MCEER-07-0014 | 9/7/2007 | 130 pages
TOC: The table of contents is provided.
Keywords: Numerical simulations. Computer-based models. Disaster recovery. Disaster resiliency. Disaster resilient communities. Northridge, California earthquake, January 17, 1994. Urban areas. Recovery indicators. Los Angeles, California.
Abstract: This report describes a computer-based model of urban disaster recovery. The model simulates the recovery dynamics of households, businesses, neighborhoods, and the community following a disaster. Building on prior work, this model represents a second-generation prototype. Like its predecessor, the model is based in the empirical literature and is distinctive in its emphasis on recovery time paths, spatial disparities, and linkages between different sectors of a community. Household recovery, for example, is influenced not only by housing damage but socio-economic attributes such as income level as well as by business recovery and the loss and restoration of critical infrastructures. Significant improvements have been made to both the underlying conceptual model and the modelís implementation. A key refinement of the conceptual model pertains to the use of more meaningful indicators of recovery. With respect to implementation, the model is now fully modular in design, which provides substantially greater flexibility in implementation and testing. The model is also now scalable, allowing ready representation of any number of neighborhoods and agents within these neighborhoods. The refined model is applied to the City of Los Angeles for the 1994 Northridge earthquake. Extensive efforts were made to gather detailed data on the conditions and effects of the Northridge earthquake, and to use these data to test and calibrate the model to the extent possible. Nonetheless, available data were found to be quite limited for model calibration purposes. Results indicated favorable performance in certain aspects of the model and identified areas where further refinements are needed. Models of urban disaster recovery have several potential uses, including decision support and education. Examples of "what-if" explorations are provided to illustrate the types of analyses that can be conducted with this model. The report concludes with a discussion of potential applications, advances, limitations, and priorities for further research. One of the greatest needs is for more systematic empirical data on pre-disaster urban conditions, as well as disaster recovery.