Characterizing uncertainty in city-wide disaster recovery through geospatial multi-lifeline restoration modeling of earthquake impact in the district of North Vancouver

This study presents a city-scale, data-driven model of multi-infrastructure recovery in a suburban municipality. The approach uses the Graph Model for Operational Resilience, a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time. A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake. The model comprises municipal water and wastewater, power distribution, and transport systems.

Key findings indicate that repair times for electrical power and road networks are highly variable and influential in the overall recovery of neighborhoods within the district. Other infrastructure systems are individually variable in their repair times, but do not affect overall recovery to the same extent that power and road networks do. Water and wastewater systems are expected to recover most quickly for the studied magnitude 7.3 earthquake. It is important to note that these repair times represent full recovery of the systems studied rather than the time at which society can adequately function and prevent further losses after a disaster. Partial functionality in some sectors may provide an opportunity to expedite repairs in others. Therefore, an awareness of the ways in which neighborhoods can continue to function while disaster recovery occurs is essential to improving outcomes for residents after a disaster.