Scott B. Miles

Modeling Community Recovery from Earthquakes

This paper sets out the foundations for developing robust models of community recovery from earthquake disasters. Models that anticipate post-disaster trajectories are complementary to loss estimation models that predict damage and loss. Such models can serve as important decision support tools for increasing community resilience and reducing disaster vulnerability. The paper first presents a comprehensive conceptual model of recovery. The conceptual model enumerates important relationships between a communitys households, businesses, lifeline networks, and neighborhoods. The conceptual model can be operationalized to create a numerical model of recovery. To demonstrate this, we present a prototype computer simulation model and graphical user interface. As the model is intended for decision support, it is important to involve potential users in model development. We conducted a focus group involving Puget Sound, Washington, area disaster management practitioners to elicit local insight about community recovery and model development needs, using the prototype as stimulus. Important focus group issues included potential model inputs, useful recovery indicators, potential uses of recovery models, and suitable types of software systems.

Rigorous landslide hazard zonation using Newmark's method and stochastic ground motion simulation

Researchers and practitioners in earthquake engineering have recognized geographic information systems (GIS) to be a significant tool in modeling spatial phenomenon related to hazard and risk. GIS, as an engineering tool, has been primarily used for its spatial data storing and presentation features. Models are often simplified to be more compatible with the light computational capabilities of many GIS. If not simplified, heavy computations are generally performed external to the GIS. A prototype vector-based GIS was developed that employs a rigorous approach to Newmarks displacement method for assessing earthquake triggered landslide hazards. The rigorous Newmarks analysis provides desirable flexibility by allowing input of actual ground motions. The prototype hazard GIS incorporates a popular shot filtered noise technique for generating artificial ground motions. The rigorous approach was compared to a popular simplified approach for computing Newmark displacements. Distribution of regional displacements was found to be similar with the simplified approach giving more and larger extreme displacements. The rigorous approach is suitable for large scales to model various seismic scenarios and their effect on seismically induced landslide potential.

ResilUS: A Community Based Disaster Resilience Model

A resilient community is one that does not experience serious degradation in critical services when a hazard occurs and, in the event of degradation or failure, recovers to a similar or better level of service in a reasonable amount of time. The most efficient means of making a community resilient is to make its critical services and capital robust – minimize damage/loss probability or the consequences from damage/loss through mitigation. If a communitys critical services and capital are not robust, efforts must be put into recovery. Based on the measurable aspects of community capital, we have developed a simulation model called ResilUS that operationalizes community resilience across multiple, hierarchical scales in relation to a range of policy and decision variables associated with each scale. ResilUS is implemented using fragility curves to model loss and Markov chains to model recovery with respect to time. ResilUS was applied to the 1994 Northridge earthquake disaster in order to calibrate several output variables with empirical data. ResilUS represents a significant step forward for spatial decision support for disaster mitigation and recovery planning, in comparison to existing loss estimation models.

The Dynamics of Recovery: A Framework

Each disaster reminds us that, from an economic standpoint, losses do not occur instantaneously, but are accumulated over the course of a sometimes long and complex recovery process. Moreover, disasters are spatial events that impact some places and some groups within those places more heavily than others. These effects can be observed in both natural disasters and human-induced events. Thus in the September 11th tragedy of 2001, the loss of the World Trade Center towers and the thousands of human lives do not in themselves constitute the economic impact of the disaster. Neither does the loss of gross regional product (GRP) on the 11th itself. Rather, the economic impact of the disaster is strongly influenced by the multitude of decisions made in the days and months following — decisions regarding whether to relocate an office to New Jersey and for how long, whether to lay off workers and how many, and whether to inject stimulus spending into the New York City economy and how much. Similar post-event decisions strongly influence recovery in natural disasters such as floods or earthquakes. In other words, the process of disaster recovery is critical to understanding the spatial economic impacts of disasters, yet the recovery process itself is extremely complex and uncertain.

Disaster risk reduction capacity assessment for precarious settlements in Guatemala City

This study presents findings of an institutional capacity analysis of urban disaster risk reduction for informal settlements in the Guatemala Metropolitan Region. It uses a resource access perspective of vulnerability, actor-network theory, and qualitative data collection. The analysis reveals that there is interest in disaster risk reduction for the informal settlements; however, there is little in the way of direct financial or oversight relationships between informal settlement residents and all other actors. Respondents observed that informal settlements would probably remain inhabited; thus, there is a need for disaster risk reduction within these settlements. Disaster risk reduction capacity for informal settlements exists and can be further leveraged, as long as steps are taken to ensure appropriate access to and control of resources and oversight. Further, the nascent institutional arrangements should be strengthened through increased communication and coordination between actors, a decentralization of oversight and financial relationships, and mediation of identified resource conflicts.

Evaluating post-disaster ecosystem resilience using MODIS GPP data.

Abstract An integrated community resilience index (CRI) quantifies the status, exposure, and recovery of the physical, economic, and socio-cultural capital for a specific target community. However, most CRIs do not account for the recovery of ecosystem functioning after extreme events, even though many aspects of a community depend on the services provided by the natural environment. The primary goal of this study was to monitor the recovery of ecosystem functionality (ecological capital) using remote sensing-derived gross primary production (GPP) as an indicator of ‘ecosystem-wellness’ and assess the effect of resilience of ecological capital on the recovery of a community via an integrated CRI. We developed a measure of ecosystem resilience using remotely sensed GPP data and applied the modeling prototype ResilUS in a pilot study for a four-parish coastal community in southwestern Louisiana, USA that was impacted by Hurricane Rita in 2005. The results illustrate that after such an extreme event, the recovery of ecological capital varies according to land use type and may take many months to return to full functionality. This variable recovery can potentially impact the recovery of certain businesses that rely heavily on ecosystem services such as agriculture, forestry, fisheries, and tourism.

The Role of Critical Infrastructure in Community Resilience to Disasters

This paper issues a call to improve the conceptual underpinnings of community resilience to disasters as it relates to critical infrastructure. It is argued that, broadly, infrastructure is the combination of both capital and services. Loss and recovery, and thus resilience, of infrastructure do not make practical sense without consideration of both. Specifically, infrastructure is characterized by its relationship to other infrastructure, agents, possible disruptions, possible interventions, jurisdictions and markets. Based on this and previous development work related to the resilience simulation model ResilUS, the beginnings of a new conceptual model are proposed. The comprehensive nature of the model suggests it is appropriate for planning purposes. The conceptual model provides opportunities for advancing ResilUS, specifically, and infrastructure and community resilience research and planning broadly. It facilitates the creation of a database schema for infrastructure loss and restoration and its impact on indicators of community resilience. Population of this schema will push understanding of community resilience and facilitate the development of better tools for supporting resilience planning.

Social Impacts of the 12 January 2010 Haiti Earthquake

The 12 January 2010 Haiti earthquake resulted in some of the most significant social impacts from an earthquake in recent decades. In early March, an Earthquake Engineering Research Institute (EERI) social impacts reconnaissance team documented broad impacts on shelter, livelihood opportunities, and service provision through direct observation, photo documentation, interviews, and a review of other sources. The earthquake left over half of the residential housing in Port-au-Prince heavily damaged; widespread fear that even undamaged structures were unsafe swelled the number of homeless to 1.3 million. The infrastructure damage and significant loss of life within the Haitian government and international aid agencies slowed the early response and reduced the already low levels of basic service provision. Continued research is needed on media portrayal, outcomes of injuries, sheltering decisions, social networks, and learning trajectories for Haitis youth, among other areas.

U.S. Earthquake Policy Activity and Coverage

The goal of this study was to first develop a systematic data collection strategy to create and maintain a database of policies in the United States that promote seismic mitigation. With this database, indices were developed to facilitate understanding of the relationship between policy activity, policy coverage, and seismic risk, as well as to perform cross-state comparison. The most basic index is a count of the number of policies each state has adopted. An index was developed that directly accounts for the seismic risk of each state. A Guttman scale was developed to characterize states’ policy coverage, as well as the level of intensity represented by states’ policy activity. The relationship between policy coverage and seismic risk was also explored. For the most part, this study found a moderate relationship between seismic risk and policy activity, as well as a moderately strong relationship between risk and policy coverage.

Socio-Technical Impacts of Hurricane Isaac Power Restoration

This paper describes the socio-technical restoration process and impacts associated with Hurricane Isaac (August, 2012) in Louisiana. Hurricane Isaac had few other impacts besides the power outage—there was extremely limited wind or flood damage. This isolation provides a relatively rare opportunity of seeing the linkages between electrical network disruption dependent infrastructure, and impacts and responses that might be obscured or overlooked in larger disaster. Thirty-three participants were asked five open ended questions about 1) the significant impacts from the outage, 2) what (if any) lasting effects would result from the outage, 3) the relative performance of Entergy’s restoration, 4) the effectiveness of Entergy’s communication, and 5) factors influencing the public and political dissatisfaction with the restoration performance. Other collected data included content from the news and social media, government documents, press releases, situation reports, and publicly available data. In sum, these data were synthesized to develop a broad understanding of the case study and identify significant themes with respect to impacts, as well as public and political reactions.