Researchers Meeting Abstracts

After the August 2023 Maui wildfires, the Centers for Disease Control and Prevention-funded Public Health Extreme Events Research network (PHEER) pilot-tested its concept of operations plan for a “virtual” deployment, a first-stage mobilization in which a small volunteer task force of PHEER members identified and collated secondary data sources. PHEER serves as an organizing resource for the public health disaster science community of practice, with a particular focus on supporting the deployment and dissemination of rapid public health disaster research in the public's interest after large-scale or highly significant extreme events. The objectives of the Maui Virtual Data Dashboard were to: (1) develop a process for identifying, collecting, analyzing, and sharing post-event secondary data relevant to the health and well-being of a disaster-exposed population; (2) use such data to support PHEER decision-making, particularly related to decisions to mobilize a PHEER field operation or to support public health research efforts in the area; and (3) create a widely available dataset for the public health disaster research community of practice and other interested stakeholders.  This data initiative was also intended to serve as a template for future virtual mobilizations. After briefly describing the phases involved in standing-up and managing a crowd-sourced virtual field team, this research sought to engage discourse to (1) identify candidate metrics and data sources, (2) suggest effective ways to communicate with data owners, (3) find solutions to barriers and roadblocks in securing appropriate data, and (4) make data widely and publicly available.

This presentation discusses the specific consequence prediction data most useful to decision-makers when preparing for major coastal storms (e.g., hurricanes, tropical storms, nor'easters.) Following an “implementation research” approach, findings are presented from a New England regional data needs survey of 36 state and local emergency managers conducted in 2023, along with 10 follow-up interviews. Results suggest categories of critical infrastructure of greatest interest to local emergency managers. Results further indicated how respondents feel access to data can help them to reduce unanticipated storm consequences. Progressive effects of climate change, together with growing societal dependence on complex critical infrastructure, make it increasingly difficult for emergency managers to predict specific consequences of storms for coastal communities. Advancements in high-resolution storm simulation and consequence modeling can help emergency managers make preparedness and response decisions, but these tools do not always deliver localized, actionable data, or they may deliver an overwhelming volume of information that emergency managers liken to “drinking from a fire hose.” To address the resulting data gap, researchers need to better understand end users' data needs. This research leveraged the Coastal Hazards Analysis, Modeling, and Prediction (CHAMP) project to explore the practical application of decision support tools to improve local storm preparedness and response. Results of this research identified the best practices for CHAMP and similar tools based on stakeholder and end-user input. Contributions included advancing understanding of emergency managers' community storm vulnerability assessment and informing further development of decision support tools like CHAMP.

Federal disaster recovery support includes several short- and long-term programs assisting disaster survivors in fulfilling immediate needs to bounce back and longer-term rebuilding. Among such programs, the Federal Emergency Management Agency’s (FEMA) Individuals and Households Program (IHP) is designed to support disaster impacted homeowners and renters in covering various expenses such as temporary housing, funeral assistance, personal property losses, and repairing or replacing damaged homes. Research shows that social vulnerability indicators such as race, class, poverty, and gender significantly impact the pace, progression, and success of these programs across disaster-impacted areas. To date, IHP program success has been measured by the amount of recovery funds spent and the number of fund recipients with little interest in equitable distribution of these federal resources, especially to renter populations who are not accounted for regarding real property losses by FEMA. Although FEMA does collect a limited number of vulnerability indicators (i.e., age, income, access and function needs, household composition), few studies have explored the significance of these variables in assessing disaster damages and aid distribution. Guided by social vulnerability index (SoVI) literature, we investigate how the renter population fare in the recovery process and which social vulnerability variables play a key role in understanding assessed damage and recovery assistance. We analyze IHP assistance provided to renters between 2011 and 2021 at the applicant level. The preliminary findings exhibit that multiple social vulnerability variables are significant and play a role in determining losses and aid distributed to the survivors, and the influence of social characteristics is becoming more influential over time.

With the rapid growth of urban areas, the issues concerning their resilience have become more important now than ever. This is particularly true in the developing world, where resilience building efforts are rarely embedded into development planning and policy interventions are unable to keep pace with the overwhelming expansion of urban areas. Assessing the resilience of urban areas is imperative for Disaster Risk Reduction (DRR). Srinagar City's state of resilience and progress in capacity building process remain largely unknown. This study aimed to assess the disaster resilience of Srinagar city using a resilience scorecard designed by the United Nations Office for Disaster Risk Reduction (UNDRR). The scorecard is comprised of 117 indicators under 10 broad elements of resilience. The study design was implemented through a participatory approach, recording the response on the selected parameters from 300 stakeholders representing a range of sectors to derive inferences about the resilience status of the city. With an average score of 284 out of 560, our assessment suggested that the city is experiencing a chronic resilience deficit with noticeable gaps in the planning. This analysis identified the weak areas and will help in prioritizing the sectors and realigning investments for building urban resilience and achieving the DRR goals of the city.

The landscape of disaster research has evolved from predominantly measuring the immediate impacts of disasters to a more nuanced focus on strategies to accelerate long-term community recovery. This new focus requires an understanding of the connection between pre-event characteristics, initial and long-term impacts of the disaster, and the corresponding recovery over time. Because much of the existing research on recovery has been limited to households and businesses, there is a growing demand for multidimensional and quantitative measures to assess and track recovery of communities following disasters. A key dimension of community recovery is the restoration of organizations responsible for delivering critical social services, including healthcare and education. Researchers at the National Institute of Standards and Technology are working to identify and develop metrics that are relevant to an organization's recovery by combining insights from field observations and case study research in communities that have experienced disasters with a systematic literature review. The literature review examined key factors related to organizational resilience and recovery, including existing efforts to operationalize recovery, while the field observations and case study research highlights the experiences of school and hospital organizations navigating the challenges of post-disaster recovery. By combining real-world examples and strong theoretical underpinnings, this work contributes to the evolving discourse on organizational recovery, providing valuable insights for enhancing the resilience of organizations and, consequently, the communities they serve.

Power outages are a secondary hazard that often co-occur with natural hazards and force people to change their routines through behavior changes to survive until power is restored. Due to climate change, more anomalous weather events are expected to occur more frequently, causing infrastructure systems to experience conditions outside their design standards, further exasperating their operational limits. Therefore, the same infrastructure systems could fail more often, especially electrical infrastructure. This research sought to understand how people were affected by power outages caused by the December 2022 winter storm (also known as Winter Storm Elliott) in counties surrounding Buffalo, New York, and Raleigh, North Carolina, to determine if any relationship exists between household demographics, like race and income, and adverse power outage effects. A household survey collected data via a Qualtrics quota sample that targeted participants affected by the winter storm, even if they did not lose power. The survey collected information from 2,063 participants about their power outage experience, their preparedness for the storm, adaptations used, and their overall mood during the outage. Difference-in-means tests assessed if there were statistically significant differences between outage length and socioeconomic factors like race and income. This research hypothesized that racial and ethnic minority groups and those earning lower incomes are more likely to experience more prolonged power outages than whites and those who earn higher incomes. Results showed that these social vulnerability indicators are not necessarily as predictive of power outage impacts as initially hypothesized.

Insurance is a critical tool for mitigating financial losses from natural hazards and enabling recovery. Payments received from these policies allow homeowners to make the necessary purchases or repairs to restore normalcy to their lives. Therefore, because people depend on these payments, the timeliness of payments matters. However, recent reports suggest that wait times between submitting claims and receiving payments are steadily increasing, raising questions about the ability of insurance to enable efficient recovery. Using a survey of U.S. households impacted by a major hurricane between 2018 and 2023, this research aims to understand household expectations of timing for insurance payments, consequences of delayed payment, and preferences for alternative payment plans. Drawing upon literature on lottery payouts, the hypotheses are that individuals prefer to receive a greater portion of their insurance payout sooner than later and are willing to accept a delay in receiving their payment as long as a more timely, partial payment is guaranteed. Additionally, people are more willing to accept a faster process despite a lower payout because of a less detailed damage assessment. Giving a quicker option can benefit insurance companies by reducing the administrative burden and can enable a quicker recovery for policyholders. The findings from this work will quantify the effects of delayed insurance payments on household recovery while offering solutions to improve the claims process for insurers and households.

Public policies often exert enduring effects well beyond their temporal enactment. In the mid-20th century, the United States witnessed the emergence of "redlining" as a quasi-legal segregation practice, delineating communities along racial lines. This not only prolonged racial disparities but also systematically contributed to the formation of socioeconomically disadvantaged areas marked by substandard infrastructure. This research investigates prevailing flood exposure disparities in 239 United States metropolitan areas where redlining maps are publicly accessible. The flood exposure experience is evaluated using mean inundation depths and severity of the events community members may encounter. The research used Fathom Flood Maps to provide high-resolution flood inundation data under climate change scenarios coupled with a high-granularity geospatial stochastic population data inventory characterized by social vulnerability levels. The researchers overlayed flood maps for 7 mean return intervals (5 to 1,000 years), onto the study area's population data and conducted a spatial statistical analysis across the populated regions. The initial findings revealed the disproportionate burden on community members characterized by higher levels of social vulnerability. Taking the Kansas City Metropolitan Area as an example, "High" socially vulnerable populations experienced mean flooding depths that are 2.5 times greater than their "Low" socially vulnerable counterparts. Furthermore, "High" socially vulnerable populations regularly experienced severe flooding whereas for "Low" vulnerability populations to experience the same level of severe flooding, the event has to be 200 times less frequent. Findings have important implications for resilience, highlighting the imperative need to address historical legacies of inequities.

This study explores how poor Black women define and navigate the long-term recovery process in a structurally and culturally violent society. More explicitly, it explores the specific ways in which they actively resist structural and cultural violence, and how poor Black women understand and define their own vulnerability and resiliency in the context of disasters and their recovery process. From a theoretical perspective, this work proposes a Critical Black Feminist approach to disaster science's understanding of how poor African American women recover in the larger context of violence and thus, how their recovery post-disaster is influenced by said violence. Through a radical ethnographic study, this work is centered around the lived experiences of 29 low-income Black women in Lake Charles, Louisiana, and their experiences facing and recovering from disasters. Methods of this study include interviews, field observations, and archival data, to provide a historical and contemporary analysis of their experiences and to inform larger disaster theoretical concepts such as recovery, resilience, and vulnerability. Findings suggest that low-income Black women defined their resilience in relation to the process of recovering rather than seeing resiliency as an outcome of recovery. Most women denied traditional framings of vulnerability and defined their recovery in terms of their well-being and that of their families. Data was analyzed using a qualitative data analysis software and was coded in relation to interview topics using the study's theoretical framework: cultural violence, structural violence, structural dislocation, recovery theory, and sites of resilience theory.

Improving access, timeliness, and integration of wildfire exposure and health data can help to advance research and inform targeted public health responses to wildfires. A scoping review was conducted to (1) understand wildfire-related health effects, (2) identify and describe environmental exposure and health outcome data sources used to research the impacts of wildfire exposures on health, and (3) identify gaps and opportunities to leverage exposure and health data to advance research. A literature search was conducted in PubMed, and a sample of 83 articles met inclusion criteria. Most studies examined respiratory and cardiovascular outcomes. Hospital administrative data was the most common health data source. Health data were not generally available in real-time and often lacked extensive spatial and temporal coverage. Wildfire smoke, specifically PM2.5, was the most common exposure measure and frequently estimated from monitoring networks or satellite data. Exposure data were often available in real-time and provided better spatial and temporal coverage but did not capture the complex mixture of hazardous smoke toxicants nor exposures from non-air routes such as soil, food, and water. Real-time health data with more precise geospatial linkages and expanded environmental measures would facilitate research into the acute and longer-term health effects of wildfire exposures. Addressing the gaps identified with this review, and improving methods to effectively integrate these data sources, will help researchers and the public health community to better characterize and understand the health impacts of wildfires and to develop effective measures to reduce the adverse impacts in the United States and globally.

Cultural gender norms impact how people behave during a crisis, and how authorities and at-risk populations approach disaster risk reduction strategies. At Fuego volcano, Guatemala, residents prioritize women, children, and older adults for evacuation while men stay back to protect property. This disproportionately exposes men to the threat and places the burden of evacuation on women. The authors of this study applied qualitative methods to investigate women's experiences of the evacuation process after a paroxysmal eruption on March 7-8, 2022, and how these experiences might inform future risk reduction efforts. Results show that the women interviewed took on additional caretaking responsibilities throughout the evacuation process, were motivated in their decisions primarily by the safety and wellbeing of young children, deferred to men for decision-making, but also described defying male partners to prioritize their own responsibility to their children, and held significant influence over the decisions of their extended families and neighbors. These findings indicate that messaging and services focused on the health and wellbeing of young children may encourage evacuation; that women must be involved in the development of evacuation strategies to ensure those strategies address their needs and risk tolerances; and that officials should consider the influence of gender norms on evacuation decision-making during crises.

Infrastructure systems provide critical services, and thus, effectively managing infrastructure service disruption risks is crucial to support communities and improve their disaster resilience. Often, populations of greater social vulnerability are disproportionally impacted by disasters, especially by infrastructure outages, resulting in disaster impact inequities. These areas of greater social vulnerability are often serviced by less adept infrastructure more likely to fail, which only increases the impact inequities from service outages. Service inequities pose a significant obstacle to achieving community resilience and should be considered in infrastructure risk management. Yet, conventional infrastructure risk management is based on system performance and least-cost. To date, equity-driven risk management has not often been conducted and few metrics exist to support this approach. This study implemented a recently developed equity metric to assess infrastructure service equity performance alongside traditional performance and cost considerations across retrofit selections. The equity metric is derived from Theil's T and benchmarks the service provision inequity among vulnerable and non-vulnerable groups of concern. The inequity assessment was implemented for Galveston, Texas's electric distribution network (EDN) and its retrofit selection relative to a hurricane. The implementation allowed for an assessment of equity gains across degrees of EDN retrofit and contextualized other ramifications when adopting an equity-driven paradigm. Yet, high resolution infrastructure quality data was not available for this investigation site nor is commonly available for alternative locations. Therefore, this assessment was conducted for multiple simulated quality assignments to investigate the equity impacts across different quality characterizations.

This research presents the Rhode Island Consequence, Hazards, Analysis, and Prediction (RICHAMP) tool. The Participatory Action Research (PAR) approach captures critical infrastructure managers concerns about hurricanes and nor'easters across the state of Rhode Island (RI). RICHAMP is an online dashboard viewer that integrates these concerns with wind, wave, and surge storm model outputs. Emergency managers (EMs) need access to nuanced data that contextualize the local-scale risks and impacts posed by major storm events. Traditional tools available to EMs, such as vulnerability assessments, do not provide actionable data regarding specific local concerns, such as emergency vehicle access and potential communication disruptions. The development of high-resolution storm models can aid EMs in making informed storm preparedness measures at the local scale. This work focuses on statewide critical infrastructure sectors, expanding upon methods and research developed during two pilot studies which captured facility manager concerns in Providence and Westerly, RI. Data collection included focus group interviews and site interviews with critical infrastructure managers. The authors’ approach utilizes web and mobile applications to simplify the data collection process, and establish a workflow, for critical infrastructure managers to report and maintain their hazard concerns in an Infrastructure Assets Consequence (IACT) database. The online dashboard viewer that integrates numerical storm models outputs with the IACT database will be used in an Emergency Operations Center (EOC) to flag the potential flooding and wind impacts during a real-time storm event or for planning scenarios, thus informing local and statewide emergency response activities.

Natural hazards generate tremendous amounts of debris that negatively impacts communities. Many of the disaster debris prediction models currently used in practice exhibit significant inaccuracies due to their generality and inherent uncertainty. Additionally, no methods address urban flooding. Studies have yet to use unsupervised algorithms for investigating the mechanisms influencing flood debris quantities across a region, which would help guide flood debris models. Thus, this study demonstrated a hybrid unsupervised and supervised machine learning approach for understanding the drivers influencing flood debris quantities using post-disaster waste data acquired in Beaumont, Texas, after widespread flooding from Hurricane Harvey. The authors performed K-means clustering to categorize debris tonnage per census block into “high,” “medium,” and “low” clusters followed by statistical testing to reveal relationships between flood debris and its drivers. A Random Forest (RF) classification model was developed to demonstrate a method for predicting flood debris and to evaluate relative variable importance in model construction. Results revealed that census blocks with the largest debris amounts generally had greater flood depths, steeper terrain slopes, and newer, more expensive homes. Conversely, blocks with the least debris had higher first-floor elevations. The RF model achieved an accuracy of 70% on a blind test set and relative variable importance was analyzed. An unsupervised machine learning approach can provide a good first step towards reducing uncertainty in predicting disaster debris. First-floor elevation emerged as a significant driver but is not currently considered in prediction models

The health and well-being of women is known to be disproportionately affected during public health emergencies (PHEs), including increased risk for experiencing intimate partner violence (IPV). This research summarized the recommendations from a comprehensive consensus report conducted by the National Academies of Science, Engineering and Medicine and sponsored by the Health Services and Resources Administration. A multidisciplinary expert committee developed a conceptual framework and recommendations for delivering essential healthcare services related to IPV, using an all-hazards approach. The population of focus was women aged 13 and older who directly experienced or are at risk for IPV. For the purposes of the study, women were defined as cisgender women, transgender women, and people whose gender identity is not male, who are non-binary or otherwise gender expansive. The report made 11 recommendations defining essential health care services related to IPV, addressing IPV-related health inequities, and ensuring women can access this essential care when disasters and PHEs occur. Services identified include reproductive care, forensic exams, treatment for physical injuries, HIV treatment and screening, and support for women to connect with other helpful resources to protect women's safety. Planning and operationalization considerations for federal and state, local, tribal, and territorial response teams or volunteer organizations active in disaster are prioritized for preparation and response phases of PHEs, including open-access training and appropriate supplies for emergency health responders. When implemented, the recommendations will increase access to essential health care services related to IPV and ultimately save lives.

Parents of school age children struggled during COVID-19 pandemic school closures. The stress, uncertainty, and role conflict they experienced as they worked from home, managed their children's education, and maintained a healthy household placed strain on their own mental health. How was the mental health of parents impacted by the strains of pandemic life? How did parents foster resilience through their social connections and resource networks? This study explores these questions using in-depth qualitative interviews and social network analysis with parents of school-aged children (n=39). Interviews focused on the experiences of at-home education, mental health outcomes, and family wellbeing. Social network analysis was used to identify resource networks and their impacts on parental mental health. Parents reported an increase in stress, loneliness, depression, anxiety, fear, and guilt due to pandemic pressures. These effects were greater for parents of children with disabilities, single parents, and lower income families. Social network analysis uncovered how parents utilized their traditional social networks and formed new support networks to foster resilience. Parents experiencing greater levels of mental health strain had smaller social networks and less diverse types of social connections than their peers. The results of this study illuminate the impacts of school closures on parents of school age children during a disaster and the need for equitable educational and social welfare policies that support children and families. This work also highlights the need for increased access to mental health resources.

This research examines household evacuation behavior during two devastating storms that struck Louisiana on the same day years apart, Hurricane Katrina in 2005 and Hurricane Ida in 2021. Based on responses to three post-storm behavioral surveys conducted in Louisiana, some of the household evacuation-related choices seem to have shifted, as indicated by the change of evacuation rate (74% in Katrina versus 68% in Ida), evacuation timing (more households evacuated three days before landfall and on the day of landfall during Ida), and evacuation destinations (fewer households evacuated to Central Louisiana and more on I-10 west heading to Lake Charles and Houston). This research answers the following questions: (1) what factors might lead to the behavioral shift observed from survey statistics; (2) whether evacuation behavioral models estimated for the earlier hurricanes perform well in predicting choice behavior in new storm scenarios; (3) what factors affect model prediction accuracy; and (4) how those factors can be updated for higher prediction accuracy. This study provides lessons learned from data collection for model application and parameter update for model transfer, which are expected to improve the usefulness of estimated statistical models in practical applications. Results from this study are also expected to be useful in gaining a better understanding of short-term evacuation decision-making and long-term population migration due to storm impacts.

Disaster scholars and practitioners have largely shifted from thinking about disasters as unpredictable “natural” events to an understanding that disasters are created by social, economic, and political processes which enable the conditions for vulnerability and exposure to risks. One difficulty with this transition is the increased complexity from considering multiple complex systems and their interactions to predict and understand disasters. This presentation explains how a scenario-based game was created and used to facilitate dialogue about individual and community values and priorities for adaptation and retreat in Southwest Florida. The game verified previous research findings that games are a successful engagement tool for diverse audiences and promote social learning and demonstrated the importance of design elements to elicit multiple perspectives. The future-oriented scenarios were realistic, yet fictional, allowing participants to draw on their lived experience and develop imaginative capacity to think of the unthinkable. The trade-off decisions presented to the participants in the game prompted engaging, open-ended discussion of values and constraints. Used in conjunction with other methods, this research demonstrated that a futures-oriented scenario game increases understanding of the intersectionality of vulnerability and the driving forces of risk-related decisions within a particular case study. This presentation will share the methodology for creating a scenario game, identify transferable lessons on how to help research participants imagine an unpredictable future, and present critical reflections on how this tool can be used for understanding and communicating disaster risk.

With over 1,350 miles of coastline and 89% of the population living in coastal cities, Florida residents are likely to experience one of the most damaging consequences of disasters, temporary or permanent displacement. This risk is increasing due to rising temperatures in the Gulf Coast. The values, risk perceptions, and human biases related to disaster risk are naturally complex and counterintuitive. There are trade-offs between short-term and long-term priorities, as well as individual and community benefits. This doctoral research project uses systems thinking to explore the complex socio-political nature of disaster risk and better understand disaster vulnerability in Southwest Florida. The study documents system behaviors (i.e., thresholds, feedback loops, and trade-offs) as well as the underlying values and beliefs of stakeholders through three methods: (1) systems mapping, (2) a scenario-based game and focus group, and (3) semi-structured interviews. The results identify strong building codes as an enabling factor for adaptation, yet also identify loose development regulations in Southwest Florida as a key factor for increasing future risk. Insurance impacts residents' ability to live in high-risk areas and rebuild after a storm, although results indicate the impacts vary and are closely related to income and housing affordability. The research also identifies a need for better communication and training to build risk literacy among local professionals and residents. This presentation will elaborate on key findings and discuss future research needed to better transition communities in areas of increasing disaster risk.

One of the most consequential effects of climate change is the increased likelihood of a maritime accident in the Arctic, a result of increased traffic during longer ice-free seasons. In Arctic Alaska, a maritime disaster would pose challenges for disaster preparedness and response owing to the vast distances between Arctic Alaska and major population centers in the state. Our interdisciplinary effort modeled and analyzed the effects of planning for these events. Planning efforts such as prepositioning emergency response supplies or making assumptions about how search and rescue would be coordinated can have profound effects on Arctic communities, including effects on subsistence hunting and fishing, impacts to local facilities and utilities, and disruption of community life. Communities would be challenged to respond to oil spills, or to handle people evacuated from ships. This latter challenge is becoming more common as more cruise ships begin to call on small ports in the Arctic. The challenge in preparing for these more likely Arctic maritime emergencies is in balancing the quality of preparedness with reducing the burdens, and potentially creating benefits, for the communities that will be most affected by these potential emergencies. Our research focused on modeling potential scenarios for understanding the effects of emergencies in the Arctic. We found that such responses are possible to organize but require an understanding of the remarkably complex system of governance in Alaska, which involves local, state, and national governments, as well as Alaska native corporations and private sector interests.

Climate change and related environmental disasters have profound and disproportionate impacts on historically marginalized communities. The Queer community—used here to include the entire 2SLGBTQQIA+ population—is a quickly growing, and historically marginalized population across the United States and Canada. This widespread growth is especially true among emerging adults and college students in Gen-Z, whose generation has been characterized by climate change anxiety and activism. Although the emerging adult Queer population is growing, research that engages with this diverse and intersectional population in the context of disasters is severely lacking. To contribute to this body of research, this study engaged with Queer and non-Queer students at an Atlantic Canadian university following Hurricane Fiona in 2022 to examine their distinct experiences, challenges, and needs throughout the hurricane cycle. The authors employed a qualitative approach using four focus groups: (1) Queer students from hurricane-prone areas, (2) non-Queer students from hurricane-prone areas, (3) Queer students from non-hurricane-prone areas, and (4) non-Queer students from non-hurricane-prone areas. Four focus groups enabled the authors to compare potential challenges and service needs between Queer and non-Queer students, and students with or without prior hurricane experience. Results indicate a need for accessible university information, programming, and assistance especially in the preparedness and recovery phases. Using the insights from students, the researchers created recommendations for university policy through infographics and planned student-faculty-administration workshops to mobilize the knowledge

Post-disaster recovery in rural communities remains understudied, though these communities have been known to have disaster risks. This study aims to better understand what factors in rural communities serve as barriers to recovery and which contribute to wildfire resilience. In addition to researching rural community recovery, this study takes a targeted interest in the public health concerns of children impacted by wildfire. Happy Camp, California, was impacted by the 2020 Slater Fire and is over three years into their recovery efforts. This research analyzed data collected through interviews, focus groups, and surveys, conducted with Happy Camp community members to understand their recovery experience. Findings support establishing positive recovery pathways for rural communities.

As governments race to implement new climate adaptation policies that prepare for more frequent flooding, they must seek effective policies for all communities and uphold climate justice. This requires evaluating policies on their overall effectiveness and on whether their benefits are felt across all communities. This research illustrates the importance of considering such disparities for flood adaptation using the Federal Emergency Management Agency National Flood Insurance Program Community Rating System and its dataset of approximately 2.5 million flood insurance claims. CausalFlow, a causal inference method based on deep generative models estimated the treatment effect of flood adaptation interventions based on a community's income, diversity, population, flood risk, educational attainment, and precipitation. The authors found that the program saved communities $5,000–15,000 per household. However, these savings were not evenly spread across communities. For example, for low-income communities, savings sharply declined as flood risk increases in contrast to their high-income counterparts with all else equal. Even among low-income communities, there was a gap in savings between predominantly white and non-white communities; savings of predominantly white communities could exceed $6,000 per household. As communities worldwide ramp up efforts to reduce losses inflicted by floods, simply prescribing a series flood adaptation measures is not enough. Programs must provide communities with the necessary technical and economic support to compensate for historical patterns of disenfranchisement, racism, and inequality. Future flood adaptation efforts should go beyond reducing losses overall and aim to close existing gaps to equitably support communities in the race for climate adaptation.

Every year, wildfires in the United States cause many deaths and bring enormous economic losses. The frequency and harm caused by wildfires are projected to grow with changes in the climate and shifting population centers. Wildfires represent a significant threat to critical infrastructure systems. These challenges are compounded by the observation that rural and disadvantaged communities are often the most susceptible to wildfire disasters. Although significant progress has been made in predicting wildfire propagation, less is known about the complex interactions between wildfires, critical infrastructure, socially vulnerable populations, and emergency management practices. The focus of this project is therefore on strengthening the emergency management of critical infrastructure systems, with special attention to the disproportionate societal impacts of wildfires. One critical challenge in this area is understanding how essential services, such as electricity, water, and transportation, might fail due to their strong interdependencies when facing a wildfire. Another major challenge is that the needs of socially vulnerable communities residing at the interface between wildlands and urban areas are often unseen. As a result, the disproportionate impacts of wildfire-induced critical infrastructure failures on these communities are not adequately considered in emergency planning and practices. This presentation will focus on the evaluation of the social burden of wildfire-induced critical infrastructure service disruptions on rural and disadvantaged communities to inform more equitable emergency management protocols.

Authors of this study ask three key questions: (1) what are the prevailing concepts, focuses, methods, and theories, in assessing the inequities of disrupted infrastructure services?, (2) what are the similarities and differences in pathways of equity?, and (3) what are the current gaps of knowledge and future challenges of studying equity in infrastructure resilience? Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the authors conducted a systematic literature review examining the role of equity in infrastructure resilience in natural hazards. The study developed an 8-dimensional assessment framework encompassing four definitions of equity: distributional-demographic, distributional-spatial, procedural, and capacity. The framework utilizes the concept of “pathways” to understand how equity is constructed, analyzed, and integrated within these dimensions. Results show that descriptive and open-data methods are frequently used, with a notable absence of international studies using human mobility data. There is a focus on distributional-demographic and distributional-spatial equity which show the disproportionate impacts on vulnerable populations and regions. A common pathway was studying distributional inequities in power, water, and transportation losses caused by flooding and hurricanes. Other equity pathways, such as stakeholder involvement (procedural equity) and household capabilities (capacity equity), are less explored in current literature. The research highlights knowledge gaps and proposes a comprehensive roadmap for future studies. 

Despite advancements in the understanding of community engagement, there continue to be challenges in how it is implemented in practice. This is especially true for first responders who work closely with communities, despite minimal discussion of how their work aligns with theoretical frameworks. To address this gap, this study analyzed how first responders conceptualized community engagement during the COVID-19 pandemic. Through an analysis of semi-structured interviews collected from U.S. first responders, the authors developed a First Responder Ladder of Community Engagement informed by Arnstein's Ladder of Citizen Participation. Findings show that first responder community engagement during the COVID-19 pandemic predominantly focused on informing activities and offered minimal evidence of higher levels of engagement, highlighting the potential disconnections between theories and practice of community engagement. These findings work to advance knowledge of the application, variations, and broader framings of community engagement approaches used by first responders surrounding hazards and disasters.

Disaster-struck Canadian homeowners have limited alternatives for recovery financing compared to other countries. While affordable insurance, low-interest loan programs, and federal grant programs targeted at lower-income individuals exist in the United States and New Zealand, uninsured Canadians must pay out-of-pocket for damages caused by extreme natural events, leaving Canadians financially vulnerable. This study investigated disaster financing alternatives that exist in the United States and New Zealand and evaluates their effectiveness in reducing post-disaster unmet housing needs in Canada. This analysis built on regional seismic loss assessments developed under the Canada Seismic Risk Model and evaluated the costs and benefits associated with the potential implementation of programs to provide (1) subsidized retrofits, (2) low-cost insurance, (3) low-interest loans, (4) disaster recovery grants for disaster-struck Canadian homeowners. Preliminary results considering one earthquake in British Columbia indicated that subsidies of up to 50%, loan programs with interest rates as low as 3% annually, and insurance programs with premiums of 50 cents per 100 dollars insured can provide more benefit than their costs. Subsequent analyses expanded the scope to other Provinces to provide a comprehensive assessment of the viability of these programs for implementation by the federal government.

This paper updates decade-old findings - regarding demographic changes resulting from disasters in which at least half of the community's structures suffered major damage or total destruction. Three questions are addressed: (1) what changes in population have occurred within the previously studied United States communities that suffered devastation between 1992 and 2008?, (2) what changes in population occurred in other American communities that suffered similar disaster devastation between 2008 and 2018?, and (3) what communities in the United States have been largely destroyed since 2018, where it is too early to fully measure the long-term demographic consequences? Over half of communities devastated by tornados before 2009 have smaller populations today than at the time of the earlier study. The same is true for just under half of flood damaged communities. No Louisiana communities devasted by the 2005 hurricanes have regained year 2000 populations, and three of them continue to lose residents. The average annual number of communities suffering complete destruction or major damage to at least half of their structures has grown since the earlier study.

This paper explores the narratives shared by emergency management officials, community organizations and community members to encourage civic participation and volunteering in disaster preparedness. To improve disaster preparedness, it is crucial for preparedness initiatives to extend beyond individual and familial levels and focus on the broader community. Initiatives should empower community members to act together, collaborate, and mobilize collective resources to reduce disaster risks. Existing disaster narratives in the mainstream media often fall short in highlighting citizen agency and promoting collective efficacy beliefs among community members, thus lacking the capacity to encourage civic participation and volunteering in preparedness efforts. Utilizing a qualitative approach, this study examined three community groups in New Zealand working with emergency management officials to improve preparedness of their areas. The study analyzed the communication, interactions, and perspectives of the group members, emergency management agencies, and relevant stakeholders to identify communication elements that favorably contributed to encouraging and promoting participation in disaster preparedness. The findings suggest that four narratives different from the mainstream disaster narratives are shared at the neighborhood level. The first narrative is of everyday heroes, which reframes our understanding of who is a valuable contributor in a disaster context. The second highlights the collective efficacy of the community, the third associates risk messages with collective responsibility, and the fourth builds on identity narratives. While the narratives are powerful in promoting collective preparedness, the study also underscores the existence of tensions and conflicts within some narratives and seeks to identify strategies for navigating them.

In recent years, many community groups have been working with emergency management agencies to reduce disaster risks facing their communities. Members of these community groups often engage in dialogue with emergency managers, voice community concerns, and collectively take steps to improve preparedness of their communities. However, little is known about why people decide to actively participate in such activities and volunteer in collective disaster preparedness. To understand why people participate, this paper examined the motivations of people to participate in collective actions and volunteer for community groups working on disaster preparedness in New Zealand. The research utilized a mixed methods approach to conduct this study. The findings from the quantitative survey suggested that both instrumental factors (like risk knowledge, efficacy beliefs, costs, positive outcome expectancy, etc.) and intrinsic and social factors (like emotions, sense of community, sense of responsibility, ideology, and values, etc.) influence people to engage in collective disaster preparedness. The qualitative insights highlighted that while risk perception and hazard experiences influence intentions, the values of the community members and the social dynamic within the community, such as neighborhood interactions, relationships, and sense of belonging, play an important role in forging the intentions to actions for collective preparedness. The authors compared the findings with individual preparedness research and reflect the implications of this paper's findings on disaster literature and practice.

This presentation provides insight into how non-governmental organizations (NGOs) support socially and historically marginalized communities through a climate disaster. Prior research has found a disconnect in communication and mistrust between communities and agencies, creating longer recovery times for impacted groups. We present findings from three years of data collection to show (1) how NGOs describe the best methods to build trust with disadvantaged groups, (2) where these organizations are located spatially, and (3) how they communicate with marginalized groups and respond to disasters. Our mixed methods approach employs focus groups, surveys, and web-scraping techniques to pull data from over 5,000 NGO websites and social media accounts. Our research helps to identify and characterize those organizations best positioned to support marginalized groups through hazards. We use these results to propose a new toolkit for communities and administrators to improve relief efforts for marginalized groups.

Resilient infrastructure, designed to withstand, adapt to, and recover from disasters, is crucial for minimizing the impact of disruptions to infrastructure services and reducing the time and resources required for recovery. However, during disasters, the impacts on infrastructure are not uniformly distributed across various communities. Therefore, it is imperative to consider such disparities or inequalities when evaluating infrastructure resilience. To address this need, this presentation introduces a new model (SW-Infra-RA) for assessing infrastructure resilience based on the social welfare theory and functions. The model aims to quantify the collective resilience of infrastructure serving multiple communities by considering two key factors: (1) disaster inequality, which denotes the uneven distribution of disaster impacts on infrastructure among different communities, and (2) disaster vulnerability, indicating the disaster impacts on the infrastructure of communities facing the most severe consequences. Both factors significantly influence the collective resilience of infrastructure. The presentation will also demonstrate the application of the proposed model through hypothetical and real case studies focusing on Florida communities, illustrating its capability to quantitatively assess infrastructure resilience while considering equity. This study contributes to the body of knowledge by presenting a new infrastructure resilience assessment model that takes into account disaster inequality and vulnerability. The proposed model has the potential to support the development and investment in infrastructure in a more equitable manner, fostering equitable resilience in future infrastructure planning and management.

Building community resilience against tropical cyclone hazards, especially in the context of climate change, necessitates a thorough understanding of population situational preparedness. This study addresses a notable research gap of focusing solely on preparedness for single tropical cyclone events. The authors analyzed preparedness for 27 pairs of sequential tropical cyclones affecting eight states from 2017 to 2022, using big digital footprint data (i.e., visits to points of interest) as a proxy of preparedness. This study answered the following research questions: (1) Is the level of preparedness consistent across two sequential tropical cyclones? and (2) How do the interval and relative intensity (indicated by wind speed at landfall) of two sequential tropical cyclones affect preparedness? The findings show a statistically significant increase (nearly 10%) in the visits to grocery stores, gasoline stations, and construction supply dealers before the first tropical cyclone's landfall, reflecting people's proactive preparedness for supplies, evacuation, and structural reinforcement. Preparedness for the following tropical cyclones decreases as the interval shortens, while a similar preparedness pattern with the previous landfall occurs when the interval is no less than seven days. Further, visits to points of interest increase more before the landfall of more intense tropical cyclones. This study offers new insights into preparedness for sequential tropical cyclones, providing stakeholders and policymakers with data-driven evidence to improve disaster mitigation strategies and practices for sequential tropical cyclone hazards.

Infrastructure service interruptions are inevitable, and directly impact the user. The intertwining of the system functioning and societal functioning requires understanding the consequences of service interruptions to develop effective hazard mitigation measures. To do so, this study asks: (1) How are people impacted when they have no power or water? (2) How do they respond? (3) What would be the response of a city for a future event? The authors developed a computational framework used to conduct probabilistic risk analysis of an infrastructure system in terms of household impact with a set of multi-hazard scenarios. The model computes several component damage scenarios for each hazard scenario, along with the outage locations and durations. With reduced levels of service, using statistical models based on a survey, the impact on households is estimated by obtaining the aggregate user adaptation profile, and the level of unhappiness experienced. This framework was applied to the water and electric network in Los Angeles, California to estimate household-level impacts, the uptake of different adaptation measures, and the likelihood of unhappiness when experiencing outages. It also analyzes geographic and earthquake scenario variability. This research provides risk assessment for infrastructure systems in terms of household impact metrics rather than physical damage or economic loss., This study combines all the necessary modules—hazard, physical damage, system functioning, restoration process, and societal impact—in a scenario-based probabilistic analysis, which can help tailor-make restoration plans to specific geographies.

A recent hurricane evacuation study highlighted the intricate interplay between individuals' risk assessments and their mental patterns, particularly in the evaluation of threats within social and environmental contexts. It suggests that diverse risk assessment patterns could either amplify or diminish the influence of respondents' worries on evacuation decisions. Notably, existing literature lacks the tools to discern specific mental patterns during evacuation decision-making and fails to pinpoint the effect routes. To address this gap, this study utilized household datasets gathered from Hurricanes Katrina, Rita, Ike, and Ian. The first objective of this study was to dissect respondents' risk assessment patterns along two dimensions: the level of their overall concerns and the heterogeneity in their risk assessments. The former was quantified through respondents' average ratings across 20 concerns, while the latter was determined by the interrater agreements of these ratings. Employing clustering analyses, this study identified distinct patterns in respondents' risk assessments and rigorously assessed the consistency of these patterns across different hurricane datasets. Subsequent multivariate analyses were conducted to scrutinize the specific moderating effects of these risk assessment patterns on evacuation decisions. The findings promise to enhance the comprehension of the psychological and behavioral aspects of evacuation decision-making. Furthermore, the outcomes of this study are poised to offer valuable insights for the development of simulation models in future computer-based studies.

As the risks of climate change impacts become more apparent and severe, communities are engaging in a wide range of planning efforts to increase resilience. Differential vulnerability and disparate impacts from hazards and disasters mean that resilience planning must explicitly address inequities. A team at the United States Environmental Protection Agency Office of Research and Development developed the Equitable Resilience Builder (ERB) to support practitioners and technical assistance providers in centering equity in resilience planning through engagement that is inclusive, transparent, and accountable and that builds relationships and strengthens capacity. The application was developed with input from municipal, county, and Tribal government agencies, planning professionals and academic experts. A prototype was tested through case studies with three different communities and qualitative data was collected on the effectiveness of the ERB process and engagement activities. Findings include challenges associated with social vulnerability framing, accessing useful data on hazard risk, and sustainability of initiatives without dedicated funding. Positive outcomes stemmed from bringing together diverse community members, officials and organizational representatives, facilitation that encouraged productive discussions about equity, and recognizing individual and community trauma. The results support approaches to building resilience that are inherently relational and holistic, considering compounding stressors and building networks so that resources and information flow in ways that equitably support preparedness and responses to environmental, social, economic, and health related crises. The views expressed in this abstract are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.

During power outages from extreme weather events individuals and communities can impact communities and individuals, impeding resilience and making it difficult to return to regular routines and business. This study uses data from focus groups of 30 participants in socially vulnerable areas of central Florida to explore resources that impact behavior during power outages. Specifically, the study explores the following research question: what resources impact behavior during power outages during extreme weather events to make individuals and communities more resilient? To answer the research question, qualitative methods, including inductive and deductive coding for themes will be used. The results and findings can be used by lawmakers to create public policy solutions enhancing resilience during power outages from extreme weather events.

This research investigates whether residents in high-risk disaster zones are aware of their evacuation zones and explores differences between those who are aware and those who are not. Using rigorous probability-based sampling techniques, data were collected from two populations regularly threatened by natural disasters. A representative sample of Florida residents was surveyed online during the 60 hours prior to Hurricane Irma's landfall in 2017, completing a second survey one month later (N=1,412). Residents from Lake County, California, a region extremely vulnerable to wildfires (60% having burned since 2015), were surveyed in summer 2023 (N=813). Residential addresses were available for both samples. Findings revealed a substantial lack of awareness regarding evacuation zones and status. In Florida, under imminent threat of Hurricane Irma, 39.69% of respondents were incorrect in reporting their evacuation zone status: 17.29% evacuated unnecessarily, while 5.84% were unaware they were under evacuation orders. In California, despite significant efforts by emergency management personnel to educate residents, 61.25% of participants were unaware of their evacuation zone; among the 38.75% who claimed awareness, a substantial proportion was partially or completely incorrect. Those who did not know their zone were significantly younger (OR=.98, 95% CI [.96,.99], p<.001) and reported lower income (OR=.91, 95% CI [.87,.96], p<.001) than residents who did know their zone. This presentation also addresses the challenges and necessity of conducting methodologically rigorous research in this domain by behavioral scientists. Practical implications of this research highlight the need for more successful communication strategies and educational initiatives to enhance public preparedness and evacuation adherence in disaster-prone areas.

Accessibility to critical services, such as emergency healthcare, is a crucial metric of community resilience following a hazardous event. Structural damage and power and water outages in critical buildings result in functionality loss, necessitating the reassignment of people seeking services to alternative facilities. Moreover, due to the damaged bridges and partially functioning transportation networks, people must take longer routes and endure increased travel times to reach critical facilities. To minimize the adverse impact of uncertain hazards on a community's infrastructure and, in turn, on accessibility to critical services, a decision framework was developed. The two-stage stochastic program underlying the framework considers the diverse priorities of community stakeholders to optimize various metrics, including net economic losses, population displacement, casualties, and functional recovery times. A case study on Shelby County, Tennessee, subjected to earthquake hazards, was developed, and the framework was applied to identify optimal mitigation strategies for residential and critical buildings and critical infrastructure, including power, water, and transportation networks, to illustrate its effectiveness. The case study results highlighted different trade-offs in alternative mitigation plans and helped prioritize resource allocation to make communities more resilient. The framework's design allows easy integration with the decision support system underlying the National Institute of Standards and Technology (NIST) Alternatives for Resilient Communities (ARC) software, an interactive tool developed by NIST to assist in community-level resilience planning.

There is a strong literature on forms of collaborative governance for disaster risk reduction (DRR). Still, a challenge remains to translate and transfer this to practical uses for Civil Protection Authorities and Emergency Managers. Although the Command and Control Model of disaster management has been critiqued by generations of scholars (and some practitioners), it remains dominant in many locations and practice areas. In attempting a shift to more collaborative and two-way forms of communication and engagement, the literature is sometimes lax in offering guidance for how to engage for those without experience of attempting such collaborations. The RiskPACC Project (www.riskpacc.eu) funded by the European Union, is working on co-developing such guidance in a form and language that is understandable by the majority of those who might work with it. Work so far has developed a draft collaborative framework but this has raised many questions that are yet to find complete answers, such as: how do you carry out co-creation or co-development work within tight timescales and with partners who have no history of working this way? How do you encourage practitioners to explore the relevance of going beyond their narrow mandates to understand the diversity of the communities that they serve and how a collaborative relationship with them may lead to an improved understanding of risk management decisions and the varying contexts in which they take place? The authors seek to reach out to others to exchange knowledge and experience to increase the likelihood of closing existing risk perception and action gaps.

In fall 2020, Hurricanes Laura and Delta wrought large-scale damage to homes in Calcasieu Parish in southwest Louisiana. Blue tarps were installed on damaged roofs to prevent further damage until repairs were addressed. Yet, a slew of barriers, including slow and insufficient insurance payouts and denials of federal government assistance among uninsured households, delayed reconstruction of homes in Calcasieu Parish. These delays manifested as the prolonged installation of blue tarps on homes, signaling a form of ongoing recovery. Eventually, though, blue tarps disappeared in some neighborhoods while remaining in others. A driving challenge in evaluating the social and economic conditions of disparate recovery is the lack of fine-scale indicators to track disaster recovery over time. This research triangulated earth observation of blue tarps with interviews with residents to document how spatial and temporal patterns of tarp installation and removal map onto geographic trends in racialized economic segregation, housing tenure, and financial protection via homeowner insurance. As maps of blue tarps elucidated recovery gaps, interview data contextualized what blue tarps signify as recovery markers and the conditions that hamper recovery, including insurance affordability and access. Using this novel combination of quantitative and qualitative data sources and analysis, this research exposed fine spatial estimates of variation in rebuilding and contextualized these findings with residents' narratives on recovery. In doing so, this research proposes advances in recovery monitoring, critical for building evidence of where and how gaps in disaster recovery occur to prioritize resource needs and reforms to disaster policy.

Hazards rarely occur in isolation, but disaster scientists and practitioners are still developing the tools and language to address overlapping hazards. Academics around the world publish research on compound hazards in many different contexts, but they use a variety of definitions, such that it is hard to know if they are describing the same phenomenon. Different terms (e.g., compound, multi-hazard, simultaneous, complex, cascading disasters) have important distinctions for theoretical analyses and practical applications. An accurate typology is critical for scholars and practitioners to address the distinct challenges and requirements for different compound disaster situations. This study used a systematic literature review to develop a comprehensive lexicon of terms, and to create a typology that categorizes compound hazards into three overarching categories—compound, cascading, and simultaneous—based on their causal relationships. These categories are theoretically important to academics and have practical implications for emergency managers because they involve different responses and preparations. The categories also provide a framework to unify language and concepts between researchers and practitioners. Without common terminology, there are issues communicating results and coordinating improvements in practice. Compound events are common and need clarity in research and practice to effectively study, plan for, and respond to these disasters.

After a disaster, shared loss of homes and communities may enable homeowners to collaborate with other community members to navigate recovery and rebuilding. However, little is known about what and when homeowners choose to act collectively versus individually, and how this decision impacts rebuilding outcomes including cost, expediency, resiliency, and sustainability. This study asks two questions: (1) For what rebuilding processes are homeowners acting collectively versus individually? (2) How are rebuilding outcomes of cost, expediency, resiliency, and sustainability influenced by homeowners' collective goals? Over 50 interviews were conducted with homeowners, leaders/facilitators of neighborhood groups, and builders, following the 2021 Marshall Fire. Interviews were transcribed and qualitatively coded. Survey data was also collected and analyzed. The study found that project phase influenced individual versus collective actions. For instance, homeowners relied on group participation for early informational needs, to vet potential builders, and to influence local policy. As homeowners signed contracts with builders, group participation waned. Thus, construction activities and rebuilding decisions regarding home design were largely individual rather than collective homeowner processes. These results have several practical implications. The vetting process of builders highlights the influence of homeowners' collective goals on builder selection, which in turn influences rebuilding outcomes. Policy changes enacted through collective action showed homeowners collectively prioritized cost and ability to rebuild over goals of resilience and sustainability. Given the influences of collective goals, and the high level of individual rebuilding decisions made post-contract, it is important to understand both of these processes.

Lake Tahoe is a series of communities situated along a single highway that runs between the steep, forested mountains of the Sierra Nevada and the lake. The 2021 Caldor Fire necessitated the unprecedented evacuation of 50,000 people from the lake basin, which spans both Northern California and Nevada. Despite being an international tourist destination, the jurisdictions in Tahoe are relatively small, with planning and transportation agencies with limited capacity, while the topography and relatively rural nature of the area results in limited and challenging evacuation routes. During the Caldor Fire, the local transportation district played a significant role in evacuating people via public transit, including people with disabilities who needed paratransit services and the unhoused residents of the area. Interviews with agency staff revealed a lack of formal inclusion in the emergency response planning and operations during the early days of the fire that resulted in frustration, confusion, and delays. There were also multiple successes highlighted by employees, with a strong shared commitment that no one be left behind. This case study added to existing research showing that transit, and transportation agencies more broadly, still need inclusion in emergency preparedness and evacuation plans, especially for vulnerable populations, such as older adults, people with disabilities, and the unhoused. Despite research into transit evacuation following Hurricane Katrina, there are still gaps in knowledge about how transit can be used in during an evacuation for both existing riders and additional groups of people, and what plans and emergency response structures are required.

When communities make decisions surrounding mitigation of natural hazard impacts, they often use benefit-cost analysis tools that calculate the risk-neutral expected value of a decision. Natural hazards are often low-probability and high-cost events for communities, so not accounting for risk preferences of communities could lead to suboptimal decisions if the community is risk averse. The goal of this research paper is to examine how community-level risk preferences, including risk aversion, can impact optimal decision making for community resilience planning. The paper begins with an abstract exercise that bounds the types of decisions impacted by risk preferences at a community level. For example, a decision that does not contain uncertainty is not impacted by a community-level risk preference; however, a decision with a high level of uncertainty is highly sensitive to the level of risk aversion of a community. Additionally, the amount of damage caused by a natural hazard event relates to the impact that risk preference has on the optimal decision for community resilience planning. Understanding the types of problems that are impacted by risk aversion is vitally important in understanding when adding community-level risk preferences are vital to optimal decision making. The paper also contains a worked example of how risk aversion impacts a community that is trying to decide if they should relocate a library due to wildfire risk. This work demonstrates the need for changes to the process typically used for benefit-cost analysis for community resilience planning.

Tornados are unpredictable storms that can cause widespread financial and infrastructural damages, as well as pose a hazard to human well-being. Much of the U.S. Midwest endures cyclonic-capable storms annually, yet building codes do not ensure safe shelter for at-risk residents. Behavioral economics, aiming to understand decision-making, allows for function-informed approaches to community safety while providing actionable steps for policymaker pursuit. The authors will present a multi-stage, interdisciplinary effort between behavioral economists and civil engineers. They will describe their experimental efforts to crowdsource data collection across regions most impacted by tornados, as well as their translational efforts to apply behavioral economic principles (e.g., operant demand) to evaluate lexical manipulations designed to increase the willingness of respondents to purchase residential tornado safe rooms approved by the Federal Emergency Management Agency. Although quantitative data failed to reveal a statistically significant difference as a function of framing effects, qualitative data (i.e., written feedback) presented notable takeaways to be integrated in future applications.

When medical emergencies create sudden and massive surges in the demand for medical supplies, it is crucial to respond rapidly. In the United States, the Strategic National Stockpile (SNS) is designed to provide rapid delivery of stockpiled medical materiel and products. There is a need to understand the projected impact on both the response and on routine everyday healthcare delivery if surge needs exceed quantities stockpiled by the SNS. For the case of one crucial product, needles, and syringes, in a notional anthrax response scenario, this paper evaluates and compares several strategies for responding to demand surges, including policies for inventory, production capacity, and product substitution, based on their impact on the response and on the commercial supply chain. A straightforward simulation method was developed and insights were drawn that may be applicable to other types of medical products. Among the surge strategies evaluated, the use of substitute products was the best strategy to improve performance of both the response and the commercial supply chain.

Statistical analysis of extreme events in complex engineering systems is of vital importance for system planning, design, and resilience assessment. However, due to the rarity of extreme events and the nonlinearity involved in evaluating system performance, estimating the probability associated with extreme failure scenarios in a system through random sampling methods is prohibitively expensive and impractical. In this study, a novel approach called Importance Sampling based on Graph Auto-Encoder (GAE-IS) was proposed to address this challenge. A Machine Learning model based on Graph Auto-Encoder, referred to as GAE for Importance Sampling Density function estimation (ISD-GAE), was proposed to identify the components that exert a significant impact on the functional performance of infrastructure networks. During the important sampling process, higher failure probabilities were assigned to these critical components to enhance the efficiency of sampling extreme failure scenarios. In the experimental study of the road transportation network in Berlin and Chicago, the proposed methodology demonstrated a sampling efficiency improvement of 2-3 orders of magnitude compared to crude Monte Carlo. Moreover, ISD-GAE, trained on a smaller road network, exhibited transferability to a much larger road network, offering a practical and effective approach for sampling extreme failure scenarios and assessing resilience in large-scale infrastructure networks. Moreover, this research outcome can be leveraged in resilience enhancement related decision-making, such as pre-disaster mitigation resource allocation.

Snow avalanches are a serious threat to people travelling in mountainous backcountry terrain. On average, 140 people—mostly self-directed recreationists—die in snow avalanches in North America and Europe each winter, and many more get seriously injured in avalanche accidents. The risk from avalanches in the backcountry must be managed by monitoring avalanche conditions and combining this information with an understanding of the terrain of potential destinations to make informed choices about when and where to travel in the backcountry. To assist backcountry travelers, avalanche warning services produce daily avalanche forecasts that describe the severity of the avalanche hazard. This presentation summarizes the recent work of the research group examining the effectiveness of avalanche forecasts to promote informed avalanche safety decision-making among recreationists with different backgrounds and experience levels. Employing both qualitative and quantitative research approaches, this body of research provides a comprehensive perspective of what works, what does not and for whom. Examples results include insights about users' interpretation of the avalanche danger scale, the effectiveness of different presentation formats for geospatial information, users' interpretation of technical terminology, the benefit of reducing technical jargon, and the effect of including uncertainty information in avalanche forecasts. While the work offers very practical directions for improving avalanche risk communication practices, this presentation focuses on the more general lessons from the research approach and results that contain valuable insights for risk communication of other natural hazards and supporting research.

This project identifies barriers to implementing applied research in emergency management. It proposes Open Innovation in Science (OIS) best practices that support open and collaborative research, and its transition to practice. This project focuses on a partnership between an interdisciplinary team of University of Rhode Island researchers and emergency managers in Rhode Island to develop a storm hazards prediction tool called the Coastal Hazard, Analysis, Modeling, and Prediction (CHAMP) system. The need for collaboration between researchers and end-users of research has become apparent as government organizations seek to develop the capacity to address today's problems. The OIS framework has the potential to lead to more impactful research, but there is a need to further examine the practices that drive its successful application. Given the increasing complexity and severity of coastal storm impacts, emergency management agencies face increased pressure to utilize research to inform their practice. Improvements in the capabilities of storm modeling and decision support tools, achieved in a collaborative approach, can help save lives and reduce damages. However, barriers between research and practice in emergency management can prevent the adoption of such tools. This project applied the OIS framework to the Rhode Island CHAMP case study to explore how the co-production of research with policy makers and practitioners can support the transition of research into practice.

Communities face a growing threat from increasingly severe weather events driven by a changing climate. The threat is especially acute in US coastal communities where current regulations have proven ineffective in stemming mounting hurricane losses. In lieu of meaningful regulatory reforms, climate adaptation in coastal zones will largely reflect the voluntary actions of homeowners. This work introduces a novel methodology to study those actions in a post-hurricane landscape where damage necessitates reconstruction decisions. The methodology includes (1) a modular survey instrument robust enough to document diverse damage experiences and recovery journeys, (2) indices that detail homeowner protective actions over time and holistic damage exposure measures, and (3) a sampling methodology that uses secondary data to target households likely to be engaged in recovery actions, maximizing yields in settings characterized by low response rates. The efficacy of this research methodology was demonstrated through the study of 373 homeowners in Calcasieu Parish, Louisiana, a community still recovering from Hurricane Laura. On average, homeowners invested in protection before the storm, increased that protection level after the storm, and intend to continue to invest in protections for their homes. Their actions may be partly attributed to damage exposure from direct experience, daily visual cues, and the experiences of family and friends. However, despite homeowners' promising actions, homes in Calcasieu Parish achieve, at best, half of the measures necessary to stem losses in future hurricanes, underscoring a sizable gap in household adaptation strategies for a changing climate.

Prescribed burning can be an effective management technique to reduce the risk of catastrophic wildfires as their environmental and social impacts grow in the US and worldwide. Despite potential benefits, prescribed burning remains challenging to implement and faces public scrutiny in some areas, due in part to its own risks, including smoke exposure and escaped fire. Making decisions about prescribed burning as a wildfire mitigation practice requires making informed tradeoffs between these risks and the risks associated with unplanned wildfires. Understanding these tradeoffs is critical to shaping risk management policy. This multi-year interdisciplinary research project used a mixed methods approach to answer several research questions aimed at informing prescribed burning decisions in Colorado. In the current stage of the project, activities focus on (1) facilitating stronger partnership building with an array of prescribed burn implementer agencies (2) field data collection (including air quality and emissions monitoring, lung function and health assessments, opinion surveys) and (3) refining protocols for quicker research team response to prescribed burn activity alerts to initiate the study before burn activities begin. This presentation will outline the project's approach and developments to date and will conclude with an open discussion with the audience to solicit feedback and practical advice related to the methodological and logistical challenges encountered when studying such a complex management practice.

Despite the potential benefits, skepticism persists among disaster management (DM) professionals regarding the use of artificial intelligence (AI) in day-to-day operations, from talent acquisition to disaster impact assessment and mitigation. Moreover, challenges related to the scarcity of unbiased, clean, and representative data may hinder the development of AI solutions that respect ethical considerations and effectively intervene in vulnerable communities. This project offers knowledge dissemination from “Harnessing AI for Disaster Management: Bridging Research, Practice, and Community Engagement,” a workshop funded by the National Science Foundation (NSF). This workshop was a collaborative effort between the University of Colorado Boulder, Texas A&M University, and the University of Florida, and brought together 30 participants who are DM practitioners, academic researchers, or community or nonprofit leaders. The event was hosted at the Institute of Behavioral Science and sought to provide an overview of AI applications in the DM domain and encourage conversation about AI-informed solutions tailored to their specific roles and contexts. The workshop program included a series of brainstorming sessions, panel discussions, application demonstrations, and idea formation activities to promote collaboration and knowledge sharing among various related disciplines. By focusing on how responsible AI can transform the DM profession, the workshop contributed to advancing the collective understanding of human-machine intelligence, a topic aligned with the NSF 2026 Idea Machine initiative. Insights from this workshop stimulated discussions about the benefits of integrating AI into the DM practice while addressing challenges such as potential biases in workforce recruitment and damage assessment, thus promoting equity and efficacy in disaster management.

Global climate change is causing more frequent and severe natural hazards and climate disasters. Sea-level rise (SLR) and coastal flooding will significantly disrupt many coastal communities through direct and indirect effects. Particularly, SLR will threaten the primary source of the local tax base through impacts on property values and lead to fiscal challenges across U.S. coastal municipalities. While recent studies have begun to identify SLR's impact on the local tax base, the measurements primarily rely on inundation, i.e., direct flooding. In this work, the authors investigated the spatial and temporal pattern of municipal fiscal risk based on both direct inundation and indirect isolation risk. Based on the projection by the National Oceanic and Atmospheric Administration (NOAA), this project examined how SLR scenarios can affect municipal fiscal stress using parcel-level contemporary and historical housing data from Dorchester County, Maryland. Preliminary findings suggested that 33.2% of properties in Dorchester County, Maryland, may lose their property values due to flooding at the SLR of 4 feet. Properties built between 1940 and 1950 were most vulnerable to SLR across all projected scenarios. The study provided insights into sustainable climate adaptation strategies and climate-informed local fiscal policies at the municipal level.

The American Red Cross Home Fire Campaign (HFC) conducts smoke alarm installation and helps households develop fire escape plans through in-home visits. The Wildfire Preparedness Education Visit Pilot Program educates households at risk for wildfires on fire safety, mitigation, and escape route planning. This multimethod study involved a survey conducted by NORC at the University of Chicago and interviews with participants in the Wildfire Preparedness Program. We addressed three research questions: (1) Do the Red Cross programs reach at-risk communities? (2) How did program activities contribute to changes in knowledge, attitude, and behavior? and (3) How satisfied were program participants with the visit experience? Findings showed that intervention households have more smoke alarms in their homes than comparison households and they are more likely to have a home fire escape plan. The average number of smoke alarms reported in intervention households in 2020 was 3.8 compared to 2.8 in the comparison group. The households that received the Wildfire Preparedness Program intervention were more likely than the comparison group to demonstrate preparedness behaviors, such as being signed up for local alerts (85% vs. 67%), having a planned evacuation route (92% vs. 60%), and having a Go Bag (62% vs. 32%). Our findings show that conducting in-home visits to install smoke alarms and teach household members about fire safety and prevention practices is a valuable tool to reduce home fires and increase wildfire preparedness in the United States. 

Avoiding floodplain development has long been recognized as critical for limiting flood damage. Local governments, with primary responsibility over land use and development decisions, play a major role in floodplain development or avoidance. While research has examined the quality of local plans and how they relate to other local policies, there is scarce evidence to date on what local government actions shape development (or lack thereof) in the floodplain, hampering broader learning and adoption of successful strategies. This research addressed how and why some communities can avoid developing housing and infrastructure in flood-prone areas. The authors provide new systematic, nationwide measures of floodplain development at the community scale, and findings from in-depth case studies identifying the plans, policies, and regulations that shape floodplain development (or avoidance). The floodplain development measures combined remote-sensing capacities and data science tools to answer long-standing questions about where development is taking place in communities across the United States. Based on these novel floodplain-development measures, the authors discuss how municipalities have successfully limited development in the floodplain, including social, economic, and geographic factors, the law and policy tools that are relevant for both avoidance and retreat, and lessons learned across cases.

This paper examines how just transition ensures a climate-neutral sustainable economy and work-environment by securing the livelihoods of garment workers in Bangladesh. It also explores how green transition with the support of multi-stakeholders, secure all garment workers, affected by global warming, and reduces greenhouse effects at workplace and create balanced environment. It further audits how just transition supports the production-relations by transforming non-renewable energy towards renewable energy. It further analyze how different milestones of the Just Transition—such as the United Nations Sustainable Development Goals (SDGs) which include SDG 7: affordable clean energy, SDG 8: decent work and economic growth, SDG 12: responsible consumption and production, and SDG 13: climate action; the Paris Climate Agreement; the COP27 and Mujib Climate Prosperity Plan of Bangladesh—support for greening factories, ensuring decent work and reducing the risks of climate induced hazards and disasters. The study follows qualitative research methods and secondary sources of data and information.

Social media messages posted by people during disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many of these location descriptions go beyond simple place names, such as city names and street names, and are difficult to extract using typical named entity recognition (NER) tools. While advanced machine learning models could be trained, they require large, labeled training datasets that can be time-consuming and labor-intensive to create. This study presents a method that fuses geo-knowledge of location descriptions and large artificial intelligence (AI) models for extracting location descriptions from disaster-related social media messages. Generative Pre-trained Transformer (GPT) models, such as ChatGPT and GPT-4, are utilized to develop geo-knowledge-guided GPT models. Only 22 training examples encoding geo-knowledge are needed in this method. The authors conducted experiments to compare this method with nine alternative approaches on a dataset of tweets from Hurricane Harvey. The geo-knowledge-guided GPT models demonstrated over 40% improvement compared to typically used NER approaches. The experiment results also showed that geo-knowledge is indispensable for guiding the behavior of GPT models, and geo-knowledge-guided GPT models showed over 76% improvement compared with default GPT models without geo-knowledge. The extracted location descriptions may help disaster responders reach victims more quickly and even save lives.

As the deadliest disasters in the United States, tornados pave a trail of destruction in their wake, ripping apart buildings, uprooting trees, and destroying powerlines. To effectively reduce these disasters' devastating impacts, improved models are needed to help decision-makers prioritize retrofitting strategies under resource constraints. The Alternatives for Resilient Communities (ARC) software, first developed for application to riverine flooding and seismic hazards, is extended to address tornadic hazards in this project. ARC is an interactive tool to aid communities and stakeholders in developing sets of viable strategies to improve community-level resilience while meeting constraints related to system interdependencies and socioeconomic considerations. This generalization of ARC allows for optimization of adaptation strategies including installation of tornado shelters in residential homes, structural wind retrofits of buildings, and improved power system maintenance, such as strengthened poles or vegetation management. To consider the diverse priorities of community stakeholders, ARC incorporates the modeling of various objectives, including net economic losses, structural damages, population displacement, casualties, and recovery times. Under various potential tornado intensity scenarios and budgetary constraints, the optimal resilience enhancement strategies are determined within the mathematical programming framework. As a case study, the model is run and validated for the testbed city of Joplin, Missouri, which was devasted by an EF-5 tornado in 2011. This development creates a flexible and interactive tool for community use, and the results highlight different trade-offs in resilience planning for tornados, helping compare potential alternatives and prioritize investments, with the goal of making communities more resilient to tornados.

College students are a vulnerable population that is often understudied in disaster risk perception research. This population is diverse and includes those who may not be familiar with natural hazards in the region where they are attending college. The home regions of college students can possibly influence their perception of tornadic risk due to lack of experience with past events. On March 31, 2023, two EF3 tornados occurred in Arkansas. This study asks: What are the differences in risk perception between student groups from different geographic areas? This quantitative study employed a survey to college students in the two regions affected by the tornadic events to assess their risk perceptions. Risk perception along with tornado experience were examined comparing groups based on home region: those from regions that are tornado prone (in-region) and those from regions that are not tornado prone (out-region). Home region was found to have a relationship with tornado experience and knowledge. Home region was also found to play a role in risk perception. These findings have a practical application for campus emergency planners and risk communicators.

The escalating frequency of catastrophic wildfires across the United States has heightened concerns about the effectiveness of risk management strategies. Community Wildfire Protection Plans (CWPPs) are key in establishing long-term strategies for mitigating such risks. The application of land use planning as a proactive tool for enhancing resilience and adapting to wildfire risks remains underutilized. Current wildfire management practices disproportionately emphasize mitigation measures such as fire suppression and fuel management, thereby overshadowing adaptive land use strategies. This is particularly evident in unincorporated areas, which are increasingly susceptible to wildfires and less inclined to engage in mitigation and adaptation actions. This study examined the extent to which land use planning is integrated into the wildfire management of unincorporated communities, especially in the wildfire-prone Western states. The research includes an analysis of 60 county-level CWPPs across 11 states in the census-defined West Region, each with a "Very High" or "Relatively High" Wildfire Risk Rating according to the Federal Emergency Management Agency (FEMA) National Risk Index. The study used content analysis for plan quality assessment and a multivariate regression model to evaluate how various county characteristics, including policy context, planning process, and local community characteristics, affect the integration of land use policies in these plans. The findings highlight the need for a more robust policy mandate addressing hazards and a greater emphasis by state authorities on integrating land use planning strategies into more comprehensive plans.

The 2018 Central Sulawesi earthquake caused geophysically unusual tsunamis, flow slides, and liquefaction resulting in more than 4,400 deaths and displacement of 170,000 people in the Pasigala region. To rebuild safely, the government revised the regional hazard map in three months to urgently rebuild, although there was yet no reliable explanation on hazard information. One of the key rebuilding policies was to resettle residents in safe locations, using the hazard map. This study examines the current living status of earthquake-affected residents in the region to explore barriers to reestablishing life through relocation programs developed under uncertainty. We interviewed two types of residents in eight communities who (1) continue to live in original areas newly defined as red zones (high-hazardous areas where residency is prohibited) and (2) resumed life in "safe" relocation sites developed post-earthquake. The Pasigala region is unique in its demography and culture, with more than 15 ethnic groups, tribes, and transmigrants. Fieldwork has been underway since 2019, and these semi-structured, open-ended interviews took place in 2023. Our primary results suggest that first, multiple changes in resettlement plans, rules, and programs by the government have led residents to continue living in the red zone areas. Second, many residents continue to live in insecurity without permanent places to settle due to a lack of fit between the government's resettlement programs and traditional ways of life in the communities. The government's reliance on uncertain hazard information as the basis for resettlement policies has led to unintentional outcomes, including continued hazard exposure and residents' distrust of their government.

In recent years, the Taiwanese government and nongovernmental organizations have been vigorously promoting disaster-resilient communities. Disaster preparedness and response information is accessible to community members via websites (e.g., National Science and Technology Center for Disaster Reduction), LINE (a social media platform), hard copy of manuals, and more. However, community members who live in disaster-prone areas still do not seem willing to take action. It is worth exploring how to enhance community members' willingness to take action. This study utilized a qualitative approach and collected the perspectives and experiences of community leaders in disaster preparedness, response, and post-disaster recovery through semi-structured in-depth interviews. Four village chiefs and nine community leaders from local community development associations participated in this study. Five themes for enhancing community members' willingness to take action in building a disaster-resilient community are summarized as follows: (1) Leading by example strengthens community cohesion; (2) Local community leaders are the experts on community strengths and concerns; (3) The model of community-led disaster preparedness and response allows community members to come up with solutions and priorities; (4) Opinions from community elders are valuable in building disaster resilient communities; and (5) Personal experiences in disaster response and relief work may increase community leaders' courage to express community perspectives.

As focusing events, natural disasters can reveal harms that reframe the way people think about a problem. Disasters are also associated with an increase in public attention to the policies around the disaster. This surge of attention and potential for new ways of framing policy problems creates the conditions under which previously settled policy issues might be revisited during a period of disaster recovery, potentially leading to lower levels of community resilience. In the case of the 2021 Marshall Fire, the city of Louisville, Colorado had recently adopted green energy codes with broad public support for what was seen as important action against climate change. After the fire, Louisville experienced protests against the energy codes that framed the codes as a financial burden for those rebuilding their homes. This paper builds on prior work on the Louisville case by comparing the post-disaster community narratives and policy preferences across three of the most significantly impacted communities from the Marshall Fire. The authors use public comment data, news coverage, panel survey data, and semi-structured in-depth interviews with key decision makers to triangulate changes in the narratives about green building codes. Using a comparative case design and mixed methods, the authors of this study test two key research questions: (1) What factors influence shifts in issue framing after a disaster? (2) To what extent do changes in how an issue is framed effect public support for a policy after disaster?

In the domain of travel demand research, limited research has focused on unplanned travel to avoid extreme weather event risks. Using multiple hurricane surveys collected from different areas in the United States, this project estimated distances traveled by the hurricane evacuees to get to their evacuation destinations. Regression results indicated that household income, flood risk, respondent's age, and education levels significantly affect travel distances during hurricane evacuation events. Moreover, the price and income elasticities of travel demand (i.e., distance, duration, and destination) for hurricane evacuation were estimated. The estimated price elasticities of distance (-0.2) from different samples revealed that travel demand to avoid extreme weather event risks is inelastic demand as safety is essential for everyone. The positive income elasticity (0.1) suggested that traveling for safety to avoid hurricane risk is a normal good. Given that the income elasticity of demand is less than one, as expected, it is a necessity good. This finding provided implications for emergency management agencies to meet the evacuation travel demand more efficiently and ensure safety in vulnerable communities.

Climate displacement is an issue that could adversely affect communities across Federal Emergency Management Area Region 8. In particular, the desiccation of the Great Salt Lake may result in an environmental disaster that could displace thousands. Proper planning can help prepare communities for large-scale resettlement. However, we draw on two related research projects to demonstrate how most environmental, disaster, and climate plans in the region fail to adequately factor in the effects of climate displacement. Then, we discuss specific concerns and mobilities as they relate to the case of the Great Salt Lake. Finally, we offer suggestions to better incorporate these considerations into future planning and policies. We expect this topic will generate discussion on both barriers and opportunities to develop a cohesive framework to address the problems resulting from climate displacement and implement solutions in plans across the region.

Organizational resilience is considered essential not only for the survival of organizations but also for bouncing back from adversity and maybe even thriving in the aftermath of a crisis. While much is known about organizational resilience in different types of high-risk professions, less is known about the development and impact of organizational resilience within public first-response organizations. First responders are constantly coping with emergency situations and, therefore, must continually assess and reassess organizational resilience. To address this gap, this study explored the management of first-response organizations during the COVID-19 pandemic. Using visual methods and qualitative interviews with firefighters, police officers, emergency medical technicians, and paramedics working in the U.S. during the height of the COVID-19 pandemic, this study examined the impact of the internal and external context as well as specific organizational capabilities on the challenges and opportunities for organizational resilience. Common challenges impacting organizational resilience included inaction, inconsistent decontamination procedures, and a lack of perceived community support. Opportunities for promoting organizational resilience in first-response agencies included consolidating information, using equipment creatively, balancing protocol and patient needs, and sharing personnel and resources.

Tornado fragility curves have been found to be a useful tool for assessing potential damages to structures and an essential component of tornadic wind risk assessment procedures. However, prevailing fragility assessment approaches have been prevalently employed for tornadic vulnerability assessment for non-deteriorating structures while traditionally overlooking the impact of deterioration resulting from poor maintenance. This research aims to provide an enhanced understanding of the impact of deterioration on tornadic vulnerability of building materials. The key research questions were (1) Does deterioration affect the tornadic wind loading response of building materials? and (2) How significant are the shifts in tornadic fragilities of deteriorating buildings compared to non-deteriorating ones? To answer these questions, this study developed structural resistance capacity for deteriorated building materials based on deterioration rates, created time-dependent fragility models for deteriorated materials and compared them with the behavior of those for pristine materials, and evaluated the impact of deterioration on the Enhanced Fujita (EF) Scale wind speed upper bounds and degrees of damage for various commercial buildings. Results showed that material deterioration over time reduced structural resistance, potentially affecting the entire building system. Fragility curve analysis revealed a significant shift in the probability of exceedance for individual materials, indicating increased tornadic demand. Probabilistic analysis showed up to a 37% increase in individual material vulnerability due to deterioration over time. This implies that these materials may be prone to failure at lower wind speeds than indicated by the upper bounds of both the EF Scale and Degrees of Damage.

Real estate purchase is a major transaction for many households in the United States of America and the price of real estate properties may or may not reflect a wide range of associated environmental risks (e.g., geological risks like land subsidence and sinkholes, and hydro-meteorological risks like hurricanes and floods). Hedonic price models have been frequently used to value environmental risks and amenities. Earliest hedonic studies considered one or the other type of these risks and analyze how that affect the property values. The authors considered both geological (sinkholes) and hydrometeorological risk (hurricanes) and analyze their impacts on property values. The authors investigated if information revealed through one type of risk triggers the impact of other types of risk. The authors focused on Lake County, Florida, which has a large amount of identified sinkholes and has experienced a recent hurricane. First, the authors investigated how the location/proximity of sinkholes affected the housing price and if that effect changed following a hurricane event. The study used real estate sales data of almost 35,000 single family homes in Lake County from 2014 to 2018, an area that experienced significant damage during Hurricane Irma in 2017. The authors found that houses near known sinkhole locations experienced larger price discounts following a hurricane event. The authors also analyzed the effect of a new sinkhole insurance law on housing prices in Florida. The results were that houses located close to known sinkhole locations faced significant price discounts due to reduced sinkhole damage protection offered by the new sinkhole insurance law.

With competing, contested notions of equity, there are further vexing challenges to researchers measuring and evaluating disaster response and recovery and progress before, during, and after hazard events. Planning involves not just “knowledge to action” but also the generation and evaluation of alternative ends and means of goal attainment. Equity is seen as both a desired goal but also as a vital ingredient in the design and implementation of strategies, processes, and actions. Using both theoretical and philosophical perspectives and case-based analysis of events and interventions, this research addressed ongoing dilemmas in understanding and evaluating equity, fairness, and justice across time and space. In addition to recent calls to address equity, there have been longstanding efforts to address horizontal, vertical, and procedural equity as well as confront both intergenerational as well interspecies equity. In addition to sorting through and classifying terminology and definitions, this research identified units of analysis and initial metrics for comparison across diverse dimensions, contexts, systems demonstrating complexities and uncertainties associated with the management of equity. The framework provided a basis for both further discussion and deliberation as well as groundwork for continued revision, consideration, adaptation and transformation of both knowledge and action. The presentation is structured into three parts: (1) conceptual discussion of equity with references to disasters, response and recovery, and community resilience; (2) development of a framework for assessing equity across time, space, and diverse contexts; (3) testing of the framework through examination of recent disaster cases involving human, natural, technological hazards.

When natural hazards occur in rural communities, emergency response resources can be quickly overwhelmed. Model-based systems engineering (MBSE) methods can support effective planning by considering disasters from a systems perspective and examining how the system behaves under different scenarios. The two research questions addressed by this research were (1) how do rural healthcare system components interact with other related systems during an acute natural hazard response, and (2) can these interactions be modeled in a multi-method computer simulation? Outputs from stakeholder engagement workshops were combined with MBSE methods to design a computer simulation model that accurately characterizes the key systems involved in rural disaster response. The simulation was developed to track key public health and healthcare response outputs that occur during and after such an event. The final simulation included preparedness and response subsystems (i.e., public health, healthcare, emergency management, and emergency response), key factors (e.g., interagency trust, preparation, communication between subsystems, and community resilience), and user-modifiable components (i.e., healthcare, hazard, population factors).The simulation accurately modeled the interactions of these elements, predicted actual outcomes experienced in historical events, and modeled best- and worst-case scenarios yielding plausible outputs. This public health disaster preparedness tool provides an in-depth understanding and simulation of how rural preparedness systems interact to prepare for and respond to a disaster. It will be useful to test existing rural preparedness policies and procedures, determine how to use existing resources most effectively and identify where additional resources are needed and will have the greatest impact

Within Minnesota's portion of the Red River basin–a mostly rural area with a history of significant flooding–flood mitigation efforts have been approached in a unique way. In 1998, the Minnesota State Legislature mandated a "mediation" process to resolve longstanding flood disputes between local, state, and federal entities. The result was the convening of a Flood Damage Reduction Work Group (FDRWG) representing the local watershed districts, the state Department of Natural Resources, other federal and state partners, environmental interest groups, and citizens. The FDRWG was charged with creating a consensus-based framework establishing a collaborative approach to flood damage reduction efforts in the Red River basin. This was done, and, for the past 25 years, the FDRWG has successfully operated to achieve the goals outlined in this framework, which came to be called the 1998 Mediation Agreement. This study employed semi-structured interviews with FDRWG members and key partners–as well as the review of important documents related to FDRWG's operations and the observation of FDRWG meetings–to learn more about this novel approach to flood mitigation and how it has influenced flood mitigation outcomes in the region. Specifically, this study explored the extent that the Flood Damage Reduction goals outlined in the 1998 Mediation Agreement have been achieved and what has either facilitated progress or served as barriers towards meeting these goals. The results of this work can inform our knowledge of factors that influence the successful implementation and adoption of local mitigation strategies, particularly in a rural context.

Hurricanes are increasing in frequency and intensity, with damage imposing substantial economic costs on exposed communities. Disaster victims are not always able to access federal aid and other forms of financial support. Research has demonstrated financial burdens and lack of social support mediate the association between disaster exposure and poor psychosocial outcomes. However, the concept of financial loss from disaster exposure is multi-dimensional and can be difficult to parse out from other post-hurricane experiences, complicating attribution of negative health outcomes in disaster survivors to financial losses they may experience. This study used data from the Dynamics of Extreme Events, People, and Places (DEEPP) survey to assess financial impacts on well-being among survivors differentially exposed to and impacted by two major tropical cyclones, Hurricanes Florence and Dorian in North Carolina. A latent class analysis (LCA) was conducted to assign hurricane survivors to groups based on pre-disaster household income, home value, and measures of financial loss, including damage to property, personal assets, and to businesses. Models were compared using Bayesian information criteria (BIC). The best fitting model identified three latent classes. These grouped respondents into classes as a function of pre-disaster economic status coupled with degree of financial loss. This study demonstrated latent class analysis as a tool to characterize multi-faceted experiences of economic status changes resulting from disaster exposure. These latent classes were used to evaluate the relationship between financial loss and measures of post-disaster well-being, adjusting for demographic characteristics and factors associated with post-hurricane well-being.

Developing economies are seen to prioritize disaster rehabilitation and rescue over risk reduction and preparedness due to limited resources for planning and resilience building. Cities like Mumbai claim to be India's greatest metropolis due to their enormous population and economy. However, Mumbai’s large slum population on elevated terrains, riverbanks, and obstructed drainage systems, with a persistent demand for resources, make it vulnerable. When confronted with limited data and substantial uncertainty, expert knowledge and linguistic assessments often become a necessity. Fuzzy set theory serves as a foundation for modeling non-probabilistic uncertainty, incorporating subjective insights and human expertise to represent uncertainties in parameters. The project incorporated various socio-economic variables in a suitable hierarchical structure, along with their interdependency analysis. Surveys were conducted to include domain expertise at two stages of the process. The Hierarchical Fuzzy Logic Process was used for fuzzification, inferencing, and aggregation at each level of the hierarchy until the final output set was obtained, representing a ward's performance in terms of its belongingness in good, average, and poor categories. The methodology was kept defuzzification-free to preserve the subjectivity of performance until the highest level of hierarchy. The wards' performances were compared at all levels of hierarchy across each dimension. It also provided insight into understanding risk as a composite of not just external hazard factors, but also of intrinsic characteristics that may act as vulnerabilities or capacities for systems, people, the economy, governance, and built environment in coping with external forces.

As the frequency and intensity of disasters increase, so, too, does the need for research on disaster response, particularly in utilizing real-time data from smartphones, such as social media data (e.g., Tweets) and GPS tracking data. This study focused on designing and exploring agent-based simulations for disaster evacuations, validated using data-driven approaches with real-time heterogeneous data. The two central research questions are: (1) How can real-time heterogeneous data be incorporated into an agent-based evacuation simulation to accurately reflect the environmental dynamics? (2) How can the evacuees' emotions and actions during the evacuation be tracked in real-time to represent the variability of the agents' evacuation decisions? The machine learning-based Overview, Design, and Details (ODD) framework is proposed to capture the environmental dynamics under disasters, employing a Bayesian network with real-time data. Moreover, a stochastic approach—the Ornstein-Uhlenbeck (OU) process—is utilized to apprehend the uncertainty of individual evacuation decisions, initially parameterized with pre-disaster data and dynamically updated using real-time inputs. These approaches capture the intercorrelation of evacuation decisions, such as timing, route, and destination, quantifying the influence of environmental dynamics and social interactions on those decisions. The framework's validity was investigated through two case studies of California wildfires and Hurricane Laura, leading to enhanced predictive accuracy and adaptability of the model in evacuation scenarios. The practical implications are significant, providing policymakers and emergency responders with decision support systems for more effective real-time evacuation and control strategies.

Disaster risk reduction (DRR) policies, like building codes and construction regulations, can save lives and protect property. These policies are designed and enforced within particular social and political contexts, which can be shaped, in turn, by hazard events themselves. Disasters potentially serve as “focusing events,” providing opportunities for change in public policy. One of the ways in which a focusing event—like a disaster—can catalyze change is by shifting public opinion and heightening risk perception. But the causal relationships between experiencing disaster, perceiving risk, and supporting disaster risk reduction policies are not well understood. This paper analyzes public support for disaster risk reduction policies in Latin America and the Caribbean (LAC). Using original survey data from 16 LAC countries, we test a series of hypotheses about the factors that shape public support for DRR policies. In particular, we focus on the interrelationship of past experience with disasters, perception of risk from future disasters, and support for DRR policies. We hypothesize that there is both a direct and an indirect causal relationship between experiencing a disaster and supporting stricter or more costly DRR policies. Our results indicate that risk perception has a mediating effect on the causal relation between experiencing disaster and supporting disaster risk reduction policies. Also, neither the recency of disaster experience nor the severity of personal harm experienced significantly predict risk perception or support for DRR—and the effect of “experiencing” a disaster is more collective than individual.

The stock of subsidized housing in the United States continues to erode. Moreover, subsidized tenants are vulnerable to climate disasters because they have limited funds for recovery, their housing assistance is often tied to a single property, and they are more likely to have health conditions that could impede their evacuation. Understanding the exposure of subsidized housing to flooding is needed to protect assisted tenants and efficiently allocate mitigation funds. To examine the relationship between housing subsidy and flood risk, I created data linkages between a mix of open-source and proprietary datasets. I use the National Housing Preservation Database and datasets from the US Department of Housing and Urban Development on public housing and other subsidized housing, First Street Foundation on flood risk, and Boston University on land prices. I control for other factors at different geographic levels like structure types, home values, year of construction, and race and ethnicity. Importantly, I control for coastal vs. inland areas, given their differing paradigms around building in floodplains. My results show that subsidized housing is more likely to be in the floodplain in inland areas, even controlling for sociodemographic and housing quality characteristics. These findings are a necessary first step for developing policies to address this concentration of risk. Next steps include identifying and addressing the root causes behind this concentration of risk to protect the diminishing stock of affordable housing in the United States from escalating flood risk.

This study provides a descriptive account of organizational models used by emergency operations centers (EOC) in Colorado. EOCs are locations from where decisions are made that support emergency incident response, including through management of information flows/communications and coordination of strategic decision-making and activities across diverse communities and organizations. To date, knowledge is limited about practices in structuring and operating EOCs at public offices of emergency management and influencing factors. A range of EOC structural models are promoted in the guiding literature and formalized instruction from the Federal Emergency Management Agency. Through the review and analysis of organizational documents, this study examined the models used by offices of emergency management, including the factors that influence the choice of models and organizational perception of the effectiveness of the employed models. The results indicated that the emergency support function model is the most commonly used, followed by a hybrid model, the incident command system model, and finally, the departmental structure and incident support model. The authors found no single model to be decisively superior; rather, different models are appropriate depending on personnel, resource availability, and the context of the jurisdiction. Although most commonly used, the emergency support function model appeared to be difficult to employ effectively when organizations have limited access to trained personnel, who are required to carry out the range of functions specified in the model. In comparison, the other models appeared better suited to handling personnel constraints

Hydrometeorological disasters in the United States necessitate the collection of perishable data for proper physical characterization and understanding the related dimensions of impacts to populations and buildings. Yet, such field work varies across hazards. For example, tornados obligate federal scientists to investigate evidence of high winds, whereas beyond automated gauge stations, in situ data collection throughout flooded areas is discretionary and leads to inequitable disaster recoveries. Hurricane Ian (2022), the costliest disaster on record in Florida and the third costliest nationally, led to federal agencies recording high-water marks in some impact areas. The City of Cape Coral, Florida, however, was excluded from federal data collection despite severe storm surge flooding along hundreds of miles of intracoastal canals–the most extensive network in the world. This exclusive data collection overlooked flooding among tens of thousands of residential buildings, leaving vulnerable homeowners and local officials without information for mitigation measures. The University of Central Florida responded to this omission by urgently deploying a research team to preserve post-flood evidence with photography, GPS surveys, and descriptive notation. Through these observations the authors found significant variances in flood inundation models and community impacts, with older residential buildings more likely damaged than newer, higher elevation buildings that appear to displace floodwaters onto older, lower elevation structures, begging questions of the cumulative impacts and effectiveness of “no rise” floodplain management policies. Further, preliminary estimates show that displaced floodwaters resulted in higher storm surge flooding and associated damages in Cape Coral.

In the first year after a major international disaster, early recovery frameworks are often developed by the national government of the affected country with support from multilateral agencies. These early recovery frameworks are important since they shape the recovery from the disaster for years after the event; though evaluating the effectiveness of these frameworks is challenging because conducting household-level assessments of recovery throughout this period is time and resource-intensive. This project leverages earth observation data to develop a method to monitor recovery remotely, which can complement a small sample of field surveys of recovery to inform recovery policy evaluation. Specifically, we develop a times series change detection technique leveraging both SAR (Synthetic Aperture Radar) amplitude and InSAR (Interferometric SAR) coherence data using data from the Nepal 2015 earthquake. We compare the change-detection recovery assessment to a longitudinal survey of recovery conducted between 2015 and 2019 for a range of n = 2,980 (2015) to n = 5,857 (2019) respondents as well as secondary data on aid received from nongovernmental and governmental organizations. Preliminary results show large-scale differences in recovery change from the InSAR assessment between those areas that received aid and those that did not. Developing this method further will allow for a more objective evaluation of early recovery frameworks and funding decisions by providing a method to remotely assess disparities in regional recovery long after a disaster occurs.

The process of sending rapid and accurate emergency alerts is a difficult endeavor as diverse populations have varied communication needs. In the United States, people with Limited English Proficiency (LEP) and those with auditory or visual disabilities often must rely on unofficial sources, word-of-mouth, or other modes of communication to understand and receive emergency messages since official messages are not always accessible. This can imperil people's lives, making it paramount that alerting authorities send messages in accessible formats. While the importance of developing inclusive alerts and warnings has long been recognized, there has been limited focused research in this area. In 2023, however, the Natural Hazards Center was directed through House Bill 23-1237 to conduct a study on challenges and opportunities to develop more inclusive emergency alerting systems for the State of Colorado. The authors conducted a review of relevant research literature, a survey of 222 local emergency response personnel, and held 18 partner meetings with local organizations and alerting authorities. The study revealed a patchwork of alerting systems and low alert opt-in rates statewide. The authors also identified significant technical and resource constraints at the local level. The project offers actionable recommendations, such as enhancing staffing and funding alerting authorities, providing guidance for standardized practices, and developing formal relationships with LEP populations and those with disabilities. The findings are particularly useful to emergency management personnel, state-level actors, local officials in the emergency alerts space, and researchers interested in advancing the state of the art for inclusive alerts and warnings.

Disaster aid distribution in the United States exacerbates social inequities. Public demand to incorporate social vulnerability into disaster aid policy could lead to more equitable disaster recovery. In 2 studies (N = 664) the authors examined what predicts support for needs-based disaster aid policy which distributes aid based on social vulnerability and whether support for needs-based aid can be increased. In Study 1, participants were asked about their preferences for disaster aid distribution policies and completed measures of individual differences and disaster perceptions. The work found that general worldviews - belief in a just world and social dominance orientation - predicted less support for equitable aid. While these worldviews are difficult to change, the results showed that people who did not endorse common disaster myths (e.g., that crime rates increase after a disaster) and who see climate change or wealth distribution as causes of disaster harm support needs-based aid. In Study 2, the authors developed messages targeting these three beliefs which were compared with a control message. While support for needs-based aid did not differ by condition, beliefs about inequities shifted. In both studies, conservative political ideology related to less support for needs-based aid. Trust towards government and attributing responsibility to government to address disaster harm predicted greater support for needs-based aid. These two studies shed light on factors that relate to preferences for needs-based disaster aid policy and provide a starting point for future efforts to increase support for more equitable disaster aid policy.

It has been widely recognized that community resilience can reduce climate shocks and disaster risk. This study evaluated factors that have promoted or impeded recent disaster risk reduction (DRR) and climate change adaptation (CCA) efforts in central Bangladesh's coastal communities. It also searched for alternative strategies to enhance climate resilience and reduce risks from future climate change. Barguna, Patuakhali and Bhola district of Barisal division, and Khulna, Bagerhat and Satkhira district from Khulna division were studied using a mixed method approach. One of the main barriers against community resilience and risk reduction is poor socio-economic conditions. The results show a need for special disaster considerations because of the area’s dependence on agriculture and fishing. Along with locally grounded community solutions for climate change, the authors recommend sustainable livelihood, and social and institutional support to build local community disaster resilience.

Effective response to disasters requires extensive coordination and collaboration between responding agencies, the management of which is a significant challenge in emergency response. Coordination and collaboration efforts are complicated by unexpected circumstances that arise from a disaster, giving rise to emergent multiorganizational networks (EMONs) of collaborations between those who may not have worked together before. Previous literature has discussed task completion as a motivation for collaboration during disaster response, in which organizations may choose to collaborate to join forces on shared tasks or because their tasks depend on the completion of others' tasks. Although there have been qualitative discussions on the dependence of tasks on emergent collaborations, this relationship has not been well-studied quantitatively. This work explored the extent that an organization's task performance shapes its collaborations in response to a disaster. The authors first systematically extracted information on each organization’s tasks reported in situation reports (SITREPs) written during the 2005 Hurricane Katrina. This work builds upon prior work which coded for EMONs from Hurricane Katrina but did not code for the nature of organizational collaborations. The authors then performed social network analysis to understand how commonalities in tasks performed by each organization are associated with their propensity to collaborate in response to a disaster.

In recent years, there has been growing attention paid to the long-term impacts of post-disaster housing reconstruction. However, there are still fewer studies that focus on the long-term outcomes for effected residents, compared to research on the housing reconstruction process or post-occupancy evaluation in the early phases of reconstruction and housing recovery. Looking back at the housing recovery after the 1995 Great Hanshin-Awaji Earthquake that struck Kobe City and Hyogo Prefecture almost 30 years ago, and the 2011 Great East Japan Earthquake, tsunami, and nuclear accident that devastated Japan's northeast Tohoku coastal region 13 years ago, this research considered the long-term and even ongoing impacts of housing reconstruction policies. Drawing also from previous literature, this research was based on semi-structured interviews with key stakeholders involved with different aspects of the housing recovery process including planning and implementation, to gather their feedback on the policy decision and impacts on the affected areas and residents. In addition, semi-structured interviews with residents who participated in various housing recovery support schemes including public disaster recovery housing, land readjustment, and collective relocation and rebuilding were conducted. Findings suggested which housing recovery policies were most effective from the immediate, short-term, and long-term point of view in support of disaster survivors towards rebuilding their lives.

Picture books take up varied themes of disaster experience, including narratives of disaster preparation/escape, loss, displacement, and rebuilding. This is the case in Japan, with its long history of repeated disasters, and active cultures of passing down disaster experiences in picture book publishing. There was a large increase in the number of picture books published in Japan after the Great East Japan Earthquake, tsunami, and nuclear disaster of March 11, 2011 (hereafter 3.11), by large and small publishers, local governments/non-profit organizations, and crowdfunding/self-publishing efforts. Facing the devastating loss of life and damage of 3.11, these books deal with survival and disaster prevention, death of family members and destruction of towns, individual and collective disaster trauma, displacement, and recovery. The authors identified 101 picture books fitting the criteria of having a narrative about 3.11. The majority focused on the tsunami, including stories highlighting effective evacuation and survival, and stories dealing with the loss of homes and loved ones. Twenty-eight of the picture books deal with the impacts of the nuclear accident, including evacuation and displacement, the sadness of lost hometown connections, and the desire to return. In both cases, many of these books feature narratives of localized experiences in specific towns/communities, reflecting place attachment. In this research, the authors analyzed the text and visual methods used in these books to convey narratives, representative contents, and treat sad, difficult, and traumatic issues

Better understanding of flood risk management in land use planning policy is needed to assist governments around the world with planning for population growth and climate change related flood hazards. Population growth and weather-related climate change impacts are projected to doubly impact sub-Saharan Africa where lack of food security already exists. While small in land area, Rwanda has the highest population density of any country in mainland Africa. Due to geography, steep topography and climate, the nation is experiencing the brunt of climate related hazards, particularly flooding and landslides. Rapid urbanization is occurring but much of its population remains as smallholder farmers entirely dependent upon the land for livelihoods. Rwanda's government has managed impressive economic growth and development in recent decades. To address challenges related to land use, Rwanda produced an ambitious national level Land Use and Development Master Plan. The plan outlines long term goals intended to optimize productivity and efficiency of land use types, and limit or specially regulate development in areas prone to flood and landslide. The overarching research question asks to what extent are flood and landslide risk management incorporated into national land use planning regulations in Rwanda? To address this question, the authors analyzed planning documents and land regulations, and interviewed ministry staff and supporting organizations, such as development agencies, nongovernmental organizations, and other national governments. Lessons learned from this case may assist policymakers around the world with incorporating disaster risk management into comprehensive land use planning and regulation.

Coastal urban communities are complex socioecological systems that face an elevated risk of flooding from natural hazards such as powerful storms, hurricanes, and sea level rise. However, relative flood risk can be reduced by understanding and improving social, physical, and natural resilience with targeted hazard mitigation strategies. Nature-based solutions (NBS) present a category of ecologically friendly, multifunctional hazard mitigation strategies that coastal communities can use to reduce natural hazard risk. While previous research has identified drivers of flood damages and provided evidence for strategies to enhance resilience, there is still a need to better understand NBS and green infrastructure as a natural hazard mitigation strategy under an applied socioecological framework. Therefore, this research is focused on critically evaluating the flood risk reduction benefits provided by coastal wetland ecosystems in a coastal urban community. To achieve this research objective, the authors used a machine learning model to isolate and quantify the flood mitigation effects of unique natural coastal ecosystems in a monetary value. The preliminary results suggested that different coastal wetlands have unique ecological and biogeophysical characteristics that resulted in different flood mitigation abilities. Improving the understanding of these characteristics and which natural coastal ecosystems can enhance resilience for coastal communities will provide natural resource managers and coastal decision-makers with a new metric of protective value for natural coastal ecosystems. Ultimately, this research will support integrating NBS into hazard mitigation plans and offer further evidence to protect and conserve natural coastal ecosystems.

Escalating impacts from climate change and urban heat are increasing the urgency for communities to equitably plan for heat resilience. Cities in the desert Southwest are among the hottest and fastest warming in the United States, placing them on the front lines of heat planning. Urban heat resilience requires an integrated planning approach that coordinates strategies across the network of plans that shape the built environment and risk patterns. To date, few studies have assessed cities' progress on heat planning. This research was the first to combine two emerging plan evaluation approaches to examine how networks of plans shape urban heat resilience through case studies of Tempe and Tucson, Arizona. The first methodology, Plan Quality Evaluation for Heat Resilience, adapted existing plan quality assessment approaches to heat. The research assessed whether plans meet 56 criteria across seven principles of high-quality planning and the types of heat strategies included in the plans. The second methodology, the Plan Integration for Resilience Scorecard‚™ (PIRS‚™) for Heat, focused on plan policies that could influence urban heat hazards. The authors categorized policies by policy tool and heat mitigation strategy, scored them based on their heat impact, mapped them, and compared the results with heat vulnerability indicators to assess policy alignment with risks. Results showed that both cities are proactively planning for heat resilience using similar plan and strategy types, however, there are clear and consistent opportunities for improvement. Combining these complementary plan evaluation methods provided a more comprehensive understanding of how plans address heat.

In Duval County, Florida, coastal flooding poses a significant risk to property. There is evidence that climate threats (e.g., floods) have disproportionately affected racialized communities in Jacksonville as a result of discriminatory planning and development practices, such as redlining. This study explores the transformative journey of a Participatory Action Research (PAR) project in Jacksonville, Florida. It focuses on how community-driven processes shape research and the profound impact of researcher-community interaction on research outcomes. The project, addressing coastal flooding and socio-environmental disparities, embodies the philosophy of PAR by deeply embedding community perspectives into every research phase and adopting an iterative, flexible methodology responsive to community insights and priorities. The research highlights the dynamic process of PAR, where planned activities and structures evolve through active community engagement. The community's narratives and experiences guide the research questions and redefine the research design, shifting the focus from preconceived academic objectives to community-identified needs. This approach ensures that the research is contextually relevant and fosters a sense of ownership and empowerment within the community. Moreover, the study delves into the impact of the community's storytelling on researchers' positionality. By engaging with and immersing themselves in community narratives, researchers undergo a transformative experience. This engagement challenges their preconceptions, enriches their understanding, and reshapes their role from distant observers to active, empathetic participants. The profound interaction between the community's stories and the researchers' reflexivity illuminates the mutual learning process, highlighting the dual journey of knowledge co-creation and personal growth.

Conventionally, hazard reduction plans are developed by technical teams in isolation, without the input of residents. This study examines how community members' lived experiences can inform local governments' flood strategies. The project took place in Belle Air, an underserved neighborhood prone to flooding in the San Francisco Bay Area. Hindered by complex jurisdictional challenges, responsible entities have struggled to coordinate flood mitigation efforts, resulting historically in minimal engagement between government officials and residents along the flood-prone 7th Avenue. Additionally, since 2020, homeowners have been mandated to purchase flood insurance, creating new costs and potential protections for the community. In 2023, a county agency, a city government, and a community-based organization established a coordinated initiative with the objective to connect with Belle Air's residents and understand their lived experiences with chronic flooding. The team distributed flyers in a targeted campaign and conducted grief-informed listening sessions in both Spanish and English. To gain longitudinal insights, residents were enlisted as Community Leads and actively documented their experiences through free-form weekly updates from January to April 2024. This study aims to identify and prioritize Belle Air's flood-related pain points. The authors analyzed transcripts from listening sessions to examine how the government mandate for flood insurance has affected residents. Textual and visual content provided by Community Leads was cross-referenced with data from a creek gauge and pump stations to compare experiences at different levels of flooding. The findings will guide the development of tailored social and physical interventions to alleviate flood impacts in Belle Air.

Addressing the health risks from climate change and natural disasters requires comprehensive, accessible, and harmonized data across multiple disciplines, including climate, environment, sociodemographic, and health to conduct research, analysis, and policymaking. The National Institutes of Health (NIH) is leading a project called CHORDS (Climate and Health Outcomes Research Data Systems) to develop data resources to better understand the impact of climate change and natural disasters on human health. This transdisciplinary initiative involves building a comprehensive data ecosystem, tools, and other resources with information from multiple fields of study, which can be easily used and accessed by researchers, healthcare providers, policymakers, and community groups. The project has five main goals: (1) to build a web-based catalog of data related to climate and health with a focus on wildfires; (2) to link climate, health, and demographic data into standardized datasets; (3) to provide tools that help researchers connect health and climate data; (4) to develop a use case study on the effects of wildfires on human health; and (5) to include stakeholder feedback to ensure the needs of users are met. With guidance by a panel of experts from government and academia, CHORDS aims to improve experts’ ability to understand and mitigate the harmful effects of climate change and natural disasters on health. This presentation will introduce the online data catalog and initial vignettes covering climate data with exploratory statistical analysis and visualization and share upcoming products in development.

In 2018, the town of Paradise was largely destroyed by the deadliest and most destructive wildfire in California history. Five years later, less than a third of the former residents of the burned area had returned. This work shares results of a survey of past and present Paradise residents conducted in Spring 2023, focusing on how former residents' perceptions of why the wildfire happened influence their decisions about rebuilding or relocating, their risk tolerance, and their overall quality of life since the wildfire. The research team used household-level credit bureau data to obtain current addresses for over 8,000 households formerly in the fire footprint and collected 680 surveys from these households. Initial findings indicate that residents who did not consider climate change to be a factor in the wildfire are more likely to move back to the burned area when controlling for demographic factors. These results point toward potential climate gentrification in wildland-urban interface communities if those with greater awareness or acknowledgement of climate change are less likely to return to hazardous areas.

In an era increasingly affected by natural and man-made disasters, the critical role of social media in disaster communication has become ever more prominent. While substantial research has explored the role of social-media during crises, a critical gap remains: the lack of focus on information-switching behavior during compound hazards. This aspect is fundamental for detecting deviations in information and curbing the spread of misinformation. This study introduces a disaster communication dynamics model, a novel approach designed to examine information switching behavior during compound hazards. This model focused on the temporal changes in sentiment within social-media discussions, providing a deeper understanding of the dynamic evolution of public sentiment in real-time during crises. Utilizing advanced natural language processing techniques, network science, and census data, the study analyzed geotagged tweets related to compound disaster events in Oklahoma throughout 2022. A key finding of this research is the identification of distinct patterns in the engagement of different user types‚ such as bots, private and government agencies, and news media ‚across the various stages of a disaster. Understanding these engagement patterns is crucial for leveraging social media as an effective risk communication tool. The study underscores the importance of temporal aspects in social-media narratives, drawing a connection with the progression of real-world events. The model map’s time-sensitive sentiment changes offer key insights for emergency responders and policymakers. This aids in detecting and mitigating misinformation, enabling the development of targeted communication strategies, and ultimately enhancing disaster response and recovery efforts.

This theoretical effort considers how seemingly unconventional hazard events can be conceptualized using the traditional hazard event scale—that is, the model that classifies hazard events as either emergencies, disasters, or catastrophes. Taking COVID-19 as the focusing event, the researchers consider how duration of event response affects the various characteristics of hazard events (i.e., their impacts, needs, management approach, and stakeholder involvement). This work provides an exhaustive background on the hazard event scale and how it has been formulated by scholars since the inception of disaster research. It also proposes the addition of the duration dimension in order to explain events in which aberrant behaviors are observed during response. The updated hazard event scale has significant implications for emergency management practitioners and policy makers and provides an opportunity to more holistically address all of the hazard events their communities may face (e.g., the Jackson, Mississippi, water crisis and Cancer Alley in Louisiana). It can also help researchers committed to incorporating research findings into practice by giving them tools to properly categorize the events they study.

The north shore of Willapa Bay in Pacific County, Washington, is a rural community experiencing rapid erosion of its shoreline, intensified storm seasons, and rising sea levels. It is also a diverse community that includes conservative, lower-income agriculture and aquaculture workers, as well as historically marginalized members of the Shoalwater Bay Indian Tribe. Despite cultural differences, community members have rallied around their shared goal of preserving the coastal lands central to their history and future. In 2015, community members established Willapa Erosion Control Action Now (WECAN) to coordinate local approaches to nature-based adaptive management. Building on this momentum, University of Washington researchers partnered with local activist group WashAway No More and WECAN leaders to augment measurement capabilities from their community-driven beach photo stations and to build new pathways for local knowledge to inform mitigation and adaptation approaches. This research utilized modified Photovoice discussions with four to five groups of Willapa Bay community members. Existing community-submitted photographs from the North Cove beach photo stations were used to spur discussion about community perceptions about climate change impacts, as well as inputs on mitigation and adaptation solutions and future project directions. Participants were also encouraged to bring their personal photos of the coast to discuss their personal experiences with their beach. The discussions were recorded and professionally transcribed. Transcripts were deductively coded and thematically analyzed using NVivo qualitative analysis software. Coded text was synthesized to develop salient themes, which will be presented here.

Disaster losses and expenses are increasing rapidly in coastal regions, highlighting the pressing need for effective mitigation strategies. The voluntary buyout program is an effective approach to reducing risks of future flooding, often funded by federal grants after disasters. However, following a disaster, decision-making tends to be reactive, potentially leading to a haphazard selection of properties and households for program participation. It is crucial for local governments in charge of these programs to be informed by who may or may not benefit from program participation when deciding which properties to select and prioritize. Therefore, incorporating social equity in those decisions prevents unintended consequences for the program participants. This research addresses this complexity by raising the critical question of how local practitioners can evaluate equity considerations of using federal grants for buyout projects. With a mixed-methods research design, the authors offer a systematic guideline for supporting local practitioners in evaluating the equity considerations of using funding for buyouts, ultimately leading to improved outcomes for participating households. By acknowledging the potential of buyouts in mitigating flood risks and recognizing its equity implications, this study uses advanced hazard models, buyout practitioners' and experts' insights, secondary data on property acquisition spending, and findings from past research to support local practitioners in making equitable decisions on who can receive a buyout offer through developing a decision framework.

Wildfires present a growing threat to rural and disadvantaged communities. However, these communities are often overlooked, which perpetuates a cycle of inequity in the wildfire resource allocation decision-making process. Despite many efforts of the government to reach socio-vulnerable communities, challenges still exist as many of these communities need more vital capacity to access competitive federal grants. Therefore, it is critical to understand the dynamics and complexities of the extreme effects of wildfires on these disadvantaged populations and consider equitable wildfire resilience-building approaches. Leveraging a paradigm of statistical machine learning algorithms, this study identifies key factors influencing the number of personnel dispatched to combat a wildfire and the estimated wildfire cost under various scenarios—fire severity, types of communities impacted, etc. Publicly available data from the National Interagency Fire Center, the U.S. Census Bureau, and the CDC Social Vulnerability Index were used to develop a database that includes over 230,000 wildfire instances from 2014-2022 in the United States. Results highlight that counties with higher percentages of low-income and Black populations receive less personnel and funding compared to counties with higher proportions of high-income and White populations. Findings also show that the percentage of households with annual income over $200,000 is positively correlated with both the number of personnel and estimated cost, indicating that high-income neighborhoods receive more attention in the post-disaster response/recovery phase. Findings from this research can promote a more equitable distribution of resources post-wildfire, advancing the safety, well-being, and resilience of the vulnerable wildland-urban interface communities.

There are ongoing calls in the humanitarian and disaster management (DM) sectors to localize DM, make it more participatory and involving communities. A common response to these calls by civil protection authorities and non-governmental organizations (NGOs) is to work with local actors to jointly deliver local, community based, participatory DM. However, this setup tends to be hierarchical, with external actors taking the lead on project design and local actors on implementation. As a result, key outcomes envisioned for localization and participation in DM often do not materialize. This research explored the role legitimacy work plays in maintaining this unhelpful status quo. To this end, it provided a qualitative case study analysis of a DM project in Ethiopia (2016-2020) that was initiated by two NGOs and built on government structures designed to facilitate mass volunteering at community level: the Women's Development Army. This research showed that externally driven localization is often organized around project models that are shaped by two contradictory paradigms: one centering resilience and one centering surveillance. As a result, local actors were faced with incompatible legitimacy requirements in their work. This research used a paradox perspective as a theoretical lens to explore how these local actors navigate these conflicting needs. It found that they used impression management, especially visuals and performances, to sidestep the contradictions. This imagery concealed the disconnects between project strategy, implementation, and the reality on the ground. As a side effect, it rendered the problems with the externally driven approach invisible and legitimizes the hierarchical status quo.

Hurricane Ida, which struck New York in early September 2021, exposed the vulnerable region to extreme rainfall and inland flooding. Tragically, it caused the deaths of eleven people in their basement homes, highlighting specific risks to inhabitants of low-lying units in the face of extreme weather. The intersection of natural hazards, severe housing shortages, and public safety raises the importance of identifying which neighborhoods contain the highest shares of flood-prone basement dwellings. This research measures the significance of the basement housing stock in New York City, particularly for low-income and immigrant populations. It examines the flood exposure of basements using climate risk data from the Federal Emergency Management Agency and the First Street Foundation; this data incorporates flood risk from coastal, river-driven (fluvial), and rainfall-driven (pluvial) flooding. The study focuses on the basement structures that are most likely to be in residential buildings, using the New York City Primary Land Use Tax Lot Output Database. The method for identifying basement housing adopts and modifies a data filtering process from Citizens' Housing and Planning Council and divides basements into flood-prone and viable categories. The analysis finds that basements in select census tracts are at high risk of flooding, affecting an estimated 10% of low-income and immigrant New Yorkers. However, estimates of the census tracts with highly flood-prone versus less flood-prone basement housing stock indicate that nearby and neighboring affordable and less-storm vulnerable neighborhoods could be future sites of safe dwellings.

Excessive alcohol use is a major public health concern in the United States and particularly in communities along the Gulf Coast. The COVID-19 pandemic ushered in new concerns about alcohol use as many studies reported increases in alcohol consumption. The longer-term trends in alcohol use require further exploration, particularly with longitudinal data. The Survey of Trauma, Resilience, and Opportunity among Neighborhoods in the Gulf (STRONG) is a five-wave longitudinal survey of 2,520 residents of 56 coastal counties and parishes in Texas, Louisiana, Mississippi, Alabama, and Florida. Waves of the STRONG have been fielded to explore the health, economic, and social impacts of disasters including the Deepwater Horizon oil spill (STRONG I), hurricanes (STRONG II), and COVID-19 (STRONG III, IV, and V). This study describes changes to the frequency and quantity of alcohol consumption over time and how these changes differ across demographics and disasters. Conclusions recommend interventions and policy for future public health emergencies and disasters.

While Japan has long been perceived as a demographically homogeneous country with low levels of migration, local demographic change in cities like Toyama brings levels of diversity not experienced before. In the last decade, local authorities across Japan increased their efforts to build disaster preparedness among diverse communities. Highlighting the role of the demographic change and migration-related diversification processes happening in Toyama, this study addresses the question: how are public servants and practitioners trying to adapt disaster resilience-building efforts to a diversifying population? Using qualitative semi-structured interviews and ethnographic observations with public servants and practitioners, the paper explores the challenges associated with a growing discrepancy between guiding principles based predominantly on ethno-national conceptualizations, a Japanese form of “ambiguous” multiculturalism reflected in and influenced by the logic of multicultural coexistence (tabunka kyōsei), and local disaster resilience needs shaped by migration-driven diversification. The paper also offers an empirical advancement of the superdiversity lens, beyond its predominantly Western applications, as a heuristic tool to examine the nature of 'tacit' articulations of migration-driven diversity.

Since December 2022, the U.S. Census Bureau has introduced questions regarding household experiences of natural hazards (e.g., hurricanes, floods, tornados) and displacement in their Household Pulse Survey (HPS). According to the data collected thus far, 1.2% of American households have been displaced due to disasters. Most households returned quickly: 44% within a week and 24% within a month. However, 18% of households took over one month to return, and 13% never returned. The availability of HPS microdata enabled an exploration of trends and a quantification of the influence of the available attributes (e.g., physical damage to the built environment, household demographics). Moreover, the geographic and temporal scope of the survey allowed a broader understanding of household displacement and return beyond individual case study approaches. To quantitatively understand the influence of a range of explanatory variables on household displacement durations and return outcomes, a random forest model was fit to the available household-level data and associated area attributes. After model fitting, feature importance was calculated to understand which explanatory variables more consistently drove duration and return outcomes. Consistent with disaster literature, property damage was the primary driver of displacement duration. However, this variable only explained 37% of outcomes, indicating that a broader range of factors also significantly affect household return trajectories (e.g., unsanitary conditions after disaster, housing tenure, dwelling type, vacancy rates). Understanding the influence of these factors may help identify preparedness measures to reduce displacement durations or inform post-disaster assistance programs geared toward broader and more equitable recovery.

This study analyzed the impact of climatic shocks on food consumption and farmers' decisions to join social networks as a coping strategy. The authors of this study used Bangladesh Climate Change Adaptation Survey data from Round II (2012) on 762 farming households. These households were grouped into seven broad agroecological zones by the Bangladesh Center for Advanced Studies. The survey provides information regarding demographic, networking, social characteristics, and the incidence of climatic shocks, among other traits. The authors found that farmers whose food consumption were disrupted by floods, droughts, or cyclones were more likely to join social networks and eventually improve their overall consumption compared to their counterparts. The study has multifold policy implications for developing countries. First, social networks can provide financial support and informal financial channels for farmers to cope with uncertainty and risk during natural disasters. Second, social networks may ease agricultural extension through information sharing and eventually improve production and consumption. Therefore, the study’s findings are relevant for designing policies to cope with disaster shocks, particularly for underdeveloped, agrarian countries.

Children and youth‚ defined here as those under the age of 18‚ are capable actors who can and do contribute to disaster preparedness, response, and recovery efforts. Yet, despite some notable progress in documenting children's altruism and prosocial behavior in past disasters, there has been relatively little research on the actions that children took to assist during the global COVID-19 pandemic. To fill this gap, this project team built, analyzed, and published a novel dataset of English-language news media articles describing children's helping behaviors in the United States during the pandemic. The authors found that children helped their communities, schools, adults, other children, or themselves in the following ways: (1) engaging in artistic or creative expression; (2) making, collecting, or distributing supplies; (3) offering social, emotional, or other forms of support; (4) providing tutoring or developing other educational services; (5) donating or raising money; (6) leading or getting involved in community activities; (7) cooking, serving, or distributing food; (8) participating in public health campaigns or vaccination trials; and (9) initiating or taking part in research to inform social interventions. This study contributes to research on altruistic behavior in disasters through offering a new typology of children's actions in the pandemic. The authors conclude with a call for additional research and media reporting on diverse children's contributions in future disasters.

Amidst increasing and changing risks from disasters, the climate crisis, and social inequity, public libraries are established and trusted institutions. Given their quasi-omnipresence throughout American communities and their mission of no cost public service, public libraries have played a crucial role in social life and pandemic response. This dissertation research analyzes how Delaware public libraries improvised and adapted their services to continue serving patrons in the early months of the COVID-19 pandemic (March 2020-July 2021). The study combines document analysis and more than 30 semi-structured interviews with library workers and administrators. By positioning the work of library staff and administrators in the greater context of the pandemic response, the study identifies aspects of improvised response to be formalized and structured for better local-level response to future disasters, and informs recommendations for the integration of libraries into local and regional planning processes. As a generally well-regarded manifestation of government, public libraries are uniquely suited to be partners for their patrons in everyday challenges and in emergencies, empowering the individual to actively participate in society. As a trusted entity embedded in the community, public libraries are equally well-suited to be partners for local and state administrations, serving as conduit between the population and elected officials.

For over fifty years the definition and causal attributes of disasters have been debated. Yet, as climate change increases disaster frequency, intensity, and duration at the same time as increasing politicization of environmental issues, important questions arise: Do people's causal attributions of disasters (i.e., beliefs about root causes) predict their support for disaster risk reduction efforts? Are their attributions and mitigation beliefs consistent across disaster typologies (e.g., hurricane vs. heat wave)? Do factors like geographical exposure to particular disaster types, or personal political orientation matter? For whom? Two national correlational surveys (N = 407 and N = 748), examined whether there would be meaningful variation in people's causal attributions across different hazards and whether these attributions are related to mitigation beliefs, risk perception, and policy support. Analyses also explored these constructs' relations to key sociodemographic variables (e.g., experience, political orientation). Results revealed that attributions of disasters (a) vary by hazard type, (b) are related to beliefs about mitigation potential (i.e., whether collective or individual action can reduce disaster risks), and (c) are related to support for disaster mitigation policies. That is, the more people acknowledge anthropomorphic, sociopolitical, and climate's causal impacts on disasters, the more disaster risk and mitigation potential they perceive, and the more supportive of disaster mitigation policies they tend to be. These social psychological relationships found between attributions, mitigation beliefs, risk perception, and policy support interact with political orientation, suggesting that persuasive pathways exist to help bridge polarized political divides surrounding disaster policy in the United States.

There is a growing understanding of the vulnerability of incarcerated people in disasters. Yet, the unique needs of incarcerated women have remained overlooked. Incarcerated women are routinely ignored in research efforts as the experiences of incarcerated men are often treated as the default incarcerated experience. In disasters, this has significant implications for the life safety, physical and mental health, and social well-being of incarcerated women. Lioness: The Justice Impacted Women's Alliance and researchers at Texas A&M co-developed this study with two formerly incarcerated women, co-researchers, and leaders within the organizations, to better understand how incarcerated women are impacted  in the context of disaster-related evacuations and related decision-making by prisons, emergency management, government officials, etc. The research team conducted several focus groups with formerly incarcerated women to explore these themes. Preliminary findings reveal the unique vulnerability and marginalization of incarcerated women in disasters. Furthermore, the authors share lessons learned for how academics can better partner in research activities with stigmatized and vulnerable people to center their needs and empower them in the research process in addition to improving the accuracy and quality of data collection.

According to the Intergovernmental Panel on Climate Change (IPCC), agroforestry, or the intentional integration of trees or shrubs with crops and/or livestock within agricultural systems, offers promising adaptation strategies for climate-induced challenges in agroecosystems. However, there is a lack of integrated social-biophysical research on agroforestry in the United States, particularly in regions like San Diego County. This study aimed to address this research gap by pursuing two principal objectives: to understand historical, contemporary, and projected climatic conditions within the region, drawing upon climatic models and local agriculturalists' experiential knowledge; and to highlight the adaptive strategies employed by local farmers to confront the challenges of a changing climate, with particular emphasis on the implementation of agroforestry systems. The research employed  convergent research methods, including preliminary interviews, surveys, the use of climate and terrestrial models from the National Center for Atmospheric Research (NCAR), and in-situ biophysical assessments. This study sought to comprehensively assess the biophysical and socioeconomic dimensions of agroforestry practices with the ultimate goal to provide insights into the potential benefits of agroforestry for enhancing agricultural production and quality, employing resources efficiently, informing policy decisions, and supporting farmers and stakeholders in San Diego County.

Disasters often have devastating impacts on communities, causing loss of life, damage to infrastructure, and disruption of services. While quantitative data provides critical information about economic losses, infrastructure damage, and mortality rates, qualitative data offers unique insights into how communities experience and handle disasters, playing a significant role in the in-depth understanding of needs that often escape the reach of quantitative methodologies. In that context, this research proposes a comprehensive framework for collecting and analyzing both quantitative and qualitative data from a variety of sources, including interviews, focus groups, surveys, news reports, and open-source databases to assess community perspectives and impacts after natural hazards. Specifically, it details qualitative methods like ethnographic techniques such as participant observation and in-depth interviewing with members of the affected community. In addition, the framework suggests fieldwork and textual analysis of documents and online information to enrich the findings. This community-centered, bottom-up approach complements quantitative assessments and helps create a holistic understanding of how natural hazards affect communities. The framework is applied to the 2022 Hurricane Fiona in Puerto Rico to analyze the impacts of critical infrastructure failures (i.e., the electric grid and transportation infrastructures) on socially vulnerable communities. Through fieldwork data, the authors analyzed both qualitative and quantitative data, which provided essential insights for policymakers seeking to enhance community resilience and develop equitable disaster recovery plans.

This study examines the experiences and decision-making processes of people experiencing homelessness (PEH) during evacuations in natural disasters and extreme weather events, emphasizing their heightened vulnerability due to a lack of physical protection. Acknowledging the limited exploration of homeless evacuation decision-making in existing literature, where plans for homeless populations are typically shaped by service providers, this research shifts its focus to the direct experiences of PEH. Guided by Lindell and Perry's Protective Action Decision Model, the study analyzes factors influencing PEH evacuation decisions. Through in-depth semi-structured interviews with unsheltered PEH, the research explores their daily challenges and examines how these challenges impact evacuation decisions during disasters, as well as exacerbate their physical and mental health issues. The study also emphasizes the critical role of community-based organizations and public services as lifelines, potentially influencing evacuation decisions. In conclusion, the research underscores nuanced factors shaping the evacuation decisions of unsheltered PEH during disasters, emphasizing the importance of recognizing their human agency intricately tied to daily struggles. Addressing challenges during disasters requires integrated evacuation plans considering unique circumstances and the role of essential community resources. Furthermore, the study discusses implications for public service delivery to the homeless community using a collaborative governance approach, shedding light on PEH as service recipients and service-worthy clients. The insights into the perceptions and experiences of unsheltered PEH provide valuable information for researchers, service providers, and organizations developing targeted communication systems and evacuation plans that consider the daily struggles influencing PEH decision-making.

This study explores the nuanced aspects of evacuation decisions made by people experiencing homelessness (PEH) during disasters and extreme weather events, shedding light on their perceptions and awareness of impending disasters or extreme weather events. Grounded in Lindell and Perry's (2012) Protective Action Decision Model (PADM), this research draws insights from 41 in-depth semi-structured interviews with unsheltered PEH, examining how individuals living on the streets typically receive initial disaster-related information. The responses of PEH highlight the complex interplay between technology and natural intuition in shaping their evacuation decisions. The study illuminates how technology and environmental cues are the primary drivers of their initial evacuation responses, underscoring the necessity for disaster planners and responders to leverage technology effectively, especially in providing timely information about available shelters and evacuation resources. Practical recommendations for emergency management and public service delivery include integrating technology measures into emergency planning and developing tailored local government online communications for this community. However, it also underscores the challenges associated with technology use, such as access to working cell phones, charging facilities, and the ability to understand online information sources. In conclusion, the experiences of individuals facing homelessness offer valuable insights into how technology and natural cues influence their evacuation decisions. Not having a cell phone within the homeless community, or not being near someone who does, may exclude them from crucial official warnings about disasters or extreme weather events, posing a significant threat to their survival.

Natural hazards like windstorms and earthquakes exert significant stresses on buildings and infrastructure, potentially causing failure in both structural and non-structural components, leading to extensive overall damage. The economic impact of such events necessitates reevaluating engineering approaches to resilience assessment and examination of the functional integrity of civil infrastructure. Such an assessment requires accurate and computationally efficient frameworks for predicting failures in building systems, considering both structural and non-structural elements. To this end, this study leveraged the Potential-of-Mean-Force (PMF) to the Lattice Element Method (LEM), a discrete method advantageous for simulating failure and fracture. This framework discretizes the system into a set of particles that interact through prescribed potential functions to represent the mechanical properties of members. Lending itself to damage assessment due to its discrete nature, the proposed PMF-based LEM transcends the limitations of continuum mechanics approaches. It incorporates a range of effective interaction potentials to simulate the linear and nonlinear behavior of structural components. Failure here is simulated by breaking bonds between particles according to an energy-based failure criterion. Calibration of harmonic potential parameters was carried out via a handshake with continuum mechanics theories, while non-harmonic potentials were calibrated using section properties that encapsulate material nonlinear stress-strain responses (e.g., nonlinear moment-curvature relations). The utility of the proposed method was demonstrated through its application to quasi-static nonlinear simulations of large-scale buildings and the simulation of progressive structural failure due to the propagation of local structural damage.

Flood loss estimates provide crucial information about impact severity and location, yet there is a significant gap in understanding the demographic characteristics of those who bear the brunt of these impacts. Social vulnerability indicators, widely employed in disaster research, illuminate population groups disproportionately affected by natural hazards due to social, political, and economic conditions hindering their capacity to respond during hazard events. Despite the prevalent use of social vulnerability indicators, there is limited empirical understanding of their relationship with specific hazard impacts, particularly in the context of flood losses and in small urbanizing regions. Additionally, while structural and population losses dominate discussions on flood impact assessment, there is a notable gap in knowledge regarding agricultural loss estimation. Few studies have explored how vulnerability indicators correlate with structural, population, and agricultural losses, hampering efforts to identify population characteristics associated with different types of losses and ensure equitable resource distribution. The primary objective of this study was to discern dominant population characteristics associated with various levels of flood loss in the Philadelphia Metropolitan Region. To achieve this, two key research questions were addressed: (1) What are the spatial clusters and statistical distribution for river flood loss in the study area? (2) Which social vulnerability indicators are correlated with structural, population, and agricultural flood losses? Using the National Risk Index dataset and applying Local Indicator of Spatial Association and spatial regression analysis, this research contributes nuanced insights that can inform equitable resource allocation and effective hazard mitigation strategies.

Building resilient communities requires the collaborative engagement of diverse stakeholders, including public agencies, non-governmental organizations, private industries, and local communities. However, disparities in stakeholders' value systems, which refer to ranked systems of things that are of importance and merit to stakeholders in community resilience, may give rise to conflicts that impede collaborative efforts. Currently, there is a lack of systematic understanding regarding how the value systems of different stakeholders influence their collaboration. To address this gap, this research provided a comprehensive analysis of stakeholder collaboration in community resilience planning within the context of the Greater Miami and the Beaches region. Through social network analysis and exponential random graph modeling based on survey data collected from multisector stakeholders, the study delved into understanding the roles, positions, and collaboration patterns and characteristics (e.g., nature of contact, effectiveness of collaboration) of different stakeholders involved in resilience planning. Specifically, it investigated the impact of stakeholders' value systems on their collaboration patterns. The findings highlighted academia and public agencies as central and influential stakeholders in resilience planning. Additionally, this research suggested that despite the active engagement of various stakeholders, the quality of their collaboration (e.g., collaboration density, contact frequency, effectiveness) requires further improvement. Moreover, the research revealed that stakeholders' value systems significantly impact the formation and characteristics of their collaborative relationships. The findings of this research are critical in guiding more collaborative efforts in building resilient communities, thereby fostering a culture of shared responsibility and proactive engagement in resilience initiatives.

Emergency Management Departments (EMD) and organizations are the cornerstone of Emergency Management operations at every level of government regarding disaster, event, and incident management. Even with these departments and organizations functioning and going through every phase of emergency management how often are they being assessed? Currently, the Emergency Management Accreditation Program (EMAP) is the only non-profit accreditation program for Emergency Management (EM) Programs on the planet. Since this is the only application as an assessment method for emergency management programs and organizations, the quality and value of this assessment is the only official method of organizational assessment within the emergency management and homeland security space. Data from this study addressed the process and shared information about EMAP's impact on organizational assessment, focusing on Emergency Management. This study utilized an electronic survey to provide access to as many certified emergency managers nationwide. This process for survey development and distribution is ideal with each emergency management office having access to the internet and technology in everyday operations, through the approach to leveraging access to practitioners who are credentialed by the International Association of Emergency Managers (IAEM) with either the Associate Emergency Manager (AEM) or the Certified Emergency Manager (CEM) certification.

Experience with and knowledge of hazards has been found to influence attention to warning methods and protective action behavior. On March 31, 2023, two EF3 tornados occurred in Arkansas. This study asks: What are the differences in warning sources used and protective action behavior between various student groups? This quantitative study surveyed college students in the two regions affected by the tornadic events. Protective action behavior and utilization of warning sources, along with tornado experience were examined comparing groups based on home region: Those from regions that are tornado prone (in-region) and those from regions that are not tornado prone (out-region). Home region was found to have a relationship with tornado experience and knowledge. However, while no significant differences were found between groups regarding protective actions and utilization of warning sources, these findings can still guide policy for campus emergency managers.

The increasing frequency and severity of natural hazards precipitated by climate change is anticipated to present many challenges to communities in terms of climate literacy, climate readiness, and the adoption of a resilience mindset and adaptation culture. In this project, the authors examine data-driven approaches to demystify the impacts of climate change on natural hazards and severe events and to elucidate climate change impacts on individual and community health. Case study data and analyses from Houston and Texas are presented illustrating the existing interactions and correspondence between air quality, extreme heat, and flooding when correlated to community health. Longitudinal data for PM2.5, temperature, recurring flood claims, and public health were synthesized in a geospatial modeling framework along with scenarios of projected climate change for Houston and Texas. Geostatistical data-driven models were used to project impacts under climate change. The authors also discussed strategies toward more effective climate risk communication with examples of community-based concept mapping approaches as a tool for engaging stakeholders.

Flooding is the most common and pervasive environmental hazard in the United States. Yet, most theories and tools for proper mitigation (lessening and avoidance) of flood risks are predicated on strong city-level governance. Despite a third of U.S. residents residing in “unincorporated areas” which lack city-level governance, researchers have not identified the barriers they face in mitigating flood risk or developed tools specially designed for rural contexts. Instead, recent research shows that unincorporated and rural communities often adapt their mitigation plans from templates intended for large cities, leading to poor outcomes for their plans. Additionally, unincorporated and rural communities have seen greater decreases in hazard mitigation funding relative to urban areas. This presentation reviews findings from the first phase of an ongoing CalWater project aimed to identify and address the barriers to flood mitigation experienced by unincorporated communities of color. The first phase of research includes: a literature review; analysis of existing policies, projects, and cases involving flood mitigation in unincorporated communities; and semi-structured interviews with county officials, community organizers, and city planners throughout the Bay Area of California. This data is analyzed using the analytic framework of procedural vulnerability to determine the systematic limitations facing unincorporated areas in the United States, with specific attention to how histories of racism and segregation impact inequitable access to adequate flood mitigation. The authors conclude with key takeaways and next steps as work continues with unincorporated areas of California to begin addressing these barriers to equitable flood mitigation.

The focus of this presentation is research methodology, specifically a personal reflection on the nuances of fieldwork in war-affected Israel during February 2024. This presentation addresses the question "What challenges are faced by a field researcher operating in a war-affected area?" Findings are organized as challenges faced during three distinct phases of fieldwork: before field entry, during fieldwork, and after return from the field. On October 7, 2023, Hamas terrorists staged a surprise attack on Israel involving killing, kidnapping, and damage to communities. Approximately 4 months later, the presenter was a delegate on a rapid response mission. The objectives were (1) Understanding and supporting the humanitarian efforts being implemented to restore the security and safety of Israeli society, and (2) Bearing witness to the October 7 massacre and related atrocities. To document the experience, an autoethnographic approach was taken. Proposed results and implications from the fieldwork in war-affected Israel are presented as personal reflections. Examples of reflections are the difficulty of remaining dispassionate while on task and the struggle related to not being able to unsee what one has seen. Also, do not underestimate the challenges one faces after returning from the field. Having access to mental health tools to deal with secondary traumatic stress resulting from particularly intense fieldwork experiences is highly recommended.

People with (dis)abilities, as a vulnerable and marginalized group, are more likely to experience diverse societal challenges (e.g., financial hardships, social isolation, and discrimination). COVID-19 not only exacerbated these barriers that existed pre-pandemic but also created new challenges, negatively impacting their already weakened health and well-being status. Studies have illustrated that the human-animal bond provides tremendous social and health benefits, especially in the context of COVID-19. However, research on the COVID-19-specific experiences of companion animal guardians with (dis)abilities remains scarce. Drawing on the One Health and One Welfare lens, this comparative case study employed in-depth interviews to investigate the experiences of companion animal guardians with (dis)abilities during the first wave of COVID-19 in two cities: Xi'an, China and Vancouver, Canada, where the completely different public health policies significantly shaped their experiences. Drawing insights from these different experiences and utilizing them to inform companion animal guardians with (dis)abilities-specific support, this study identified three benefits and three challenges. The benefits include (1) physical health, (2) mental health, and (3) individual resilience capacity. Challenges faced by companion animal guardians with (dis)abilities included (1) veterinary care cost and financial burden, (2) barriers to accessing veterinary care, and (3) concerns about the animal's emotional well-being. This comparative study highlights the unique needs of companion animal guardians with (dis)abilities, which require individual and community support. Addressing the unique demands helps build both individual and community resilience capacity and improve future extreme event preparedness and response.

Currently, no standardized tool or methodology exists for assessing the risk to public health from hazards; and most of the tools currently available are not specific to the health and medical aspects of risk. The Los Angeles County Department of Public Health Emergency Preparedness and Response Division has developed a new tool, the Health Impact and Likelihood Assessment (HILA), for health and medical planners, as risk assessments are often a requirement of grant funding. This tool combines existing hazard-specific data and jurisdiction-specific inputs, to produce hazard specific risk scores that can be compared against each other to prioritize jurisdictional planning, training, and exercising priorities. This new risk assessment includes over 35 hazard scenarios derived from the best available research and historical data. The methodology utilizes these hazard-specific data, or impacts, to Human Health (e.g., fatalities, hospitalizations, mental health impacts) and the Healthcare System of the given jurisdiction (e.g., impacts on hospitals, dialysis centers, and other healthcare facilities), which are combined with participant-determined weights to produce hazard-specific risk scores. Risk scores are combined with a relative probability ranking to generate a matrix of the potential risk that the hazards pose to the jurisdiction. This tool is hosted as an online survey, allowing the jurisdiction to collect data from planning partners on “weights” or values determining the importance of these variables, which are then applied agnostically across all the potential hazards.

Chronic hazards associated with a changing climate may necessitate difficult adaptation decisions in many communities. Computational tools that account for uncertainties in both future climate conditions and household responses are needed to assist in the decision-making process towards community climate resilience. This presentation describes a novel decision-support tool for modeling community adaptation and household response to sea-level rise. The model considers: (1) sea-level rise and its impact on both buildings and road/bridge transportation networks, (2) household response to sea-level rise, such as relocation within and outside of the community, and (3) community adaptation planning, such as buyout programs. Publicly available sea-level rise data – in the form of both future projections and inundation footprints – was combined with tide projections to determine future scenarios of nuisance flooding. The Interdependent Networked Community Resilience Modeling Environment (IN-CORE) was used to map hazard intensity measures to the built environment, resulting in parcel-level exposure and increases in travel time. Households were represented as agents whose behavior is modeled in response to their environment using reinforcement learning. Agents responded to nuisance flooding by considering attributes such as: (1) exposure of their household, (2) increases in travel time to community assets, (3) percentage of neighbors that have migrated, and (4) place-attachment. Through this model, the impacts of adaptation policies on individual behavior, such as engagement with buyout programs, can be simulated. The model is demonstrated using Galveston, Texas as a testbed community.

Human populations across the western United States face an increasingly flammable, smoky, and power disrupted future. These direct and indirect threats of wildfire disrupt daily activities and pose severe health risks to vulnerable groups. However, research on co-occurring and, in some cases, compounding wildfire-related hazards is limited. This study asks three questions: (1) How do individuals respond to wildfire risk, smoke, and power disruption? (2) In what ways, do these hazards compound to create unexpected impacts on individuals? (3) In what ways do responses interact with hazards creating feedback loops and additional impacts? The authors of this study draw on data from 45 key informant interviews in three Northern California counties—Lake, Tehama, and Tuolumne—with high wildfire risk, high exposure to wildfire smoke, and high past and potential future exposure to power shutoffs. The authors present a typology of hazard and response interactions that synthesizes the complexity of compounding hazard pathways and impacts on individuals. This multi-site case study aims to describe the decisions of individuals adapting to compounding wildfire-related hazards in the U.S. West.

Engaging residents in community resilience efforts is central to disaster recovery. Scholars focused on the social production of disasters have argued that mitigation, in the form of resettlement and infrastructure interventions, underestimates people’s connection to their environment, and the meaning of space and place, leading to new forms of uncertainty. Understanding the cultural landscape of communities allows rethinking how relations between ecological, social, political, economic, technical, and cultural systems inform disaster experiences. This presentation will discuss a transdisciplinary community engagement project in Puerto Rico, part of Rising Voices, Changing Coasts (RVCC): The Earth and Indigenous Convergence Science Hub. RVCC in Puerto Rico creates a space where traditional or Indigenous knowledge holders from coastal regions, collaborate with academics, scientists, and students in transformative convergence research to co-design solutions to the medium and long-term challenges their communities face. Through case studies in the municipalities of Guánica, Guayanilla, and Cataño, the authors elaborate on the methods used to engage residents in documenting their memories, culture, traditions, and history, as well as the impact of recent events on their neighborhoods to augment local capacity, nurture trust, enhance risk communication, and co-design disaster mitigation and climate change adaptation solutions that effectively and efficiently address local needs.

Aftershocks following large earthquakes can be probabilistically forecasted using statistical seismicity models. Scientific organizations compute aftershock forecasts and use these to communicate rates and probabilities of aftershocks to diverse user audiences. Some forecasts also need to be communicated internationally, e.g., for earthquakes near national borders where aftershocks can affect multiple countries. Visual forecast products may communicate aftershock forecast information more effectively if designed around the needs of their users. This research sought to identify which forecast visualizations (including maps) can serve a variety of user groups. The authors held workshops with members of target user groups, including emergency managers, civil engineers, critical infrastructure operators, firefighters, public health officials, public information officials, and other science communicators. In these workshops, users performed small-group activities to elicit specifically which dimensions of aftershock forecast information were most needed by their role (informational needs) and how this information would optimally be displayed (product needs). Workshops were held in the United States, Mexico, and El Salvador to isolate components of forecast communication that may be effective across countries as well as user groups. The researchers then developed a suite of forecast graphics and maps that aligned with these informational and product needs and ran a user experiment to test a subset of these forecast products. In the experiment, participants from these target groups used different forecast products to perform decision-making tasks based on common use of aftershock forecasts.

Building gender-inclusive infrastructure resilience is a critical component of ensuring development benefits and investments reach across community sectors equitably. It is evident that women, girls, and disabled people around the world are disproportionately affected by disasters due to different level of vulnerabilities associated with accessing public infrastructures. They are often equally burdened by a lack of access to basic infrastructure services like clean water, sanitation, health, cyclone shelter, and safe public transport particularly during the onset of sudden disaster. These gender issues are overlooked in infrastructure development and eventually create hinderances in every aspect of building back better, impacting the efforts for disaster response, recovery, and reconstruction. Though reconstruction is seen as a scope to build back inclusively and augment resilience, the rebuilt infrastructure rarely takes into consideration aspects of inclusion. Ensuring access to resilient infrastructure requires adopting structural and non-structural measures to reduce damage and loss of life for women and girls in their homes, whilst using community facilities as well as allowing accessibility, convenience, and safety. This study highlights experiences for building inclusive resilience in the Asia-Pacific context, with a particular focus on public health, and how integrating gender dimensions from the onset of infrastructure design can bolster inclusive resilience for women and girls in the long run.

The quantitative assessments of disaster resilience in cities and communities have become increasingly important in considering measures for disaster risk reduction. Although many resilience indicators have been proposed, the number of studies externally validating the indicators with empirical resilience outcome variables obtained during or after disasters (i.e., the extent of property loss and recovery rate) is still limited. Hence, it is crucial to elucidate whether such indicators are valid under any circumstances or whether they are dependent on local characteristics, such as culture and urbanization level. To address the questions, this study aimed to examine the validity of the resilience indicators, investigating how they can explain the housing recovery of districts in Mashiki Town, which was most heavily affected by the 2016 Kumamoto earthquake in Japan. The project developed a dataset of the status of 9,179 houses regarding damage classification, demolition, and reconstruction using the municipality's building damage certificate data and the building data in 2018 and 2020. The statistical data analysis clarified the correlations between the housing recovery rate and resilience indicators of districts. The preliminary findings showed that some indicators, such as the population rate above 65 years old, indicated significant correlations in the expected direction. However, other indicators, such as the population rate born in the town and still residing, demonstrated significant but contradictory correlations to the findings of the previous studies. The results imply that the validity of resilience indicators can depend on local characteristics, which should be further explored in other cases.

Flood mitigation is often based on historical records traditionally compiled using damage assessments, economic summaries, and meteorological records. Although these are useful in capturing larger events, such records often miss community knowledge. Recognizing the global imperative to develop inclusive flood policies, integrating community knowledge into policy is essential. This is especially important for pluvial (rainfall-runoff-driven) flood events, which are short-spanned, hyper-local, and have sparse historical records. In today's age of digitization, regional media has emerged as a data source that can capture community perspectives and on-the-ground socioeconomic realities. Leveraging regional English-language digital news sources (seven in total collected between 2010 and 2022), this study aims to create a historical record of pluvial floods for a case study focused on Bengaluru, India‚ a city with sparse pluvial flood records, recent occurrences of floods, and a rapidly changing climate. News articles were examined, both qualitatively and computationally, using topic modeling to answer three questions: (1) What are the causes, impacts, and frequency of pluvial flood events as described in regional news media? (2) How are the causes of and uncertainties associated with pluvial flooding explained by actors and frames within news media? and (3) What pluvial flood mitigation actions are currently in place, and what future flood mitigation actions have been identified? Alongside providing insight into flood events in Bengaluru, the authors hope this work can provide a methodological framework for those who wish to expand this approach to other locations or natural hazards.

This research addresses critical gaps in understanding social responses to climate change-attributed flooding in South Louisiana. The project explores who bears the brunt of these impacts, and how governance stakeholders and residents interpret the spatial effects. Employing an interdisciplinary approach, the project integrates climate change attribution, hydrological modeling, environmental justice, and governance, contributing to actionable insights for resilience planning. This research applied a comprehensive approach to investigate climate change-attributed flooding in south Louisiana, addressing three key objectives. The first objective involved conducting climate change attribution models for major flooding events, focusing on Hurricane Ida. This includes estimating the attribution of event intensity and creating maps of storm surge flooding, integrating the latest climate change attribution modeling. The second objective analyzed social factors contributing to spatial inequalities in climate change-attributed flooding, utilizing spatial analysis across diverse geographies. The third objective focused on understanding the perceptions and behaviors of residents and local officials through in-depth interviews, surveys, and iterative workshops. This objective bridges gaps in translating climate change attribution science into actionable policies. 

Today the field of Disaster Science is developing an interest in the relationship of disasters to time, but little research exists that examines the character and impacts of time itself on response to and recovery from disaster. This in-progress study uses critical theorist Moishe Postone's political-economic concepts of "abstract time" and "concrete time" to investigate COVID-19 relief activity as practiced by the DC Mutual Aid Network, the American Red Cross (ARC), and the Federal Emergency Management Agency (FEMA) in Washington, DC. By carrying out and analyzing three focus groups made up of staff and volunteers of these three organizations, this research provides insights into distinct organizational relationships to time and its impacts on recovery. Mutual Aid, the ARC, and FEMA each occupy distinct positions in the social field, with particular relationships to the Federal government, the business environment, and the local community. Mainstream disaster relief organizations, and the emergency managers and other street-level bureaucrats who staff them, from a Postonian view, have their actions compelled by the abstract time that governs the society surrounding them. Mutual Aid groups, with their holistically political understanding of disasters, may disrupt abstract time's compulsions to speed and the generation of profit. In so doing, they may offer alternative schemas for community thriving amid accelerating extreme weather events. This investigation offers a view into organized disaster response that draws out important distinctions between conventional emergency management and alternative community-driven approaches.

The decision to return or relocate after a disaster is often conceptualized as taking rational steps to decrease risk weighed against emotional, social, and economic attachments to a place. This study draws on survey data from northern California households affected by the 2018 Camp Fire to better understand the factors that influenced where people settled after the fire, their satisfaction with that place, and their decision to return. The Camp Fire stands apart from intervening wildfires due to its rapid destruction of nearly 14,000 residences and the ensuing displacement of over 50,000 people. Initial findings aligned with displacement and place attachment scholarship, which note much higher satisfaction among both households which move out of the area and households that opt to rebuild. Interestingly, the authors of this study find that households displaced to nearby communities reported relatively lower quality of life compared to households rebuilt within the fire footprint, and households that had relocated further away. The relative (dis)satisfaction of locally displaced households represents a knowledge gap, as place attachment studies center households that rebuild while displacement studies focus on households that relocate. Survey data from these locally displaced households challenge straightforward narratives of disaster recovery by raising questions about how risk and resources shape household satisfaction and intentions to relocate or rebuild.

In the Netherlands, extratropical storm events in the North Sea can reach wind speeds that exceed the threshold speed that defines a hurricane, last a few days, cover a large area, and accompany large fluctuations in tide (mean tide range is 1.7 miles in Hoek van Holland). These storms, and the amount of area below sea level in the country, are large contributors to the increased flood risk. With climate change increasing precipitation, nature-based solutions to flood protection that are resilient to excessive rain, wind, or waves are often sought to increase stability along earthen infrastructure such as dikes, dunes, and embankments. One climate resilient solution is to design earthen infrastructure with deep-rooted rhizomatic grasses that adapt to dynamic changes in geomorphology and climate. This solution has been widely used in the Netherlands, the United States, and Puerto Rico. Additionally, monitoring and maintenance of earthen infrastructure must consider expanding vegetation monitoring to include properties that were formerly for agricultural purposes only. By utilizing remote sensing, such as Light Detection and Ranging (LiDAR), an unmanned aerial vehicle (UAV) with multispectral lens, and high-resolution satellite multispectral and weather data, various properties of vegetated earthen infrastructure can be assessed. This information can be coupled with in-field measurements and observations to determine the impact of vegetation on infrastructure stability. In this study, investigations from Katwijk in the Netherlands and Mississippi in the United States, were used to understand the use of marram and vetiver grasses in flood protection of earthen infrastructure.

Coastal Communities are experiencing increasing impacts from coastal storms, leading to infrastructure failure, loss of access, and condemnation of structures. For instance, a recent trio of storms impacted the southern New England coast in rapid succession on December 18, 2023, January 10, 2024, and January 13, 2024. These storms came from an unusual south-easterly direction, causing extreme sea states and coastal erosion, with commensurate levels of damage. Municipalities are facing the stark reality that maintaining infrastructure and access to many properties may be infeasible. Addressing these immediate and evolving challenges requires effective communication and engagement with stakeholders, including the development of models and visualizations. This study observes, however, that the most damaging types of erosional impacts are not represented in conventional localized 3D flood visualizations commonly used for planning and coastal public engagement. The authors of this study hypothesize that more sincere representations of hazard impacts such as erosion and shoreline change in context with infrastructure and structures more effectively convey the scale and effects of coastal processes for planning and public engagement. The authors present naturalistic model-driven animated 3D landscape visualizations depicting the effects of storms and sea level rise other than inundation. These visualizations are created using Python scripts to rapidly downscale outputs from models such as X-Beach and depict outcomes in context with fixed infrastructure such as roads, buildings, and vegetation. The authors further discuss preliminary survey work exploring the application and testing of these engaging, dynamic visualizations and describe the next steps.

One of the targets of the Sendai Framework is to substantially increase the availability of and access to multi-hazard early warning systems (MHEWS) by 2030. MHEWS need to be tailored to user needs, have a broad scope of communication channels, and disseminate timely hazard information to affected communities. A key problem for technological applications is attrition—whether people remain engaged and whether people are left out due to language or technology barriers. The authors investigate the usage over time of the MHEWS smartphone app SD-Emergency, developed by the San Diego County Office of Emergency Services and Peraton. By comparing install and uninstall data for Android and iOS, the authors found that the app maintained a retention rate above 50% over the past six years. By comparing app analytics data, the authors found SD-Emergency maintained a retention rate above 50%, significantly higher than single hazard warning apps. MHEWS improves the likelihood people will retain warning capabilities, increasing the efficacy of alerting and maintaining critical communication pathways. However, the SD-Emergency app may not be used by individuals who have limited English proficiency. San Diego County serves a diverse community of over 3.3 million people with a large immigrant and refugee population that speaks varied languages. The authors surveyed residents in multiple languages to find out about their (1) earthquake experiences; (2) hazard warning experiences; (3) familiarity with the SD-Emergency app and how they use the app; (4) barriers to alert comprehension; (5) anticipated responses to EEW; and (6) suggested improvements to better fit their language needs.

In 2016, a catastrophic flood occurred in Lumberton, North Carolina following Hurricane Matthew, and the authors (team of researchers) decided to enter the field to capture ephemeral data on community-level impact, disruption, and initial household dislocation. Eight years and five waves of field-based data collection trips later—and after expanding the scope to capture decision-making and recovery processes following Hurricanes Matthew and Florence and during a pandemic—the team has concluded its data collection. Throughout this research process the team grappled with decisions on how long one needs to return to the same community, after the initial shock, to adequately document its recovery and resilience. The authors learned that this temporal decision is different across sectors and infrastructure types. The study retrospectively assesses what conclusions regarding recovery and resilience the authors may have drawn had they stopped data collection at earlier points in time in comparison to outcomes at the end of the longitudinal field study. The authors will share their insights on how future teams can navigate the decision on whether to continue returning to the field, and the labor, personnel, and professional challenges that come with adding each new data collection wave and changes in research methodology. The authors will end with a discussion on the funding, programmatic, and professional mechanisms that enable or prevent teams from capturing a comprehensive picture of medium- and long-term recovery and resilience. Ultimately, institutional and other barriers limit the advancement of science and the interventions that would arise from a deeper understanding of recovery.

First-hand accounts of disaster survivors’ experiences offer great insights into individual cognitive and behavioral changes that occur upon receiving a disaster warning as well as how their perceptions of social identities and ideologies can shape the cultural behavior of a community in life threatening situations. Previous literature on disaster warnings points out that language inevitably plays a key role in shaping public risk perception. Understanding warning recipient perceptions and responses is even more critical in the context of communicating risks to multilingual communities. This qualitative study uses discourse analysis to examine talks about the role of language in warning compliance by North Americans who currently live in Japan. A group interview revealed the research participants' perception of urgency and other social meanings linked to the call-to-action statements in Japanese and English typhoon and tsunami warnings. Their stories also illustrate their framing of vulnerability, and power within the context of receiving warnings from local authorities and friends. By presenting how sociolinguistic interviews can be used to capture a speech community's cultural knowledge, and ideology, regarding the social act of sending and receiving disaster warnings within the framework of ethnography of communication, this study offers new methodological insights into risk communication research.

The frequency and intensity of floods are expected to increase in Louisiana in the near future as climate change increases heavy rainstorm events in the region’s naturally flat terrain with impermeable soils. The U.S. Federal Emergency Management Agency (FEMA) illustrates the risk of flooding through its 100-year flood zone map. However, recent flood events have occurred outside of this risk zone, limiting the capacity of residents to determine their potential impact. A recent study about flooding during Hurricane Harvey found that the proportion of areas outside the FEMA flood zone that were flooded was in fact higher for minority communities in terms of race, highlighting a potential social disparity in federal assistance in the face of a flood emergency. This study investigated if a similar trend could be observed for the 2016 flood events in Louisiana by determining if social factors associated with race, gender, or income were predictive of the proportion of people inside or outside the FEMA flood zone at two different geographical units (parcels and block groups). This study will help consider social equity in developing local policies for flood mitigation and highlight the importance of improving flood hazard risk mapping.

This study examined the devastating effects of the flood disaster and its implication on displacement and public health in Kano Metropolis. The research questions and objectives of the study were to determine the major causes of incessant flooding, the effects of flooding on public health, and the possible ways of preventing, mitigating, and recovering from the flooding disaster in the area. Data was collected from 385 respondents using questionnaires as the primary tool for data collection using multi-stage sampling methods, comprising cluster and purposive sampling. The author presented the data using tables, frequencies, percentages, and charts, and the findings showed that the major cause of incessant flooding in Kano Metropolis was excessive rainfall attributed to changing weather conditions. Further, poor drainage systems, poor housing, and poor urban planning were other major causes of flooding in the area. Results also indicated that flooding has led to many deaths, the destruction of properties, and internal displacement in Kano Metropolis. Finally, results showed that graves and dead bodies were washed away as a result of flooding, resulting in contamination of water sources, pollution, and the outbreak of water-borne disease in the area. Based on these findings, it is recommended that government at all levels should  commit to addressing the threats of climate change and proper housing and town planning in Kano Metropolis. This study serves as a guide to governments and policymakers on disaster response and mitigation in Kano State.

The U.S. National Weather Service disseminates flood forecasts and warnings to communities across the United States who are increasingly facing flood hazards. Within the past decade, instructional risk communication has begun to intersect with public warning messages. Instructional warning messages can act as a type of risk narrative that assists in making sense of the crisis and how to prepare for it. Yet, the authors do not have sufficient evidence of how flood warning information is received, perceived, interpreted, or spread within local community organizations that are critical before, during, and after flooding events. Therefore, this research project uses social science methods to evaluate how flood warning messages are constructed and communicated along information sharing pathways. The primary goal of the study is to answer the following research questions: How do local stakeholders receive and share flood information? How are current information sharing pathways applicable to flood systems now and in the future? To answer these questions, focus groups will be conducted that are comprised of local authorities (e.g., public transportation, public works), health and human services providers (e.g., shelters, hospitals), and community stakeholder organizations (e.g., large employers, faith-based organizations). The results will be analyzed using the internalization-distribution-explanation-action (IDEA) model of strategic communication during crises. Such results will garner practical recommendations for National Oceanic and Atmospheric Administration and other flood practitioners in more effectively creating, modifying, and sharing flood information along appropriate pathways to produce more effective outcomes.

Gender consideration is a profound factor in responding to severe living conditions. This study explores the differences between women and men’s perceptions of post-disaster living conditions. The research area in this study is the Kirime area of Inami Town, Wakayama, Japan. To illustrate the relationship between residents' anxiety about living conditions in the early recovery phase and demand for measures to respond to the problems, a questionnaire survey was conducted on residents in the research area between September 12 and October 17, 2022. In the analyses, after individual question items were measured, exploratory factor analyses for both the anxiety and demand variables are performed to extract the factors on respondents' perceptions. Subsequently, constructs are composed by confirmatory factor analyses. Based on these results, the relationships between the constructs of the anxiety and demand variables in the attributes of women and men are analyzed using multiple-sample structural equation modeling. This study identified seven factors of living space problems (physical health, mental stress, changes of daily life, living problems caused by facility damage, maintaining privacy, and cooperation within the area contributing to anxiety), and five factors of support for medical and health care activities (consideration for women, common space management, responding to individual needs, and community disaster response activities in demand). Results indicated that factors of the perception of post-disaster living conditions in women are mental stress, changes of daily life, and living problems caused by facility damage. In contrast, the main factor in men is observed to be physical health.

While research investigates how disasters impact individual mental health in the United States, little is known about the cumulative impacts of disasters on communities, particularly on older adults. This research examines the depressive health outcomes of older adults who are continually exposed to disasters. In a way, it extends a temporal approach to conceptualize disasters as cumulative events, going beyond the effects of single large-scale incidents. The authors of this study created an annual panel dataset by linking three longitudinal datasets on disaster (Spatial Hazards and Events Losses Database for the United States, SHELDUS), health (Reasons for Geographic and Racial Differences in Stroke, REGARDS), and socioeconomic characteristics (Retail Environment and Cardiovascular Disease, RECVD). A three-tiered typology variable ranging from minor to severe months was employed to gauge the monthly disaster effects for each county in the US from years 2003-2007. Multivariable logistic regression models were used to determine the association (expressed as odds ratios and 95% confidence interval) between depressive symptoms and disaster events. Models were adjusted for demographic characteristics (age, race, gender, education level, annual income, and region of residence). In disaster research, there is a scarcity of comprehensive multilevel data assessing health-related social determinants. This study was done to address this crucial gap through its research efforts.

Cities are increasingly alarmed by escalating extreme heat risks, particularly as urban populations concentrate in areas that function as heat islands and the frequency, intensity, and duration of heatwaves increase with climate change. Compounding these concerns is the unequal distribution of heat exposure and impacts within cities. Certain neighborhoods consistently experience higher temperatures, disproportionately affecting vulnerable groups such as low-income, older adults, and minority populations. The city of Phoenix, Arizona, epitomizes these challenges. The rapidly growing city recorded 31 consecutive days over 110°F (43.3°C) in 2023 and a record number of heat-related deaths. In response, Phoenix established the first publicly funded city office specifically tasked with comprehensively addressing heat and is investing in various strategies to manage heat and mitigate it in the built environment. Green infrastructure, broadly defined as networks of vegetated areas ranging from individual street trees to bioswales and parks, is a key focus for Phoenix, and it is the most commonly identified strategy for addressing heat in cities across the United States. This study combined plan and policy document analyses, interviews with key decision-makers, and participant observation to conduct an in-depth case study of emerging heat and green infrastructure governance institutions and processes in Phoenix, Arizona. This research helped to fill a gap in current knowledge because while many studies have highlighted the need to proactively mitigate heat and manage its impacts or examined the potential for green infrastructure to support these efforts, limited research examines the governance structures and processes.

This study involves an intersectional, multi-level analysis of Mexican-origin women and their disproportionate vulnerability in post-disaster recovery. Specifically, this study explores how the racialization of Mexican-origin women in the U.S. impacts their long-term housing recovery in the context of cumulative disaster impacts. In the weeks, months, and years following Hurricane Harvey in 2017, which dropped an unprecedented amount of rainfall in Houston, Texas, the 56 Mexican-origin women that the author interviewed embarked on a long and tedious journey of recovery. While some women fared better than others in the months following Harvey, many more women–regardless of housing tenure, immigrant generation, and documentation status–faced significant delays in their ability to fully repair their homes, recover from the loss of income during and after the storm, and improve their mental health. Even women who were on track to finish repairs on their home and catch up with payments on repairs, delayed rent, and acquiring new personal property faced further setbacks due to subsequent disasters in the four and a half years after Harvey. For this session, the author plan to present the three stages of the long-term recovery trajectories of Mexican-origin women.

Over the past two years, the Marshall Fire Recovery and Resilience Working Group has collected perishable mixed methods data to understand policy processes and decisions as well as individual disaster impacts and recovery trajectories after Colorado's most destructive wildfire. A key interest is how commitment to policies that support equity and climate resilience change over time and across fire impact groups within the affected communities. Over 3 rounds of household survey data collection (roughly 6-, 12-, and 24-months post-fire), respondents answered questions about their home and fire impacts, rebuilding and relocation decisions, policy positions, and demographics. By combining this longitudinal survey data with publicly available building permit and residential sale data, the authors applied multivariate regression models of quantitative data and thematic analysis of text responses to answer the following research questions: (1) How does individual support for land-use regulations that mitigate disaster risk and build climate resiliency—namely building codes, wildland-urban interface codes, and energy efficiency codes—change over time? To what extent does that support vary between highly impacted individuals and the broader public? (2) In jurisdictions where Marshall Fire victims were exempt from the most stringent land-use regulations, what factors have influenced the voluntary implementation of these codes in residents' rebuilding decisions? What role have incentives and rebates played in shaping rebuilding outcomes, and how do rebuilding outcomes vary across social groups?

A recent investigation into Hurricanes Katrina and Rita revealed distinct differences in the evacuation decision-making process among older adults compared to other age groups. Notably, older adults exhibited a tendency not only to disregard official weather warnings compared to their younger counterparts, but also demonstrated a unique pattern in processing risk information. In response to these findings, this study introduced an experience-driven risk-coping model, suggesting a learning process in risk-coping that evolves with experience, coupled with different mental patterns simulating the responses to a threat exceeding the depth of one's coping capacity. Despite the model's potential, it has not yet been examined in other hurricane or hazard contexts. This study addresses this gap by examining the model's validity in the context of Hurricane Ian, which, like Hurricanes Rita and Katrina, experienced a late track change. To test the model, data were drawn from 221 households in the false alert area (Hillsborough County) and 299 households in the late warning area (Lee County). Specifically, this investigation scrutinized how older adults process risk information compared to other age groups, serving to validate the previously proposed risk-coping model. Subsequently, the study enhanced understanding of the cognitive processes employed by older adults in evaluating emergency warning messages. The study determined their perceived levels of risk, and further assessed other information-seeking processes and behaviors employed in deciding whether to evacuate or remain in their residences or perceived places of protection during an impending event.

In recent years, Houston has faced a series of devastating disasters, including Hurricane Harvey, COVID-19, Winter Storm Uri, and recurrent flooding events, each leaving a lasting impact on the city. These disasters, while pervasive, disproportionately affect low-income populations. Despite public housing's mission to provide secure housing, little attention has been given to the experiences of residents during these crises. This research seeks to address this gap by identifying the unmet needs of Houston public housing residents during Hurricane Harvey, COVID-19, and Winter Storm Uri. Objectives include assessing residents' agency in disaster planning, identifying unaddressed needs, and proposing support strategies. Collaborating with the Houston Housing Authority, face-to-face interviews with key informants, including Resident Councils, were conducted. The study aims to highlight and disseminate insights from residents navigating multiple disasters, informing policies and practices throughout all phases of disaster management to better support public housing communities.

Flooding of rural, low-income communities is increasing across the United States as storms intensify and weather patterns change. In communities experiencing repeated back-to-back flooding, residents who have lived in these areas for several generations have been impacted. Voluntary buyouts of these properties are often offered as a solution, but it is unclear whether this solution benefits the residents and the community. Therefore, this research asked how voluntary buyout programs could be improved to meet the needs of rural communities. This research identified some of the intended and unintended consequences of the voluntary buyout programs conducted in two low-income, underserved communities of Bennettsville, South Carolina and Tarboro, North Carolina. Both communities experienced compound flooding (e.g., rain and riverine flooding). Results from interviews conducted with public officials and community leaders in Bennettsville and Tarboro during summer 2023 revealed the fiscal and community impacts of buyouts, residents' connection to place, and systemic barriers affected a resident's decision to participate in a voluntary buyout. Findings also reflected similarities and differences across the study areas regarding resident experiences and the buyout processes. In Bennettsville, South Carolina there was concern for a lack of alternative, comparable housing. In Tarboro, North Carolina there was concern for loss of community cohesion. However, there was acknowledgement of risk reduction through buyouts in both study areas. The results of this study are intended to understand and guide future buyout program implementation across the Carolinas and the United States.

This presentation examines a coordinated disaster response through the innovative approach of creating a nonprofit organization to lead that process. The 9/11 United Services Group (USG) was formed by thirteen nonprofit organizations providing relief and recovery after the September 11, 2001, attack in New York City. The USG created a space for collaboration between large nonprofits like the Red Cross, Salvation Army, and Catholic Charities with smaller organizations that worked with specific communities like the Asian American Federation. This presentation centers on the specifics of operations, outlining the formation and development of the USG as well as the internal and external challenges to collaboration among nonprofit organizations engaged in disaster recovery. The USG provides an example of how to leverage multiple organizations in the response phase. With the intensity of natural hazards increasing, nonprofits are well served to learn from this example to have greater impact in their response. This research employed traditional historical methodologies, including critical analysis of sources and source triangulation to better understand the dynamic interaction of historical actors and organizations. Sources included the 24 boxes and 4600 electronic files deposited by the USG at the New York Public Library, as well as documents from the Red Cross and 50 oral histories conducted by the author and the Columbia Oral History Project. 

New emergency response tools and approaches are emerging that can help emergency response personnel respond quicker and more efficiently to crisis situations. These tools can incorporate various aspects of artificial intelligence (AI) to dispatch first responders based on severity and urgency, determine search areas in search and rescue efforts, and consolidate data in real-time to decide the safest evacuation routes. While the incorporation of AI in emergency response can inform decision-making, there are concerns regarding the accuracy, fairness, and risk of using such tools in a life-and-death situation. To address this concern, the authors surveyed 1,000 adults in the United States to determine their perceptions of the risks and benefits of incorporating AI in common crisis scenarios. The authors also asked which AI tools and scenarios they would support financially through tax increases. The authors recruited the participants using a stratified quota sampling approach to ensure that the sample was representative of the state's population based on gender, age, race, ethnicity, and political affiliation. Quotas were determined (and stratified by region of the state) based on data from the U.S. Census Bureau and Florida's Office of Economic and Demographic Research. Based on these results, the authors constructed recommendations for local emergency response agencies to implement AI within their local crisis and emergency response systems.

The animal farming communities in the Fraser Valley were devastated by the 2021 Pacific Northwest floods. These communities, as well as public, private, and not-for-profit sectors, were engaged in the evacuation. This project employs a phenomenological approach by examining these cross-sectoral, multi-stakeholder engagements in evacuation decision-making to identify promising practices and areas for improvement. Through qualitative interviews of animal farm owners, this project discovered that during the decision-making stage of the disaster evacuation (1) at the micro-level, the animal farmers' long-term engagement with their natural, built, and social environments enabled them to develop the initiatives for evacuation strategies, but they lacked resources and equipment to facilitate their evacuation; (2) at the mezzo-level, community-based service and professional organizations were equipped with specific knowledge, skills, and services to support the animal farmers' evacuation, but they lacked the capacity for large-scale coordination; and (3) at the macro-level, the governmental emergency responders could swiftly coordinate different resources to support the evacuation in Fraser Valley, but did not comprehensively understand the animal farming communities' characteristics. These three-level challenges were solved through community-based rapid response meetings, where the micro- (grassroots), mezzo- (community-based agencies), and macro-level stakeholders collaboratively shared their strengths and weaknesses to develop a community-driven evacuation plan. This micro-, mezzo-, and macro-level cross-sectoral collaboration shed light on an innovative approach for effective emergency decision-making, facilitating a two-way communication approach, so that community-based individual and collective expertise could be engaged in governmental emergency response efforts to enhance grassroots coping capacity

The concept of plan quality, which is defined by pre-established criteria, guides the assessment of plan documents. Environmental planners and scholars widely employ evaluation techniques for hazard mitigation and climate change resilience plans. However, as more plans are developed by private consultants, questions arise regarding the extent to which consultants' plans differ from those developed by county planners. To what extent do consultant-led plans include policies concerning public engagement, land use, property protection, and plan integration? What kind of consulting firms are most likely to produce good quality plans? Our study analyzes a sample of 100 county hazard mitigation plans in six states across the United States, using established plan evaluation coding. Our design accounts for variations in state mandates, planning contexts, and regional consultant availability. The baseline linear regression models indicate that there is a significant impact by consultants on plan quality. Consultants' involvement in plan development is directly associated with better plan quality, especially on plan integration and property protection policies. Subsequently, our hierarchical linear models encompassing consulting firms' organizational characteristics hint that higher plan quality is positively associated with the size of consulting firms and the services they provide. Findings imply that planning consultants are crucial to improving plan quality, and good quality plans make the first step in producing positive policy outcomes. We offer insights for understaffed communities to consider when outsourcing their planning services under the prevailing Hollow State era.

Non-synoptic wind events, including thunderstorms, downbursts, and tornados, account for most weather-related fatalities in the United States and cost billions of dollars in property damage each year. Despite advancements in incorporating non-synoptic winds into wind design codes and standards, there remains a significant gap in understanding the near-surface wind characteristics of these events. However, with the advent of smartphones, video monitoring systems, and remote sensing technologies, a wealth of media now exists that capture the real-time dynamics of non-synoptic storms, including the motion of wind-borne debris, which could be a useful source of data. This study aimed to establish a framework to infer near-surface wind characteristics from debris speed and other debris attributes in public-shared videos and other media. The framework involved three key steps: (1) accurate extraction of debris trajectories from videos in 2D or 3D space as a function of time using computer vision techniques, (2) estimation of debris attributes relevant to debris-flight motion (e.g., mass, area, aerodynamic coefficients) from the video, and (3) application of equations of motion to (1) and (2) to infer background wind flow characteristics. This study focused on applying the framework to unstructured debris-flight media (public-shared videos) and structured debris flight media from controlled experiment at the National Home Education Research Institute (NHERI) Wall of Wind shared-use facility at Florida International University. Overall, this study shows the possibility to enhance our understanding of near-surface wind and debris characteristics using wind-borne debris trajectory extracted from publicly available debris flight media.

Despite the importance of U.S. agricultural production to national and global food security, relatively little is known about the disaster resilience of individual farms and agricultural rural communities. Resilience is a complex function of socio-economic dimensions and the built environment; and the population, economics, and physical infrastructure that comprise agricultural regions are distinct from the urban and suburban areas. There is a critical need to understand the complexities and key factors that contribute to agricultural disaster resilience. This research offers an overview and preliminary results from an ongoing project that aims to address this need, in part, by studying the vulnerability and recovery of farms following windstorms. The research team employed field and digital reconnaissance, web-based surveys, and interviews to assess the immediate impacts and recovery of farms following the 2020 Iowa Derecho, the 2022 Nebraska Windstorms, and the 2023 Hurricane Idalia. The study reveals the high vulnerability of physical infrastructure supporting agriculture to windstorms, identifying key structural variables predicting performance. Notably, the vulnerability of center pivot irrigation systems increases with length and initial orientation. Furthermore, farm recovery is a lengthy process and the majority of surveyed farms do not indicate that they have fully recovered two years after the storm. Among various factors influencing recovery, the shortage of builders emerged as the most frequently cited impediment. Future endeavors will aim to inform decision-making for enhancing resilience in farms and agricultural communities.

Concerns are rising that the earth system may reach some critical tipping points in the coming decades. Though, growing evidence also supports the potential of positive social tipping points that could propel transformative changes towards global sustainability. This study proposed a systematic model on unique cases of flood resilience, which demonstrated a positive perspective over various spatial and temporal scales. The study focused on the historical Tea Horse Road area (THR), a mountainous region of the Southeast Tibetan Plateau with a well-documented history going back over 600 years. The study first set up a theoretical framework on the multi-spatial-temporal features of flood resilience at the THR region, covering the spatial differences (household, community, city, and region) over the past 600 years regarding the governance, technology, society, and culture perspectives of flood resilience. The study integrated quantitative proxy data, historical archives, literature re-analysis, statistical data, observation data and field survey data in the empirical study in the case areas and the agent-based modelling across the cases. The study aimed to further establish an understanding of the spatial-temporal scales of flood resilience and model the spatial-temporal dynamics of flood resilience using agent-based models. Preliminary results indicated that various strong and smart social regulations (governance, institutions, plans, management, motivations, orders, donations, dedication, etc.) enabled a wise development of many water conservancy projects that consequently enhanced the resilience of local communities to hydrological hazards.

By the end of the century, an estimated 2.4 million residential and commercial properties are at risk of frequent flooding. The effectiveness of the Federal Emergency Management Agency’s (FEMA) efforts in delineating Special Flood Hazard Areas (SFHAs), overseeing new constructions, and enforcing flood insurance mandates is still uncertain. This study leveraged urban analytics and causal inference methods to assess the precision of SFHAs in identifying buildings prone to flooding and to examine the state and quality of structures within and beyond these zones. Utilizing a novel database of over 100,000 buildings in flood-prone areas of Houston, Texas, this research found that 56% of structures at risk are located outside SFHAs, with a higher incidence in Black and Hispanic communities. The analysis showed that properties outside FEMA-designated zones tended to be in poorer condition, less well-maintained, and often uninsured. Although SFHA policies can reduce vulnerability, the current limitations in flood mapping may increase neighborhood disparities. The results highlight a gap in understanding how various vulnerabilities interact, showing that communities at social risk also face significant structural and financial challenges. In conclusion, this study suggests that urban analytics advancements could help improve current flood risk assessments and aid in more effective planning for future flood events

Evaluating coping strategies for community resilience planning in the context of extreme events, such as climate and weather shocks, is challenging, due to unclear system understanding, varied community priorities, resource disparities, and inherent uncertainties. Traditional resilience planning methods, often based on economic assessments, like benefit-cost analysis, focus mainly on monetary assessment, neglecting or downplaying non-monetary considerations. Recognizing these limitations, there is a growing emphasis on transdisciplinary approaches for operationalizing community-based resilience planning that prioritizes local community values and preferences that fall outside solely budgetary issues. The authors introduce a modeling framework for the evaluation of resilience planning alternatives that considers community-identified values, benefits from harnessing community wisdom, addresses uncertainty challenges, and considers the trade-offs between monetary and non-monetary criteria. The authors’ process integrates the qualitative insights of Fuzzy Cognitive Mapping (FCM) with the quantitative rigor of Benefit-Cost Analysis (BCA). This integration helps planners effectively navigate complex social-ecological systems. The study proposes the use of two accessible online tools: Mental Modeler for FCM and Economic Decision Guide Software (EDGe$) for BCA, which enhances the model's usability and effectiveness. To demonstrate the framework's real-world applicability, the authors present two proof-of-concept examples focusing on resilience planning for the food system in Flint, Michigan. These cases address resilience in the face of extreme weather events and pandemic scenarios, like COVID-19. The examples underscore the model's adaptability and relevance in real-world settings, offering valuable insights into its potential for facilitating community-driven, informed, and equitable resilience planning across diverse social-ecological systems.