Abstract
The multi-disciplinary data and information available at a community level comprise the foundation of natural hazard resilience modeling. These data enable and inform mitigation and recovery planning decisions prior to and following damaging events such as earthquakes. This paper presents a multi-disciplinary seismic resilience modeling methodology to assess the vulnerability of the built environment and economic systems. This methodology can assist decision-makers with developing effective mitigation policies to improve the seismic resilience of communities. Two complementary modeling strategies are designed to examine the impacts of scenario earthquakes from a combined engineering and economic perspective. The engineering model is developed using a probabilistic fragility-based modeling approach and is analyzed using Monte Carlo (MC) simulations subject to seismic multi-hazard, including simulated ground shaking and resulting liquefaction of the soil, to quantify the physical damage to buildings and electric power substations (EPS). The outcome of the analysis is subsequently used as input to repair and recovery models to quantify repair cost and recovery time metrics for buildings and as input to functionality models to estimate the functionality of individual buildings and substations by accounting for their interdependency. The economic model consists of a spatial computable general equilibrium (SCGE) model that aggregates commercial buildings into sectors for retail, manufacturing, services, etc., and aggregates residential buildings into a wide range of household groups. The SCGE model employs building functionality estimates to quantify the economic losses. The outcomes of this integrated modeling consist of engineering and economic impact metrics, which are used to investigate mitigation actions to help inform a community on approaches to achieve its resilience goals. An illustrative case study of Salt Lake County (SLC), Utah, developed through an extensive collaborative partnership and engagement with SLC officials, is presented. The results demonstrate the effectiveness of the proposed methodology in quantifying the loss and functional recovery of infrastructure systems, the impacts on capital stock, employment, and household income and the effect of various mitigation strategies in reducing the losses and functional recovery time subject to earthquakes with varying intensities.