Back to Normal: Earthquake Recovery Modelling
Given the high level of earthquake risk in California, all communities need to be prepared to respond to and recover from the impacts of a potentially devastating earthquake. Although there has been significant research on the estimation of direct economic losses immediately after an earthquake, there has not been enough research about long-term recovery, and even less in the development and application of computer simulation models. This is to some extent because data on building repair and recovery times from past earthquakes have not been systematically documented (Comerio M. , 2006). Moreover, the models developed so far have not successfully captured the complexity of the recovery process. Recovery depends on many factors (such as the socio-economic conditions of the affected area) that are usually difficult to measure, understand and apply to predicting or modelling the recovery process.
We acknowledge that the parameters taken into account in the present analysis may not be appropriate for application to potential earthquakes in other regions due to many factors that can affect the post-disaster recovery process. The methodology was developed using the city of Napa and the 2014 M6 South Napa Earthquake as a real-world case study. Therefore, the results are expected to apply to earthquakes with similar impact and to communities with similar socio-economic and building characteristics. To apply the resulting model in regions with different characteristics, additional data collection and validation would be necessary.
To address some of the key factors that influence recovery, the Alfred E. Alquist Seismic Safety Commission (SSC) engaged the GEM (Global Earthquake Model) Foundation and the University of California at Los Angeles (UCLA), Department of Civil and Environmental Engineering, a) to develop a methodology and an open-source and transparent software tool to estimate recovery states and recovery times following an earthquake; and b) to investigate the effect of external socio-economic factors on these recovery times. The SSC leveraged over 20 million dollars in funding from GEM supporters that has been used to develop the OpenQuake1 software package and related data sets, which the “Back to Normal”: Earthquake Recovery Modelling project uses.
Objectives and Expected Outputs
To identify the socio- economic conditions that impact the recovery time and trajectory, to estimate how long it will take an affected area to recover from a similar earthquake
United States of America
United States of America
2014 - 2016