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| Regional distribution of the increase in failure rate (freq) for different temperatures (upper), rain deficit (middle) and wind speed (lower) for all pipe materials. Four classes of each weather parameter are shown from left to right.
Source publication
The influence of the weather parameters of temperature, wind and drought on pipe failure of drinking water distribution pipes was studied for the Netherlands. Several data sources were used relating weather effects to pipe failure: pipe failure data, regional weather data from different weather stations in the Netherlands, soil settlement data obta...
Context in source publication
Context 1
... regional distribution of failure rates is shown in Figure 2, In addition, the regression is conducted for only PVC and only AC pipes. The performance of the prediction for the validation set is relatively low (Table 1), however, some valuable insights into the explanatory variables can be obtained. ...
Citations
... Climate change-driven behavioral shifts, like varying heating and cooling requirements, can also impact patterns of water usage. Elevated demands for water can lead to a rise in internal pressure within watermains, which, in turn, may contribute to the likelihood of pipe failures [6]. ...
The state of watermain systems is intrinsically linked to climate factors such as fluctuations in temperature and variations in rainfall. However, the integration of these climate-related factors into watermain failure prediction models, with a specific focus on climate change impacts, remains insufficiently explored. In response to these challenges, this research incorporates the potential effects of climate change on the frequency of watermain breaks by utilizing machine learning techniques, including K-Nearest Neighbours, Random Forest, Artificial Neural Network, and Extreme Gradient Boosting. By leveraging projected climate trends, the models provide actionable intelligence that can inform the development of more robust maintenance and rehabilitation strategies.
... In the larger WDN, both regressors worked perfectly, with RF performing slightly better. Wols et al. (2018) employed a gradient boosting regressor for predicting the failure rate in 97,000 km of water pipes in the Netherlands, which is the largest data set in terms of pipe length, in this review. They used diameter, age, material, soil type, and regional weather data, e.g., mean daily air temperature, maximum daily wind gust at ground level, daily precipitation amount, and potential evapotranspiration (i.e., rain deficit). ...
his paper provides a comprehensive review of tree-based models and their application in condition assessment and prediction of water, wastewater, and sewer pipe failures. Tree-based models have gained significant attention in recent years due to their effectiveness in capturing complex relationships between parameters of systems and their ability in handling large data sets. This study explores a range of tree-based models, including decision trees and ensemble trees utilizing bagging, boosting, and stacking strategies. The paper thoroughly examines the strengths and limitations of these models, specifically in the context of assessing the pipes’ condition and predicting their failures. In most cases, tree-based algorithms outperformed other prevalent models. Random forest was found to be the most frequently used approach in this field. Moreover, the models successfully predicted the failures when augmented with a richer failure data set. Finally, it was identified that existing evaluation metrics might not be necessarily suitable for assessing the prediction models in the water and sewer networks.
... Kakoudakis et al. (2018) used weather conditions as explanatory factors to construct an ANN. A study conducted in the Netherlands (Wols et al. 2019) also evaluated weather conditions and concluded that temperature affected the performance of asbestos cement and cast iron pipes. A recent study presented an integrated water management system, using both operational and external data as input (Bettin 2023). ...
... Continued Losses Due to Illegal Use, Estimation of Leakage Components with Explosive and Background Estimates, Estimation of Leakage and Establishment of Water Balance Based on Minimum Night Flow, GIS Based Water Balance Analysis, Water Balance Calculation Comparison with Different Calculation Methods, Analysis of Components That Need to be Reduced Priority According to the Water Balance Table, Monitoring Water Consumption and Resource Efficiency, GIS-based Integrated Water Loss Management Model, Definition of Economic Leakage Level Number of failures, Probability of failure, Time-to-failure, Risk of failure, Barton et al. Date of failure, Cause of failure, Pipe material, Pipe installation year and pipe diameter, Soil type, Mean daily air temperature, Maximum daily wind gust at ground level, Daily precipitation amount, Potential evapotranspiration, maximum daily wind gustWols et al. (2019) ...
Water utilities are affected by various social, environmental, and technological factors and are increasingly required to enhance their infrastructure and long-term efficiency. Performance indicators are useful tools for assessing the operational, financial, environmental, and social aspects of water systems. Given this background, the author reviewed the literature on performance indicators for the water sector and summarized the research trends as follows. As a perspective, there are a lot of good mathematical and theoretical studies on distribution pipes and leakage management. Future research should address the problems of water utilities, by using multiple levels of performance indicators including social and environmental context in the long term. Asset management and utility management studies address diverse and current problems faced by water utilities. However, there is still room for improvement in standardizing the methodology for data collection, processing, and integration. In addition, it is recommended for future research, to include carbon neutrality aspect, to include pipeline materials and soil information in leakage management, to extend asset management studies to treatment plants, with including additional indicators about human and financial resources.
... Environmental factors, including climatic and soil conditions, can also trigger pipe failure (Barton et al. 2019;Bruaset and Saegrov 2018;Gould et al. 2011;Wols and Van Thienen 2014a;Wols et al. 2019). For example, swelling and shrinking clayey soils can damage critical infrastructures, such as water pipes (Farewell et al. 2018). ...
... In contrast, previous studies (Barton et al. 2020;Hu and Hubble 2007;Wols et al. 2019) have noted that the failure rate of AC pipes increases in summer, owing to soil moisture deficiency and soil movement (Arsénio et al. 2015). Chowdhury and Rajput (2016) observed that the failures of carbon steel, DI, and PE pipes are relatively higher during summer. ...
... Chowdhury and Rajput (2016) observed that the failures of carbon steel, DI, and PE pipes are relatively higher during summer. However, Wols et al. (2019) reported that the failure rates of DI, PVC, and GCI pipes increased as the temperature decreased. Furthermore, temperature has no significant impact on the failure of PE water pipes (Wols et al. 2019). ...
A growing population and urbanization place increased demands on water supply and distribution networks. Pipelines are one of the most critical components of water supply systems. It is, therefore, necessary to identify the relevant factors that affect the deterioration of water distribution pipelines. This will help decision makers in future planning and prioritization of the required maintenance. In this study, a systematic review is performed to identify critical factors that affect the failure of water pipelines. A meta-analysis is conducted to determine the relative importance of each factor that contributes to pipe failure. In addition, the source of contradictory results across studies is investigated. The results show that climatic factors, such as air temperature, minimum antecedent precipitation index, and net evaporation, contribute to water pipe failure. Additionally, the results of subgroup meta-analyses show that primary sources, such as pipe material and water pipe size, can lead to high heterogeneity across studies. This study is expected to help water utility owners to collect relevant data and make timely renewal decisions.
... Increased temperatures can also influence buried infrastructure, mostly in indirect ways. Distribution pipe failure is a complex process, but it has been widely reported that some pipe materials (iron, ductile iron, and steel) are most likely to fail during cold months due to increased frost loads, while asbestos cement pipes fail more often during hot and dry months due to decreased soil moisture (Kleiner and Rajani 2002;Harvey et al. 2014;Khan et al. 2015;Barton et al. 2019;Wols et al. 2019). Thus, the type and timing of pipeline failures may change in the future as extreme weather events increase (Barton et al. 2019). ...
... The impacts of convective storms on infrastructure include power outages at water treatment plants and pumping stations, reduced structural integrity of dams, rupture of water lines and storage tanks, and flooding of treatment plant infrastructure (Khan et al. 2015;Bertone et al. 2016). High winds have been linked to increased pipe failure due to disturbances caused by uprooted trees (Wols et al. 2019). High winds can also indirectly impact water treatment and distribution infrastructure by damaging electrical infrastructure and buildings (Swanson et al. 2021). ...
... Average temperatures, including winter temperatures, are expected to increase in Canada due to climate change, as are the number of frost-free days (Bush and Lemmen 2019), which may shift existing seasonal patterns in pipe breaks across Canada. Some types of pipes, notably asbestos cement, are more likely to fail at higher temperatures (Wols et al. 2019), and it is Fig. 9. Number of BWAs issued during the study period due to E. coli, total coliforms, turbidity, and inadequate disinfection residual plotted by the month in which they were issued. Fig. 10. ...
A boil water advisory (BWA) informs the public that there is an increased level of risk associated with their water and that they should boil it before consuming. Studies show that small communities in Canada are particularly likely to experience repeat and long-term BWAs. Climate change has led to changes in precipitation and temperature patterns, leading to region-specific impacts such as increased frequency, severity, or variance in floods, forest fires, droughts, freezing rain, and sea water intrusion. Academic and non-academic “grey” literature was reviewed to establish the most likely impacts of climate change on water treatment and infrastructure. Anonymized data from public drinking water systems in Canada was analyzed to determine the most common causes of BWAs between 2005 and 2020. Most BWAs reported were related to breakdowns/malfunctions along the distribution, though inadequate disinfection residual and turbidity or coliforms in the treated water were also common. Furthermore, statistical analysis of the data showed seasonal trends in some of these parameters. The results of this study suggest that increased precipitation, flooding, permafrost degradation, and forest fires are likely to have significant impacts on water safety in Canada.
Highlights
Climate change effects are expected to worsen many current water challenges.
Climate change will disproportionately impact small, rural, and remote water utilities.
Water distribution systems are the main source of water safety risk in Canada.
Groundwater-supplied systems experience a disproportionate number of BWAs.
Seasonal trends in BWA reasons provide opportunities for targeted mitigation.
... The identified themes include 'Failure modelling of watermains' (number of studies = 54), 'Water freeze behaviour and freeze protection techniques' (n = 9), 'Climate-related resilience and risk management of watermains' (n = 4), and 'Cost modelling for watermain repairs' (n = 2). The primary theme, which is 'Watermain failure modelling', is further comprised of 4 sub-themes including 'Watermain failure considering climatic conditions' (n = 30) (Kakoudakis et al., 2018;Fuchs-Hanusch et al., 2013;Wols and Van Thienen, 2014a;Wols et al., 2019;Laucelli et al., 2014;Gould et al., 2009;Bruaset and Saegrov, 2018;Rajani et al., 2012;Friedl et al., 2012;Gregersen, 1984;Habibian, 1994;Rajani et al., 2011), 'Watermain failure considering a (Boulaire et al., 2009;Rajani and Tesfamariam, 2007;Almheiri et al., 2021;Kutyłowska, 2019;Fan et al., 2022a;Fan et al., 2022b;Yang et al., 2011;Zamenian et al., 2017;Kleiner and Rajani, 2010), 'Effect of climate change on watermain failure' (n = 7) (Wols et al., 2013;Zywiec et al., 2019;Goodchild et al., 2010;Wols and Van Thienen, 2014b;Nelson et al., 2012), and 'Watermain failure considering soil conditions' (n = 9) (Hu and Vu, 2011;Shao and Zhang, 2008;Hudak et al., 1998;Shi et al., 2020). Some of the studies associate with multiple themes and sub-themes, however, the two themes i.e., 'Watermain failure considering climatic conditions' and 'Watermain failure considering a wider set of conditions' are mutually exclusive. ...
... Climate change can also affect soil settlements which typically happen in warm and dry periods. For instance, for the northern and western parts of Netherlands, it is expected that the climate change may increase soil settlements by an additional 10-30 cm by 2050 (Wols et al., 2019). Two studies have considered the effect of climate change on watermain failure through soil settlements (Wols et al., 2013;Wols and Van Thienen, 2014b). ...
... Some of the reviewed studies within the 'Failure modelling of watermains' theme have used GIS method (n = 6) (Wols et al., 2013;Wols et al., 2019;Boulaire et al., 2009;Fan et al., 2022b;Kimutai et al., 2015;García et al., 2018). For the modelling of soil effects on watermains, some studies (n = 4) used Winkler type pipe-soil interaction model (Wols et al., 2013;Rajani and Tesfamariam, 2007;Wols and Van Thienen, 2014b;Shao and Zhang, 2008). ...
Watermains are both directly and indirectly affected by climatic conditions such as temperature and precipitation. Research has been conducted to understand and model the effects of climatic conditions on watermain breaks. However, review studies to map the knowledge development in this area, to identify key achievements and limitations of previous studies are missing, and are addressed in this study. This review uses a mixed systematic and scientometric analysis to establish the research trends, contributions, methods, and covariates employed by previous studies related to climatic impacts on watermain deterioration. Web of Science and Scopus database is primarily employed to identify 70 relevant studies on the subject matter. These studies have been mostly conducted by institutions based in Canada, USA, and Europe. There is a general lack of collaboration among different institutions conducting research in this area. Studies in the subject matter are published from 1982 onwards, however, significant number of studies per year can only be noticed from 2005 onwards. Previous studies have been mostly focused on the modelling of watermain failure and have used statistical methods, and data-driven and artificial intelligence (AI) approaches for failure modelling of watermains under climatic conditions. For testing and validation of research data, studies have employed correlation analysis, performance evaluation metrics, and descriptive statistics. Typically, climate-related variables used in studies include temperature, moisture, and precipitation. Reviewed studies have considered cold (66%), hot (31%), and dry (13%) climatic conditions. Studies have investigated watermains made of metal (56%), plastics (43%), and Concrete and Asbestos cement (31%). Future studies are recommended to consider Data-driven and AI approaches in research design; pay attention to watermains in climatically vulnerable and massively populated regions; and consider climate risk assessment and the impact of climate change and extreme weather conditions on watermains.
... For example, Żywiec, Boryczko 1 calculated the failure rate at different temperatures in the study of water system in Poland. Wols, Vogelaar 19 used the statistical analysis to study the influence of temperature, precipitation, and wind speed on the water system's failure rate. Although different models have been used to study the impacts of climate factors, only a few studies have used these models to predict the influence of future climate change. ...
Climate change is projected to have profound impacts on the resilience and sustainability of built infrastructure. This study aims to understand the impacts of climate change on water supply systems and to facilitate adaptive actions. A premium database maintained by the Cleveland Water Division, Cleveland, Ohio, USA is analyzed. It contains 29,621 pipe failure records of 51,832 pipes over the past 30 years, representing one of the largest dataset in current literature. From the database, pipe failure rate models have been developed for water pipes made of different types of materials at different ages. The influence of climate (temperature and precipitation) on fragility of water pipes are obtained. Based on the developed climate-fragility failure rate models, the impacts of climate change on the water systems located in different geographic regions are evaluated by predicting the failure rate and number of failures in the water systems in the next 80 years (2020 to 2100). Climate models are used to predict weather under different climate change scenarios. The results demonstrate that the impacts of climate change on water supply system are likely complicated and are dependent upon factors such as the geographic location, pipe material, pipe age, and maintenance strategies. Water pipes in the cold regions may experience fewer number breaks due to the warmer weather and less severe winter, whereas those located in the hot regions may experience more failures associated with more corrosion. Different pipe replacement strategies are compared, which demonstrate the importance of considering the aging of water supply system in future maintenance decisions. This study enriches current understandings on the impacts of climate change on the water systems. The results will help water utilities to design climate change adaptation strategies.
... It consists of a pipe's age, material, failure rate, and failure probability, denoted as s t ¼ hage; mat; k; pf i. The failure rate concerning the material is obtained from [41], whereas the probability of failure is elicited from Eq. 4. Besides material, the failure rate is also dependent on the length of the pipe as longer pipes are likely to experience more failures compared to the smaller pipes [42]. ...
Cost-effective asset management is an area of interest across several industries. Specifically, this paper develops a deep reinforcement learning (DRL) solution to automatically determine an optimal rehabilitation policy for continuously deteriorating water pipes. We approach the problem of rehabilitation planning in an online and offline DRL setting. In online DRL, the agent interacts with a simulated environment of multiple pipes with distinct lengths, materials, and failure rate characteristics. We train the agent using deep Q-learning (DQN) to learn an optimal policy with minimal average costs and reduced failure probability. In offline learning, the agent uses static data, e.g., DQN replay data, to learn an optimal policy via a conservative Q-learning algorithm without further interactions with the environment. We demonstrate that DRL-based policies improve over standard preventive, corrective, and greedy planning alternatives. Additionally, learning from the fixed DQN replay dataset in an offline setting further improves the performance. The results warrant that the existing deterioration profiles of water pipes consisting of large and diverse states and action trajectories provide a valuable avenue to learn rehabilitation policies in the offline setting, which can be further fine-tuned using the simulator.
... 0.05) (Supplementary material, Table S4). At an average daily pressure scale, higher internal pipe pressure contributed to higher pipe failure rates (Wols et al. 2019). The age of pipes with higher pressure rating was high and might explain the lower failure probability since the distance from the road and pipe diameter was somewhat similar. ...
... Therefore, pipe failure caused by intermittent and continuous water supply was inconclusive to enable an investigation of the influence of the spatial distribution of pressure differences across given pipe sections. However, from the authors' experience more resolved pressure data is not usually captured in failure records, and not usually included in developing pipe failure models (Winkler et al. 2018;Motiee & Ghasemnejad 2019;Wols et al. 2019;Kerwin et al. 2020) and might require installation of pressure sensors at multiple points within the WDN, unaffordable for many water utilities. ...
Statistical models can be used as proactive approaches to pipe failure management for the satisfactory and efficient functionality of a water distribution network (WDN). The study aimed to develop two logistic regression models using historical data and evaluated them based on prediction accuracy, receiver operator characteristics (ROC), and area under the curve (AUC). Pipe sizes ranging from 150 mm to 350 mm in the WDN were adequate to prevent pipe failure. However, a 250 mm pipe diameter had the lowest failure probability. Old pipes had a lower failure probability than new pipes. Although it was evident that the installation design of water pipes is changing from steel to unplasticized polyvinyl chloride (uPVC), steel pipes had a lower failure probability than uPVC at the same depth from the soil surface. Pipes buried in gravel with a small diameter had a lower failure probability than those in clay of a bigger diameter. With a median pipe age of 8 years in the WDN and greater class weight on pipe failures, the binomial logistic regression model had better performance (accuracy – 96.9%, AUC – 0.996) than the multinomial logistic model (accuracy – 90.9%, AUC – 0.992), representing reliable model predictions. The models can be used to modify data collection protocols to better identify potential water pipes that require maintenance or replacement.
HIGHLIGHTS
Pipe failure is intricate and depends on physical, environmental, and operational pipe attributes.;
250-mm pipe diameter had the lowest failure probability.;
Old pipes have a lower failure probability than new pipes.;
Pipes with low population density had a higher failure probability than those in densely populated areas.;
Binomial logistic regression model had better performance than the multinomial logistic model.;
... Asnaashari et al. (2009) found pipe length and buried depth were the main factors for bursts in ductile iron and PE pipes, and pipe wall thickness was one of the main factors for bursts in ductile iron pipes. Wols et al. (2019) proposed that pipe burst rates are higher for cast iron pipes at low temperatures and asbestos-cement pipes at high temperatures. With the in-depth study of the pipe burst mechanism, factors like diameter, material, temperature, etc. are more and more considered to develop pipe burst prediction models, which is helpful for the improvement of burst prediction accuracy. ...
Pipe bursts in water distribution systems (WDSs) lead to large water losses, pollution risks, and public discontent, attracting widespread attention from researchers and water utilities around the world. This study provides insights into the knowledge structure and emerging trends of pipe burst research from a bibliometrics perspective. We used 845 original research and review articles on pipe bursts in the period of January 1991 − June 2022 that cited 16,813 references in the CiteSpace® software for reference co-citation analysis. The results indicate that the knowledge structure of pipe burst research is classified into four categories including pipe burst mechanism, pipe burst detection, pipe burst prediction, and use of sensors. The entire research on pipe bursts advances remarkably. First, pipe burst prediction is the core research category with continuous efforts to improve prediction performance. Second, pipe burst detection is likely to define new research focus to extend existing research focus on pipe burst prediction. Third, computer science and technology are widely and increasingly applied in burst process simulation and data pattern analysis to increase accuracy and effectiveness. This study grasps a full view of current achievements in pipe burst research and provides guidance for future research directions and technological development.
