Risk-based framework for optimizing residual chlorine in large water distribution systems
Managing residual chlorine in large water distribution systems (WDS) to minimize human health risk is a daunting task. In this research, a novel risk-based framework is developed and implemented in a distribution network spanning over 64 km2 for supplying water to the city of Al-Khobar (Saudi Arabia) through 473-km-long water mains. The framework integrates the planning of linear assets (i.e., pipes) and placement of booster stations to optimize residual chlorine in the WDS. Failure mode and effect analysis are integrated with the fuzzy set theory to perform risk analysis. A vulnerability regarding the probability of failure of pipes is estimated from historical records of water main breaks. The consequence regarding residual chlorine availability has been associated with the exposed population depending on the land use characteristics (i.e., defined through zoning). EPANET simulations have been conducted to predict residual chlorine at each node of the network. A water quality index is used to assess the effectiveness of chlorine practice. Scenario analysis is also performed to evaluate the impact of changing locations and number of booster stations, and rehabilitation and/or replacement of vulnerable water mains. The results revealed that the proposed methodology could facilitate the utility managers to optimize residual chlorine effectively in large WDS.
KeywordsWater distribution system (WDS) EPANET Water quality index (WQI) Fuzzy-FMEA Risk priority number (RPN)
- Abdelgawad, M. (2010). Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. Engineering and Management, 136(September), 1028–1037. Retrieved from doi: 10.1061/(ASCE)CO.1943-7862.0000210.
- Abu-Monasar, A.A. (2014). PhD Thesis. Department of Civil Engineering, King Fahd University of Petroleum & Minerals, Dhahran 31261 Saudi Arabia.Google Scholar
- Ahn, J., et al. (2012). Application of EPANET for the determination of chlorine dose and prediction of THMs in a water distribution system. Journal of Sustainable Environment Research, 22(1), 31–38.Google Scholar
- Alidadi, M. (2013). The most effective strategy to improve customer satisfaction in Iranian banks: a fuzzy AHP analysis. Journal of Business Studies Quarterly, 4(4), 83–93 ISSN 2152-1034.Google Scholar
- Behzadian, K. (2012). A novel approach for water quality management in water distribution systems by multi-objective booster chlorination. International Journal of Civil Engineering, 10(1), 11.Google Scholar
- Haider, H. (2015). Framework for optimizing chlorine dose in small- to medium-sized water distribution systems: a case of a residential neighbourhood in Lahore. Pakistan, 41(5), 614–623.Google Scholar
- Imran, S. A., Sadiq, R., & Kleiner, Y. (2009). Effect of regulations and treatment technologies on water distribution infrastructure. Journal of American Water Works Association (AWWA), 101(3), 82–95.Google Scholar
- Jeppson, R. W. (1976). Analysis of flow in pipe networks. Ann Arbor: Ann Arbor Science.Google Scholar
- Khan, F., Husain, T., & Lumb, A. (2003). Water quality evaluation and trend analysis in selected watersheds of the Atlantic region of Canada. Journal of Monitoring and Assessment, Kluwer Academic Publisher Netherland 2003, 88(1), 221–248.Google Scholar
- McGhee, T.J. (1991). Water supply and sewerage. In McGraw-Hill (Ed.), 5th ed.. New York: McGraw-Hill. Retrieved from http://www.worldcat.org/title/water-supply-and-sewerage/oclc/21440985
- Sharif, M. N., Farahat, A., Al-Zahrani, M. A., Islam, N., Rodriguez, M. J., & Sadiq, R. (2016). Optimization of chlorination boosters in drinking water distribution network for al-Khobar City in Saudi Arabia. Arabian Journal of Geosciences, 9(9), 15. doi:10.1007/s12517-016-2552-1.CrossRefGoogle Scholar
- Shokoohi, M., Tabesh, M., Nazif, S., & Dini, M. (2016). Water quality based multi-objective optimal design of water distribution systems. Water Resources Management, 1–16. doi:10.1007/s11269-016-1512-6.
- Tabesh, M. (2010). Quality management of water distribution networks by optimizing dosage and location of chlorine injection. International Journal of Environmental Research, 5(2), 321–332 NaN-6865.Google Scholar
- Zadeh, L. (1978). Fuzzy sets as a basis for a theory of possibility. doi:10.1016/0165-0114(78)90029-5.