Back to Normal: Earthquake Recovery Modeling Project, Napa, CA Dr. Christopher G. Burton Global Earthquake Model, Pavia, Italy 26 April, 2016 – Vancouver, BC

What GEM does - Scientific Framework Integrated Risk produced by Combine socio-economic indicators into models of social vulnerability and resilience Combine with losses to produce an integrated view of risk to a given community. All three groups work closely with the GEM software development team and scientists and engineers around the world to collect data, produce tools and models.

Same Event Different Consequences (March 2015)

Same Event Different Consequences (August 2015)

Same Event Different Consequences (March 2016)

Same Event Different Consequences Bring in Policy—It’s not all about the buildings

Similar Damage, Similar Location: Different Recovery Outcomes

Vulnerability Science What circumstances place people and places at risk? What enhances or reduces the ability of populations to respond to and recover from environmental threats? What are geographic patterns among and between places? Social Systems Natural Systems Built Environment /Engineered Systems Place-based Understanding Goal: To provide the basis for risk reduction policies and mitigation initiatives; to facilitate pre- and post-disaster planning

Henry V. Burton, PhD., UCLA Christopher G. Burton, PhD., GEM

Recovery Prediction Tool for OpenQuake Develop functions that link earthquake shaking intensity to the probability of exceeding recovery-based building limit states Develop time-dependent functions that capture the trajectory of recovery at the household level that accounts for uncertainty in immediate post-earthquake limit state of building Incorporate the effects of externalities into the recovery functions Aggregate building level recovery functions to community-level Limit States for Buildings --The work concerns the development of a framework and computational tools to quantify the effectiveness of specific resilience-building actions that would increase speed of recovery following an earthquake --An overview of the proposed framework is illustrated in the figure. --Here, the PEER PBEE framework is applied to each building within the target community, incorporating new damage measures and a new decision variable, the outcome of which is a recovery function that is generated for individual buildings. --In the next stage, the building-level metrics are aggregated to produce measures of community-level performance. Adapted from PEER PBEE Framework From Burton, H.V., et al. (2015). Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience, J. Struct. Eng. .

Incorporating externalities into recovery prediction Community Transformation  Time  (a) (b) What inherent conditions within communities provide the best predictors of recovery? What pre- and post-event factors affect recovery (e.g. preparedness, political decision-making? To what extent do these factors predict a known and measureable outcome such as recovery?

Understanding Drivers of Recovery: Damage and long-term recovery assessment Despotaki et al. – In preparation

Classifying Recovery Outcomes Also Bring in Discussion about structural and non-structural components.

Why Resilience? Absorb impacts Cope Adapt Learn Change Resilience birdfluwhattodo.com

Recovery Drivers Database Variable Selection Underlying Dimensions Recovery Drivers Database Social Social capacity Community health and well-being Equity Economic Economic and livelihood stabilities Resource diversity Resource equity Economic infrastructure exposure Institutional Mitigation and planning Preparedness Political influence Development Infrastructure Housing type Response and recovery Access and evacuation potential Infrastructure exposure Community Creative class Sense of place Social capital Cultural resources Social: (differential social capacities of communities that affect their propensity to respond to external stressors) --Social Cap (context-related abilities of individuals and social groups to behave successfully in a certain situation, e.g. minorities, age, disabilities, education) -- Health and Well Being (premise is that communities that provide their citizenry with resources and support facilities will exhibit a higher standard of living, e.g. psychosocial support, healthcare, adult education, social assistance Economic: (in part a measure of economic vitality of communities and infrastructure exposure) --Livelihood, e.g. proxies for homeownership, employment status, and the mean sales volume of businesses --Resource equity, e.g. disparities in homeownership, access to lending institutions, and access to physicians --Economic diversity, e.g. employment type, the number of commercial establishments in an area, and the ratio of large to small businesses --The number and diversity of commercial establishments, retail centers, and the size of businesses directly relate to the ability of a community’s economy to maintain an acceptable level of functioning by assuring a substantial inflow of capital for redevelopment and reconstruction Institutional: (covers mitigation, planning, and disaster preparedness) --Capacity of communities to reduce risk, to engage residents in mitigation activities, and to enhance and protect the social systems on which communities depend Infrastructure: (community response and recovery capacity) --number of police, fire, emergency relief services, temporary shelters, rail and arterial miles, vacant housing units, hotels/motels, mobile homes Community Capital: (embodies the relationships that exist between individuals and their larger neighborhood and community) --based on principals of social capital (adaptive capacities in social systems that can support the process of community resilience to maintain and sustain community health --social interaction, community bonds, creative class occupations for innovation, cultural resources such as museums, etc. Environmental Systems: (concerned with measures of biophysical risk and exposure) --land area that is not in inundation zones, that does not contain erodible soils, and that is not in landslide incidence zones were incorporated to capture risk and exposure within natural systems --Sustainability—don’t cut down your wetlands, etc. Burton C.G. (2015). A Validation of Metrics for Community Resilience to Natural Hazards and Disasters using the Recovery from Hurricane Katrina as a Case Study. Annals of the Association of American Geographers, 150(1): 67–86.

Regression Modeling Overview Simulation procedure to develop a distribution of predicted recovery probabilities for block groups Overcome the problem arising from the uncertainty associated with the limited number of assessed buildings in each block group ***Gives odds of moving from one recovery stage to another **** Accounts for different Percentiles Title of slide image can go here

Linking Recovery to Indicators: Predicted vs. Observed 6 months 12 months 18 months Despotaki et al. – In preparation

Recovery Prediction: Proposed Model 6 Months After Event 50% (median), 16% and 84% percentile probabilities of recovery in the city of Napa, as determined by the proposed recovery model; at 6 months after the event.

Recovery Prediction: Proposed Model 12 Months After Event 50% (median), 16% and 84% percentile probabilities of recovery in the city of Napa, as determined by the proposed recovery model; at 12 months after the event.

Drivers and Barriers to Recovery Disaster Preplanning and Preparedness Social Networking State of the economy Race and Socio-economic Status Federal policy changes Difficulty with federal forms Earthquake insurance Education and literacy Income and employment Homeownership vs. renters ***Gives odds of moving from one recovery stage to another Title of slide image can go here

The Road Ahead Continue data to Identify recovery drivers and explain extent to which drivers predict recovery Incorporate externalities in recovery modeling framework for Southern California. Incorporate lessons learned from other long-term recovery studies (e.g. Kathmandu) to construct tools for global benefit. Software tool

Christopher G. Burton Global Earthquake Model christopher.burton@globalquakemodel.org http://www.globalquakemodel.org/