary to satisfy different requirements associated with an integrative approach for “smart water cities”. Selected for possible publication in a Special Issue in the Journal of Hydroinformatics.

Effects of impeller geometry modification on performance of pump as turbine in the urban water distribution network

Hydraulic simulation models of water distribution networks (WDN) are routinely used for operational investigations and network design purposes. However, their full potential is often never realized because in the majority of cases, they have been calibrated with data collected manually from the field during a single historic time period and reflects the network operational conditions that were prevalent at that time. They were then applied as part of a reactive investigation. An urban water distribution network real time simulation system based on SCADA system using OPC (object linking and Embedding(OLE) for Process control) communication was built in this paper. In order to make real-time simulation of water distribution network, the real-time data was collected every 15 minutes, the real time data were received and sent into water distribution network simulation model by OPC communication of SCADA system. The real-time data included total head of reservoir, flow rate, pressure, pump operation information. The real-time simulation system can give timely warning of changes for normal network operation, providing capacity to minimize customer impact and comparing the simulation results with the real-time data collected. The real time simulation system of urban water distribution network solved the problem of data input and user interaction compare to traditional network model. It offers a way for the development of intelligent water network.

Sensor placement for disaster prevention for important users in urban water distribution networks is essential for post-earthquake monitoring and repair. Herein, we proposed a sensor placement approach for disaster prevention monitoring for important users, to (a) improve the fault diagnosis ability of the water distribution network and to (b) guarantee the function of emergency services for key nodes after an earthquake. First, an evaluation system of node users’ disaster prevention impact factors was presented to evaluate the node influence degree from three aspects: post-earthquake leakage, emergency support and topology structure; and the weight values of node users’ disaster prevention impact factors were obtained. Second, a post-earthquake hydraulic analysis model based on the pressure-driven demand was used to calculate the water shortage ratio of nodes. Third, using the three-way clustering integration method, the results of four clustering techniques were integrated to divide the monitoring domain in the water distribution network based on sensitivity analysis. Finally, on basis of the sensitivity matrix, the division of the monitoring area and the impact factors of node users’ disaster prevention were combined to place sensors for post-earthquake disaster prevention in the water distribution network. Detailed computational experiments for a real urban water network in China were performed and compared with the results of other traditional techniques to evaluate the performance of the proposed approach. The results show that the approach is better than traditional methods. It not only considers the actual hydraulic information of the water distribution network, but also the important user nodes after an earthquake, and is of great significance for emergency command and rescue and disaster relief after an earthquake in the city.

Water losses in urban water distribution networks (WDN) accelerate the deterioration of such infrastructures. The enhanced hydraulic modelling provides a phenomenological representation of WDN hydraulics, including the modelling of leakages as function of pipe average pressure and deterioration. The methodological use of such models on real WDN was demonstrated to support the planning of leakage management actions. Nonetheless, many water utilities are still in the process of designing flow/pressure monitoring, thus data available are not enough to perform detailed calibration of such models.This work presents a physically based approach for the calibration of WDN hydraulic models aimed at supporting leakage management plans since early stages. The proposed procedure leverages the key role of mass balance in enhanced hydraulic models and the technical insight on pipe deterioration mechanisms for various quantity and quality of available data. Two calibration studies of real WDNs demonstrate the feasibility of the approach and show that the distribution of leakages in the WDN does not much influence the pressure values, which confirms the need for flow measurements at monitoring districts for leakage and asset management.

Urban water distribution networks (WDNs) are facing serious leakage problems. As cities expand, the leakage localization burden on large WDNs gradually increases. Although methods have been widely researched, there is a lack of studies and successful applications for large-scale WDNs. To deal with this, a stepwise fast leakage localization Method, SFLLM, utilizing the `dynamic area narrowing down (DAND)' strategy and coupled leakage features (CLF) is proposed. The SFLLM includes a fast-and-dynamic stage using the DAND strategy to reduce the potential leakage area and an accurate localization stage. Only partial representative candidate locations are required to simulate leakages by DAND, and meantime CLF is used to analyze the leakage similarities so that the localization accuracy and efficiency can be improved. SFLLM was tested on a benchmark WDN, saving more than 88% of simulation by DAND strategy and achieving localization in 11 seconds. The results also proved the enhanced performance of CLF in ensuring the stability of the accuracy against various types of uncertainties that may occur in real WDNs. Moreover, three real burst leaks in an actual large-scale WDN were localized within 205 m in about 22 minutes by SFLLM, showing the method's reliable applicability in guiding field leak exploration.