ResilUS: Modeling community recovery from disasters
What is ResilUS?
ResilUS – “Resilience United States” – is a computer model that simulates the loss and recovery dynamics of socio-economic agents (e.g., households and businesses), neighborhoods, and communities before, during, and after a hazard event. To date, modeling of recovery processes has been largely neglected by disaster science. Most current models, such as HAZUS, focus on post-disaster loss estimation, and not recovery.
The significance of this distinction is illustrated in Figure 1. Loss models generally focus on the initial loss caused by a disaster, treating the recovery timepath in a summary fashion. The recovery timepath itself makes a great difference in total loss. Moreover, the extent to which the recovery timepath can be influenced by decision variables will be of great interest to policy-makers. Figure 2 shows some of the key relationships between socio-economic agents, the built environment, the hazard event, and various community attributes or policy interventions that influence recovery.
ResilUS is unique in its emphasis on recovery timepaths, 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 (e.g., income level) as well as by business recovery (as businesses provide jobs) and the loss and restoration of critical infrastructures.
Figure 1. A representation of a community’s performance over time once a disaster occurs, and the level of resilience given certain decisions and actions that are taken as the disaster unfolds.
Figure 2. An illustration of key relationships between households and businesses, the built environment, the hazard event, as well as community and policy interventions that influence resilience.
What does ResilUS do?
ResilUS simulates community loss and recovery. Currently the model focuses primarily on indicators associated with household and business well-being, such as health, employment, productivity, and product demand. It represents the relationship between these indicators of well-being and restoration of the built environment, such as building, road network, electrical network, etc. The current model is both modular and scalable. Modularity means that different algorithms can be substituted easily without having to modify other aspects of the model. Scalability means that any number of socio-political jurisdictions, socio-economic agents and physical infrastructure elements can be represented (within limits of computer storage and processing capabilities). Currently, the model represents elements of social, economic, physical capital, and is currently being developed to represent ecological capital. ResilUS sits within the MATLAB software environment with convenient input processing using popular spreadsheet programs and results presentation using GIS.
Figure 3. A graph representing the recovery of damaged low and high-income households.
Where has ResilUS been applied?
ResilUS has been under development for almost a decade and in the prototyping process has been applied to three study areas. A prototype model was applied to the case of the catastrophic 1995 Kobe (Japan) earthquake, and a series of validation exercises were conducted. Based on feedback from hazard mitigation and recovery planners, ResilUS was updated and has been implemented for the case of the 1994 Northridge (Los Angeles) earthquake. Implemented model improvements included making the recovery indicators more conceptually relevant to planners’ information needs. The model was calibrated based on empirical data describing the Northridge, CA disaster. ResilUS is currently being applied to southwest Louisiana to model recovery of four rural parishes from Hurricane Rita. This work is focusing on building better representation of ecological and social capital into the model. ResilUS will be applied to Western Washington in the next few years as part of a recently awarded National Science Foundation grant. More about each ResilUS application can be found via the project links below, as well as associated publications.
Figure 4. An image of Los Angeles County, overlayed with areas of seismic shaking intensity and recovery timeperiod of residences.
What institute projects are associated with ResilUS?
- Repeat Disaster Impacts to Infrastructure Networks and their Effects on Economic Agent Recovery
- Community Resilience Index (NOAA CSC)
- Business Recovery Related to High-Frequency Natural Hazard Events (Natural Hazards Center, Quick Response)
What publications are associated with ResilUS?
Green, R., Miles, S., Gulacsik, G., & Levy, J. (August 2008). “Business recovery related to high‐frequency natural hazard events, Quick Response Report 197.” Boulder, CO: Natural Hazards Center.Quick Response Report 197.” Boulder, CO: Natural Hazards Center, http://www.colorado.edu/hazards/research/qr/qr197.pdf.
Miles, S.B. and Chang, S.E. (2008) “Modeling Community Capital Loss and Recovery”, Proceedings of the 14th World Conference on Earthquake Engineering, Beijing, China (DVD Proceedings).
Miles, S. B. and Chang, S. E. (2007) “A simulation model of urban disaster recovery and resilience: implementation for the 1994 Northridge earthquake”, Technical Report MCEER-07-0014, Multidisciplinary Center for Earthquake Engineering Research.
Miles, S.B. and Chang, S.E. (2006) “Modeling Community Recovery From Earthquakes,” Earthquake Spectra, 22(2) pp. 439-458.
Chang, S.E. and Miles, S.B. (2004) "The dynamics of recovery: A framework." in Y. Okuyama and S.E. Chang, eds., Modeling the Spatial Economic Impact of Disasters. Springer-Verlag.
Miles, S.B. and Chang, S.E. (2003) Urban Disaster Recovery: A Framework and Simulation Model, Multidisciplinary Center for Earthquake Engineering Research Technical Report 03-0005.