Exploration of the relationship between water main breaks and temperature covariates

Urban Water Journal

Volumn 9, Issue 2, 2012, Pages 67-84

  Rajani, Balvant ^a   Kleiner, Yehuda ^a   Sink, Jean Eric ^a  

^a NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

impact of temperature on water main breaks; non homogeneous Poisson probabilistic model; water and air temperature based covariates

Indexed keywords

AIR TEMPERATURE; CLIMATE EFFECT; COVARIANCE ANALYSIS; DATA SET; EXPLORATION; PIPE; POISSON RATIO; PROBABILITY; TEMPERATURE EFFECT; WATER TEMPERATURE;

CANADA; UNITED STATES;

EID: 84859603839     PISSN: 1573062X     EISSN: 17449006     Source Type: Journal    
DOI: 10.1080/1573062X.2011.630093     Document Type: Article

References (16)

1. Ahn, J. C. 2005. Predicting water pipe breaks using neural network. Water Science and Technology: Water Supply, 5(3-4): 159-172.
2. Bahmanyar, G. H. and Edil, T. B. Cold weather effects on underground pipeline failures. In. Proceedings of Conference on Pipelines in Adverse Environments II. Edited by: Pickell, Mark B. pp.579-593. San Diego, CA: ASCE.
3. Constantine, A. G. and Darroch, J. N. 1993. "Pipeline reliability: stochastic models in engineering technology and management". In Proceedings of the Australia-Japan Workshop on Stochastic Models in Engineering, Technology and Management, Edited by: Osaki, S. and Murthy, D. N.P. 86-95. Gold Coast, Australia: World Scientific Publishing Co.
4. Constantine, A. G., Darroch, J. N. and Miller, R. 1996. Predicting underground pipe failure. Water (Journal of Australian Water Works Association), 23(2): 9-10.
5. Economou, T., Kapelan, Z. and Bailey, T. A zero-inflated Bayesian model for the prediction of water pipebursts. Proceedings of the 10th International WaterDistribution System Analysis Conference. pp.724-734. South Africa. [CD-ROM]. Reston, VA: ASCE: Kruger National Park.
6. Goodchild, C. W., Rowson, T. C. and Engelhardt, M. O. 2009. "Making the earth move: modelling the impact ofclimate change on water pipeline serviceability. In". In Computing and Control in the Water Industry 2009: Integrating Water Systems, Edited by: Boxall, J. and Maksimovic, C. 807-811. Sheffield, UK: University of Sheffield.
7. Habibian, A. 1994. Effect of temperature changes on water-main break. Journal Transportation Engineering, 120(2): 312-321.
8. Hughes, D. 2011. Continuous system acoustic monitoring-from start to repair, Vol. 74, Denver, CO: Water Research Foundation.
9. Kleiner, Y. and Rajani, B. 2003. Forecasting variations and trends in water-main breaks. Journal of Infrastructure Systems, 8(4): 122-131.
10. Kleiner, Y. and Rajani, B. 2004. Quantifying effectiveness of cathodic protection in water mains: theory. Journal of Infrastructure Systems, 10(2): 43-51.
11. Kleiner, Y. and Rajani, B. 2009. "I-WARP: individual water main renewal planner". In Computing and control in the water industry 2009: integrating water systems, Edited by: Boxall, J. and Maksimovic, C. 639-644. Sheffield, UK: University of Sheffield.
12. Lochbaum, B. S. 1993. PSE&G develops models to predict main breaks. Pipeline and Gas Journal, 20(9): 20-27.
13. Newport, R. 1981. Factors influencing the occurrence of bursts in iron water mains. Water Supply and Management, 3: 274-278.
14. Røstum, J. 2000. Statistical modelling of pipe failures in water networks, Trondheim: Norway. Thesis (PhD). Norwegian University of Science and Technology
15. Sacluti, F., Stanley, S. J. and Zhang, Q. Use of artificial neural networks to predict water distribution pipe breaks. In: Proceedings of the 51st Annual Conference of the Western Canada Water and Wastewater.
16. Walski, T. M. and Pelliccia, A. 1982. Economic analysis ofwater main breaks. Journal American Water Works Association, 74(3): 140-147.