A Contamination Risk Model for Water Distribution Networks | IConEST

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A Contamination Risk Model for Water Distribution Networks


Dr. Thikra Dawood, Purdue University, United States of America
Assoc. Prof. Dr. Emad Elwakil, Purdue University, United States of America
Lecturer Hector Mayol Novoa, National University of St Augustin of Arequipa, Peru
Lecturer José Fernando Gárate Delgado, National University of St Augustin of Arequipa, Peru


The intrusion of contaminants into water supply networks can compromise the water quality and may cause fatal hazards to urban communities. The risk of water quality failure has been de facto an intricate and challenging field of research. This complexity is due to the fact, that these networks are subjected to various physical, environmental and operational mechanisms. In addition to the limited and uncertain data, pertaining to the deterioration and performance of these structures. The objective of this paper is to develop a risk-based assessment model based on Bow-tie modeling and probability of failure analysis to estimate the rate of failure in water distribution networks. First, the Fault-tree model is built via identifying the attributes and failure sources. Second, the Event-tree model is designed to demonstrate critical and post-failure events. Third, probability distribution schemes are generated to address the uncertainties and predict the risk associated with pipes' deterioration and failure. The proposed model is a decision support tool, expected to assist infrastructure managers and civil engineers in their future plans and decision making.


risk of contamination, deterioration, pipe failure, water distribution networks  


Dawood, T., Elwakil, E., Novoa, H.M. & Delgado, J.F.G. (2019). A Contamination Risk Model for Water Distribution Networks. In M. Shelley & V. Akerson (Eds.), Proceedings of IConEST 2019--International Conference on Engineering, Science and Technology (pp. 31-37). Monument, CO, USA: ISTES Organization. Retrieved 29 February 2020 from www.2019.iconest.net/proceedings/37/.


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