DISASTER RESEARCH CENTER

An Interdisciplinary Approach to Modeling Multiple Stakeholder Decision Making to Reduce Regional Natural Disaster Risk

RESEARCHERS: Rachel Davidson, Joseph Trainor

FUNDING: Department of Homeland Security, National Science Foundation

PROJECT DESCRIPTION:
The project will result in a new framework of interacting mathematical models that can be used to better understand, design, and evaluate government natural disaster risk management policies, such as providing funds to help homeowners strengthen their homes or requiring homeowners to buy natural disaster insurance. By supporting improved design and evaluation of public policies, the project will help the country better manage its risk. By considering the individual, sometimes competing stakeholder points-of-view up front, as an integral part of the analysis, the new framework will make it easier to identify those win-win system-wide solutions that are most likely to be put into action and to be effective. Engaging representatives of the relevant government agencies, and insurance and home building industries as partners at the beginning of the project will help ensure that the research offers usable results that can be put into practice as quickly and effectively as possible.

Co-Principal Investigators: Jamie Kruse, East Carolina University; Linda Nozick, Cornell University

Coastal Hazards, Equity, Economic Prosperity and Resilience (CHEER)

DURATION: September 1, 2022 –
RESEARCHERS: Rachel Davidson, Sarah DeYoung, Joseph Trainor, A.R. Siders

FUNDING: National Science Foundation

PROJECT DESCRIPTION:
The UD-led hub — Coastal Hazards, Equity, Economic prosperity and Resilience (CHEER) — is one of five NSF-funded projects announced recently as part of the agency’s Coastlines and People program, which is concentrating its research efforts to protect the natural, social and economic resources of U.S. coasts, and to help create more resilient coastal communities.

This five-year project will be led by Rachel Davidson, a core DRC faculty member and UD professor of civil and environmental engineering. Co-principal investigators include Sarah DeYoung, core DRC faculty member and associate professor of sociology and criminal justice at UD; Linda Nozick, professor and director of civil and environmental engineering at Cornell University; Brian Colle, professor and division head of atmospheric sciences at Stony Brook University; and Meghan Millea, professor of economics at East Carolina University.

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DRC COVID-19: Community Impacts and Adaptation to Crisis

RESEARCHERS: Tricia Wachtendorf, James Kendra

FUNDING: Internally Funded

PROJECT DESCRIPTION:
The crisis surrounding COVID-19 impacted communities across the globe. This effort examined the impact of the crisis on community in the early stages of the pandemic, exploring issues of preparedness, response, adaptation, and decision-making, among other social consequences. A concentric approach to data collection began with the impact of the crisis on an institution of higher education – the University of Delaware and its population. The examination spanned outward to include others who have relationships with the institution (e.g. community members, businesses, faith-based organizations, agencies, among others). We then circle back to those involved with the community around the core institution, to examine in greater depth core questions around impact, decision-making, and adaptation under crisis. Several hundred in-depth interviews were conducted with people impacted by the crisis, with the potential to follow up with participants at a later date.

HAZARDS SEES TYPE 2: Dynamic Integration of Natural, Human, and Infrastructure Systems for Hurricane Evacuation and Sheltering

RESEARCHERS: Rachel Davidson, Tricia Wachtendorf

FUNDING: National Science Foundation

PROJECT DESCRIPTION:
We are developing a new computational framework to support hurricane evacuation management. The framework, called the Integrated Scenario-based Evacuation (ISE), explicitly represents uncertainty in hurricane evolution and can be used to support robust, adaptive, and repeated decision-making. The hazard is represented with an ensemble of probabilistic hurricane scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. Components are integrated in a multi-stage stochastic program to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The recommendations advance the state-of-the-art because: (1) they are based on an integrated hazard assessment that includes the effects of storm surge, wind waves, tides, river discharge, inland flooding, and wind; (2) explicitly balance competing objectives of minimizing risk and travel time; (3) offer a well-hedged solution robust under the range of hurricane evolutions; and (4) leverage the substantial value of decreasing uncertainty during an event. The first version has been developed and demonstrated in North Carolina. Additional PIs: R. Kolar, Oklahoma, B. Blanton, UNC Chapel Hill, L. Nozick, Cornell, and B.Colle Stony Brook

Infrastructure System Damage Modeling with Data from the 2010-2011 Christchurch, New Zealand Earthquakes

RESEARCHERS: Rachel Davidson

FUNDING: Internally Funded

PROJECT DESCRIPTION:
The goal of this research is to develop new infrastructure system damage models using statistical methods that are new for this application. Specifically, we are analyzing a large, uniquely comprehensive dataset of water supply system damage from the 2010-2011 Christchurch, New Zealand earthquakes. We are comparing generalized linear models, boosted regression trees, and random forest models to see which provide the best fit to the data and the best predictive power. The research aims to improve prediction of water supply system pipeline damage in future earthquakes and improve methods for modeling lifeline damage in extreme events in general. Co-Principal Investigators: Matthew Hughes (University of Canterbury) and Misko Cubrinovski (University of Canterbury)

NSF COLLAB RSH CRISP TYPE 2: Defining and Optimizing Societal Objectives for the Earthquake Risk Management of Critical Infrastructure

DURATION: September 1, 2017 – August 31, 2021
RESEARCHERS: Rachel Davidson, James Kendra

PROJECT DESCRIPTION:
Critical infrastructure systems, such as electric power and water supply, must be designed, managed, and operated so they function reliably and efficiently even in the case of an extreme event. Nevertheless, the way infrastructure system services meet societal needs and the way disruptions of those services impair the ability to meet societal needs are not well understood. In this project, we will define the societal objectives for infrastructure system performance in earthquakes and develop a method to comprehensively optimize a broad range of risk management strategies to meet them, including component design, upgrading, and repair and restoration planning. Specific project tasks include: (1) Developing a probabilistic scenario-based model of the risk of multiple infrastructure systems to earthquakes with the ability to evaluate alternative risk management strategies; (2) Integrating the complementary strengths of social media, household surveys, and economic impact analyses to empirically assess societal objectives, users’ adaptive strategies in responding to disruptions, and the relationships between them and traditional measures of system functioning; (3) Developing an optimization model to optimize risk management to meet societal objectives; and (4) Demonstrating models through a full-scale case study for electric power and water in collaboration with our partners at the Los Angeles Department of Water and Power.

NSF HDBE: Collaborative Research: Leveraging Massive Smartphone Location Data to Improve Understanding and Prediction of Behavior in Hurricanes

DURATION: September 1, 2020 – August 31, 2023
RESEARCHERS: Rachel Davidson, Tricia Wachtendorf, Sarah DeYoung

FUNDING: National Science Foundation

PROJECT DESCRIPTION:
In this project, newly available anonymous smartphone location data will be used to dramatically improve understanding of how people behave during hurricanes (e.g., how many people will evacuate, when, how, from where, and to where). In this project, we will promote the progress of science by capitalizing on the availability of a new type of data—anonymous location information from smartphones—to make a leap forward in understanding and predicting the behavior of the population during hurricane evacuations. The project will advance national welfare and benefit society by substantially improving the ability to manage future evacuations. During a hurricane, officials make many highly consequential decisions, including issuing official evacuation orders, messaging the public, opening shelters, staging materials, and staff, implementing special traffic plans, executing support for vehicle-less populations, and preparing to undertake rescues. All of these depend directly on how many people are expected to evacuate, when, how, from where, and to where. By providing a more accurate and nuanced prediction of population behavior during hurricanes, this project will enable officials to make those decisions in a more informed and effective way. Our practitioner partners from the Federal Emergency Management Agency (FEMA) and the Florida and North Carolina state emergency management agencies will also help us share findings with the larger emergency management community. Combining the power of the new data with domain expertise based on traditional survey and interview data will advance the science.

NSF LEAP HI: Embedding Regional Hurricane Risk Management in the Life of a Community: A Computational Framework

DURATION: September 1, 2018 – August 31, 2023
RESEARCHERS: Rachel Davidson, Joseph Trainor

FUNDING: Cornell University, East Carolina University, National Science Foundation

PROJECT DESCRIPTION:
A breakthrough in disaster risk reduction will require an approach that views disasters not as abnormal events but as a regular part of a community’s evolution, and disaster risk management as inextricably interwoven with the normal activities of everyday life. In this project, a novel computational modeling framework will be developed using this approach to improve understanding of the underlying dynamics that lead to escalating regional natural disaster risk, and to support design and analysis of public policy interventions to address them. In a system-wide analysis, the Multistakeholder Disaster Risk Management (MDRM) framework will explicitly consider perspectives of and interactions among multiple key stakeholders (government, primary insurers, and homeowners), multiple diverse interventions (e.g., home strengthening, insurance, land use planning), and not just actions that are explicitly risk-focused but “risk-influential” actions as well. The MDRM computational framework will include seven interacting mathematical models representing physically-based simulation of damage, losses, and ways to strengthen homes; decision-making by each main stakeholder type including oligopolistic competition among insurers; and the changing building inventory and regional economy that provide the context. It will be developed with a full-scale application for hurricanes in North Carolina. This project promises improved understanding of the creation and management of regional natural disaster risk by, for the first time, uniting the conceptualization of disasters as part of the normal life of a community with the power of quantitative, dynamic engineering modeling of risk, decision-making, and economics. Principal Investigators: Linda Nozick, Cornell University, and Jamie Kruse, East Carolina University

NSF SCC-CIVIC-PG TRACK B: An Integrated Scenario-Based Hurricane Evacuation Management Tool to Support Community Preparedness

DURATION: February 1, 2021 – May 31, 2021
RESEARCHERS: Rachel Davidson, Tricia Wachtendorf

FUNDING: National Science Foundation

PROJECT DESCRIPTION:
As a hurricane approaches, emergency managers must determine when and where to issue official evacuation orders. It requires integrating large amounts of uncertain, changing information to make consequential decisions in a short time frame under pressure, and the stakes are high. An opportunity exists to leverage recent research—in particular, the Integrated Scenario-based Evacuation (ISE) tool—to help meet that challenge. This team designed the ISE tool to be run for a particular hurricane as it approaches the U.S. When run at a point in time, it generates a set of contingency plans and defines the circumstances under which to implement each, depending on how the hurricane evolves. Each plan includes recommendations about whether or not to issue an evacuation order for each geographic evacuation zone, and if so, when. While the new technology has promise, moving from research to practice brings its own challenges. The objectives of Stage 1, therefore, are to: (1) Determine how the new tool and its output can support emergency managers’ natural decision-making process; (2) Conduct a needs assessment for the tool; and (3) Advance understanding of community innovation in disaster management. The Stage 2 objective is to implement an operational prototype of the ISE-based decision support tool for North Carolina. The emergency manager partners will ensure the tool is of practical use; the researchers will ensure it reflects the best science, and the industry partner will ensure its impact is sustainable by hosting it on their platform.