Study on relationships between climate-related covariates and pipe bursts using evolutionary-based modelling

Researchers extensively studied external loads since they are widely recognized as significant contributors to water pipe failures. Physical phenomena that affect pipe bursts, such as pipe-environment interactions, are very complex and only partially understood. This paper analyses the possible link between pipe bursts and climate-related factors. Many water utilities observed consistent occurrence of peaks in pipe bursts in some periods of the year, during winter or summer. The paper investigates the relationships between climate data (i.e., temperature and precipitation-related covariates) and pipe bursts recorded during a 24-year period in Scarborough (Ontario, Canada). The Evolutionary Polynomial Regression modelling paradigm is used here. This approach is broader than statistical modelling, implementing a multi-modelling approach, where a multi-objective genetic algorithm is used to get optimal models in terms of parsimony of mathematical expressions vs. fitting to data. The analyses yielded interesting results, in particular for cold seasons, where the discerned models show good accuracy and the most influential explanatory variables are clearly identified. The models discerned for warm seasons show lower accuracy, possibly implying that the overall phenomena that underlay the generation of pipe bursts during warm seasons cannot be thoroughly explained by the available climate-related covariates.

[1]  Balvant Rajani,et al.  Quantifying Effectiveness of Cathodic Protection in Water Mains: Theory , 2004 .

[2]  Jayong Koo,et al.  Predicting water pipe breaks using neural network , 2005 .

[3]  B. S. Lochbaum PSE&G develops models to predict main breaks , 1993 .

[4]  Ahmad Habibian,et al.  Effect of Temperature Changes on Water‐Main Breaks , 1994 .

[5]  Aldrich,et al.  FROST PENETRATION BELOW HIGHWAY AND AIRFIELD PAVEMENTS , 1956 .

[6]  Tuncer B. Edil,et al.  Cold Weather Effects on Underground Pipeline Failures , 1983 .

[7]  Balvant Rajani,et al.  Exploration of the relationship between water main breaks and temperature covariates , 2012 .

[8]  Curtis M. Clark EXPANSIVE‐SOIL EFFECT ON BURIED PIPE , 1971 .

[9]  Y. Kleiner,et al.  I-WARP: Individual Water mAin Renewal Planner , 2010 .

[10]  O. Giustolisi,et al.  Asset performance analysis using multi-utility data and multi-objective data mining techniques , 2008 .

[11]  Orazio Giustolisi,et al.  Scour depth modelling by a multi-objective evolutionary paradigm , 2011, Environ. Model. Softw..

[12]  Thomas M. Walski,et al.  Economic analysis of water main breaks , 1982 .

[13]  R. E. Morris,et al.  Principal Causes and Remedies of Water Main Breaks , 1967 .

[14]  J. M. Makar,et al.  A preliminary analysis of failures in grey cast iron water pipes , 2000 .

[15]  Balvant Rajani,et al.  Forecasting Variations and Trends in Water-Main Breaks , 2002 .

[16]  Balvant Rajani,et al.  Comprehensive review of structural deterioration of water mains: physically based models , 2001 .

[17]  S Burn,et al.  Seasonal factors influencing the failure of buried water reticulation pipes. , 2011, Water science and technology : a journal of the International Association on Water Pollution Research.

[18]  B Rajani,et al.  Pipesoil interaction analysis of jointed water mains , 1996 .

[19]  Luigi Berardi,et al.  Development of pipe deterioration models for water distribution systems using EPR , 2008 .

[20]  D. Savić,et al.  A symbolic data-driven technique based on evolutionary polynomial regression , 2006 .

[21]  D. Savić,et al.  Advances in data-driven analyses and modelling using EPR-MOGA. , 2009 .

[22]  W. D. Hurst,et al.  Effects of Physical Environment on Cast‐Iron Pipe , 1955 .