A comprehensive framework for seismic risk assessment of urban water transmission networks

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Abstract

Earthquakes are natural disasters which human beings cannot control, causing significant damage to the economy and society as a whole. In particular, earthquakes affect not only buildings but also lifeline structures such as water distribution, electric power, transportation, and telecommunication networks. The interruption of these networks is critical because it can directly damage the facilities and, at the same time, cause long-term loss of the overall system for society. In recent years, there has been increasing interest in the uncertainties of ground motion, deterioration of pipelines, and interdependency of lifelines. Therefore, it is essential to predict the damage through possible earthquake scenarios and accounting for factors affecting lifeline structures. This study proposes a comprehensive framework to quantify the impact of earthquakes on the connectivity of urban water transmissions. The framework proposes the following steps to predict damage from earthquakes: (1) estimate the ground motion considering the spatial correlation, (2) propose a modified failure probability of buried pipelines considering deterioration, and (3) evaluate the seismic fragility curves of network components and the interdependency among water treatment plants, pumping plants, and substations. For numerical simulations, an actual water network system in South Korea was constructed using graph theory, and the magnitudes and locations of the epicenters were determined based on historical earthquake data. Finally, the reliability performance indicators (e.g., connectivity loss and serviceability ratio) were measured when earthquakes of various magnitudes occurred in the urban area. This framework will enable the prediction of damage from earthquakes and enhance decision making to minimize the extent of damage.

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APA

Yoon, S., Lee, Y. J., & Jung, H. J. (2018). A comprehensive framework for seismic risk assessment of urban water transmission networks. International Journal of Disaster Risk Reduction, 31, 983–994. https://doi.org/10.1016/j.ijdrr.2018.09.002

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