No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Impact of weather conditions on pipe failure: A statistical analysis
Abstract
The occurrence of pipe failures in drinking water distribution networks may be influenced by weather conditions. In this work, a statistical analysis is performed to study the correlations between weather parameters and pipe failure in the Netherlands with the ultimate aim to predict the effects of climate change on network integrity. Failure data from a Dutch national failure database were divided into different cohorts, depending on type of pipe material, year of installation, and diameter class. Weather data related to temperature, drought, and wind were collected. Relationships between weather data and failure data were sought using a linear regression analysis and a frequency analysis. The latter analysis results in a weather variable dependent pipe failure frequency. The most obvious relationships were found between pipe failure and temperature. Failures in asbestos-cement (AC) and steel pipes increased during warm periods, which often simultaneously occurred when water consumptions were high. For cast iron pipes, failures increased at low temperatures. Drought parameters had a smaller effect on pipe failure than temperature, but still an increase in pipe failure was observed during dry periods for AC and steel pipes. No effect of weather conditions on pipe failure were observed for poly(vinyl chloride) and polyethylene pipes.
... Under freezing temperatures, ground swelling and multiple freeze and thaw cycles increase external loads and thereby pipe failure (Bruaset and Saegrov 2018). While Bruaset and Saegrov (2018) did not find an increase in break rates at higher temperatures, Wols and Van Thienen (2014) observed that greater water consumption and lower groundwater levels during hot dry summers impose additional internal and external loads, also causing more breaks. Both studies used linear regressions to quantify the correlation between weather and failure rates. ...
... Bruaset and Saegrov (2018) predicted failure rates for all materials of Norwegian systems (25,573 failures) based on the average temperature the preceding week, with a R 2 of 0.813. Wols and Van Thienen (2014) developed separate models for different materials of Dutch systems (10,325 failures) and found correlations only for certain materials, i.e., asbestos cement (R 2 0.54), steel (R 2 0.71) and cast iron (R 2 0.56). Other factors that might influence the impact of weather, such as soil type, were not considered. ...
... A spike in breaks is also observed in July with hot and dry summers. This pattern matches the accounts of Wols and Van Thienen (2014) who observed that greater water consumption and lower groundwater levels during hot dry summer led to more breaks. Overall, these results show monthly differences can be significant and can be better planned for in maintenance and repairs. ...
Deterioration of water infrastructure is a global challenge that jeopardizes water system ability to deliver water safely. While various factors affect watermain failure, previous studies have focused on common pipe attributes or general protection strategies. The main objective of this study is to examine the relationship between pipe break characteristics and system properties. Comprehensive data from thirteen Canadian water systems (over 60,000 failures) are examined with correlation and chi-squared analyses. Joint and fitting failures are most likely for pipes aged 20 years or less, and universal joints are most associated with joint failure. Pipes in clay and sand soils are more likely to break due to improper bedding and differential settlement, respectively. Furthermore, in the summer, accidental breaks of asbestos cement pipes are more likely, as are failures of pipes with collar joints and coal tar lined pipes. By exploring these relationships, the paper provides insights into opportunities for reducing water main failure, through improved design, maintenance and rehabilitation.
... 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. ...
... Another study in this theme investigating the time to failure of watermains used corrosion models (Rajani and Tesfamariam, 2007). Some studies (n = 9) in this theme have explicitly indicated the type of probability distribution used in modelling the failure trends including Poisson distribution (n = 5), normal distribution (n = 3), lognormal distribution (n = 3), triangular distribution (n = 2), Weibull distribution (n = 1), uniform distribution (n = 1), t distribution (n = 1), and gamma distribution (n = 1) (Wols et al., 2013;Wols and Van Thienen, 2014a;Wols et al., 2019;Bruaset and Saegrov, 2018;Boulaire et al., 2009;Zamenian et al., 2017;Wols and Van Thienen, 2014b;Wols and van Thienen, 2016;Kimutai et al., 2015). ...
... These covariates comprise of 'Evaporation and Evapotranspiration' (n = 5) (Wols et al., 2019), 'Soil moisture content' (n = 4), 'Dry density' (n = 3) (Hu and Vu, 2011), 'Relative Humidity' (n = 3), 'Dry Index' (n = 2) (Almheiri et al., 2020), and 'Plasticity index-soil' (n = 2) (Chan et al., 2015). 'Evaporation and Evapotranspiration' is measured in terms of 'Net Evaporation' (n = 2), 'Total Evaporation' (n = 1), 'Average Evaporation' (n = 1) (Gould et al., 2009), 'Potential Evapotranspiration' (n = 2) (Wols and Van Thienen, 2014a), 'Average Evapotranspiration' (n = 1), 'Net Evapotranspiration' (n = 1), and 'Total Evapotranspiration' (n = 1) (Gould et al., 2009). ...
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.
... One of the directions of this research is the water supply network failure analysis [1][2][3][4][5][6][7][11][12][13][14][15]. Over the years, many factors that affect the failure rate of the water supply network have been identified [3,[5][6][7]11,[16][17][18][19]. There can be distinguished internal (system) factors: pipe material, pipe diameters, age of the system, pressure in the water supply network, flow rate, quality of design, construction and operation of the system, and external (environmental) factors: climate (seasonality, climate change), weather conditions (temperature, rainfall, drought), soil and water conditions (type of soil, frost depth, groundwater level, corrosivity of the soil and groundwater). ...
... There can be distinguished internal (system) factors: pipe material, pipe diameters, age of the system, pressure in the water supply network, flow rate, quality of design, construction and operation of the system, and external (environmental) factors: climate (seasonality, climate change), weather conditions (temperature, rainfall, drought), soil and water conditions (type of soil, frost depth, groundwater level, corrosivity of the soil and groundwater). Research indicates that bigger failure frequency of water supply networks is observed in cold periods due to ground freezing, and in hot and dry periods due to increased water consumption, soil shrinkage, and ground settlements [11,17,18,[20][21][22][23]. The strongest relationships between the values of failure rate were observed for the factor associated with daily temperature [11,[16][17][18]24]. ...
... Research indicates that bigger failure frequency of water supply networks is observed in cold periods due to ground freezing, and in hot and dry periods due to increased water consumption, soil shrinkage, and ground settlements [11,17,18,[20][21][22][23]. The strongest relationships between the values of failure rate were observed for the factor associated with daily temperature [11,[16][17][18]24]. As the temperature drops, an increase in the failure rate values of the water supply network is observed. ...
As a part of the critical infrastructure, water supply systems must be characterized by an appropriate level of operational reliability and safety. One of the threats to this is the failure of the water supply network, influenced by many factors, among which we can distinguish internal factors related to the process of designing, construction and system operation, and external factors related to the impact of the environment. The paper presents the influence of negative daily temperature on the failure rate of the water supply network, taking into account the material of the pipes, their diameters, and the cause of failure. The research was carried out on operational data from the period 2004–2018 from the water supply network in a city located in south-eastern Poland. The relationship between the daily temperature and the failure rate of the water supply system has been shown. As the temperature values drop, the failure rate values increase. The biggest influence of the negative daily temperature on the water supply network failure rate is observed for cast iron pipes. PE and PVC pipes are more resistant to the influence of negative temperatures. The most common cause of failure is corrosion and unsealing of the pipes. Pipes with the diameters of 100, 150, 300, 350, and 400 mm in distribution and main networks turned out to fail most often. These results can be used by water supply companies to limit the influence of factors related to negative daily temperatures on the failure rate of the water supply network.
... World literature increasingly discusses often the failure rate of water and sewage systems, the causes of which are related to both intrinsic factors (age of pipes [64,65], material [66,67], material defects, errors in the process of building or designing the network [68]), environmental factors (e.g., soil freezing around pipes [69] or climatic and ground conditions, including climate change [70][71][72][73]), and operational factors (internal water pressure and previous failures) [74]. ...
... In the UK, the most reliable weather variable turned out to be frosty days; an increase in the number of damage occurrences by 4 to 10% was observed with each additional frost day during the month [73]. Similarly, in [75], the freezing index turned out to be the most adequate indicator in relation to the failure rate of water supply networks. ...
... The publication [73] investigates a correlation between weather parameters (air temperature, drought, and wind) and the failure of pipes in water networks in the Netherlands. The temperature has the greatest impact on pipe damage, followed by periods of drought, while wind has not been found to affect pipe failure. ...
The weather derivatives market as an instrument of effective weather risk management is still not flexible enough for many industries. The water supply and sewerage industry is sensitive primarily to heavy rainfalls and periods of high and low temperatures: days with heavy rainfall may cause a hydraulic overload of the sewerage systems; on hot days, the water demand increases significantly; on frost days, the risk of water pipe failure grows. The work aimed to summarise methods of weather risk management and propose indices that will help to protect the interests of the water supply and sewerage industry in Poland. Three indices were proposed: a daily precipitation index, frost day index, and hot day index. The frequency of reaching these indices in Poland was verified with the use of meteorological data from 1970–2019, for 19 locations. The non-parametric Mann-Kendall test was used to determine the climate change impact on the exceedance frequency of the proposed indicators. The results showed that the indexes were exceeded in the past once every 6 years, on average. The hot day index was exceeded the least often, but it was the only one with a clear (growing) trend observed.
... In the last two decades, UK water companies have increased the quantity and quality of network data, enabling a wider range of data correlated with pipe failure to be considered when building statistical models. An understanding of how each variable influences pipe failure is important and recent studies have provided useful insights, exploring environmental effects on pipes [6][7][8][9][10] . ...
... Pipe failure mechanisms are unique for different pipe materials. The literature has reported a correlation between seasonal variation and pipe failures, as a consequence of changing weather (temperature, frost and rainfall deficit (RD)) and soil conditions (pH, ground hazards such as shrink swell, texture, moisture content) [6][7][8]11,12 . Failures during the winter are typically found in iron and to a lesser extent steel and ductile iron (SDI) pipes, and are associated with cold temperatures (typically below 3°C), internal water temperature, rapid temperature transit and prolonged periods of frost 8,9,13 . ...
... Failures during the winter are typically found in iron and to a lesser extent steel and ductile iron (SDI) pipes, and are associated with cold temperatures (typically below 3°C), internal water temperature, rapid temperature transit and prolonged periods of frost 8,9,13 . During the summer a higher number of pipe failures are typically found in asbestos cement (AC) and polyvinyl chloride (PVC) pipes 6,7 and are associated with temperature and high RD which results in ground movement from soil shrink swell, associated with clay soils. Although not the same, soil moisture deficit (SMD) can be used as a corollary for RD since both are measures used to understand soil moisture content and the subsequent effects on volumetric expansion and contraction in clay soils 14 . ...
Predicting pipe failures using statistical modelling benefits from detailed knowledge of the conditions and circumstances which influence such failures. Incorporating this knowledge into model building improves failure predictions. In this study, we model weather, soil and hydrogeological variables in a generalized additive model for five common pipe materials separately, using partial dependence plots to understand the partial effects of each variable on pipe failure. We show how severe temperatures are associated with high pipe failure. Cold temperatures and air frost and their interaction with soils represent the key factors for pipe failures during the winter for metal pipes. Warm temperatures, high soil moisture deficit and soil movement results in higher pipe failures in asbestos cement pipes during the summer. Warm temperatures, ground movement and soil wash out, and water demand are key factors for polyvinyl chloride pipe failure during the summer. Frost is a key factor influencing polyethylene pipes during winter. An understanding of the physical principals concerning pipe failures can enable the development of more accurate models, guiding network management plans to help reduce asset leakage through appropriate interventions.
... The objective is to develop a model that predicts future pipe failures to assess the effect of changes in climate and composition of the DWDS. Recently, we performed a statistical analysis on the effects of weather parameters on pipe failure (Wols & Van Thienen 2014a). The weather parameters temperature and drought were recognized as most influencing on pipe failure. ...
... The failures were divided into different cohorts (Table 1), classified by pipe material. For this selection of cohorts, it was shown that each cohort has its specific response to variations in weather conditions (Wols & Van Thienen 2014a). For predicting the effect of climate change on pipe failure, no distinction of pipe age, pipe diameter and soil material was made. ...
... The failure frequency as a function of a weather variable (e.g. temperature) has been determined in Wols & Van Thienen (2014a). By combining the weather dependent failure frequency with the expected weather variable distribution, the distribution of failures as a function of weather variable can be determined for a specific climate scenario. ...
The integrity of drinking water distribution systems (DWDS) may be influenced by climate change. Using the statistical relations between failure frequencies and weather conditions described in our previous work (Wols & Van Thienen 2014a), a methodology is proposed to assess the effect of climate change on future DWDSs. The effect of climate change is combined with the evolution of the DWDS. This analysis can be conducted for any DWDS, for which historical failure registrations and weather parameters are available. The proposed methodology can therefore assist in the construction and maintenance planning of DWDSs. The methodology has been worked out for the Dutch drinking water distribution network. The results show that failures in networks with high AC proportions will increase as a result of expected climate change in the Netherlands, whereas failures in networks with high PVC and GCI proportions will even slightly reduce.
... Considering that the model results agreed with the typically expected weather, soil, and temporal impacts on the water network and consistency with the literature in potential leakage location, this proves the model's accuracy and efficiency in water leak detection [49]. Additionally, the real-time analysis creates an added benefit of increasing the time to respond or take action, minimizing future risk, understanding the network's behaviour as leaks occur, and identifying the common areas of leaks/bursts, while simultaneously saving unnecessary costs [49]. ...
... Considering that the model results agreed with the typically expected weather, soil, and temporal impacts on the water network and consistency with the literature in potential leakage location, this proves the model's accuracy and efficiency in water leak detection [49]. Additionally, the real-time analysis creates an added benefit of increasing the time to respond or take action, minimizing future risk, understanding the network's behaviour as leaks occur, and identifying the common areas of leaks/bursts, while simultaneously saving unnecessary costs [49]. Finally, the model results can be displayed in the GIS in combination with other layers, including the topographic layer of the city, the road layer, and the water treatment plants in the vicinity, which can provide an understanding of the network behaviour and critical zone identification for optimal management and operation of the pipe system. ...
Pipe leakage in water distribution networks (WDNs) has been an emerging concern for water utilities worldwide due to its public health and economic significance. Not only does it cause significant water losses, but it also deteriorates the quality of the treated water in WDNs. Hence, a prompt response is required to avoid or minimize the eventual consequences. This raises the necessity of exploring the possible approaches for detecting and locating leaks in WDNs promptly. Currently, various leak detection methods exist, but they are not accurate and reliable in detecting leaks. This paper presents a novel GIS-based spatial machine learning technique that utilizes currently installed pressure, flow, and water quality monitoring sensors in WDNs, specifically employing the Geographically Weighted Regression (GWR) and Local Outlier Factor (LOF) models, based on a WDN dataset provided by our partner utility authority. In addition to its ability as a regression model for predicting a dependent variable based on input variables, GWR was selected to help identify locations on the WDN where coefficients deviate the most from the overall coefficients. To corroborate the GWR results, the Local Outlier Factor (LOF) is used as an unsupervised machine learning model to predict leak locations based on spatial local density, where locality is given by k-nearest neighbours. The sample WDN dataset provided by our utility partner was split into 70:30 for training and testing of the GWR model. The GWR model was able to predict leaks (detection and location) with a coefficient of determination (R²) of 0.909. The LOF model was able to predict the leaks with a matching of 80% with the GWR results. Then, a customized GIS interface was developed to automate the detection process in real-time as the sensor’s readings were recorded and spatial machine learning was used to process the readings. The results obtained demonstrate the ability of the proposed method to robustly detect and locate leaks in WDNs.
... In 2010, another work [27] appeared, presenting research on the relationship between the failure rates of main water supply networks in the UK and climatic factors. A large number of papers concerning the identification of factors influencing pipeline failures, which are related to the impact of climate, was published in 2010-2020 [28][29][30][31][32][33][34][35]. These analyses took into account pipe materials, pipe diameters, weather factors (temperature, precipitation, snow cover, wind and humidity) and soil settlement. ...
... The results of the analysis also indicate gaps in ongoing research, which may indicate research directions for other researchers. So far, most attention has been focused on issues related to the identification of factors related to the impact of climate on the failure rate of water distribution systems [7,12,[28][29][30][31][32][33][34][35][36][37][38][39]49,50]. A popular research topic was also the prediction of water supply network failures, taking into account the impact of climatic factors [40][41][42][43][44][45][46]. ...
With ongoing climate change, new threats appear to the operation of water supply systems (WSSs), which are related to the amount of available drinking water resources, its quality, the operation of existing water supply infrastructure and changes in consumer behavior. The paper presents a bibliometric analysis of the state of knowledge on the impact of climate change on the failure of water supply infrastructure. The bibliometric analysis was performed based on the VOSviewer program. The results of the analysis indicate current research trends in this area around the world and allow the identification of strengths and weaknesses. Most research concerns the identification of factors related to the impact of climate on the failure rate of water distribution systems. A popular research topic was also the prediction of water supply network failures, taking into account the impact of climatic factors. The main research gap is determining the impact of climate change on water quality. The acquired knowledge can be used by water companies, policy-makers and other researchers to plan adaptation strategies to climate change, which pose new challenges for the operation of water supply systems. The conducted bibliometric analysis also allowed for identifying research gaps.
... On the other hand, plastic pipes (PVC or PE) better withstand the effects of thermal expansion and contraction than iron pipes, making them less susceptible to the cold winters 10 . However, plastic pipes were found to be more prone to fail in dry summers 11,12 . Compared to the studies on the influence of temperature, fewer studies OPEN ...
... Many specific combinations of temperature and precipitation have not been recorded in the historical data, but a regression model allows to recognize the probable outcomes for those inputs. Thus, a regression model is necessary for computing the impacts of climate change in the long-term future 11 . The Kriging algorithm is a spatial interpolation technique that has been widely used for geospatial and hydrogeologic discipline analysis 32 . ...
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 is seen in Figure 5(a) that the scatterings are too excessive with 52.64%, according to the 1:1 straight line (45°) used for the comparison of actual and predicted data of the DMT model. A similar effect of temperature, which is a meteorological variable, on the failure has been also revealed by certain researchers such as Wols & Van Thienen (2014), Pietrucha-Urbanik (2015), and Wols et al. (2019). The determination coefficient of the MAP model, another independent variable effective on DFR, is 0.23 and its mean square error is only 0.023. ...
... According to the model charts, there is a directly proportional relationship between the DMT and DFR. Similarly, the failure increase depending on the increasing temperature has been also revealed in the studies conducted by Wols & Van Thienen (2014) and Wols et al. (2019). The failure reasons depending on the temperature are briefly as follows; excessive soil shrinkage, absence of appropriate depth of excavation according to the meteorological conditions, and especially deformation of service connections due to not being covered. ...
In this study, 41 models used for the prediction of daily failure rates in water distribution networks have been designed via the Serial Triple Diagram Model (STDM) and artificial neural network (ANN) methods. For this purpose, daily failure data measured coordinately in the water distribution system network in Gebze and transferred to the geographic information system (GIS) has been used. The data has been normalized through the min-max technique to scale it at regular intervals and develop the model prediction performance. In this study, certain meteorological variables such as temperature and precipitation have been taken into account as model input for the first time. According to the increasing values of these two variables, it is observed in the model results that daily failure rates tend to increase. The expected model accuracies in failure rate prediction could not be obtained through the suggested ANN models. The higher prediction performances have been obtained through the STDM, a structure that enables visualization of the model results by making inferences. The STDM method is a significant alternative approach to determine the relationship of the variables on the failure and to predict the failure rate. It is predicted that the suggested STDM charts will contribute to the decision-makers, experts, and planners to determine effective infrastructure management. Also, investment planning prioritization will be able to reduce failure rates by interpreting prediction charts.
HIGHLIGHTS
Counter maps have been used for predicting and interpreting failure rates.;
Temperature and precipitation effect has been directly taken into consideration for the first time.;
The highest accuracy has been achieved with the least input in models.;
... Statistical (Wols and van Thienen 2014), data-mining (Harvey et al. 2013), and Bayesian (Kabir et al. 2015b) methodologies have been contemplated for modeling pipe failure. For instance, Wols and van Thienen (2014) performed a statistical analysis to study the correlations between weather parameters and pipe failure to understand the effect of climate change on network integrity. ...
... Statistical (Wols and van Thienen 2014), data-mining (Harvey et al. 2013), and Bayesian (Kabir et al. 2015b) methodologies have been contemplated for modeling pipe failure. For instance, Wols and van Thienen (2014) performed a statistical analysis to study the correlations between weather parameters and pipe failure to understand the effect of climate change on network integrity. 1 Nishiyama and Filion (Nishiyama 2013) applied artificial neural networks to predict pipe failure considering pipe physical attributes, operational practices, and the effect of environmental conditions. ...
... Statistical (Wols and van Thienen 2014), data-mining (Harvey et al. 2013), and Bayesian (Kabir et al. 2015b) methodologies have been contemplated for modeling pipe failure. For instance, Wols and van Thienen (2014) performed a statistical analysis to study the correlations between weather parameters and pipe failure to understand the effect of climate change on network integrity. ...
... Statistical (Wols and van Thienen 2014), data-mining (Harvey et al. 2013), and Bayesian (Kabir et al. 2015b) methodologies have been contemplated for modeling pipe failure. For instance, Wols and van Thienen (2014) performed a statistical analysis to study the correlations between weather parameters and pipe failure to understand the effect of climate change on network integrity. 1 Nishiyama and Filion (Nishiyama 2013) applied artificial neural networks to predict pipe failure considering pipe physical attributes, operational practices, and the effect of environmental conditions. ...
Water mains are the essential component of a water supply system (WSS) buried underground, and they account for 80% of total system expenditures. Deterioration of this asset, as a result of an aggressive soil environment, is inevitable over a pipe's service life. Although an increasing number of studies have estimated the remaining service life (RSL) of metallic pipes, most of them either are data intensive or consider limited soil and pipe parameters. In this paper, a Bayesian belief network (BBN) model is proposed to handle the problem of varying data availability and the dependency between parameters. First the proposed approach uses a combination of empirical data, experimental data, expert opinion, and a mathematical model to predict soil corrosivity and pit depth. Then a simple programming logic is used to predict RSL. Finally, the performance of the model is evaluated using a BBN sensitivity analysis. Monte Carlo simulations (MCSs) are performed using randomly generated input from measured statistical parameters (i.e., mean and standard deviation) to indicate the effect of input parameters on metallic pipe RSL and safety index (SI).
... There are other variables which are not considered in this study but are deemed important in literature. Specifically, this study lacks the environmental factors such as soil type (especially corrosive soils), weather-related variables (e.g., temperature, soil moisture, seasonality) [24,52,70,74] which are deemed to be important [4]. The existing literature lacks a holistic understanding of all the variables, along with their respective rankings, that influence the failure probability of pipes. ...
... 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). ...
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.
... Gould et al. [20] found that soil shrinkage in nonfreezing regions that result from lower soil moisture enhances the pipe failure rate. Statistical methods [5,21] performed to study the impact of climate variations on the integrity of water distribution systems. ...
Urban water distribution systems are critical infrastructures, and their failure can lead to significant economic, environmental, and social losses including flood streets and loss of treated drinking water. Identifying the failure patterns of water mains over time under various conditions is an inexpensive approach for estimating the structural deterioration of water distribution systems. It is also an alternative method for direct inspection that requires intensive efforts and budget. Time-dependent factors such as temperature and precipitation variations can lead to changes in frost depths and ground movements, resulting in stresses that exceed design values and increasing the potential of water main failures. A few studies have addressed the impact of climatic variations on the failure prediction of water mains. To fill this gap, a temporal approach for the failure prediction of water mains under climatic variations is presented. The proposed approach can predict the failure of water mains at selected locations (not only one location) and allow to not only predict the failure by a one time-step ahead but also obtain accurate failure predictions up to 9 months ahead. Another purpose of the proposed model is to accommodate additional variables to predict the failure of water mains at selected locations. To achieve this objective, a vector autoregression model with exogenous variables that incorporates the impact of climatic variations was developed. Spatiotemporal data of water mains failure events and climate data are collected for this study from Quebec and Ontario, Canada. Monte Carlo method was applied to validate the reliability of the predictive model. In other words, the failure prediction of water mains uncertainties was generated using Monte Carlo simulation. Results show that climatic variations can provide valuable information for the failure prediction of water mains. Results also prove that the proposed model can accurately predict the temporal failure patterns of water mains at two water distribution systems simultaneously.
... There are few studies taking into account the impact of temperature on the failure of the water supply network, therefore continuous monitoring taking into account the impact of atmospheric factors on the failure rate of the water supply network is necessary [4,[16][17][18][19][20][21][22][23]. As available literature on the subject shows, the factors affecting the damage of the water supply network are the material of the pipes, the age of the network, the function of the pipes, water pressure in the network and the quality of repair works. ...
The consequences of climate changes are felt by society every day. A sudden increase or decrease in air temperature, increasingly frequent, extreme weather phenomena can cause enormous economic damage to countries and cities. The occurrence of random weather phenomena and their negative impact on technical infrastructure nowadays are the basic problem related to ensuring the safety of the functioning of each system. Climate changes and significant air temperature amplitudes have a direct impact on the functioning of the critical infrastructure of cities, which includes collective water supply systems (CWSS). The paper presents the impact of climate change on the failure of a water supply network. Correlation between failure rate and air temperature was determined. This was used to determine the number of failures for the near 2036–2050 and distant 2086–2100 future in terms of climate change (temperature increase). The results confirm the thesis known from the literature that the failure rate decreases as the temperature increases. For forecasted periods as a result of temperature rise due to climate change, the reduction of the number of water pipe failures is expected in the range of 1.22% to 2.35% for the 2036–2050 period and from 2.96% to 8.66% for the 2086–2100 period, depending on the development of Representative CO2 Concentration Scenarios (RCP). The decrease in the total number of failures will have an impact on the increase in the reliability and safety of water supply to consumers.
... soil parameters, traffic/roads, weather parameters, construction nearby). Such analysis have contributed to PFD (Kwakkel et al, 2015, Moerman et al, 2016, Wols et al, 2013, 2014. USTORE has been used also for perform failure forecast combining PFD and statistical modelling. ...
Pipe failure data provides valuable information on the mechanisms and conditions which cause drinking water pipes to break or leak. Such data feeds asset management models, helping water utilities to decide future interventions at different timelines. Among countries, and even within countries, utilities apply different pipe failure data collection methods, for a-posteriori analyses. This contribution focuses in the comparison of pipe failure data collection methods and practices in three countries: Japan, Sweden and The Netherlands. We compare their methodologies and the use that such data is given. We identify the potential for knowledge transfer of methods between the three countries. This paper stems from the Watershare knowledge sharing platform, where the three organizations are active members, along with 17 other knowledge institutes spread across the world.
... Plastic pipes, especially in a small diameter (less than 300 mm), are widely used in the DWDSs nowadays due to the low cost, structural strength, ease of installation, and corrosion-resistant properties. Furthermore, no influence of weather conditions on pipe failure were observed for plastic pipes (Wols and van Thienen 2014). In China, the DWDSs lines have been replaced quickly over the last few years. ...
The update of pipeline was quick over the last few years and the plastic pipes were widely used in the drinking water distribution systems (DWDSs), especially in the small-diameter pipes. In this study, the iron adsorptive characteristics and the affecting factors in unplasticized poly(vinyl chloride) (PVC-U) pipe were investigated. Results showed that the average amount of iron in the 10-year-old PVC-U pipe’s interior surface was 2.80 wt% which was almost 187 times larger than that in a new one. Goethite (α-FeOOH) and magnetite (Fe3O4) were the major iron compounds in the scales which covered on the old pipes’ interior surface and showed loose and porous images under a scanning electron microscope. Moreover, the influence of the iron concentration on the adsorption amount and rate was discussed. The adsorption amount was significantly influenced by iron concentration, but similar adsorption rate was discovered. Notably, iron was quantitatively adsorbed by PVC-U pipe during the experimental period in accordance with the pseudo second order kinetic model. Meanwhile, regression model and response surface methodology were used to analyze the regular of iron adsorption in different concentrations of chloride (Cl⁻), sulfate (SO4²⁻), and hydroxyl (OH⁻). It can be concluded that Cl⁻ and OH⁻ showed the strong ability of iron adsorption which were larger than SO4²⁻.
... Furthermore, the proposed water main failure BBN model can be integrated with Markov deterioration process and life cycle costing analysis to arrive at some rational decision about when to replace, renew or re-inspect the pipe and to perform risk-benefit analysis. The proposed model will be extended into a multi-hazard framework, where external factors, such as earthquake (Jeon & O'Rourke, 2005;Pineda-Porras & Najafi, 2010;Tesfamariam & Liu, 2013), seismic ground movement (Liu & Tesfamariam, 2012;O'Callaghan, 2012;Pineda-Porras & Ordaz, 2010), ground rupture (Da, 2007), landslides (Kinash & Najafi, 2012), scouring (Rajani & Tesfamariam, 2004), and climate change (Wols & van Thienen, 2013) will be incorporated within structural integrity index to find out their effect on water main failure. ...
It has been reported that since year 2000, there have been an average 700 water main breaks per day only in Canada and the USA costing more than CAD 10 billions/year. Moreover, water main leaks affect other neighboring infrastructure that may lead to catastrophic failures. For this, municipality authorities or stakeholders are more concerned about preventive actions rather reacting to failure events. This paper presents a Bayesian Belief Network (BBN) model to evaluate the risk of failure of metallic water mains using structural integrity, hydraulic capacity, water quality, and consequence factors. BBN is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. The proposed model is capable of ranking water mains within distribution network that can identify vulnerable and sensitive pipes to justify proper decision action for maintenance/rehabilitation/replacement (M/R/R). To demonstrate the application of proposed model, water distribution network of City of Kelowna has been studied. Result indicates that almost 9% of the total 259 metallic pipes are at high risk in both summer and winter.
Effective functioning of water systems is critical to ensure the quality of human life. Therefore, failure prediction of water mains under climatic variations is necessary to avoid socio-economic and environmental losses. This paper aims to propose a hybrid model named STL-GC-LSTM for an accurate failure prediction of water mains under the impact of climatic variations. Firstly, the seasonal-trend decomposition based on Loess (STL) method is employed to decompose the failure time series. Next, significant climate variables are selected from the Granger causality (GC) test. Lastly, the final predicted failure of water mains is acquired by adding up the predictive results of the three components which are learned by Long Short-Term Memory (LSTM) models. Several evaluation metrics are used to assess the prediction performance. The results from a case study in Hong Kong imply that STL decomposition is promising for fully mining intrinsic properties of failure series. The developed hybrid models are effective in specifically identifying which component climatic variations exert influence on, and the final failure predictions show satisfactory agreement compared with peer models. This paper could provide an accurate estimation for failures of water mains ahead of time and be used as an essential complement to other numerical prediction models.
Hydrogeological effects of climate change will continue to affect water reservoirs worldwide. Some regions are experiencing and will experience severe decline in their water resources due to prolonged periods of drought. Since emergency practices such as the provision of emergency drinking water and forest firefighting depend on regional surface and groundwater resources, the safety of the hydro geosphere’s of a region is of fundamental importance, especially in times of crisis. The study uniquely addresses the integration of emergency water management within broader sustainable practices, particularly in the German context where such an analysis has not been previously consolidated. Using the example of emergency drinking water management, the paper elaborates the extent to which measures of emergency response are currently recognised as part of sustainable water management. In an analysis, 79 documents addressing emergency drinking water management of both water supply companies and crisis management authorities in Germany were analysed. The findings revealed a general lack of documents addressing the long-term dependencies between water resources and emergency measures currently applied. Furthermore, the documents do not elaborate on how to implement these measures in a sustainable way recognising the distinctive characteristics of a region. Since response measures can potentially intensify water stress in a region, emergency water management must be consequently included in a holistic water management process to protect landscapes and communities for the future. This paper provides a first comprehensive compilation of essential documents dealing with emergency drinking water management in Germany. It furthermore introduces a new approach to emergency water management and identifies necessary research that could serve as a baseline for future crisis decision making to strengthen national and international initiatives on water resource protection.
The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human‐caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.
Rapidly changing climate combined with aging and deterioration of water supply system pipes present a significant challenge to most water utilities. Water transmission and distribution pipes are most often susceptible to the risk of failure because of their spatial diversity and inaccessibility with limited information available to understand their deterioration process. This article provides a modeling approach, Bayesian Model Averaging (BMA), for using climate projections in conjunction with other operational, physical, and environmental factors to predict/forecast cast iron (CI) pipe failure rates in the city of Calgary. The data from the city of Calgary, which constitutes operational factors, pipe physical attributes, and soil properties, and a statistically downscaled climate data from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used for the demonstration of the developed BMA model. The result of parameter identification shows that the climatic parameters are found to be less sensitive; however, a significant change in sensitivity over time was exhibited during 1956–2014. The model results showed that there is a decrease in the failure rate for all CI pipes. However, the highest failure rate is expected for smaller‐diameter pipes compared to medium‐ and larger‐diameter pipes.
Multi-Criteria Decision-Making (MCDM) includes methods and tools for modeling and solving complex problems. MCDM has become popular in the production and service sectors to improve the quality of service, reduce costs, and make people more prosperous. This book illustrates applications through case studies focused on disaster management.
With a presentation of both Multi-Attribute Decision-Making (MADM) and Multi-Objective Decision-Making (MODM) models, this is the first book to merge these methods and tools with disaster management. This book raises awareness for society and decision-makers on how to measure readiness and what necessary preventive measures need to be taken. It offers models and case studies that can be easily adapted to solve complex problems and find solutions in other fields.
Multi-Criteria Decision Analysis: Case Studies in Disaster Management will offer new insights to researchers working in the areas of industrial engineering, systems engineering, healthcare systems, operations research, mathematics, business, computer science, and disaster management, and, hopefully, the book will also stimulate further work in MCDM.
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 scenerios. 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 less number breaks due to the warmer weather and less servere 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.
Asbestos cement was a common construction material for water pipes during the twentieth century, as a replacement for metal piping that was vulnerable to corrosion. We report on the presence of asbestos fibres in drinking water supply in Christchurch, New Zealand from ageing asbestos cement reticulated water supply. By sampling the mains water supply via hydrants, 19 of our 20 samples showed long asbestos fibres (>10 μm), with an average concentration 0.9 million fibres per litre (MFL). Short asbestos fibres (>0.5 μm) had an average concentration of 6.2 MFL. Sampling was targeted to pipes from 1930 to the 1960s and there was abundant evidence of fibres being released from pipes of this age. Municipalities cannot continue to rely on ageing asbestos-cement piping, as it appears to be releasing asbestos fibres into drinking water with uncertain health implications, and should prioritise replacing pipes greater than 50 years in age, especially where high water pressures or land disturbance occur, to reduce the risk of water-carried asbestos being released into urban environments, and mitigate any risk of asbestos from ingested contaminated water sources. HIGHLIGHTS
Municipalities should monitor for the presence of asbestos fibres as a strategy for detecting pipe corrosion.;
Asbestos cement piping is reaching its end-of-life stage and is releasing short and long asbestos fibres into the water supply.;
Municipalities with soft water supply are vulnerable to cement pipe decay and we observed high corrosion rates of 0.20 mm a−1 averaged over a lifetime from asbestos pipes.;
Among the many factors affecting water supply system failures are the weather conditions that change over the year. Since this is an important research issue, as part of this study, investigation of water supply system failure seasonality by the selected statistical approaches was presented. The basis of the research was monthly number of the pipelines' failures from the multi-year period of 2007–2017 of the municipal water network located in southern Poland. Mann–Kendall test results proved decreasing seasonal trend of the failure rate indexes λ. In turn, the results of the Colwell indexes' calculations allowed it to be stated that seasonal course of the water pipelines' failure events can be relatively easy to predict. As it turned out, it is difficult to determine unambiguously the impact of a given period of the year on the water pipeline failure events' occurrence. However, greater failure-free operation of the water pipelines may be expected in spring and summer months than in autumn and winter months. Because using Colwell indexes for seasonality analysis has no limitations compared to other methods, Colwell indexes may be considered as reliable tools for the assessment of the seasonal course of the water pipelines' failure events. HIGHLIGHTS
Statistical analysis of the water supply system failure seasonality.;
Using the selected statistical approaches for the analysis of water pipelines failure rate indexes λ.;
Seasonal course of the water pipelines failure events can be relatively easy to predict by using the Colwell indexes.;
Not clear impact of a given period of the year on water supply system failures was found.;
To solve the frost heave failure of water pipelines in winter, studying the frost heave failure mechanism of water pipes is a critical issue for ensuring the safety and reliability of field irrigation and urban water supply. This paper is based on the investigation of the current polypropylene random copolymer (PPR) pipe frost heaves in residential buildings. According to theory analysis and model testing, the frost heave failure mechanism of the PPR water pipe is studied systematically. The formula of ice expansion pressure was derived based on ASTM E28-02 standard and related mechanical theories. Then the theory of PPR pipe anti-frost heave failure was proposed. The pipe thickness can be determined from the proposed theory, and the selection criteria of the PPR pipe was also provided for engineering application. Theoretical calculations and frost heave testing results showed that it is more economical and reasonable to choose S4 series PPR water pipes by comprehensively considering the factors of pipe life cycle and cost.
The health condition of infrastructure including water transmission and distribution mains has a great impact on the quality of human life. The performance of these water infrastructure is affected by the surrounding soil environment as well as the weather or climate changes. To investigate the structural response of water mains to varying soil movements, field data were collected with a sensor monitoring system. This included pipe wall strain in-situ soil water content, soil pressure, and temperature. Combined with weather factors, an automatic variable selection method, i.e., recursive feature elimination, was first applied to identify critical predictors contributing to pipe deformation. Then, a super learning algorithm was employed to characterize the relationship between pipe deformation and environmental factors. Both base and super learners were built to predict three types of pipe deformation which verified the adaptability of two modeling methods to different predictive models. Predictive performance was evaluated through R-squared, root-mean-square error, and mean absolute error values. The performance metrics demonstrate the advantage of the super learning algorithm in comparison with the baseline methods, especially its capability to further incorporate extra base learners and predictors in a more complex setting. This study shows that the pipe structure behavior could be successfully inferred from surrounding soil properties and weather conditions.
This paper examines the impact of weather conditions on pipe failure in water distribution networks using artificial neural network (ANN) and evolutionary polynomial regression (EPR). A number of weather-related factors over 4 consecutive days are the input of the binary ANN model while the output is the occurrence or not of at least a failure during the following 2 days. The model is able to correctly distinguish the majority (87%) of the days with failure(s). The EPR is employed to predict the annual number of failures. Initially, the network is divided into six clusters based on pipe diameter and age. The last year of the monitoring period is used for testing while the remaining years since the beginning are retained for model development. An EPR model is developed for each cluster based on the relevant training data. The results indicate a strong relationship between the annual number of failures and frequency and intensity of low temperatures. The outputs from the EPR models are used to calculate the failures of the homogenous groups within each cluster proportionally to their length.
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 obtained from satellites and (modelled) pressure data. For asbestos-cement (AC) and cast iron (CI) pipes, temperature was an important factor. CI pipes showed increased pipe failures at low temperatures, which confirms results from previous studies, whereas AC pipes showed increased pipe failures at high temperatures. Pipe failure rates were higher for pipes that on average received higher internal pressures. This study also showed that wind resulted in additional pipe failures caused by uprooting of trees during a severe storm. With respect to drought, in some regions in the Netherlands, increased pipe failures during periods of drought were found. A small influence of soil settlement on pipe failure was found using remote-sensing techniques for a small area (5 × 10 km) in the Netherlands.
In the future, the more frequent occurrence of severe heat waves and long dry periods due to climate change can cause lowering of the ground water level and therefore consolidation of the soil. Consequently, increased differential settlements are expected that may damage underground water infrastructure. Models were developed to assess the impact of differential settlements on pipe failure. The main concept of these models is that the pipe-soil system is schematized as a beam on an elastic foundation using Winkler type springs. For climate change induced settling, a parametric function of the soil settlement is proposed. A Monte-Carlo analysis has been applied to predict pipe failure probabilities.
The causes of pipe damage that lead to leakages and bursts in water distribution networks are numerous, and the significance of each possible mechanism is not yet fully understood. This paper reports field monitoring and numerical modelling carried out to evaluate the potential for vegetation-induced desiccation to impose significant bending and therefore additional stress on buried water pipes. Over a period of two years, vertical and horizontal deflections were measured along two flexible pipes buried in London Clay in the vicinity of an oak tree. Meteorological measurements made at the site allowed soil moisture deficit to be computed, and these values were compared with regional values supplied by the UK national meteorological office. Finite difference continuum analyses were carried out in order to permit the interpretation of measured deflections in terms of the equivalent stress increases that would be imposed on a rigid cast iron water pipe. The calculated maximum tensile stress increase was found to be significant in terms of the residual strength of a corroded cast iron pipe.
Pipelines used in the distribution of potable water are a vital part of everyday life. The pipelines buried in soil-backfill are exposed to different deleterious reactions; as a result, the design factor of safety may be significantly degraded and, consequently, pipelines may fail prematurely. Proactive pipeline management, which entails optimal maintenance, repair, or replacement strategies, helps increase the longevity of pipelines. The effect of different deterioration mechanisms and operating conditions needs to be understood to develop good proactive management practices. In this paper, a Winkler-type analytical model is developed to quantify the contributions of different stress drivers, e.g., pipe material type and size, bedding conditions, and temperature. Sensitivity analyses indicate that the extent of the unsupported length developed as a result of scour has a significant influence on the flexural pipe-soil response. As well, plastic pipes tolerate less loss of support than metallic pipes.
Effective planning for the renewal of water distribution systems requires accurate quantification of the structural deterioration of water mains. Direct inspection of all water mains in a distribution system is almost always prohibitively expensive. Identifying water-main breakage patterns over time is an effective and inexpensive alternative for gauging the structural deterioration of a water distribution system. While the structural deterioration of the pipe is generally considered to be a steady, monotone process, some of the environmental and operational stresses acting upon it are time dependent, steady, or transient. These stresses result in sets of "noisy" breakage rate data that often mask the underlying deterioration (aging) patterns, especially in small data sets. If the cause of these random stresses can be identified and attributed to measurable phenomena (for example, temperatures, precipitation, and so on), a more accurate pipe deterioration pattern can be obtained. Further, better predictions of water-main breakage could be made if these phenomena could be forecast with any degree of accuracy. A method is presented for analyzing how breakage rate patterns of water mains are affected by time-dependent factors. The method is versatile enough to consider any number of underlying factors, but the solution becomes more complex and more data are required as the number of factors increases. A case study is presented to demonstrate the method. Several time-dependent factors were examined, some of which were found to be significant contributors to the time variation of breakage rates.
The antecedent precipitation index (API) has been full indicator of soil mositure conditions for watershed runoff calculations and recent attempts to correlate this index with spaceborne microwave observations have been fairly successful. The recession coefficient for API is found to depend on soil texture as reflected by field capacity and permanent wilting point. A recently developed model for global insolation is used with climatological data for Wisconsin to simulate the annual trend of recession coefficient. This study suggests that API could be a unifying concept for watershed and atmospheric general circulation modeling.
This paper presents a state-of-the-technology literature and current practice review on water pipe condition, deterioration and failure rate prediction models in order to identify the gap between the models found in literature and those currently used by utilities around the world. Researchers have developed various methodologies in determining pipe condition and failure prediction over the last three decades. Their efforts are discussed in many literatures and articles but are not summarised by one document. In this report, more than 50 articles were reviewed from the last decade and are presented based on the type of methodology utilised. Nine utilities across the world with significant undertakings of water pipe infrastructure management are also presented which underline the current practice. In summary, both the literature and current practice are summarised to identify the gap between the models found in literature and water utility asset management practices.
Municipal water infrastructure systems are in poor condition and are deteriorating rapidly. A general diagnosis of the actual structural state of these systems is needed, as are tools to assess their rate of deterioration. To make a diagnosis, one must collect and analyze data on the characteristics of water pipes and on their breakage histories. Unfortunately, many municipalities have only been rigorously recording breakage histories for a decade, while their pipes have been in the ground for much longer. A modeling strategy, inspired by survival analysis and using the annual number of water pipe breaks as an indicator of the structural state of a network, was applied to three municipalities characterized by their brief recorded pipe break histories. This paper presents a descriptive analysis of the water pipe and breakage data, and the application of the modeling strategy to these municipalities. Different replacement scenarios were also simulated to assess their impact on the evolution of the annual number of breaks in the three municipalities.
While the use of environmental factors in the analysis and prediction of failures of buried reticulation pipes in cold environments has been the focus of extensive work, the same cannot be said for failures occurring on pipes in other (non-freezing) environments. A novel analysis of pipe failures in such an environment is the subject of this paper. An exploratory statistical analysis was undertaken, identifying a peak in failure rates during mid to late summer. This peak was found to correspond to a peak in the rate of circumferential failures, whilst the rate of longitudinal failures remained constant. Investigation into the effect of climate on failure rates revealed that the peak in failure rates occurs due to differential soil movement as the result of shrinkage in expansive soils.
Field tests of buried PVC (polyvinyl chloride) water mains have been undertaken to identify the mechanisms of pipe-soil interaction. Temperatures and strains on the pipes have been continuously measured since late 1993 for over two years. In a theoretical study, a simplified Winkler model was previously developed to simulate the response of a jointed pipe subjected to temperature and water pressure changes. The objective of this paper is to substantiate the theoretical understanding of responses of stresses and strains of the jointed pipes through comparative study of the field measurements and theoretical analyses. In general, good agreement was found between the predicted and measured strains, which supports the notion that the development of the strains is mainly a consequence of the seasonal pipe temperature variations. Possible reasons for some deviation between the predicted and measured strains are analyzed.
Water mains are important lifelines of modern urban infrastructure. However, in most developed countries, the average life of these cast or ductile iron pipes approaches 5075 years. In recent years, the disruption of water sevices as a consequence of water main breaks is on the rise in most Cadadian cities. This paper describes the developement of a simplified Winkler model to stimulate the responses of a jointed water main subjected to differential temperature change and water pressure. The simplified Winkler model accounts for axial and radial restraints offered by the surronding soil. In spite of its simplicity, the Winkler model is able to predict the overall response of strains and stresses, which confirms satisfactorily some of heuristic and documented observations on water main breaks.
Key words: water main breaks, pipesoil interaction, temperature influence, Winkler model.