Poster Session Abstracts

The Federal Emergency Management Agency's (FEMA) Public Assistance (PA) program provides essential financial support to state and local governments for repairing public infrastructure damaged by federally declared disasters. To encourage long-term financial responsibility, the program enforces an “Obtain and Maintain” (O&M) requirement, mandating that recipients purchase insurance coverage equal to the amount of prior eligible damage for assets such as public buildings and equipment. However, this retrospective design fails to reflect actual future risk, potentially leaving communities underinsured and increasing federal liability. This poster describes a study addressing these limitations by evaluating alternative policy frameworks through a simulation model applied to a case study of flood risk in Fargo, North Dakota. The analysis compares the current O&M policy against two risk-based alternatives: a fully private insurance model and a Public-Private Partnership (PPP). Using Monte Carlo simulations to estimate losses over a 30-year period, the study calculated the net loss shares for FEMA, local governments, and insurers. Results indicate that while shifting to a fully private risk-based model significantly reduces FEMA's expenditures, it drastically increases costs for local governments, potentially exceeding their fiscal capacity. Conversely, the PPP model (incorporating premium caps and federal reinsurance) offers a balanced solution. This approach reduces the federal burden compared to the current system while preserving affordability for local communities, suggesting that risk-based PPPs can better align incentives for resilience without overburdening local budgets.

Despite the rapid expansion of electric vehicle (EV) adoption, the increasing intensity and frequency of climate-related events, such as flooding and hurricanes, pose significant challenges for EV owners and infrastructure. During and after extreme events, EVs increasingly play a crucial role in supporting evacuation efforts and in accessing emergency services. Strengthening the resilience of its charging network is an essential component of minimizing disruptions and accelerating post-disaster recovery. However, should EV charging stations (EVCSs) become unavailable—whether due to station and facility damage, power outages, or flooded roads—usage patterns may be significantly affected, and recovery stymied. This poster describes a study establishing a comprehensive framework by defining metrics to compare EVCS usage patterns, applying machine learning to categorize variation circumstances, and identifying optimal EVCS locations to enhance network resilience and access during disasters. We applied this fr

This poster describes a study investigating whether housing conditions can serve as predictors of disaster-related protective behaviors. Specifically, it addressed the research question: Can housing conditions be used to predict individuals' preparedness for disasters? A quantitative research design was employed, utilizing a structured questionnaire administered to 909 participants across North, Central, and South Florida. The survey instrument was developed through a comprehensive review of existing literature and was carefully aligned with the study's research objectives. To ensure content and face validity, the questionnaire was reviewed by five scholars from diverse disciplinary backgrounds. The survey focused on two key preparedness behaviors: (a) developing an emergency communication plan, and, (b) assembling an emergency supply kit. In addition, seven behavioral constructs were examined: risk possibility, risk severity, subjective norms, personal responsibility, perceived behavioral control, outcome

Coastal Oregon communities face significant risks from a Cascadia Subduction Zone (CSZ) earthquake and tsunami; however, hazard preparedness resources do not serve all residents equitably. Predominantly Spanish-speaking immigrant residents face significant barriers to disaster preparedness due to limited availability of culturally and linguistically appropriate hazard information. CSZ hazard awareness and preparedness materials have been developed for residents and visitors who have one or more of the following qualities: high English proficiency, homeownership, financial resources, and physically mobility. This poster describes a research project evaluating existing CSZ preparedness resources from federal, state, and local governmental agencies. Using a content analysis approach, a structured scorecard was used to evaluate each resource across eight categories: (a) Material Characteristics, (b) Readability and Literacy Demand, (c) Graphics, (d) Cultural Appropriateness, (e) Layout and Typography, (f) Dissemination, (g) Content, and (h) Learning Stimulation and Motivation. These categories, taken from the risk communication literature and modified for this study with community partners, were used to evaluate each hazard resource, with total scores determining overall appropriateness for underrepresented populations and quality. Together, both the scorecard and rating of each resource can provide clear recommendations to emergency managers, community partners, educators, and other interested parties to advance more equitable hazard communication and preparedness for predominantly Spanish-speaking immigrant communities. 

Extended power outages following hurricanes can severely impact community well-being, particularly among vulnerable populations such as the elderly and individuals with medical conditions. While previous studies have investigated disparities in outage recovery, many focus on single events and rely on general social vulnerability indices, limiting their ability to identify consistent patterns or capture the specific factors that heighten vulnerability to power disruptions. Moreover, few studies have examined the influence of economic activity or the presence of critical facilities on recovery times. This study analyzes power outage recovery trajectories across 27 U.S. states affected by 21 hurricanes between 2017 and 2024. Using spatial regression analysis, we assess whether counties’ socioeconomic vulnerability, levels of economic activity, and the number of critical facilities consistently explain differences in post-hurricane power outage recovery times. A customized Social Vulnerability Index (SVI) was used to more accurately capture population vulnerability to power disruptions. Results indicate that the SVI does not have a consistent effect on recovery times, suggesting no systematic disparities based solely on socioeconomic characteristics. However, when considered independently, median income is negatively correlated with recovery time, although the effect varies with outage severity and the extent to which other factors are controlled for. Higher economic activity (measured by GDP per capita) is associated with longer recovery, although this relationship is also dependent on the severity of outage and whether other variables are included in the model. The number of critical facilities does not show a consistent standalone effect once other county characteristics are accounted for.

Household reactions are a critical yet understudied mechanism linking disaster exposure to recovery service use. This poster describes a study advancing hazards and disaster research by demonstrating that household-level reactions partially mediate the relationship between disaster-related risk exposure and service referrals following natural disasters, shifting attention from individual outcomes to household recovery processes. Using a large national dataset of household disaster encounters in the United States, we tested a structured mediation model in which disaster-related risk exposure served as the predictor, household event reactions (behavioral, emotional, physical, and cognitive) functioned as the mediator, and referral to services was the outcome. Analyses included univariate, control-only, and multivariate models stratified by disaster type (wildfires, hurricanes, and storms or floods) and by state (California, Colorado, Louisiana, Missouri, New Jersey, and Tennessee), with adjustment for demographic and contextual factors. All hypothesized pathways were supported. Greater disaster-related risk significantly predicted stronger household reactions, which in turn predicted a higher likelihood of service referral. The total effect of risk on referrals remained significant but was reduced when household reactions were included, indicating partial mediation. Disaster-related unemployment, witnessing death or injury, and separation from social networks were the strongest risk factors. Behavioral reactions were the most consistent predictor of referrals, with effects strongest for wildfires and hurricanes. These findings underscore the importance of incorporating household-level reactions, behavioral indicators, and localized hazard contexts into disaster recovery planning.

During landslide emergencies and following consequential landslide events, U.S. Geological Survey (USGS) landslide scientists have long worked with partner agencies to provide scientifically grounded information on what happened, possible causes, and what might happen next. In 2023, this capacity was formalized through the establishment of the "Landslide Assessments, Situational awareness, and Event Response research" (LASER) team. The formation of LASER has resulted in a dedicated cadre of scientists within the USGS with both field and remote capabilities and establishes a framework for rapidly providing information to government agencies, emergency managers, the media, and the public. The LASER team also conducts research and development to improve methods for rapidly detecting, mapping, monitoring, communicating, and characterizing landslides during future responses. This poster summarizes the LASER framework and illustrates a variety of products and capabilities under development using examples from several recent LASER responses, from region-wide landsliding triggered by Hurricanes Helene and Melissa to localized rapid assessments of tsunami-generating landslides in Alaska.

This poster describes a project providing the first large-scale, rigorous test of whether the Firewise USA® program produces measurable reductions in wildfire fuels and, when wildfire occurs, also reduces damage to structures and communities. The results will directly inform how federal and state agencies design and allocate support for community-led wildfire adaptation. Firewise USA is the primary national program supporting collective action for wildfire risk reduction. Launched in 2002, the program encourages neighborhoods to self-organize, create risk reduction plans, and carry out vegetation management activities each year. Nearly 3,000 communities have enrolled, but three key empirical questions remain unresolved: (a) whether participation leads to detectable changes in vegetation management, (b) whether those changes reduce losses when wildfire materializes, and (c) whether the program works broadly or primarily in communities with strong preexisting civic capacity. We address these questions using satellite imagery from the Landsat program, which provides consistent measurements from 2000 onward at 30-meter resolution. We track fuel management indicators, including fine-fuel reduction, canopy thinning, and spatial patchiness of vegetation, across all Firewise communities over two decades. We estimate program effects by comparing communities before and after enrollment to communities that enroll later. We link communities to fire perimeter and damage inspection records to test whether collective vegetation management translates into reduced losses. We also examine heterogeneity in program effectiveness across communities with varying levels of social capital and civic organization.

Many post-disaster recovery indicators are reported without the benchmarks needed to judge whether recovery is adequate, lagging, or on track, limiting their usefulness for needs assessments and program decisions. We conducted a scoping review of peer-reviewed studies published between 2007 and 2025 to document how housing-relevant recovery indicators are benchmarked and what reference points are available for interpreting recovery levels and timelines. Across 58 studies spanning 16 country contexts, we extracted 293 unique indicators and coded 340 study-indicator entries for the presence and type of an explicit benchmark, defined as a threshold, target, or comparison value. Only 42.9 percent of entries reported an explicit benchmark, indicating that much of the academic measurement record remains descriptive rather than decision ready. When benchmarks were provided, they were primarily event-specific empirical patterns such as rebuilding timelines and return-rate trajectories; operational thresholds were less common at 16.4 percent, and program planning targets were rare at 3.4 percent. We found no prescriptive benchmarks specifying what timely or equitable housing recovery should look like. Benchmark coverage was highest for housing and shelter indicators at 61.6 percent and quantitative studies at 63.9 percent, but substantially lower for sub-dimensions such as housing quality, equitable access to rebuilding resources, and displacement duration, where practitioners still need interpretable thresholds to prioritize assistance and evaluate progress. The poster presents a typology of benchmark reference points, identifies priority gaps for tool builders, and proposes benchmark metadata schema and minimum reporting standards to improve interpretability and equity sensitivity in future housing recovery assessment.

Cultural heritage encompasses both tangible and intangible elements, including irreplaceable historic value and the significance of place attachment. However, with the exacerbating impact of climate change-induced and other disasters, cultural heritage is under threat. Unfortunately, hazard mitigation planning often prioritizes critical infrastructure while treating historic preservation as a secondary, resource-intensive concern. This poster describes a systematic literature review synthesizing evidence to demonstrate why urban planners must prioritize the integration of cultural heritage into disaster risk reduction strategies. It identifies critical themes, including vulnerability assessment, policy gaps, and resilience-building strategies. Heritage assets function as critical social infrastructure, enhancing community resilience through traditional knowledge and social cohesion. The review exposes significant institutional and systemic barriers, ranging from regulatory fragmentation (macro-level) to attitudinal resistance (micro-level), that hinder the inclusion of heritage in mainstream hazard planning. Findings indicate that while technological tools such as GIS are invaluable for mapping vulnerability, their effectiveness is limited by gaps in policy and interagency coordination. Furthermore, the research evaluates emerging methodologies for vulnerability assessment, emphasizing the shift toward multi-criteria frameworks. The study concludes that planners must adopt a systems-thinking approach, recognizing heritage not merely as a vulnerable artifact but as a vital driver of proactive disaster recovery and adaptation, ultimately aiding the preservation of both tangible and intangible heritage.

The increasing frequency and intensity of natural disasters in the United States make it difficult to establish disaster-resilient, interdependent critical infrastructure. As a result, disaster managers and decision-makers are seeking timelier, location-based, and representative data sources to rapidly understand disaster impacts and plan for recovery, particularly in densely populated urban areas. Near-real-time, location-specific information remains a persistent gap in disaster response and recovery, especially for interdependent urban infrastructure systems. This poster describes a study proposing to demonstrate how proxies, such as 311 call data, can serve as timely, spatially resolved indicators of post-disaster conditions, such as sewerage disruptions, before typical damage assessments are available. We analyzed 311 service request records from two major Louisiana parishes, Orleans and East Baton Rouge, to characterize short-term, community-reported sewerage issues following natural disasters. The datasets were filtered using disaster- and sewerage-related keywords and partitioned into disaster and non-disaster periods. We then tested whether sewerage-related reporting differed significantly in frequency and spatial distribution between these periods. Results showed that sewerage-related 311 reports increased significantly during disaster periods in areas of higher estimated damage and distinct demographic characteristics. These findings highlight the vulnerability of urban sewerage infrastructure to disaster impacts. Additionally, it demonstrates the value of 311 call data for supporting earlier situational awareness, faster prioritization of response actions, and more effective engagement with residents during recovery.

This poster describes a study analyzing the group dynamics of disaster volunteer activities over the past 30 years, from the 1995 Great Hanshin-Awaji Earthquake, which was called the “first year of disaster volunteers,” to the 2024 Noto Peninsula Earthquake. We have conducted collaborative practices and action research in many disasters in Japan, including the 2004 Niigata Chuetsu Earthquake and the 2011 Great East Japan Earthquake and Tsunami, over the past three decades. It was revealed that the group dynamics of disaster volunteers for 30 years could be conceptualized as the conflict between two intricately intertwined social drives: social drive for order and social drive for unstructured as the former gradually surpassed the latter. We attempted to theorize these group dynamics in the context of other international research findings on disaster volunteers (i.e., Delaware model). We concluded that the social drive for unstructured should be emphasized rather than order in future disasters for which th

Hurricane Helene triggered an extensive landslide disaster across the southern Appalachian Mountains between September 25 and 27, 2024, the effects of which remain visible more than a year after the storm. Prolonged rainfall and high winds led to widespread slope failures, debris flows, flooding, and tree blowdown across western North Carolina, eastern Tennessee, and southwestern Virginia. These effects damaged transportation networks, homes, and other critical infrastructure, and complicated emergency response and recovery. During and immediately following the event, the U.S. Geological Survey (USGS), in coordination with state, federal, and local partners, mobilized the landslide response team (LASER) to support situational awareness and decision-making. Event-specific landslide hazard models, developed with NASA and the National Weather Service, were used to identify areas of likely landslide concentration. Aerial reconnaissance, remote sensing, and field investigations confirmed extensive landsliding along the Blue Ridge Mountains, where spatial clustering strongly influenced access, isolation, and response priorities. A multi-institution effort involving more than 30 scientists documented nearly 2,000 landslides in a public, live-updating mapping platform, over half of which affected infrastructure or stream channels. These data provided identification of high-consequence locations, technical assistance to partners, and safety messaging for responders and communities. This poster summarizes the information and support that was provided by the USGS during and after Hurricane Helene. We invite emergency managers and practitioners to share what products or communication were useful, what could be improved, and what information or tools are most critical during response and recovery.

This poster describes a study contributing to hazards and disaster research by demonstrating how climate displacement reshaped health through the combined effects of environmental stress, gender norms, and post-relocation social change. It investigated the socio-climatic determinants of health-seeking behavior among climate-displaced residents of the Khurushkul Ashrayan Project (KAP), Bangladesh's largest planned relocation project for populations affected by sea level rise, salinity intrusion, and recurrent flooding. The study used a mixed-methods design: A survey collected quantitative data from 250 randomly selected households; meanwhile qualitative data was collected through three focus groups and five key informant interviews with health officials, local administrators, and community representatives. Results showed significant barriers to health care access, including cost, distance, and gendered dependency, with women using health services at significantly lower rates than men (chi-square = 159.46, p < 0.001). Logistic regression analysis indicated that gender (odds ratio [OR] = 0.11, p < 0.001), age (OR = 0.19, p < 0.05), and recent climate events (OR = 0.31, p < 0.01) significantly influenced their health-seeking behavior. Qualitative findings supported statistical patterns, highlighting mobility constraints for women, reliance on male guardians during extreme weather, and weakened social cohesion in multi-storied resettlement housing. While relocation reduced direct hazard exposure, social fragmentation and limited-service readiness generated new health risks. The findings suggest that community-level health system reforms are necessary to ensure equitable outcomes for climate-displaced populations. The poster provides actionable guidance for policymakers, planners, and humanitarian practitioners working in climate adaptation and disaster risk reduction contexts.

Chronic health risks linked to housing and environmental exposure represent a slow-moving disaster in many U.S. cities. In Jacksonville, residents of Health Zone 1, which encompasses predominantly low-income and African American communities shaped by redlining and disinvestment, experience severe respiratory health burdens alongside aging housing stock and limited public intervention. Poor ventilation, mold, pests, indoor smoking, overcrowding, and proximity to pollution contribute to elevated indoor and outdoor PM2.5 exposure and persistently high asthma rates, making this issue increasingly urgent as housing conditions continue to deteriorate. Many disaster risk reduction and public health efforts rely on top-down models that overlook how housing conditions, daily behaviors, and place-based inequities interact. Community knowledge is frequently excluded, resulting in interventions that are misaligned with lived realities and fail to build trust or sustained impact. This poster presents ongoing coalition-based research that links lived experience with technical evidence to support measurable health and disaster risk reduction outcomes. Led by the Disaster, Trust and Social Change Lab, this work brings together Health Zone 1 residents, youth leaders, community organizations, and researchers through participatory action research conducted between 2022 and 2025. Community priorities shifted the research focus from mental health toward indoor air quality and housing. Coalition partners co-designed PM2.5 monitoring and informed a community-validated agent-based model simulating housing conditions, behaviors, and intervention scenarios. Early deployments of low-cost interventions, including portable air filtration, demonstrate indoor PM2.5 reductions exceeding 50 percent. Beyond Jacksonville, this work offers a transferable framework for equitable, evidence-based disaster risk reduction and health policy.

Numerous studies have established that the risk of vehicle crash increases during winter weather as compared to days without precipitation. Few, if any, studies have explored the relationship between snowfall accumulation and changes in risk. Recent research has found that snowfall totals are likely to change as climate warms. Decreases in the frequency and magnitude of snowfall events in the future could paradoxically lead to more crashes during snow if people are more likely to drive when snowfall totals are lower and if they tend to crash at rates in the future similar to those that are seen now. Therefore, to understand how crash risk during snowfall might change in the future, this poster describes a study examining the relationship between snowfall totals and crash risk in the recent past. Vehicle crash data are gathered from the state of Iowa and combined with sub-daily snowfall and precipitation data, and then a relative risk approach is used to determine the risk of crash across different snowfall

Effective communication of hurricane risk is critical for shaping public risk perception and motivating protective action. This poster describes a study using an experimental approach to examine how the visual organization of hurricane warning messages and social cues influence participants’ hurricane risk perceptions and protective action decisions. The experiment employed a 2 X 2 X 6 mixed factorial design, with message layout and social confirmation manipulated between subjects and hurricane advisory intensity manipulated within subjects.

The first factor manipulated message layout on a display board: (a) text-based hurricane warning information presented on the left with graphical information (forecast cone and storm track) on the right, versus (b) graphical information on the left with text-based warnings on the right. The second factor manipulated social confirmation, exposing participants to a scenario in which one friend confirmed the official hurricane warning while another expressed doubt

Forecasting wildfire risk is typically done with respect to vegetation and weather conditions. However, 84% of wildfires are started by humans, either accidentally or intentionally. Past studies have sought to use human-relevant data to explain human-caused wildfire behavior, but not to forecast risk at a granular level (e.g., identifying specific potential causes). Such a forecasting capability, along with a wildfire spread potential model informed by remote sensing data, can be used by utility companies, state and local municipalities, land or resource managers (e.g., U.S. Forest Service, Bureau of Land Management), or power companies to inform management and public safety actions. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration.

In 2022, 26 descendants and survivors of a brutal, city-authorized, forced dislocation filed a lawsuit against the City of Portland and its partners. The plaintiffs argued that public and private actors conspired to remove Black residents from a high-functioning neighborhood in order to clear land for a hospital expansion that never materialized. In the process, the city laid waste to livelihoods, stripped descendants of intergenerational wealth, and dismantled a vibrant cultural community. Framed through disaster studies, this case treats racially targeted urban redevelopment as a slow-onset, human-caused disaster, the cascading impacts of which have unfolded for more than 50 years. I was retained by the legal team to develop an evidence-based framework for documenting social, cultural, and psychological harms that conventional damage models ignore, including disrupted kin networks, loss of place-based identities, erosion of social trust and safety, and enduring trauma. Standard legal and planning assessments tend to monetize only physical assets and immediate economic losses, leaving lived harm unmeasured and therefore legally invisible. Despite minimal legal precedent for recognizing such non-material losses, the case settled in 2025 with a landmark agreement that included $8.5 million in cash compensation, transfer of three parcels of land, formal acknowledgement of systemic racism, and symbolic measures of redress through public exhibits and dedications. This poster presents the analytic template I used to translate lived experience into legally actionable claims, offering disaster scholars and practitioners a solid methodology for supporting other displaced communities seeking accountability for the long-term, discriminatory impacts of past development practices.

As climate-related disasters intensify, emergency management agencies face mounting pressure to evolve beyond reactive response models. This poster describes a project advancing research by providing a baseline based on practitioners in the field before and during the shifts of the Emergency Management profession including but not limited to the changes in funding, national organizational structure, and weighted priorities on the federal and state/local levels. Deloitte's recent insights aim to highlight a comprehensive lifecycle approach to Emergency Preparedness and Response, emphasizing preparedness, mitigation, response, recovery, and resilience. By aligning strategic planning with technological innovation, agencies can shift from reactive cycles to proactive resilience-building. This research underscores the importance of inclusive policy design, modernized infrastructure, and community engagement in strengthening national disaster readiness. The 2025 Deloitte-NEMA National Risk Study identifies critical barriers—funding constraints, workforce shortages, and outdated technologies—that hinder proactive disaster management. The significance of this project is consolidated by the inclusion and feedback from state directors across the country who drove the concerns, highlights, and discoveries throughout this study. This poster explores how public sector agencies can overcome these challenges by integrating emerging technologies, particularly generative artificial intelligence (AI), into emergency preparedness and response frameworks. AI-driven tools offer enhanced situational awareness, predictive analytics, and streamlined service delivery, enabling faster, more equitable responses. However, successful implementation requires ethical governance, cross-sector collaboration, and investment in workforce development.

Extreme weather events like hurricanes cause long-lasting disruptions to housing markets, yet measuring housing recovery still is complicated. Property values are used as indicators of neighborhood stability, investment and recovery following disasters. However, recovery trajectories are usually uneven across space and socioeconomic contexts. Hurricane Ian created lasting damage across Lee County, Florida, especially in coastal and low-lying communities. Though prior research has examined post-disaster housing outcomes, they haven't leveraged parcel level tax assessment data to track recovery dynamics over multiple years at spatial scales. This poster describes a study evaluating changes in property values before and after Hurricane Ian using longitudinal, parcel-level tax roll data from Lee County spanning 2021 to 2025. The data includes the assessed market and taxable values, as well as related housing characteristics linked across years using parcel identifiers. Descriptive statistical analysis will be used to compare year-to-year changes in property values. We will focus on spatial variation and disparities based on housing type, tenure status, age of houses, and socioeconomic features of neighborhoods. Summary statistics and distribution of value changes will be examined to assess differences in disaster impact and recovery patterns across jurisdictions. It is expected that property value changes will show uneven housing impact and recovery across Lee County, with better trajectories in high value or resource areas and delayed recovery in vulnerable communities. The findings contribute to more discussions regarding equitable disaster recovery and could inform policymakers trying to support housing stability and resilience in climate vulnerable regions. 

The pilot LandslideReady community engagement program is carried out by the Puerto Rico Landslide Hazard Mitigation Office and supported via a collaborative agreement with the U.S. Geological Survey. In 2025, six municipality-level emergency management offices in Puerto Rico completed the program and were formally recognized as LandslideReady. An important step to standardize the program structure has been the development of the LandslideReady cycle, which serves to guide collaborators through the structured process. We emphasize that the cycle continues after formal recognition, to encourage continued partnership and collaboration between our office and the municipality and to illustrate the concept of recognition renewal, which we envision to occur after a 4-year period. Important milestones in the cycle include (a) community-level presentations designed to inform residents about landslide hazards and decision-making before, during, and after landslide-triggering events; (b) targeted workshops for municipality employees involved in landslide-related work; and (c) completion of a comprehensive LandslideReady manual, which documents municipality-specific landslide hazards and outlines assessment, preparedness, and response strategies. The first cohort of recognized municipalities in 2025 included Utuado, Maricao, Ponce, Adjuntas, San Germán, and Cabo Rojo. During the same year, we directly interfaced with more than 2,500 individuals via LandslideReady community engagement activities. In 2026, we are working to expand the LandslideReady program to recognize 10 additional municipalities across the island. To monitor and evaluate program implementation, our team is measuring risk perception with participants during pre- and post-recognition stages.

The Atmospheric River (AR) scale is a five-level classification system designed to communicate the intensity and potential impacts of ARs, which are long, narrow corridors of concentrated moisture that can produce hazards ranging from beneficial rainfall to destructive flooding and high winds when they make landfall. Developed in 2019 by researchers at the Center for Western Weather and Water Extremes in collaboration with operational partners, the scale was intended to improve situational awareness and forecast communication during these high-impact events. This poster describes a study advancing hazard communication research by providing the first nationwide, bilingual (English and Spanish) evaluation of how the public interprets and responds to the AR scale. Using a nationwide survey of U.S. adults, the study examines three key dimensions of scale interpretation in both English and Spanish: (a) comprehension of hazard potential across categories, (b) perceived benefits and risks associated with different scale levels, and (c) perceived thresholds for taking protective action. Preliminary results indicate substantial misalignment between the intended meaning of AR scale categories and public interpretation, with respondents frequently underestimating or overestimating risk and expressing uncertainty about when protective action is warranted. These results may help improve the design of AR forecast products, supporting better decision-making during these high-impact events.

Wildfire risk is increasing across the western United States due to climate change and historical land management practices, with projections indicating substantial growth in wildfire frequency and severity. In Utah, wildfire exposure is rising alongside development in the wildland-urban interface (WUI), while insurance coverage is becoming harder to obtain with increasing non-renewals in high-risk areas. These challenges highlight the need for community-scale, science-supported approaches to wildfire mitigation and resilience that account for how decisions are made across multiple institutions and actors. This poster describes a project examining how communities in Utah understand, plan for, and respond to wildfire risk by centering perspectives from a diverse set of stakeholders involved in wildfire mitigation and planning. Rather than focusing on a single group, the study engages planners, policymakers, fire and emergency management officials, homeowners associations (HOA), community leaders, and residents to better capture the complexity of wildfire-related decision-making. The study uses a qualitative, non-experimental research design combining semi-structured key informant interviews, observation of community and HOA meetings, and two stages of focus group discussions conducted in Salt Lake City and Park City. Stage 1 involves focus groups examining perceptions of wildfire risk and preferred mitigation and resilience strategies, while Stage 2 focus groups build on these findings to assess perceived benefits and challenges, and find pathways to implementation. This project aims to integrate insights across stakeholder groups to inform more effective and inclusive wildfire resilience and insurability in Utah. 

The COVID-19 pandemic caused significant shocks to businesses and economies around the world. However, the breadth and diversity of policy responses present an opportunity to better understand the role of financial and non-financial assistance on business outcomes. This poster presents the findings of an international, collaborative effort to understand business recovery and the role of these supportive policies after the COVID-19 pandemic and related lockdown measures. We present the findings of a survey of businesses that took place between July 2024 and May 2025 across 10 cities and seven countries, including Vancouver, Calgary, Miami, Los Angeles, Amsterdam, Auckland, Christchurch, Cape Town, Bangkok, and Osaka. Using 3,435 individual responses, we explore business impact and recovery, business adaptations, access to financial and non-financial assistance, supporting program characteristics, the extent of short- and long-term business adaptation, and the role the pandemic played in changing business readiness for future disruption.

The growing reliance on composite indicators to assess climate vulnerability, resilience, and adaptive capacity has raised concerns about their validity and real-world applicability. Many indices aggregate exposure, sensitivity, and adaptive capacity into a single measure, obscuring their distinct roles and theoretically causal relationships. This poster describes a study seeking to externally validate an adaptive capacity composite indicator by disaggregating vulnerability components and empirically examining the association between adaptive capacity and sensitivity. Rather than relying on proxy indicators, sensitivity is empirically estimated as observed changes in impact outcomes resulting from climate exposure. Under this framing, adaptive capacity is expected to influence how exposure translates into impacts, such that higher adaptive capacity should be associated with lower sensitivity under comparable exposure conditions. Using panel data from Kansas between 2011 and 2018, the study estimates sensitivity across counties and census tracts using annual climate exposures and observed outcomes, including crop indemnities, population change, and unemployment. To capture temporal dynamics and spatial heterogeneity, fixed-effects panel regression and geographically weighted panel regression are employed. Results reveal substantial spatial and contextual heterogeneity in climate sensitivity. Absolute SPEI-6 emerges as the most influential exposure across outcomes, suggesting that prolonged climatic stress has more pronounced impacts than isolated events. At the statewide level, adaptive capacity is negatively associated with sensitivity, consistent with theoretical expectations. However, this relationship varies across metropolitan, non-metropolitan, and farming contexts, and by outcome type. The findings highlight the importance of adopting place-based approaches to climate adaptation.

Funded by the National Science Foundation's Natural Hazards Engineering Research Infrastructure (NHERI) program, the DesignSafe project has supported natural hazards research since 2015 by providing an integrated cyberinfrastructure for data-driven discovery. DesignSafe offers researchers access to high-performance computing resources, geospatial analysis tools, data analytics and visualization capabilities, robust data management and sharing services, and formal data publication workflows. As the project enters its next five-year phase, a central focus is the systematic expansion of artificial intelligence (AI) across the platform. These efforts aim to enhance data discovery, analysis, and reuse; improve user workflows; and enable new research capabilities that accelerate scientific insight and interdisciplinary collaboration within the natural hazards community. DesignSafe’s AI capabilities employ retrieval-augmented generation over its curated research holdings, ensuring responses are grounded in verified community data and minimizing the risk of hallucination or factual error.

Building codes are critical tools for enhancing disaster resilience, yet their uneven adoption and inconsistent enforcement limit their effectiveness in reducing hazard losses and supporting equitable recovery. This poster describes a study advancing understanding of how community and nonprofit organizations—including those working on construction, rebuilding, retrofitting, and advocacy—navigate building code systems to strengthen the built environment under conditions of variable regulatory support. Drawing on qualitative interviews with organizational leaders across Texas, the research examines how groups balance safety, speed of recovery, affordability, and equity when engaging in building-related activities, and how building code adoption and enforcement—or their absence—influence organizational decision-making and resilience outcomes. Findings reveal common strategies used to advance hazard resilience through building activities, including informal advocacy, partnerships, and negotiated compliance approaches, as well as structural barriers associated with resource constraints and jurisdictional variability in code enforcement. The study also identifies perceived gaps in current building codes and implementation practices that limit their ability to address climate-amplified risks such as hurricanes, flooding, and extreme weather. Results contribute to advancing both practice and research by highlighting how regulatory frameworks intersect with on-the-ground resilience efforts and by identifying opportunities for policy improvement to support more consistent and equitable building code outcomes. Insights from this work aim to inform academics, practitioners, and policymakers seeking to strengthen building code systems, complementary incentives, and community capacity to reduce disaster risk and enhance equitable resilience statewide.

This poster describes a study advancing understanding of how resilience and adaptive capacity are measured at the local level utilizing the Baseline Resilience Indicators for Communities (BRIC) framework. We reviewed the literature on the BRIC framework and selected indicators that could be translated to the census tract level and that were appropriate to evaluate flooding in the Texas Lower Rio Grande Valley. We constructed our index based on 37 variables that represented social capital, economic capital, community capital, institutional capital, built capital, and natural capital. The internal consistency of the index was assessed using Cronbach's alpha. The index was validated against the Social Vulnerability Index (SoVI). Results from our index were mapped and hot spot analysis was conducted for the composite score and the score for each of the capitals. This will provide a greater understanding of the variability in resilience as well as identify where high and low resilient communities are clustered. Finally, we compared urban census tracts with rural census tracts to further understanding of the urban-rural divide in community resilience. This study adds to the BRIC literature and represents a step forward in understanding adaptive capacity and drivers of community resilience at a sub-county level. This study also provides information to decision-makers regarding community variability and can be used to help target policies, programs, and interventions where they are needed most.

Federal flood buyouts are voluntary programs to move people out of high-risk floodplains by allowing the government to acquire the properties and make the sites open space. While flood buyout programs have been implemented for several decades, there has been a lack of assessment of the built and social-environmental impacts of these programs. This poster describes a study examining the long-term outcomes of flood buyout sites in the City and County of St. Louis using socioeconomic information and visual observations of the surrounding areas of the sites. This research site was selected because the St. Louis area in Missouri has a substantial number of flood buyouts. A database was created at the census tract level with data pertaining to the presence of flood buyouts, land uses, and demographics for the years 1990, 2000, 2010, and 2020. A flood extent shapefile was then overlayed to include census tracts that are part of the flood extent but did not receive buyouts. The results suggest that 38.8% of the flood buyout sites in the City and County of St. Louis remain non-vacant even though 89.5% of the total buyout claims were filed in 1994. The study also found that most commercial, industrial, and institutional property sites remain non-vacant, while residential sites are relatively more vacant. 

The City of Charlotte, North Carolina—one of the fastest-growing cities in the United States—is experiencing rapid urban development and tree canopy loss, exacerbating the impacts of the urban heat island effect on residents. Although some government-designated cooling facilities are available to residents during extreme heat events, these facilities are inequitably distributed and inadequate for serving the city's large population. Another barrier to equitable cooling access is that individuals do not always feel safe or welcome in government-designated cooling centers. One potential solution to filling this gap is establishing informal, community-run cooling centers. In this poster, we describe a study asking place-based community organizations in Charlotte about their capacity to serve as informal cooling centers, including needed resources and anticipated barriers. This research builds on the results of Charlotte's 2024 Urban Heat Island mapping campaign and directly supports an ongoing heat action planning initiative. Using semi-structured, in-depth interviews with leaders of place-based community organizations, we investigate their organizations' capacity to serve as informal cooling centers during extreme heat events. Findings include an improved understanding of the impacts of extreme heat on Charlotte communities and community organizations; identification of opportunities and barriers associated with establishing informal cooling centers; and guidelines for ways in which community-government partnerships could help to support more equitable cooling access. Practical implications of the research include recommendations for incorporating community-operated informal cooling centers into extreme heat response planning. These guidelines will be incorporated into the Charlotte-Mecklenburg Heat Action Plan and can also be used by other communities seeking to develop similar resources.

Trust failures during disasters disproportionately harm marginalized populations. When African Americans drowned during Hurricane Katrina, when Puerto Ricans died in the aftermath of Maria, when undocumented immigrants lost their homes to wildfires, these were not random tragedies but systematic failures rooted in distrust of institutions that have historically failed vulnerable populations. This poster describes a qualitative study examining a question rarely asked in disaster research: Do emergency managers believe they deserve the trust that vulnerable communities place in them? Drawing on interviews with 22 community gatekeepers in Eastern North Carolina, this research reveals how leaders assess their own trustworthiness when serving African Americans, Hispanic and Latino immigrants, low-income families, rural communities, and other marginalized groups. Findings demonstrate that historical trauma actively constrains current trust, that economic vulnerability creates rational distrust, that gender and geography intersect to shape credibility, and that many professionals lack critical consciousness about how their systems perpetuate marginalization. This study contributes to disaster equity scholarship by centering the uncomfortable self-examination that emergency managers must undertake to transform systems that have historically failed the very populations they claim to serve.

Disaster preparedness policy increasingly requires formal plans, yet this poster shows that these requirements can shift attention from practical readiness to documentation while also creating conditions that enable improvisation. Based on action research and ethnographic fieldwork in aging care service organizations in Fukuchiyama City, Kyoto, Japan, this project advances hazards practice and research by conceptualizing ritualized attention as situations in which organizations are institutionally compelled to display concern for disaster preparedness through plans without being able to fully invest in them. Field observations documented how ritualized attention contributes to “paper plan syndrome,” with care organizations outsourcing plan production, preparing meeting records for board reporting, and completing evacuation planning templates only to satisfy oversight and reimbursement rules. At this level, attention is bureaucratically organized and may displace time and resources from practical preparation. However, a second layer emerged in which staff, aware of these institutional demands, strategically limited formal engagement while preserving discretion for situated judgment. We implemented two interventions: (a) a dilemma game supporting collective decision-making under uncertainty and resource constraints, and (b) a first mission box limiting planning to initial post-impact actions. Preliminary findings indicate these interventions redirected discussion from document completion to shared judgment, role expectations, and tacit priorities not specified in formal plans, suggesting ritualized attention can also function as a flexible buffer that protects space for improvisation. These findings suggest disaster preparedness frameworks should move beyond evaluating the existence of plans toward supporting collective judgment, initial action coordination, and context-sensitive improvisation. 

Multilingual immigrant workers in the United States face disproportionate risk during extreme weather events because limited access to multilingual information, unclear workplace protocols, and workplace power imbalances constrain their ability to take protective action. This poster advances hazards and disasters scholarship by demonstrating how structural and social vulnerabilities undermine workplace safety during weather emergencies, even when forecasts and guidance are available. In collaboration with a local nonprofit organization, the research team conducted seven focus groups with 29 Hispanic and Latinx immigrant workers in Wichita and Garden City, Kansas—two cities with frequent extreme weather exposure and large Spanish-speaking immigrant populations—and analyzed translated transcripts using a phronetic iterative approach. Findings showed that gaps in hazard knowledge, inaccessible preparedness resources, and fear of retaliation inhibited workers' ability to interpret risk and respond effectively as weather and climate disasters increased in frequency. While workplace emergency preparedness planning often emphasizes man-made hazards such as fires, chemical spills, and acts of violence, protections for natural hazards remained underdeveloped despite existing federal guidance, leaving multilingual immigrant employees at heightened risk. To strengthen trustworthiness and provide immediate community benefit, the research team conducted a weather safety workshop following each session, offering practical safety guidance, Spanish-language resources, and information on employee rights during emergencies. 

In this poster, we explore how people and companies donate after disasters and what happens to these donations once they enter humanitarian supply chains. Drawing on 205 studies across psychology, sociology, economics, business, and humanitarian logistics, we bring together findings on why people give, how firms decide to contribute, and how these choices shape what actually arrives in the crisis scenario. We pay particular attention to material convergence, the unplanned influx of donated goods that can overwhelm response systems. We argue that disaster giving is best understood as a single behavioral-institutional-operational system, where internal motives, social and institutional pressures, and logistical capacity interact. Within this system, we distinguish between the extensive margin (who gives, and whether they give at all) and the intensive margin (how much they give and in what form). Across these strands, the review shows that the core challenge is not the lack of generosity, but how to align that generosity with the capacity of humanitarian logistics, so that donations support rather than disrupt response efforts.

This poster is part of an ongoing effort to understand how researchers, agencies, and community partners can more respectfully and effectively engage with communities in Southwest Louisiana and across Acadiana. Much of the work so far has focused on the early steps—learning who the right contacts are, understanding governance structures, community decision-making, and participating in regional planning efforts. Because many of these communities have different histories, levels of recognition, and relationships with local and state governments, there is no one-size-fits-all approach. Our goal is to build a flexible engagement framework that centers relationships first and supports long-term collaboration around climate resilience and hazard mitigation. This includes paying attention to tribal sovereignty, data governance, and how to incorporate ecological knowledge in ways that are community-led and not extractive. We are also looking at different governance frameworks—formal, informal, and historical—to understand how they shape participation in resilience planning. This poster will share what we've learned from the earliest phases of outreach, including what has worked, what still needs improvement, and what questions we're bringing back to community partners. The intention is not to present a "finished model," but rather to outline the beginnings of a process that is grounded in trust, respect, and actual community priorities. By focusing on listening, relationship-building, and co-creating next steps, this work aims to support stronger, more sustainable community partnerships.

On June 21, 2021, a massive rainstorm affected Detroit, Michigan, causing widespread overland and basement flooding. Although officially declared a disaster the following month, little national attention was paid to this event, making it an example of the understudied phenomenon of low-attention flooding. This poster explores and describes the relationship between sociodemographic characteristics, housing status, and flood-related outcomes for this case study event. Using data from the Detroit Metro Area Communities Study (DMACS) Wave 21 survey (n=2,288), a representative panel survey focused on community concerns and public opinions, we examined how pre-flood characteristics such as race, income, and housing type, relate to multiple flood-related outcomes, including water in the home, lost access to essential services, and short-term displacement. Preliminary results indicate correlations among sociodemographic characteristics, housing status, and the severity of flood-related outcomes. For instance, respondents with household incomes under $35,000 were more likely to report higher rates of short-term displacement and longer displacement periods, regardless of housing type and ownership status. While these results illustrate relationships within the representative sample of Detroiters in DMACS, next steps will evaluate statistical significance of these relationships and compare them to catastrophic flooding events. Overall, this study improves our understanding of the otherwise under-researched phenomena of low-attention flooding. 

What does it mean to be dis/abled in an area prone to repeated disasters? For marginalized groups in Eastern North Carolina, "ordinary" everyday realities are often experienced as emergency, crisis events. Everyday things people may take for granted, such as food and safe housing, can create everyday disasters for people with disabilities and other marginalized identities. This poster describes 12 months of ethnographic fieldwork examining how experiences of disaster (broadly defined) shape perceptions of and experiences with dis/ability in Eastern North Carolina. Participant observation with a Healthcare Preparedness Coalition (HPC) and Center for Independent Living (CIL), along with semi-structured interviews with HPC and CIL staff and consumers, reveals that marginalized groups face ongoing, chronic struggles while simultaneously preparing for, responding to, and recovering from disasters. Because "disasters" are often framed as immediate and acute, overlooking the extended time it takes marginalized communities to recover from such events, recovery is not always framed as dynamic and ongoing, which neglects interrogating "normal" pre-disaster conditions that recovery processes aim to return to. What is a "return to normal" when the normal everyday lives of people with disabilities often include harm and suffering? In addition to advancing anthropological engagement with disability and disaster, this research contributes to disability and disaster studies, public health, and policy, and provides evidence of the importance of including marginalized groups in research and policy processes. Examining disasters through dis/ability narratives advances social justice and helps create environments that prioritize access for all stigmatized and devalued bodies and minds.

The Extension Disaster Education Network (EDEN) is a network of cooperative extension professionals from across the U.S. Land Grant System. EDEN was born out of the Midwest floods of 1993 as a disaster reduction group of the Land Grant System tasked with engaging locally embedded extension professionals in support of preparedness, response, recovery, and mitigation efforts in the communities they serve. This is accomplished by reducing the impact of disasters by bringing together and coordinating the expertise and resources of the Cooperative Extension System to address the critical needs of individuals, families, and communities.  EDEN is supported by the U.S. Department of Agriculture’s National Institute of Food and Agriculture (USDA-NIFA) through a Food and Agricultural Defense Initiative (FADI) grant and works in alignment with the Extension Committee on Organization and Policy (ECOP). The EDEN network comprises a collaboration of member institutions from the three Land-Grant University Systems, Sea Grant, and other dedicated member partners.  This collaboration drives the mission of EDEN to reduce the impact of disasters through the aggregation of research-based resources and coordination to ensure these resources are readily available to the Cooperation Extension System, other stakeholders, and the communities they serve.  This mission is achieved through the delivery of preparedness education to individuals, families, and communities, responding to disasters in coordination with other emergency management agencies and organizations, serving as a national source of research-based disaster information, and supporting applied research efforts to mitigate future events.

Previous hurricane evacuation studies have largely conceptualized household evacuation decisions as the outcome of comprehensive risk assessments and risk perceptions formed through the processing of risk messages. However, these studies often inadvertently or intentionally overlook the irregular influence of impediment-related concerns on evacuation decisions, as well as the role of structural inequality underlying those concerns. To address this gap, this poster describes a study that reanalyzes hurricane evacuation data from 1,277 coastal households in Texas and Louisiana affected by Hurricanes Katrina and/or Rita. It examines the influence of perceived evacuation impediments on decision-making relative to demographic and socioeconomic variables. Employing a machine-learning approach, the study first reclassifies these variables based on respondents' actual evacuation behaviors. Surprisingly, moderation analysis reveals that the effect of perceived impediments is contingent on demographic characteristic

California's public safety agencies coordinate wildland fire responses through a connected system; however, this system lacks clearly documented guidelines facilitating a consistent response. Furthermore, gaps remain in the details of how law enforcement and emergency management personnel respond and collaborate with their fire partners, as well as in understanding the complexities the fire service experiences during chaotic situations. This poster describes a study addressing these gaps by examining 27 guidance-focused documents from two sources. The first source consisted of California documents of after-action reviews from eight significant wildland fires between 2003 and 2024, along with state-level wildland fire response guidelines. The second source included the federal guidance outlining the baseline conceptual framework—the Maranghides-Link framework—developed from case studies of the 2018 California Camp Fire. A content-analysis-based document analysis was conducted to identify conflicts and areas of insufficiency. The results indicate that the California wildland fire response model highlights distinctive features in how fire service agencies organize their regional crisis-response operations, contrasting with the top-down approach emphasized in federal guidance. The model is supported by a comprehensive network, including mutual aid and resource deployment, which enables rapid response and evacuation decision-making during crises. In contrast, the Maranghides-Link framework aligns with the national wildland response guidelines but provides limited detail on the regulations governing interactions between first responders and emergency management personnel. Notably, regulations governing resource allocation and coordination among law enforcement agencies differ between California and federal guidelines. Furthermore, operational challenges related to cross-disciplinary and cross-agency coordination remain insufficiently addressed on both sides. 

In the Fall of 2025, we collected data via a survey in Houston, Texas, as a collaboration between the nonprofit organization, The Restoration Team (TRT), and the Coastal Hazards and Economic Resiliency (CHEER) Hub. The survey included past and current TRT clients who had done home repairs after disasters, including Hurricanes Harvey, Beryl, and Winter Storm Uri. TRT employees and a CHEER researcher visited over a dozen clients in their homes to discuss the previous work they had received from the nonprofit, as well as take note of any additional repairs the clients may need. This highlighted ongoing housing repair needs, stemming from water damage to termites, which can be weak points in a home during future disaster events. Survey results indicated positive outcomes with TRT and the work they had done for the community, and the need for organizations such as themselves to exist in high-hazard areas like Houston. Qualitative field notes and open-ended responses further highlight the role of trust, continuity, and community connection fostered between TRT and their clients, reinforcing the relevance of sustained, relationship-based recovery efforts in disaster-affected, high-hazard communities.

In late September 2024, Hurricane Helene impacted the southeastern United States and became the deadliest hurricane in the country since Hurricane Maria in 2017. This poster describes a study advancing hazards and disasters research by examining the severe and improbable effects of Helene in Appalachia, a region largely unaccustomed to powerful tropical systems and underprepared for what officials described as a one-in-a-thousand-year event. Despite being nearly 400 and 600 miles, respectively, from Helene's landfall, western North Carolina and southwestern Virginia experienced some of the storm's most severe consequences, geographically isolating communities for days. Response and relief efforts unfolded within a context shaped by the novelty of the disaster and heightened political scrutiny associated with the 2024 presidential election. Building on more than two decades of scholarship on recreancy, defined as the failure of institutional actors to carry out their responsibilities with sufficient vigor to merit societal trust, this study examines institutional performance before, during, and after Hurricane Helene. The study draws on a survey to be administered in February 2026 to approximately 1,000 residents affected by the disaster in western North Carolina and southwestern Virginia. The analysis extends beyond the Federal Emergency Management Agency to include public perceptions of local government, state government, state emergency management agencies, the National Guard, the federal government, and insurance companies. Anticipated findings will offer insights into institutional performance and public trust in disaster response amid climate change and debates over the future of federal disaster management.

Disasters are increasing in severity, with losses rising each year. Emergency managers are increasingly being called upon to address social crises that are not traditionally associated with emergency management. There is some evidence that accumulating crises are leading to burnout among professionals working in emergency management and related professions, but evidence is limited. This poster describes a study seeking to increase knowledge in this area by answering the following research questions: (a) How is burnout experienced by emergency/disaster managers? (b) What do emergency/disaster managers perceive to be the cause of their burnout? (c) How does collaborative capacity influence burnout? The project uses a mixed-methods approach to analyze data obtained through a web-based survey deployed in May 2025 (N = 937). Findings indicate emergency managers are experiencing burnout because of their work. Six major qualitative themes were identified as factors contributing to burnout: (a) Too much work, (b) Lack of capacity, (c) Leadership issues, (d) Workplace culture and mental health, (e) The current political climate, and (f) Major and compounding disasters. Collaborative capacity was found to have a negative influence on burnout. These findings suggest emergency/disaster managers may need additional support in order to fulfill their roles and also highlight the importance of collaboration; however, collaboration alone cannot be the answer, as collaboration is dependent on individual and organizational capacity as a prerequisite.

As climatologists, we sought to quantify the thermal exposure of people experiencing unsheltered homelessness (PEUH) while sleeping in tents. This poster describes how we conducted this work in close partnership with the Volunteer Ministry Center (VMC), a nonprofit organization that provides specialized services to PEUH and supports permanent supportive housing and homelessness prevention. Social workers from VMC's street outreach team were essential to the study, recruiting participants who lived in tents and were interested in reliable participation. The street team brought participants to the VMC building for an initial interview, where participants discussed how extreme weather affects them and the strategies they use to cope inside their tents. Social workers then guided the research team to tent locations across the city to install temperature sensors for in situ observations. The VMC team also coordinated with local police to pause camp sweeps during the period, providing temporary stability that enabled participation. VMC staff were motivated to support the study both because of this stability for their clients and because participants received grocery store gift cards for their time. The data showed that winter coping mechanisms were often effective at warming tents but required forfeited sleep and the acquisition of large amounts of materials. These strategies were difficult to maintain due to camp sweeps and theft, particularly when individuals used shelters. Overall, the findings highlight the partial effectiveness of behavioral and material coping strategies and demonstrate how the criminalization of homelessness and restrictions on movement increase PEUH's exposure to extreme weather and related health risks.

More people die from snow avalanches in Colorado, both historically and annually, than from other natural hazards. Accurate estimates of avalanche extent, primarily runout distances, are crucial for avalanche safety operations, public warning programs, and hazard mapping efforts. We developed a methodical, repeatable workflow for delineating avalanche runout paths. Systematic mapping of avalanche runout extent will allow recreators and professionals to better identify and avoid hazardous terrain. Previous efforts to map avalanche paths across Colorado lacked consistency due to variations in individual contributors and overestimated runout extents. Our workflow provides consistent, reproducible path definitions by differentiating paths based on terrain and forest density rather than post-event disturbance signatures. Rule-based thresholds for slope angle (30 degrees, 45 degrees), terrain curvature, and canopy cover density identify likely release areas. Release-area polygons and high-resolution digital elevation models are input into FlowPy, an open-source gravitational mass-flow simulator, which produces flow-intensity values for each potential release. For each path, a post-processing routine thresholds these values to identify the most probable flow corridor and converts the result to a polygon representing the runout zone of a typical large avalanche. Finally, we validate the model by comparing the generated runout path polygons with disturbance patterns observed in imagery from large-avalanche cycles. This work aims to provide a standardized product for avalanche runout paths along Colorado transportation corridors and extend this systematic mapping approach to all of the Colorado Avalanche Information Center's forecast areas by fall 2026. 

Post-disaster recovery research needs clearer explanations of how victims decide whether to relocate according to land use, housing conditions, and neighborhood recovery change over time. This poster describes a study advancing that understanding by developing a dynamic model that represents relocation as a step-by-step decision process shaped by spatial changes. The model incorporates household attributes (such as income, age), the condition of housing supply, and land-use patterns. It is applied to the 2016 Kumamoto Earthquake, a major urban earthquake in Japan now reaching its 10th year of recovery. Using datasets from national and local governments and research institutions, the model is validated by comparing with annual municipal population statistics from 2016 to 2025. This study's main contribution is that it extends existing recovery models by linking physical and policy changes such as temporary housing construction or land-use change with how households interpret their options and choose whether

Rapid post-earthquake casualty transport must balance overall throughput, protection of the most severely affected areas, and community-level equity under tight time and capacity constraints. We develop a time-expanded ambulance-dispatch model that enforces non-anticipative decisions across stochastic demand realizations, penalizes tail shortfalls using Conditional-Value-at-Risk (CVaR), and incorporates a population-weighted equity penalty. The formulation respects ambulance time budgets and hospital intake capacities, producing planner-oriented diagnostics, including equity–efficiency frontiers, Lorenz curves, and capacity-versus-fleet heatmaps. In a county-scale earthquake case (201 zones, 8 hospitals, 3,696 casualties), the proposed policy raises the minimum zone-level service rate by about 9-10% relative to a triage-greedy heuristic and reduces population-weighted inequality by roughly 35%, with only a small reduction in overall treatment; FCFS performs worse on both equity and throughput. Results are robust across transport-time sensitivity analyses and replicate trials. The study operationalizes explicit risk–equity trade-offs and translates them into actionable guidance for planners, clarifying the capacity or fleet increments required to meet minimum service targets and improving transparency in crisis and emergency management. 

In collaboration with two other universities (University of Nevada-Reno and University of Idaho), this project contributes to broader collaborative efforts to understand climate adaptation at the community level and inform strategies for public resilience-building. Specifically, we address how adults living in rural areas of South Carolina perceive and respond to changes in local weather patterns, particularly focusing on drought, heat, and wildfire. Using a weather perception survey and subsequent interviews, we present research observations related to how the broader community in Allendale County perceives changes in heat, drought, and wildfire hazards over their lived experience in this place. The survey consists of thirty-three questions asking how the three target hazards have changed in duration, frequency, magnitude, and timing, as well as how individuals are impacted by the hazards and the adaptation actions they have taken. These perceptions are compared to instrumental records for each of the thr

Streamflow drought—periods of abnormally low river flows—poses significant challenges for water resource management, yet operational forecasting tools remain limited compared to flood or meteorological drought prediction. The U.S. Geological Survey (USGS) has developed River DroughtCast, an experimental web-based platform providing sub-seasonal to seasonal forecasts of streamflow drought across the conterminous United States. Leveraging machine learning (ML) approaches, including Long Short-Term Memory (LSTM) neural networks and Light Gradient-Boosting Machine (LightGBM), the system predicts weekly streamflow percentiles up to 13 weeks ahead for over 3,000 gaged locations. Forecasts target drought intensities defined by percentile thresholds (moderate: 20%, severe: 10%, extreme: 5%) and incorporate seasonally varying baselines to capture hydrologic variability. Evaluation against benchmark models (persistence, ARIMA) demonstrates that ML methods outperform traditional approaches for continuous low-flow prediction and drought onset/termination, particularly at shorter lead times (1–4 weeks). The tool integrates interactive visualizations to support decision-making by water managers, enabling early warning for drought onset, duration, and severity. This work represents a critical advancement in operational hydrological drought forecasting, addressing gaps in national-scale preparedness and resilience planning.

City-scale digital twins (CDTs) offer significant potential for advancing disaster risk management (DRM) through capabilities such as enhanced visualization, multi-system simulation, GeoAI integration, and real-time interaction with physical systems. While CDTs are increasingly used in urban planning and citizen engagement, it remains unclear how they support public participation specifically in DRM contexts. To address this gap, we conducted a systematic review of academic literature to examine CDT applications in DRM with a focus on participatory practices. Our findings show that CDTs are particularly useful for integrating diverse models and platforms, enhancing scenario planning, and supporting collaborative decision-making—areas where traditional DRM approaches face challenges. However, limitations persist, including data privacy concerns, digital inequities, and underdeveloped participatory mechanisms. Research rarely explores concrete methods for citizen engagement, despite acknowledging its importance. In response, we propose a conceptual framework to assess and enhance participation across CDT development stages. Through case studies on heatwaves and evacuation planning, we illustrate how evolving CDT capabilities—from static maps to real-time GeoAI systems—can support various modes of participation, such as scenario co-creation, real-time feedback, and public oversight of AI decisions. These insights help bridge technological advancement and inclusive governance in DRM.

This poster describes a study assessing the risk of severe weather property damage across the contiguous United States using historical data (1952–2024) from the National Oceanic and Atmospheric Administration (NOAA). The project advanced disaster preparedness research by developing a scalable, data-driven framework to quantify infrastructure vulnerability at the county level. A Bayesian machine learning model was implemented to calculate risk indices for nine hazard types, including tornadoes, hurricanes, and floods. Specifically, the study calculated risk indices for counties within a 60-mile radius of processing plants to evaluate the severity of weather impacts on critical infrastructure. The methodology involved cleaning and standardizing over 70 years of weather event records, removing outliers, and applying a Bernoulli Naive Bayes classifier to predict high-damage probabilities. Hypothesis testing (t-test) was conducted to validate the statistical significance of these risk indices against a damage

Disaster aid is central to recovery, yet concerns persist about whether assistance aligns with documented needs. This poster describes a study mapping the distribution of Federal Emergency Management Agency (FEMA) aid after Hurricane Helene (2024) across 562 counties in Florida, Georgia, South Carolina, North Carolina, and Tennessee. We combine county-level FEMA Individual and Household Program disbursements (Housing Assistance and Other Needs Assistance) with point-level American Red Cross dwelling damage assessments (including destroyed, major, minor, and affected). To account for spatial differences in storm intensity, we use county-level wind speed and precipitation metrics from National Oceanic and Atmospheric Administration (NOAA) national weather stations during the impact period. We then construct an Aid-Damage Ratio Index to measure dollars of assistance per unit of documented damage. Using this index, we test whether aid responsiveness varies with rurality, lower-to-moderate income status, racial/ethnic composition, and prior federal disaster experience, measured by historic FEMA assistance and Presidential Disaster Declarations (2013–2023). Preliminary findings show clear spatial disparities where some counties receive substantially less aid per reported damage. Patterns are consistent with uneven capacity to apply for, document, and navigate federal assistance. We expect lower Aid–Damage ratios in rural, lower-income, and higher non-White counties, and higher ratios in places with prior disaster funding and declaration experience that may strengthen administrative capacity. Results will clarify distributive and procedural equity in post-disaster assistance and inform reforms that improve fairness in federal recovery. 

This poster describes a study examining how business leaders apply the principles of complex adaptive systems to create organizational systems that are open, self-organizing, adaptable to external influences, and proactive in the face of disruption. In the last five years, businesses have faced a worldwide pandemic, multiple billion-dollar disasters, economic downturns, and newly imposed tariffs on goods and services. Research on the actions taken by business leaders to manage disruption, using principles of complex systems, has the potential to advance the study of organizational science in a technologically advanced, globally connected environment. General Qualitative Inquiry was used as the methodology. The study consisted of 15 semi-structured interviews employing purposive non-probability sampling. Participants were selected from across the United States, representing 12 industries. Both inductive and deductive thematic analysis were used. The literature review outlined the principles of complex systems, and the interview transcripts identified themes grounded in those principles. The information provided from the interviews ultimately led to actions that fell within five core areas: (a) people-centered leadership, (b) constant feedback loops, (c) emphasis on adaptation and learning, (d) decentralized decision-making, and (e) high levels of autonomy. The findings from this study emphasize the importance of adaptive and open systems processes in complex business organizations, particularly during periods of unpredictability or disruption. The results of this study provide real-world implications for business leaders and a roadmap for action to move from rigid hierarchies to more flexible, adaptable team-based organizations.

While several studies have demonstrated the power of community characteristics in disaster recovery and relocation decisions, it has been difficult to capture the effects of the web of capital resources at scale or in a generalizable form. Even more challenging is the dynamic relationship between household capitals and community capitals for resilience. Because different households will have different needs and resources, they will perceive and draw upon collective community resources differently. This poster describes a study examining the interaction between household and community capitals in shaping relocation decisions. Specifically, we ask: How do household capitals affect the relative importance of community factors in willingness to relocate? We expect households with fewer capital resources may be more reliant on their current community, or, may not have the capacity to adapt as they would prefer either through relocating or bolstering physical safety. We employ a mixed methods design utilizing da

Nature-based solutions (NbS) are increasingly promoted as effective and sustainable strategies for reducing flood risk in coastal communities, yet public support remains a persistent barrier to widespread implementation. Understanding what drives public acceptance is critical for translating NbS from planning documents into on-the-ground hazard mitigation. This poster describes a study examining the psychological factors shaping support for government-led NbS initiatives in Wilmington, North Carolina—a flood-prone coastal city experiencing recurrent storm and rainfall flooding. Using survey data from 153 residents, we apply Protection Motivation Theory to assess the relative influence of threat appraisal (e.g., perceived flood risk and past flood damage) and coping appraisal (e.g., confidence in NbS effectiveness and access to technical assistance). To evaluate policy-relevant interventions, we compare regression models that isolate the effects of technical assistance and full cost coverage. Results show that coping appraisal factors are the strongest predictors of public support for NbS. Access to technical assistance and belief in NbS effectiveness significantly increase support, while threat-based perceptions—including flood risk awareness and prior flood experience—have minimal influence. Model comparisons reveal that technical assistance explains substantially more variation in support than full cost coverage alone. Moreover, financial incentives without accompanying technical guidance do not increase support and may undermine confidence in NbS implementation. These findings highlight the importance of capacity-building and implementation support in coastal flood mitigation efforts. Rather than relying primarily on risk-based messaging or financial subsidies, NbS programs may be more effective when they emphasize technical guidance, hands-on support, and clear communication of effectiveness.

This poster describes a comparative case study examining how urban and rural contexts shape disaster preparedness and recovery strategies for heirs’ property communities in Texas. Heirs’ property, where tangled titles leave families without clear legal standing, affects tens of thousands who face systemic barriers accessing disaster recovery aid. Without clear title, owners are routinely excluded from federal aid, insurance claims, and nonprofit rebuilding programs, leaving a critical equity gap in disaster policy. Following Hurricane Harvey (2017), Houston developed a government-led approach integrating title-clearing into federally funded recovery. The Homeowner Assistance Program, coordinated by city agencies, the Texas General Land Office, and legal aid partners, links title remediation with reconstruction funding. In contrast, Southeast Texas communities affected by Hurricanes Ike (2008), Harvey, and Imelda (2019) developed cooperative, faith-based, and grassroots networks sustaining land ownership and preparedness with minimal government support. Using document analysis, interviews, and field observations, this study compares these models to identify effectiveness factors. This study examines unexplored heirs’ property strategy differences across governance and resource contexts to inform government, nonprofit, and community decisions for equitable disaster preparedness and recovery. By clarifying how government-led, community-based, and hybrid approaches differ in reach, equity, and sustainability, findings will guide policy and program design. This project will reveal how differing governance and resource contexts shape heirs' property strategies for disaster preparedness, recovery, and land retention.

This project advances practice-oriented understanding of disability-inclusive disaster risk management (DiDRM) by identifying the institutional, social, and infrastructural factors that enable or constrain inclusion in hazard-prone communities. Findings show that Non-Governmental Organization (NGO)-led capacity building, community-level coordination, and inclusive preparedness initiatives are strengthening disability inclusion. However, inaccessible infrastructure, limited support from Government Organizations (GO), and persistent stigma continue to create significant barriers. The poster describes a study that was conducted in Northern Bangladesh, one of the most flood-prone areas in the country. Following a qualitative approach, data were collected through six focus group discussions, 25 in-depth interviews, and 12 key informant interviews with persons with disabilities, their caregivers, local officials, and NGO representatives. A thematic analysis approach was used to examine disability inclusion across disaster preparedness, early warning, response, recovery, and rehabilitation phases. Results indicate that community risk assessments, disability-inclusive simulation drills, assistive device distribution, caregiver training, and disaster-resilient livelihood programs function as key enablers of inclusive disaster risk management. Increased awareness of disability rights and improved coordination among NGOs and local disaster management committees have also improved preparedness efforts significantly. However, major barriers identified by the study participants include, but are not limited to, (a) inaccessible shelters and WASH facilities, (b) absence of formal sign-language early warning systems, (c) inadequate caregiver training, and (d) lack of governmental support during post-disaster recovery. These findings highlight the importance of GO-NGO collaboration, accessible infrastructure, and sustained capacity-building initiatives for advancing DiDRM in hazard-prone regions.

This project advanced disaster resilient construction research by introducing a cost-effective framework for early-stage structural evaluation of 3D printed concrete wall systems. By integrating parametric design, scaled ceramic prototyping, and finite element analysis, wall infill geometries were evaluated prior to full scale concrete printing, reducing material use, cost, and experimental uncertainty in hazard prone housing applications. An integrated computational to physical workflow was applied to assess the structural behavior of three wall infill typologies: offset modified zigzag truss infill walls designed to improve printability and reduce stress concentration, a gapped infill wall configuration representative of fabrication feasible industry practice, and offset modified truss based infill configurations used to examine the broader applicability of geometric offset strategies. All wall geometries were parametrically developed at full scale using Rhino Grasshopper with toolpath informed control. The designs were fabricated as one-tenth scale PLA models and then printed at one-fifth scale in clay using an extrusion based ceramic printer. After drying and kiln firing, the clay specimens underwent uniaxial compression testing to evaluate deformation behavior and failure modes. Full-scale digital counterparts were analyzed using nonlinear finite element analysis in ANSYS under equivalent axial loading conditions. Results showed strong qualitative agreement between experimentally observed failure modes and simulated stress concentrations, confirming the framework as an effective early-stage tool for geometry-driven structural evaluation prior to full-scale concrete printing. The upcoming work is a full-scale debris impact resistance test of the shortlisted 3D printed concrete walls at the National Wind Institute, Lubbock, Texas. Stay Tuned! 

This poster describes research advancing disaster science scholarship and practice by demonstrating how spatial variation in warning issuance and message strength throughout Hurricane Helene may shape life-safety outcomes during a catastrophic inland flooding event. The study examines whether warnings and evacuation-related messages varied across space and how these differences relate to impacts across 300 disaster-declared counties in the southeastern United States. Using Helene as a case study, this project shows that consistent, high-severity messaging from the National Weather Service was comprehensive and spatially clustered in the hardest-hit areas, while other public alert messaging varied widely in content and emphasis. A mixed-methods design integrates geospatial and statistical analysis with qualitative content analysis of three warning types. Warning locations were analyzed for spatial clustering and relationships with Helene impact variables, while more than 1,000 qualitatively coded words and phrases were used to assess message content and severity framing across four key themes (message structure, message emphasis, orders/guidance, and hazards/risks/impacts). Preliminary results show significant clustering of warnings in the Greenville–Spartanburg NWS Forecasting region and significant differences across Weather Forecast Offices, with no evidence of reduced warning issuance in rural areas. Warning location density is significantly related to precipitation, landslides, and disaster losses. Thematic message analysis indicates that other public wireless emergency alerts were inconsistent in including all five key warning elements, whereas NWS messages consistently included all five. These findings highlight the critical role of consistent, high-severity messaging in extreme inland flood events and provide actionable guidance for improving interagency warning coordination and risk communication. 

Extreme event impact attribution research on hurricanes, which assesses whether and to what degree climate change has intensified hurricane impacts, is characterized by two key research gaps. First, studies have predominantly focused on precipitation-related impacts, with limited attention to wind damage. Further, despite efforts to enhance building codes reflecting higher construction standards to ameliorate extreme hurricane winds, their potential to offset climate change-driven impacts remains largely overlooked. Using data on Hurricane Ida in South Louisiana, this poster describes research addressing these gaps by examining wind-related damages attributable to climate change and the extent to which the enforcement of enhanced building codes may have mitigated them. The study estimates structural damages attributable to Hurricane Ida under three climate scenarios: 1971 ("the storm that could have been"), 2021 ("the storm that was"), and 2071 ("the storm that could be"). It then evaluates damages across the same climate scenarios under hypothetical mitigation scenarios, including enhanced roof deck attachment and secondary water resistance. Results indicate that damages from Ida's wind impacts increased by 33% from the 1971 counterfactual to observed 2021 conditions. Under future climate conditions, wind damages are projected to rise by 194% relative to the 1971 baseline and 121% over 2021 damages. Analyses of potential reductions in climate change-attributed wind damages achievable through enhanced building code enforcement are ongoing. Overall, this study contributes to disaster research by demonstrating, in quantifiable terms, the extent to which climate change amplifies hurricane wind damages and the potential effectiveness of enhanced building codes in mitigating these impacts.

Recently, extreme snowfall events have intensified due to climate change, resulting in significant damage to horticultural and specialty crop facilities in Korea. In particular, record-breaking snowfall in November 2024 highlighted the limitations of existing snowfall-related design criteria, which are largely based on historical observations. In response to these challenges, this poster describes a study investigating changes in design snowfall characteristics by incorporating historical snowfall data and future climate change scenarios. Using SSP (Shared Socioeconomic Pathways)-based projections, the frequency characteristics of design snowfall were analyzed for regions with documented snowfall damage. Based on the results, this study discusses the necessity of improving current snowfall-related design and disaster prevention standards to enhance their applicability under changing climate conditions. The findings of this study are expected to provide a scientific basis for revising snowfall-related desig

Efforts to incorporate equity into disaster mitigation are expanding, yet there is limited empirical evidence demonstrating how different equity definitions influence funding allocation and risk reduction outcomes. This poster describes a study examining how alternative equity frameworks shape flood mitigation investment decisions and community resilience outcomes using the Stakeholder Based Tool for the Analysis of Regional Resilience (STARR) modeling framework. The research evaluates how mitigation funding changes when equity is introduced through both prioritization rules and optimization objectives. The analysis compares nine allocation scenarios that combine three optimization approaches, efficiency-focused Net Benefit, equity-focused Risk Burden, and a Hybrid objective, with three prioritization strategies based on economic vulnerability, population exposure, and a status quo allocation approach. Outcomes are evaluated across three core performance dimensions: system-level risk reduction and cost-effectiveness, the distribution of mitigation investments across communities and populations, and changes in household-level financial risk burden following mitigation investments. The analysis investigates how allocation strategies influence trade-offs between maximizing overall loss reduction and redistributing mitigation benefits toward communities facing higher relative risk. It also evaluates whether equity can be more effectively incorporated through eligibility prioritization, allocation optimization, or a combination of both mechanisms. By systematically comparing allocation strategies across multiple performance metrics, this research provides decision-relevant insights for mitigation programs seeking to balance efficiency, equity, and long-term flood resilience while supporting more transparent and evidence-informed funding decisions.

We developed a pre-approved umbrella protocol framework that enables rapid deployment of infectious disease surveillance research during disasters, addressing the fundamental mismatch between regulatory requirements and emergency response timelines. Climate change is increasing disaster frequency while expanding infectious disease risks; however, existing disaster research protocols lack the methodological infrastructure to capture communicable disease epidemiology, including temporal sampling for incubation periods, pathogen-specific specimens, and public health surveillance integration. Building on the National Institute of Environmental Health Sciences Disaster Research Response Program model, our framework employs an umbrella protocol structure where standardized elements receive pre-approval while event-specific parameters are specified through expedited amendments. Key components include: (a) disaster-specific pathogen-exposure matrices, (b) tiered specimen collection strategies scalable to field conditions, (c) multi-timepoint sampling capturing seroconversion and disease kinetics, and (d) standardized common data elements for cross-study harmonization. A Research Electronic Data Capture system with 181 variables enables standardized data collection. The complete institutional review board submission package includes umbrella research protocol, pathogen-exposure matrices for multiple disaster types, specimen collection field cards with cold-chain alternatives, laboratory network specifications, comprehensive data dictionary, informed consent templates, and sub-study amendment checklists for rapid activation. This framework supports multi-site deployment with harmonized data collection, requiring coalition partnerships across research institutions, public health laboratories, health departments, and community organizations, embodying the conference theme through coordinated network infrastructure built before disasters occur. 

Large wildfires are becoming more frequent worldwide, raising urgent questions about how communities prepare for and recover from these events. California and South Korea both experience repeated wildfires that threaten residential areas, yet they operate under very different environmental conditions and response systems. In California, wildfire risk is shaped by the expansion of housing into fire prone landscapes and aging power infrastructure, while in South Korea, mountainous terrain, strong seasonal winds, and a highly centralized response system strongly influence wildfire impacts. These contrasts show that wildfire resilience is not only an environmental challenge but also a spatial and institutional one. This poster describes a study comparing the 2020 North Complex Fires in California and the 2025 Yeongnam Complex Fires in South Korea to examine how communities respond to wildfire risk before and after major events. Using a comparative case study approach, the research analyzes actions across three dimensions: the natural environment, the built environment, and the social environment. The analysis draws on governmental reports, post disaster evaluations, wildfire risk maps, and satellite imagery through qualitative document review. Preliminary findings suggest that California increasingly relies on state-led risk mapping and infrastructure regulation, while South Korea's centralized system enables rapid mobilization but faces challenges related to interagency coordination and community engagement. By placing these two cases side by side, the study shows how land use, governance structures, and local participation shape resilience outcomes and identifies practical lessons for improving wildfire planning and community-based preparedness in fire prone regions.

As natural disasters in the United States grow more frequent and costly, budgets at all levels of government are increasingly strained. While prior research has emphasized presidential authority and administrative implementation in disaster recovery financing, far less attention has been paid to Congress's role in determining which disasters receive supplemental funding. Drawing on Intergovernmental Relations (IGR) theory, this poster describes a study examining how congressional characteristics shape the allocation of supplemental disaster assistance following presidential disaster declarations. Using an original dataset of 1,389 presidentially declared disasters between 1992 and 2018, this research analyzes the likelihood that disasters receive funding from two congressionally appropriated programs: the Community Development Block Grant–Disaster Recovery (CDBG-DR) program and the Small Business Administration (SBA) disaster loan program. Logistic regression models assess the influence of structural congressional factors—including appropriations committee membership, party majority status, and state population size—alongside programmatic indicators of community need, such as property damage, homeownership rates, and small business concentration, while controlling for disaster characteristics and sociodemographic conditions. Findings show limited and mixed support for structural congressional influence but stronger and more consistent effects for programmatic and disaster-related factors, particularly property damage. These results suggest that disaster recovery financing reflects both institutional design and political capacity, reinforcing the relevance of IGR theory while highlighting important limits to congressional influence. Overall, this study advances disaster governance research by situating Congress as a conditional—but consequential—actor in post-disaster recovery.

Founded in March 1983, the International Journal of Mass Emergencies and Disasters (IJMED) is one of the longest-standing and most respected journals in disaster science. Published triannually, IJMED provides an internationally refereed platform for high-quality scholarship addressing hazards, disasters, and mass emergencies across all phases of the disaster cycle, including mitigation, preparedness, response, and recovery. The journal serves researchers, practitioners, and specialists seeking rigorous, evidence-based insights into disaster-related challenges. IJMED publishes a wide range of article types, including peer-reviewed empirical research, theoretical contributions, methodological innovations, literature reviews, and teaching pedagogies. Central to the journal’s mission is advancing knowledge on how social systems, institutions, and policies influence disaster vulnerability and outcomes; how natural and built environments interact with social processes to shape hazard risk; and how methodological advances can improve the accuracy, ethics, and practical relevance of disaster research. The journal also highlights pedagogical approaches that support education and professional training in hazards and disaster studies. Interdisciplinarity is a defining feature of IJMED. Submissions are welcomed from across the social, behavioral, economic, physical, and engineering sciences, as well as emergency management, geography, and environmental and disaster sciences. Since 2023, IJMED has placed increased emphasis on interdisciplinary research addressing the complex interactions among climate change, evolving hazard profiles, social systems, and the built environment. Affiliated with the International Sociological Association's Research Committee on the Sociology of Disasters (ISA RC39), IJMED remains committed to advancing global, inclusive, and theoretically informed disaster scholarship.

This poster describes a study exploring how rural communities in Bangladesh understand and respond to flood early warning systems (FEWS). This study was conducted in four flood-prone villages in Sirajganj district, Bangladesh. These villages were selected due to their repeated exposure to seasonal flooding and their diverse social and economic characteristics. To understand how community members perceive and respond to flood early warning systems (FEWS), we used qualitative research methods. Data was collected through 20 in-depth interviews and 5 focus groups. Findings suggest that many respondents had heard of FEWS, but very few received clear, timely messages. Most did not understand the warnings or take action. Instead of relying on formal systems such as IVR (interactive voice response) or water-level gauges, people used indigenous knowledge. They observed natural signs such as river color, wind direction, and rainfall patterns. These methods were passed down through generations and often proved more u

The Community Emergency Response Team (CERT) program, more than 30 years old, is often one of few educational programs that teach community members about hazards and localized risks; this has become critical due to limited resources of rural areas to focus on hazard reduction. The CERT program is often studied in more urban areas, leaving it understudied in rural areas and, especially, in rural places of color.  Rural communities of color have higher social and physical vulnerabilities because of historic disenfranchisement, low economic investment, higher exposure to hazards, and repeated impacts from low attention disasters. This project seeks to understand the impact of the CERT model as a disaster preparedness and emergency management program in rural communities of color in the United States. Using geospatial analysis, this project identifies the geographic relationship between the location of CERTs, relative hazard exposure, rurality, and social vulnerability. Preliminary findings indicate that counties with a rural urban continuum code (RUCC) of 4 or greater were less likely to have an active CERT team, lower social vulnerability, and less access to critical infrastructure like hospitals and emergency services.  The spatial analysis provided insights for emergency preparedness planning for rural areas to include local capacity building programs like the Community Emergency Response team (CERT) program.

This poster presents preliminary findings from an ongoing systematic literature review synthesizing research on evacuation decision-making and behavior in multispecies households. While prior research has established that animals influence evacuation outcomes, relevant evidence remains dispersed across disciplines, limiting comprehensive understanding and integration into policy and practice. This review draws together literature from psychology, emergency management, public health, and human-animal studies to examine how companion animals shape evacuation decision-making and behavior during natural disasters. This review has conducted preliminary searches using systematic methods informed by Campbell Collaboration methods for systematic literature reviews in the social sciences, with reporting aligned to PRISMA standards adapted for interdisciplinary and qualitative evidence. Initial screening suggests a robust but dispersed body of relevant evidence, indicating the necessity of a review. Initial screening has revealed early thematic patterns that emphasize differences in evacuation decision-making and behavior for multispecies households. Early thematic patterns emphasize delayed evacuation, conditional compliance with evacuation orders based on the ability to evacuate animals, and decisions to shelter in place rather than evacuate when animal evacuation is perceived as unfeasible. The literature also highlights risk trade-offs made by household members, including prioritizing animal safety over personal safety, modifying evacuation timing to accommodate animals, and selectively evacuating with some animals while leaving others behind. These dimensions appear unevenly distributed across households, with vulnerable households facing heightened constraints and risk trade-offs.

This poster describes a case study investigating differing social perceptions of storm risk protection provided by a dike and saltmarsh at Cape Cod National Seashore. Hatches Harbor at the end of Cape Cod provides a rare comparison between the two infrastructure types in the same environmental condition. The dike was constructed in the 1930s behind a natural salt marsh to protect the adjacent Provincetown Municipal Airport. This study addresses the research question: in what ways and to what extent do the presence of grey infrastructures and Natural and Nature Based Features (NNBFs) affect perceived protection from storms? The study employs grounded theory and semi-structured interviews with key stakeholders such as town officials, airport commissioners, park service employees, visitors, and others. This poster illustrates the background and initial findings. Inductive thematic analysis is being used to reveal factors affecting community perceptions of how effectively grey infrastructure and NNBFs can prot

Post-disaster recovery is often judged by how fast places “bounce back,” yet reconstruction policies can lock regions and communities into recovery pathways whose benefits and burdens emerge slowly and unevenly. This poster describes research evaluating whether ecological-oriented, industrial-oriented, and hybrid reconstruction regimes after the 2008 Wenchuan earthquake produce durable, path-dependent socio-environmental effects, and how these effects persist across recovery stages. A county–year panel for extremely severely affected counties links environmental outcomes (vegetation, ecosystem service value, and pollution proxies) with socioeconomic indicators (GDP, sectoral structure, investment, and population). To address non-random policy adoption and place-specific shocks, a mixed causal design combines counterfactual benchmarking with comparative policy evaluation. First, the Synthetic Control Method (SCM) constructs no-earthquake counterfactual trajectories for affected counties, benchmarking long-run disaster impacts and identifying post-reconstruction turning points. Second, Difference-in-Differences (DiD) models leverage variation in policy intensity and heterogeneity by disaster severity to estimate average and differential long-run effects across policy regimes, supported by pre-trend diagnostics and robustness checks. Findings show persistent divergence across regimes and stage-specific trade-offs: some pathways achieve faster economic rebound alongside environmental slowdowns or deterioration. Counterfactual results also reveal overlooked disaster legacies—several counties fail to converge to the no-earthquake baseline many years later, indicating lasting scarring rather than full recovery. The research advances “build back better” debates by reframing evaluation from short-run rebound to pathway persistence and offers a portable SCM+DiD template for identifying long-run policy trade-offs under complex, place-specific reconstruction regimes. 

Wetland ecosystems can function as protective infrastructure that reduces flood and public health disasters, but their effectiveness depends on hydrologic stability and durable partnerships. This poster describes research examining how effective water management and multi-sectoral coalitions influence disaster risk reduction by comparing the deteriorating salt marshes of Antelope Island in the Great Salt Lake (GSL) with the thriving Bamseom Island in South Korea. The most critical takeaway is that the survival of urban and saline wetlands depends on integrated water governance that prioritizes ecological flow to mitigate public health and flood risks. While Antelope Island faces an impending health disaster due to desiccating wetlands that expose toxic arsenic dust, Bamseom Island demonstrates a successful resilience model where natural hydrologic recovery has created a vital flood buffer for the city of Seoul. This study utilizes a comparative case study methodology to analyze the contrasting outcomes of water scarcity versus hydrologic abundance in these two ecosystems. Preliminary results indicate that the crisis at Antelope Island is driving a new emergency coalition among Utah state officials and conservationists, whereas Bamseom serves as an established benchmark for nature-based solutions through long-term scientific and governmental partnerships. By contrasting the failure of water stability in the GSL with the successful ecological integration of the Han River, this project advances the disaster field by highlighting the necessity of coalitions that view wetlands as essential protective infrastructure. These findings offer a scalable framework for international partners to develop proactive strategies for wetland preservation as a primary defense against climate-induced disasters.

Many tourism-dependent communities with rich natural resources have become increasingly vulnerable to complex natural hazards. Hualien, Taiwan, faced a significant impact on tourism development following a magnitude 7.2 earthquake in April 2024 and subsequent heavy rainfall. Similarly, Japan's Noto Peninsula was struck by a magnitude 7.6 earthquake on New Year's Day of 2024. In these devastated communities, tourism workers suffering from property loss and economic distress could play a vital role in recovery if they become mentally resilient. Their psychological resilience leads to greater mental well-being, fostering healthy tourism and sustainable development in a changing world. Therefore, this poster describes research aiming to understand the staged changes in tourism workers’ mental stress and resilience within one year of a disaster, and how external factors (e.g., interventions) and internal factors (e.g., coping strategies) buffer stress. In late 2025, 13 interviews were conducted with tourism sec

We analyzed the spatial distribution of avalanche fatalities in the western United States. This helps identify areas where expanding public safety programs would have the greatest impact or where efforts could be concentrated within existing programs. Snow avalanches kill more people on lands managed by the U.S. Forest Service than any other natural hazard. Avalanche forecasts are used by millions of people each winter and provide vital safety information about avalanche conditions. Forecasts are issued by local and regional programs known as avalanche centers. The location and the extent of the areas forecast centers cover have developed over time, driven by community needs and available resources. Coverage of avalanche forecasts for backcountry recreation is focused on high-use areas or areas perceived as needing them. We compiled a dataset of almost 200 accidents from October 2014 to June 2024. We determined if the death occurred within an area covered by an avalanche forecast, outside of an area covered by a forecast, or at a location where the forecast was not applicable. Existing forecasts cover approximately 3% of the mountainous terrain in the United States, but almost 80% of the avalanche fatalities occur in those areas. Fatal avalanche accidents have high spatial autocorrelation and are tightly clustered. Most clusters are encompassed by the existing avalanche forecast area. Clusters outside current areas are where new efforts could have the greatest impact. The spatial structure also suggests potential scales for forecast coverage.

Living With Water was a collaborative, community-engaged disaster research project in Seattle's Duwamish Valley that aimed to identify and develop flood adaptation strategies that respect and incorporate local values. In December 2022, unprecedented flooding of the Duwamish River damaged more than 40 households in the South Park neighborhood, prompting the Duwamish River Community Coalition to partner with the University of Washington on flood adaptation research. This poster highlights the importance of including community perspectives in planning for climate-related hazards and best practices for pursuing interdisciplinary, intersectional disaster research. Through a multi-method approach involving a literature review, community interviews, and community workshops, the project team developed deliverables including a list of flood adaptation strategies and a conceptual map of where flooding solutions could be located within South Park. The team identified community members' strong preference for nature-based solutions over gray infrastructure solutions. Community members also demonstrated a deep attachment to the South Park neighborhood and a desire for solutions that allow them to stay within their community. The results of this study will inform local government representatives and community members about community flood adaptation priorities, ideally facilitating the development of flood adaptation plans that integrate community priorities.

The progress of permanent housing recovery is inconsistent. Numerous studies have indicated that housing types, disaster damage levels, and the socioeconomic factors of households significantly influence the recovery process. However, most research utilizes the damaged structure rather than the household as the primary unit of analysis, making it relatively difficult to identify the impact of different recovery pathways on the overall timeline. This poster describes a study conducting a survey in 2024 of households residing in red- or yellow-tagged housing following the 2016 Meinong earthquake or the 2022 Taitung earthquake in Taiwan. The data collected included recovery duration, recovery pathways, housing types, and household socioeconomic characteristics in order to analyze the effects of these variables on the recovery process. The analysis reveals that the chosen recovery pathway has a significant impact on duration: households opting for in situ reconstruction require more time than those who choose

As federal disaster recovery programs expand in scale, duration, and administrative complexity, understanding how governmental capacity shapes post-disaster recovery performance is increasingly important for natural hazards governance. This poster describes a study developing a longitudinal framework to measure governmental capacity in administering Community Development Block Grant–Disaster Recovery (CDBG-DR) funds and to assess its effects on recovery outcomes following Hurricane Harvey in Texas. Using quarterly data from 2018-2025, including HUD Disaster Recovery Grant Reporting (DRGR) narratives and Quarterly Performance Reports from the Texas General Land Office (GLO), we apply natural language processing (NLP) and large language models (LLMs) to extract city and county-level indicators of administrative capacity, institutional attributes, and implementation conditions. These measures are integrated with financial performance indicators—such as disbursed-to-obligated and expended-to-obligated fund rat

Disaster risk reduction systems face increasing pressures from climate extremes, conflicts, and fragmenting institutions. There is a critical need for a range of stakeholders to be involved in risk governance. This poster showcases how museums, as custodians of heritage, can contribute to disaster risk management systems by assisting as partners in strengthening disaster risk reduction across different cultural, urban, and community settings in sub-Saharan Africa. It also shows, however, that museums are often excluded from formal participation in risk management systems in the region. The study uses mixed-methods design, combining a review of disaster risk, cultural heritage, and governance literature with Geographic Information Systems (GIS)-based spatial analysis. Museums across Eastern, Western, Southern, and Central African locations are analyzed together with conflict intensity data to identify hazard exposure, spatial clustering, and gaps in preparedness. This approach supports coalition building by making risk visible across sectors and scales. Preliminary results show that museums in countries such as Cameroon, Mali, and Kenya are located in high conflict environments and face threats. In Zimbabwe, museums are vulnerable due to aging infrastructure, inadequate emergency planning, and minimal integrations into municipal disaster risk management processes. Across regions, fragmented governance and limited partnerships impact risk reduction outcomes. By positioning museums as underutilized but crucial partners in cross-sector coalitions for disaster risk management, this research advances disaster scholarship and contributes to inclusive governance frameworks. It also proposes a coalition-based approach, grounded by spatial risk analysis, participatory processes, and inter-governmental partnerships. This project contributes to building inclusive, multi-hazard coalitions that are capable of reducing systemic vulnerability and strengthening resilience. 

Emergency managers often rely on U.S. Geological Survey (USGS) communication products to inform first responders and public safety decision-making during disasters triggered by natural hazards. The USGS has organized landslide hazard response in the Landslide Assessments, Situational Awareness, and Event Response Research (LASER) project established in 2023. One objective of LASER is to create standardized communication products to support response operations and increase the public's understanding of the hazards. LASER has responded to over one dozen landslide events since 2023, including the widespread landsliding caused by Hurricane Helene in Appalachia in 2024. During the Hurricane Helene landslide hazards response, emergency responders indicated the need for informational handouts, prompting the creation of a landslide safety fact sheet. Additionally, residents in other landslide-affected areas have expressed to field reconnaissance teams a desire for better landslide hazard information (for example, in Puerto Rico after the 2020 earthquake sequence) and would be served by fact sheets explaining what happened. LASER is developing informational fact sheets as part of its suite of response products. Fact sheets provide concise and accessible information for a variety of audiences that can be viewed online or printed for public distribution. In this poster, we outline the proposed suite of fact sheets and present prototypes. We are seeking feedback from potential users such as emergency managers, responders, and other scientists so that the final informational materials we release will be relevant and as beneficial as possible.

This poster describes research evaluating the cumulative impacts of land use policies on flood risk management in the Republic of Rwanda. The findings from this case highlighted lessons that may assist policymakers around the world with addressing some of the challenges of flood risk management through comprehensive land use planning and regulation in development contexts. Rwanda has ambitious development targets and aims to reach upper-middle-income country status by 2035 despite high levels of poverty and climate risk. The Rwandan National Land Use and Development Master Plan discloses concern for sustainability in the face of high population growth projections and an increasingly variable climate. The plan refers to land use efficiency as key to solving the “national spatial puzzle.” Policies describe designating the most productive and sustainable uses for its lands to support population growth, food production, and prevent losses due to natural and human-caused hazards. This study investigates questions of (a) to what extent flood and landslide risk reduction is incorporated into national land use planning and governance in Rwanda, and (b) the social, equity, and development implications of Rwanda's land use and flood risk management strategies. Plan evaluation and content analysis methodology was developed based in planning literature. Land use policies and planning documents were analyzed for impact on physical vulnerability to flood and landslide, along with influence on social vulnerability. Research found that land use policies generally target physical vulnerability reduction; however, policies also reveal concerns over effective enforcement mechanisms, desires to improve regulatory processes, and capacities.

The people who often best understand a local hazard context are those who live within it. Yet, residents' perceptions are difficult to capture in a way that helps local decision-makers develop equitable policies that align with and respond to residents’ needs. This poster describes research addressing this gap by exploring how modeling residents’ beliefs and perceptions can support disaster resilience in Southeast Texas (SETx). As part of the SETx Urban Integrated Field Lab, researchers conducted interviews with community members—including local government officials, nonprofit leaders, and community leaders—between August 2024 and August 2025. Twelve semi-interviews were transcribed and qualitatively coded for relationships among variables related to flooding and the direction and strength of each relationship. The coded relationships were then “mapped” into a Fuzzy Cognitive Map (FCM), a mental model that combines qualitative connections-based modeling with quantitative definition of causal relationships between variables. With the developed FCMs, we aim to highlight community-identified drivers of flooding, flood mitigation, and flood recovery to assist decision-makers in tailoring tools for equitable hazard mitigation (e.g., social vulnerability indices) that reflect local realities and facilitate the implementation of local mitigation measures. Next steps include meeting with interview participants to present the FCMs, receiving feedback on the accuracy of perceived relationships, and adjusting FCMs to align with participant perceptions. As preliminary observations, participants have emphasized a lack of adequate drainage—including aged storm sewer infrastructure and the generally low elevation of the region—and recent more intense precipitation patterns as challenges for flood mitigation.

Due to the prolonged nature of pandemics, they are more likely than other disasters to occur simultaneously with other emergencies, creating potential compound and cascading effects that risk societal disruption. This was evident during the COVID-19 pandemic, when the United States experienced both the burden of the pandemic and several other billion-dollar disasters (BDDs). Given the potential for multiple complex emergencies to overwhelm systems, this poster describes a study aiming to identify state-level characteristics that might increase the likelihood or severity of health and disaster impacts when these events occur concurrently. Publicly available data were analyzed to investigate health and disaster burden during BDDs throughout the COVID-19 pandemic (2020-2023) and to compare these impacts with a baseline of 2018-2019 BDDs. A database was compiled using the National Oceanic and Atmospheric Administration's BDD data, COVID-19 cases and deaths, all-cause mortality, electrical outages, and mobility data as potential indicators of burden and societal disruption. Each event was qualitatively classified for compound or cascading potential using multiple sources. These classifications and the compiled database were used in regression analyses to identify the relationship between state-level characteristics and the likelihood of experiencing significantly greater health and disaster burden associated with BDDs during the pandemic. From 2020-2023, 46 BDDs impacted U.S. states as 396 unique events. Events with cascading potential during the pandemic were rather rare (<15%) compared to compound events. The results of this study will help expand our understanding of the factors that lead to and exacerbate the likelihood and consequences of compound and cascading effects in the context of a pandemic.

This poster describes a study advancing disaster research by showing that displacement after disasters affects life recovery not only through housing loss but also through the disruption of livelihoods, everyday rhythms, and a sense of purpose in life. Focusing on the Great East Japan Earthquake of 2011, it demonstrates that displacement can lead to psychological distress and social isolation when ties between people, land, and daily practices are severed. Drawing on qualitative case studies based on fieldwork in tsunami-affected coastal communities, this poster examines how evacuation and relocation reshaped post-disaster lives. The earthquake forced many people to evacuate and relocate due to tsunami damage and radioactive contamination following the accident at the Fukushima Daiichi Nuclear Power Plant, separating them from the land on which their lives had been grounded. As described by Bourdieu as “uprooting,” displacement fundamentally transformed people's ways of living. The findings reveal that the loss of rural housing styles and livelihoods caused not only economic difficulties but also the erosion of ikigai (a sense of purpose in life) and the disappearance of the rhythms connecting land, body, and everyday practices. While post-disaster mental health discussions have often emphasized community rebuilding, this study highlights the importance of relationships with land and the natural environment as elements supporting life recovery. Reconstructing these relationships can itself function as a form of care, offering a more concrete understanding of long-term life recovery in post-disaster contexts.

Artificial intelligence (AI) is starting to play major roles in disaster prediction, response planning, resilience initiatives, and post-disaster resource allocation. However, rapid adoption of AI without ethical integration risks reinforcing existing social inequities in communities. This poster highlights designing ethical AI to serve the people equitably before, during, and after any disaster. This study will propose policies by examining how design decisions in emerging AI applications can either strengthen or diminish equity outcomes in disaster management. Investigating interdisciplinary research in climate-resilient infrastructure, emergency management, and human-centered design, this poster identifies the demands of a move toward inclusive innovation that incorporates the voices of the community, ethical oversight, and public policy frameworks. The analysis looks at three ways to ensure ethical results: evaluating the impact on equity during the design phase, creating governance structures that involve community members, and providing professional training that includes ethical thinking in engineering and public policy decisions. Methods involve comparing AI practices in reducing hazards and disasters, analyzing ethical guidelines, and creating policy suggestions based on human-centered engineering ideas. Preliminary findings show that AI systems developed without participatory oversight can reduce human agency, while those that embed community priorities enhance trust, transparency, and long-term resilience. By emphasizing inclusive innovation, this project contributes a practical pathway for aligning technological advancement with social justice, ensuring that AI enhances rather than undermines equitable disaster resilience. Ultimately, the purpose of this contribution is to advocate human-centered AI designs that place disadvantaged communities at the center of disaster resilience.

Gaps remain in our understanding of factors that contribute to the critical development and implementation of community partnerships related to public health emergency preparedness (PHEP), particularly following the COVID-19 pandemic. This poster describes a survey study of PHEP coordinators at local health departments (LHD) in Health and Human Services (HHS) Region 10 (Alaska, Idaho, Oregon, and Washington) which assesses contextual factors that are associated with PHEP community engagement. We developed a novel Community Engagement Scale (CES) to measure the level of community engagement activities among each LHD and adapted the Implementation Leadership Scale (ILS) to measure participants' commitment to community partnerships in PHEP. One-third (n=26) of LHDs within HHS Region 10 responded to our survey, including 17 from Washington, four from Oregon, and three from Idaho. Participants had approximately 5 years of experience on average in PHEP. The mean CES score was 13.4 out of 32, with a higher score indicating a greater number and frequency of community engagement activities. The mean ILS score was 30.1 out of 48, with a higher score indicating greater participant commitment to PHEP community engagement. Individual years of experience in PHEP was associated with commitment to community partnerships. This study provides a baseline assessment of engagement and partnership activities among LHDs in Region 10. While reliance on one person to sustain partnerships can be a barrier to sustainable community engagement, training early career professionals may support organizational commitment to community engagement in the absence of experienced professionals.

Cruise ports are highly susceptible to coastal hazards. Coastal hazards can be both widespread and region-specific, impacting the cruise industry in pre-disaster planning, during-event operations, and post-event recovery. The severity and frequency of these hazards will increase with climate change, presenting an essential need to understand the cruise industry's capacity, perspectives, and planning for cruise port resilience. This poster describes research which conducted a baseline, global survey of cruise industry practitioners to determine industry perceptions around coastal hazard impact to operations, future perspectives and concerns, and best practices regarding hazard impacts to ports, destination communities, and operations. In partnership with the Cruise Line International Association (CLIA) and a steering committee comprised of relevant industry experts, the survey yielded 89 usable responses from cruise ports, cruise lines, trade associations, and other relevant practitioners. Key findings incl

Standard pre/post property-value metrics often overstate post-disaster recovery by conflating rebuilding with background market appreciation. To estimate the true duration of housing recovery, we paired a donor-deflated counterfactual benchmark with survival analysis to track 42,639 storm-damaged homes on Staten Island following Hurricane Sandy. While nominal comparisons suggested recovery in about two years, trend-adjusted estimates indicated a realistic timeline of 5 to 6 years. Even after controlling for damage severity, recovery was faster on higher-income blocks (18.7% per quartile) and slower in predominantly nonwhite blocks (64%), with additional slowing observed for older housing stock and higher pre-storm values. Trajectories also diverged by damage level: moderate-damage properties sustained a persistent 16–19% value deficit, while severely damaged properties eventually exceeded baseline values, consistent with substantial reconstruction. These findings suggest housing programs should plan for support horizons of at least 5–6 years, with targeted assistance for moderate-damage properties and marginalized neighborhoods.

The increasing frequency and severity of extreme weather events such as flooding underscore the need to identify effective pathways for building property resilience. A devastating flood in central Texas exposed previously unrecognized vulnerabilities, threatening lives, infrastructure, businesses, and natural systems. Economic analysis by a local economist estimated approximately $1.1 billion in damage to residential buildings alone. Notably, most affected homeowners lacked flood insurance, leaving individuals to bear the full cost of recovery and influencing decisions about whether and how to invest in flood resilience measures. Previous studies hypothesize that flood risk perception acts as a mediating factor, translating risk information into adaptive behavior. Adaptive behavior is defined as actions taken before, during, or after flood events to minimize anticipated or realized damages. However, a critical question remains: why do heightened risk perceptions often fail to generate sufficient adaptive a

Sea-level rise and recurrent coastal flooding threaten coastal infrastructure and the fiscal stability of local governments that rely heavily on property taxes. Most local risk assessments focus on direct inundation and overlook service isolation when road disruption cuts off access to parcels outside flooded areas and accelerates property devaluation. This poster describes a study developing a parcel-level exposure framework that quantifies both inundation and isolation under different sea-level rise scenarios. We apply the framework to two regions with extensive low-lying development and historically constrained fiscal capacity: Southern New Jersey (Salem, Cumberland, Cape May, and Atlantic Counties) and Maryland's Eastern Shore (nine counties). Using parcel and land-use data, we assess how exposure expands when isolation is included and where risk concentrates across residential, commercial, and critical community-serving parcels. Across both regions, our findings show that isolation substantially affects more parcels than inundation alone, indicating broader long-run tax-base and service-delivery risks. Roads and access often fail before widespread flooding occurs, so many parcels become “cut off” at low sea-level rise thresholds (about 2–4 feet). Our spatial analysis indicates distinct patterns across the two states. In New Jersey, exposure emerges early and saturates quickly, driven largely by residential parcels, whereas in Maryland, exposure increases in stages. Overall, results show that fiscal and service-delivery risk can extend far beyond parcels that flood directly. Findings can help planners identify infrastructure and tax-base vulnerability earlier in the sea-level rise timeline and target adaptation actions before widespread inundation.

Coastal agricultural communities have unique strengths and challenges in responding to extreme weather, sea level rise, drought, and other hazards. Many resilience initiatives struggle to engage these communities at the intersection of climate and agricultural concerns due to gaps in resources, trust, and knowledge. Cooperative extension systems are uniquely situated to be effective partners in building climate resilience in rural coastal communities. As the community-based education partnerships of land-grant universities, extension systems have a long history of providing collaborative education and assistance to address agricultural, environmental, and community development problems. This poster describes a project aiming to understand and enhance the capacity of cooperative extension programs to build climate resilience in agricultural communities in coastal Delaware, Maryland, and Virginia. Through interviews with extension professionals, we are examining how resilience strategies are currently incorporated into agricultural programming and identifying factors that enable or constrain this work. Preliminary findings highlight key strengths, including strong relationships with producers and specialized crop expertise, as well as common challenges related to regional information sharing, coastal hazard knowledge, and risk communication. This study contributes to a larger effort to build agricultural community resilience through the National Oceanic and Atmospheric Administration's Climate Resilience Regional Challenge. By documenting current successful strategies, as well as barriers extension agents face, findings will inform the development of tools and training designed for extension systems’ needs. More broadly, this research offers future directions for university extension systems aiming to become stronger partners in climate adaptation and disaster risk reduction.

National estimates of landslide losses in the United States largely rely on studies conducted more than four decades ago, limiting the ability of scientists, emergency managers, and decision-makers to evaluate current risk, quantify impacts, and assess mitigation benefits. In response to this information gap, the Landslide Loss Interest Group (LLIG) was established in 2025 under the U.S. Geological Survey-supported National Landslide Hazard Risk Reduction (NLHRR) Working Group, in support of national priorities to improve landslide loss understanding and reporting. This poster highlights the group's first-year accomplishments and key takeaways, demonstrating progress towards a more comprehensive understanding of landslide loss and identifying critical challenges that remain. The LLIG is a multidisciplinary working group convening quarterly, with members from federal and state agencies, emergency management, transportation, academia, and the private sector. In its first year, the group advanced three core objectives: (a) identifying scientific and operational uses of landslide loss information, (b) developing best practices for transparent and consistent data collection and management, and (c) exploring opportunities to improve data compatibility nationwide. By the end of 2025, the LLIG produced two key deliverables: a documented matrix of known and potential uses of landslide loss data and an inventory of agencies and partnerships currently collecting or applying such information. Discussion revealed persistent challenges, including variable definitions, inconsistent reporting, limited institutional capacity, and barriers to accessing privately held data. These findings underscore the need for standardized, decision-relevant landslide loss datasets to support effective hazard risk reduction.

Communities face rising disaster risks, and resilience has become a central concept for understanding and planning recovery. Existing metrics capture key dimensions—such as infrastructure strength, social cohesion, and economic stability—and public agencies increasingly rely on these measures to guide investments. But most indicators remain siloed by discipline and data type, making it difficult to see how social, economic, and physical systems interact to shape real outcomes. As a result, resilience is often treated as an abstract ideal rather than an operational tool. This poster describes research which develops an AI-informed framework for integrated resilience metrics that unite socioeconomic, infrastructural, and hazard-exposure data. Implemented through the APRED Platform (Analysis Platform for Risk, Resilience, and Expenditure in Disasters), the framework produces transparent, reproducible indices that better align with disaster loss and recovery outcomes—advancing more equitable, data-intelligent decision-making for resilience planning.

Children in foster care who have experienced disasters represent a uniquely vulnerable population often overlooked within traditional emergency management frameworks and not previously included in research on children and disasters. While emergency plans frequently categorize residents into broad, generalized groups, this approach fails to recognize the complex subpopulations within a community, such as foster families, who face distinct needs, risks, and legal restrictions that biological families may not experience. This research poster highlights the critical need for emergency managers to move beyond one-size-fits-all planning and instead acknowledge foster youth and families as a specific subcategory requiring adjusted preparedness, response, and long-term support strategies. By understanding the extensive differences and assets foster families have, emergency managers can create more equitable, inclusive, and effective disaster systems that reflect the diverse realities of the communities they serve. 

To what extent can regression and classification models explain census tract-level insured housing losses, and can models developed for one event be applied to another in the same location, or even an event in a different location? This poster describes a study addressing a key limitation in how flood impacts are compared and used for post-disaster decision-making. Using National Flood Insurance Program (NFIP) claims data, we analyzed 6,065 census tracts affected by the 2016 Tax Day Flood, 2017 Hurricane Harvey in Texas, and 2017 Hurricane Irma in Florida. We developed a unified hazard, exposure, and vulnerability (HEV) framework to explain and predict disaster impacts by combining sustained rainfall with pre-disaster exposure and social vulnerability indicators. Comparing cross-event regression and classification performance across linear, spatial, and ensemble models, we determined that ensemble methods consistently outperformed linear models for within-event prediction, while spatial lag regression impr

Large-scale investigations of the human health consequences of floods frequently rely on binary indicators that exhibit temporal variation over coarse spatial scales. On the other hand, computationally intensive hydrologic and/or hydraulic simulations have traditionally been used to generate detailed flood depth profiles that are temporally punctuated and spatially restricted, with a focus on specific events over smaller geographies. Probabilistic flood model simulations have been used to bridge the gap between these two approaches, collapsing over time to estimate depth exposures on different return periods at decision-relevant resolutions. However, many of these products are proprietary, which has thus far inhibited their widespread application to epidemiologic analyses and community-scale adaptation planning. Here we document the results of a large-scale assessment using open-source information. We analyze the intersection of projected inundation on different return periods from the Copernicus Emergency

As climate impacts become more visible and pressing, understanding household response to such pressures increases in importance. This poster describes a study seeking to understand how disaster aid programs shape post-disaster migration patterns. Using Hurricane Harvey as a case study, this study analyzes the role of disaster aid programs in exacerbating or attenuating population movement after disaster in Texas. Specifically, this research reveals how different levels of distribution of disaster aid—including support from the Federal Emergency Management Agency Individual Assistance (IA) and Public Assistance (PA) programs, Small Business Administration (SBA) loans, and National Flood Insurance Program (NFIP)—are associated with migration patterns post-disaster. To track population movement, the Internal Revenue Service (IRS) migration data is used at the county level from two periods: 2015 to 2017 for the pre-disaster period and from 2017 to 2019 for the post-disaster period. The analysis compares differ

Managing debris left behind by disasters is one of the most important steps in the disaster recovery process. The substantial threats disaster debris poses to the environment, public health, and safety make it a significant challenge for those involved in disaster management. Disaster debris management is a complex task due to the range of activities involved, including debris collection, sorting, transportation, and disposal, as well as the multiple levels of government, community groups, and private contractors involved in the process. Thus, effective debris management plays a critical role in post-disaster recovery, yet limited attention has been given to residents’ experiences and perceptions of cleanup processes following major events. This poster describes a study employing a household survey to examine perception and satisfaction with debris management after Hurricanes Helene (September 2024) and Milton (October 2024) in Florida. The survey instrument asks residents about their experiences with disaster debris, including the debris type and amount encountered,  their access to information and understanding of sorting and disposal procedures, and their interactions with local officials. Furthermore, we assessed their perceptions of timeliness, fairness, environmental safety, and satisfaction with debris removal services. Lastly, we analyzed demographic differences of disaster debris cleanup across different communities. By analyzing these dimensions, this study aims to identify key drivers of satisfaction and equity in disaster debris management, highlighting gaps in communication, accessibility, and disposal practices. The findings will contribute to developing more inclusive, transparent, and efficient post-disaster debris management policies that strengthen community resilience to future disaster events.

The National Landslide Hazard Reduction Program is a coordinated Federal effort to reduce landslide risks and losses in the United States. Created in 2021 by the National Landslide Preparedness Act ("the Act"), the Program aims to bolster national capacity to assess landslide hazard and risk; coordinate landslide risk reduction activities; prepare and plan for landslide impacts; and respond to landslide events. The U.S. Geological Survey (USGS) is the lead Federal agency for Program implementation. To support implementation, the Act establishes two new coordination bodies: (a) The Interagency Coordinating Committee on Landslide Hazards (ICCLH), with representation from multiple federal agencies whose mission space includes landslide hazard and risk; and (b) the Federal Advisory Committee on Landslides (ACL), which is composed of external advisors from state, tribal, territorial, and local geological and emergency management organizations, academic institutions, and the private sector. The ICCLH ensures coo

This project advances hazards research and practice by developing a conceptual, operational framework for subnational government capacity specific to long-term housing recovery—the arena where coalitions among state, local, nonprofit, and community partners must function over years. We address the long-recognized gap between calls for “capacity building” and the absence of a precise, housing-focused definition that can be used to organize efforts, target assistance, and evaluate progress. Our aims are to: (a) clarify what capacity means for housing recovery within U.S. federalism; (b) distinguish housing recovery needs from short-term response; (c) identify government capacity components essential to housing recovery; and (d) propose measurement of these concepts and components. We have conducted a targeted review of more than 50 years of interdisciplinary scholarship and approximately 20 original interviews with local officials, planners, and recovery managers from two contrasting cases: the 2018 Camp Fir

Preparing climate change action plans is a complex, data-driven, and contextually specific endeavor aimed at preventing losses to people, habitats, and places. With advancements in computational capacities and access to large language models (LLMs) trained on granular climate data, the question remains: can planners use LLMs to write their plans, and what are the implications for the quality of such plans? We take an exploratory step in this direction by asking ChatClimate, ClimateGPT, and ChatGPT to write portions of a Heat Action Plan for two cities in Arizona: Tucson and Flagstaff. Using the recently published and award-winning 2024 Tucson Heat Action Roadmap as an example of a high-quality plan, we compared the quality of both plans. We organize our findings around two questions: (a) How does the quality of a heat-action plan prepared by climate LLMs compare with the original? And, (b) What types of information are needed to improve the quality of the climate LLMs plan? The contribution of this study is twofold. First, this is a novel systematic investigation into the implications of relegating plan-making to current open-access LLMs. Second, we project data adjustments needed in LLMs to prepare a high-quality heat action plan.

Disaster risk is shaped not only by extreme events but also by everyday infrastructure systems that influence access, mobility, and health. In Jacksonville, decades of auto-oriented transportation planning have produced disconnected neighborhoods where many residents—particularly in historically marginalized Black communities—face persistent barriers to reaching schools, healthcare, and other public resources. These conditions are especially evident in Health Zone 1, where hurricanes and flooding intersect with long-standing social and health inequities. Many disaster risk reduction and infrastructure planning efforts rely on technical assessments that overlook lived experience and the social consequences of resilience-oriented investments. In Jacksonville, these limitations are becoming visible alongside the development of the Emerald Trail, a citywide green infrastructure project intended to improve connectivity and environmental performance. While similar projects elsewhere demonstrate benefits such as stormwater management and active transportation, they also reveal risks of displacement, rising property taxes, and green gentrification when equity concerns are not addressed. This poster presents ongoing participatory action research conducted as part of the NSF-funded project Community-Centered Modeling of Housing-Related Health Disparities. The project engages residents, community organizations, planners, and researchers through workshops and dialogue that position residents as co-interpreters of risk rather than passive stakeholders.  The work is generating shared problem definitions and building a platform for more inclusive infrastructure decision-making, offering insights for other cities navigating climate adaptation and social inequity.

Community outreach and education are essential components of emergency management, building trust and preparedness among residents and developing future workforce capacity. However, few programs are intentionally designed for youth using a simulation-based learning method. This poster presents work from a study on the Model Emergency Operations Center (ModelEOC) program, developed by the Sonoma County Department of Emergency Management, to introduce high school students to emergency management through an immersive, experiential summer learning experience. Using a qualitative research design (n=15), findings highlight key program components, including funding strategies, recruitment, scheduling, and instructional methods. Results show that the ModelEOC program increases participant understanding of their community emergency management system and fosters civic engagement and awareness of careers in public service after graduation. 

The issue of representativeness in social network interactions (e.g., social media) has long been a concern within the field of disaster informatics. The lack of alignment between the demographics of these platforms and broader societal demographics presents a significant challenge for using social media in incident detection and making analyses applicable to entire regions. This poster describes a study addressing this gap by administering a national survey designed to capture detailed sociodemographic information from individuals who report on social media usage during disasters. Utilizing the Prolific platform, the survey will recruit a sample that is representative across all FEMA regions. This approach enables the creation of a pilot, community-scale dataset that provides insight into which sociodemographic groups commonly use social media during disasters, how and why they use it, and who may be underrepresented or absent in commonly used digital datasets. Guided by this design, the study examines (a) how sociodemographic factors (i.e., location, gender, race/ethnicity, age, income, education) and prior disaster experience influence patterns of social network interactions during hazard events (e.g., panic buying); (b) how these characteristics shape perceptions of social media as a disaster information source (i.e., trust, credibility, and mis- and dis-information); and (c) the selection of communication channels and platforms for disaster risk communication. Findings will help enrich future disaster research and practice by providing a clearer understanding of who uses social media during such events, enabling researchers to better account for demographic variation when interpreting or designing social network-based analyses. 

This poster describes research examining the gap between perceived and measured water quality in privately owned wells along the Texas Gulf Coast, where groundwater over-extraction, land subsidence, rapid urbanization, and natural disasters all intersect. Natural disasters, among many other challenges, perpetuate the difficulty of ensuring groundwater resource sustainability across the expansive Gulf Coast Aquifer subsurface system. In this study we aim to advance hazards and disaster research by assessing whether private well stewardship (i.e., private well owners) can accurately determine whether or not their water is potable, or whether perception-based stewardship is inaccurate for measuring risk. This is accomplished through survey analysis in which private well stewardship perceptions are compared to in situ measurements from privately-owned wells located in Galveston, Harris, Calhoun, Jackson, and Matagorda counties. Water samples are tested using critical physical, biological, and chemical indicators associated with a higher likelihood of post-disaster groundwater degradation, including salinity and other water quality parameters. Previous studies indicate that private well-owners tend to overestimate or underestimate the quality of water their private wells contain, leading to misguided perceptions of assuming their well water is safe for human consumption. The gap between perception and measurements of water quality is important to discern for hazards and disaster research because current water governance supports private well stewardship placing the responsibility of water quality solely on the private-well owners. This study highlights the importance of habitual testing, knowledge of water quality standards, risk communication and perception, and governance strategies for groundwater resource sustainability in a hazard-prone coastal region. 

The Rohingya refugee crisis in Cox's Bazar since 2017 has posed profound challenges for information and knowledge management (IKM) in humanitarian operations. This poster describes a study examining these challenges through qualitative research with stakeholders across government agencies, NGOs, INGOs, UN bodies, diplomats, and media. Findings highlight persistent gaps in professional capacity, technological infrastructure, coordination, and uncertainty management, revealing a disconnect between IKM theory and practice in protracted humanitarian settings. By combining stakeholder perspectives with official reports, the study advances a more grounded understanding of how knowledge circulates across humanitarian systems. The poster concludes with recommendations for adaptive governance, inter-organizational learning, and digital innovation to strengthen IKM in complex refugee responses.

Even while there is evidence that climate change has increased the frequency and intensity of natural hazards across the United States, individual and household preparedness in the country remains alarmingly low, with a significant gap between risk awareness and actual protective action. In this systematic review of preparedness indicators in the United States, we identified that widely used preparedness indicators can be categorized into four primary domains (a) Resource and Action-Based, (b) Socio-Demographic, (c) Psychological and Cognitive, and (d) Community and Social. In addition, findings also highlight theoretical frameworks including Protection Motivation Theory (PMT), Protective Action Decision Model (PADM), and information-seeking theories that explain motivations, attitudes, and actions associated with disaster preparedness. This study reveals whether existing metrics adequately capture the full scope of household preparedness by identifying missing dimensions that are essential for translating preparedness into practice. Rather than relying solely on a checklist of preparedness indicators, this study demonstrates factors that standard indicators often fail to incorporate, that is, how each variable reflects underlying systemic vulnerabilities and household capacity to prepare for disasters.

This poster describes research filling the gap of current flood-related risk studies by quantifying the often-overlooked secondary risk of flood-induced waste contamination, revealing critical environmental disparities in the coastal industrial hub. By integrating spatial modeling of potential waste contamination threats with neighborhood-level socioeconomic and demographic data, this research provides a framework for identifying high-risk regions that require prioritized mitigation and environmental impact reduction action. These findings highlight the necessity of addressing the subsequent mobilization of residues from waste management facilities to ensure the disaster resilience of communities. For the analysis, this research employs a spatial risk assessment framework centered on Corpus Christi, Texas. First, the probability of flood-induced waste contamination at the parcel scale was quantified by measuring the proximity to waste management facilities that are at risk of floods. These quantified hazard probabilities of each parcel were then overlapped with the neighborhood-level demographic and socioeconomic characteristics at the block-group scale, which represent vulnerability. The results effectively mapped comprehensive risks, exhibiting environmental disparities and showing disadvantaged neighborhoods in need of prior attention. This data-driven approach can significantly enhance the awareness of contamination risks for both municipal stakeholders and the general public, providing a more robust foundation for inclusive disaster planning and practice.

Large-scale disasters often produce uneven and prolonged recovery processes. In depopulating regions, recovery may be further constrained because returning to pre-disaster conditions is not always feasible. Empirical evidence is still needed to identify the factors shaping recovery trajectories and to clarify what forms of recovery are desirable in regions facing population decline. This poster reports preliminary findings from a large-scale resident survey conducted in the depopulating city of Wajima, Japan, following the 2024 Noto Peninsula Earthquake and a subsequent flooding event. In November 2025, a self-administered questionnaire was distributed to 14,300 residents aged 18–79 listed in the municipal resident registry. A total of 7,762 responses were collected (response rate: 54.3%). The survey covers residents’ sociodemographic characteristics, housing damage and bereavement, post-disaster employment and economic conditions, living environments, self-reported recovery, and pre-/post-disaster community resilience factors (e.g., community resources, social ties, leadership). 

Descriptive analyses reveal substantial disparities in self-reported recovery. While 23.4% of respondents reported that their daily lives had “completely” or “almost” returned to pre-disaster conditions, 70.1% indicated “halfway,” “partial,” or “no recovery,” suggesting widening gaps. Perceived neighborhood recovery was markedly lower: only 5.1% reported that their pre-disaster neighborhoods had largely recovered. Notably, even among respondents who reported substantial recovery of daily life, more individuals expressed uncertainty about their future lives than those reporting clear prospects, indicating widespread anxiety amid slow neighborhood recovery. Furthermore, 61.8% of respondents supported a recovery vision that embraces change and adaptation to post-disaster conditions, exceeding preferences for restoring (16.5%) or surpassing (14.2%) pre-disaster conditions.

Urban flooding is becoming increasingly frequent in rapidly urbanizing cities, where intertwined hydrological, infrastructural, and governance systems shape household vulnerability and preparedness. Protection Motivation Theory (PMT) is widely used to explain why individuals adopt protective behaviors, yet its focus on threat and coping appraisals can limit its usefulness in contexts where responsibility for protection is fragmented and adaptive capacity is shaped by socio-spatial inequality. Building on recent PMT extensions that incorporate ownership appraisal (households’ perceived responsibility for flood protection), this study advances PMT by integrating spatial dimensions of flood exposure. Drawing on primary household survey data collected between August and September 2025 (administered in English and Kannada) from 316 respondents across ten high-risk flood zones in Bengaluru, India, this poster examines how socio-economic characteristics, perceived severity and susceptibility, coping efficacy, governance trust, and localized flood experiences shape preparedness. Methodologically, this study combines qualitative thematic analysis with elastic net modeling and regression to assess which households adopt structural actions, non-structural actions, or take no action, and how these responses relate to spending patterns. Spatial variation in preparedness and flood experiences is examined through cluster-level proportional mapping across survey sites. Together, these approaches highlight how household disaster preparedness is shaped by behavioral perceptions.

Post-disaster housing recovery is often viewed as a resource problem; however, the timing of funds is just as critical as the total amount. Despite billions of dollars in federal aid for Hurricane Harvey, the rebuilding of single-family homes in Texas faced a long period of slow progress. This poster describes research investigating the “Reconstruction Gap,” defined as a systemic funding discontinuity where the transition between short-term relief and long-term programs leaves households without accessible funds. To analyze this, we developed a System Dynamics model to simulate the 8-year recovery timeline from 2017 to 2025. The model organizes funding into three streams based on time: (a) immediate relief via Federal Emergency Management Agency (FEMA) and insurance, (b) bridge financing via Small Business Administration (SBA) disaster loans, and (c) long-term recovery via Community Development Block Grants for Disaster Recovery (CDBG-DR). Using data from OpenFEMA, SBA records, and the Texas General Land Office, this approach explicitly incorporates the 15-month administrative lag often observed in long-term grant implementation. Initial simulations show a structural issue in the recovery timeline. Access to bridge loans diminishes before long-term grants become fully available to homeowners. This creates a temporary gap that slows reconstruction momentum between the response and recovery phases. The model suggests that remaining unmet needs are caused not just by a lack of money but by these implementation delays which limit the effective use of funds. By looking at the flow of money over time rather than just the total cost, these findings help policymakers predict when reconstruction might stall. The study emphasizes the need for better coordination to bridge these gaps.

Across Minnesota, climate change is driving an increase in average temperatures, dangerously hot days, and warmer nights. Emergency managers, public health professionals, and other decision-makers need reliable data to help prepare for and respond to extreme heat events in a cold climate where extreme heat risk is often underestimated. U-Spatial, the University of Minnesota's center for geospatial advancement, and the Minnesota Department of Health (MDH) partnered to create a campaign that included maps and dashboards to communicate heat risk in Minnesota communities. By building on the current statewide U-Spatial Hazard Mitigation Planning program, the dashboards immediately connected MDH's heat risk messaging with a relevant audience. Minnesota's first-in-the-nation interactive county-level hazard mitigation plans will now include tailored extreme heat information in their hazard mitigation planning websites. This collaboration also streamlines and ensures consistent communication across Minnesota state agencies regarding extreme heat risks through the use of shared data and research. The resulting dashboards incorporate data from the National Weather Service's HeatRisk tool, future climate projections from the University of Minnesota Climate Adaptation Partnership, data on heat-trapping surfaces, and nearly 20 indicators pertaining to health, exposure, socioeconomics, and socio-demographics. This poster will illustrate the indicators selected to demonstrate risk from extreme heat and examine the intended uses of the dashboards, including their incorporation into county-level hazard mitigation plans.

Post-disaster recovery plans routinely promise outcomes that are equitable, resilient, and risk-reducing, yet disaster recovery scholarship emphasizes that these outcomes do not flow automatically from planning language. Instead, equity and resilience are shaped by how recovery programs are designed, sequenced, and implemented through eligibility rules, prioritization criteria, administrative capacity, and the timing and geography of funded projects. This poster examines whether Lee County's post–Hurricane Ian Community Development Block Grant for Disaster Recovery (CDBG-DR) commitments on equity, resilience, and mitigation are reflected in the County's allocation of that funding for its recovery project portfolio. Using a mixed method approach and historical archival analysis we assess alignment between those goals and funding allocation across three dimensions: (a) project type mix (housing versus infrastructure, planning, and public services), (b) spatial allocation (coastal and tourism areas versus in-land renter-heavy and lower-income communities), and (c) timing (time-to-award and time-to-implementation). We coded various types of Lee County's CDBG-DR planning records—including procurements, action plans, and contracts—for stated priorities and decision rules and compiled a project-level dataset of funded activities, dollars, phases, and locations. By comparing stated commitments to observed project outcomes, this analysis identifies where recovery implementation aligns with equity goals and where tradeoffs or capacity constraints shape post-disaster housing recovery. 

Extreme weather-related climate events affect public transit, impacting travel behavior, human health, and quality of life. Transit agencies seeking to increase transit ridership as an efficient transportation measure must adapt to these events. Transit users are more vulnerable to extreme heat than people driving, as they mostly have to wait outside for their ride or walk/bike to and from transit stops. Here, we propose a study exploring transit agencies’ proactive efforts toward disaster-resilient transit facilities. We focused on the 50 largest transit agencies in 2021 based on ridership from the National Transit Database by the Federal Transit Administration. We examined how public transit agencies include disaster resilience strategies in their strategic plans, long-term transportation plans, sustainability plans, and other similar plans. Transit agencies adopt various short-term and long-term strategies for disaster resilience based on the type of public transit facilities and disaster experience. For rail services, transit agencies build sea walls, elevate critical facilities, relocate or harden critical infrastructure, install power transformers and sensitive power equipment, and implement other strategies. To implement these strategies, transit agencies focus on pre-seasonal and preventive maintenance, vulnerability assessment of infrastructure, increasing system redundancy, collaboration and coordination with other agencies and institutions, and other initiatives. Transit agencies are also adopting disaster forecasting tools (e.g., on-demand flood simulations) and early warning systems, emergency protocols, and management plans. This study can help planners and policymakers understand the major climate events that transit agencies face, their associated impacts, and the strategies used to address these issues.

Hurricane Ian triggered devastating physical damage in Southwest Florida and intensified the already brewing insurance affordability and accessibility crisis. This disaster generated massive claims, overwhelming insurers and revealed widespread underinsurance and uninsured losses. In the aftermath, many homeowners experienced insurance claims delays or had underpaid claims, while insurers responded by sharply raising premiums, increasing deductibles, tightening coverage, or leaving the market altogether. While the goal of insurance is to facilitate recovery by transferring the financial risk, the actual operation of the insurance system can fundamentally determine the course of recovery. This poster describes a study examining the mechanisms through which insurance dynamics shape housing recovery processes and outcomes following Hurricane Ian. Using post-Ian survey data from approximately 300 households and more than 20 household interviews in Lee County, Florida, the analysis focuses on three dimensions: (a) the effect of insurance coverage type and availability on recovery timing, (b) the relationship between payout delays, adequacy, and displacement duration, and (c) how these patterns differ among housing types, ownership structures, and socioeconomic conditions. We combine quantitative analysis with qualitative evidence from household narratives and historical archives to understand how insurance processes may translate into unequal recovery outcomes. This study frames insurance systems as a structural determinant of inequality in post-disaster housing recovery.

This poster presents the development and operationalization of a Community Well-Being Index (CWBI) designed to evaluate the spatial heterogeneity of community resilience, environmental cumulative impact, and resource accessibility within Louisiana at the census-tract level. Seventeen indicators across social, environmental, economic, infrastructural, and health domains were synthesized using a GIS-based framework with standardized normalization and adaptable weighting framework to accommodate local priorities. Empirical application of the CWBI across Louisiana revealed significant geographic disparities, with zones of concentrated socio-environmental burden exhibiting strong correlations with adverse health outcomes, climate hazard exposure, infrastructure inadequacy, and economic distress. To bridge the gap between technical assessment and policy implementation, the framework incorporates interactive visualization modalities such as dynamic dashboards and community-specific scorecards, facilitating the translation of complex spatial data into actionable intelligence. The CWBI effectively distinguished gradients of community resilience and risk, enabling identification of priority intervention zones. An embedded monitoring framework supports longitudinal tracking of community conditions and policy outcomes. Results indicate the CWBI's utility as a scalable decision-support instrument for equitable resource allocation, climate adaptation planning, and targeted community development strategies.

The National Weather Service (NWS) is training an in-house artificial intelligence (AI) model to translate weather information from English into other languages almost instantly. This helps make sure that the nearly 68.8 million people in the United States who speak a language other than English at home can get the same life-saving information during extreme weather disasters. Working closely with the NWS, our team first trained the AI tool using tens of thousands of past English-to-Spanish forecasts so it could learn the proper context and terminology. We then tested the automated translation software with several NWS offices, where bilingual meteorologists reviewed translations and continued enhancing the model. Through these improvements, we managed to reduce translation time for certain NWS offices from up to an hour to just minutes, and improved accuracy drastically. Based on that success, we created similar machine translation models for other languages such as Mandarin, Vietnamese, French, and Samoan. To release experimental translated NWS products to the public, we used mapping tools to locate multilingual populations across the country and rolled out these materials in an efficient, strategic manner. Today, more than 30 NWS offices are using this system through weather.gov/translate. Our poster highlights the NWS AI Language Program from its infancy to present day and invites discussion on how AI-supported translation can be responsibly integrated into weather operations to share life-saving information more quickly and equitably.

ntal hazards. Understanding how climate risk is priced in housing markets, particularly how public availability of risk information influences buyer behavior is essential for hazard risk management and has gained increasing attention. This poster describes a mixed-methods study examining homebuyers’ risk information behaviors and how access to risk information influences their decision-making. Qualitative in-depth interviews were conducted with real estate agents in Washington and Elizabeth City, North Carolina, to understand risk disclosure practices, the impact of such disclosure on pricing, and the role of third-party websites in risk information disclosure. Quantitative aspects include geospatial data acquisition and analysis using descriptive statistics and Pearson's correlation coefficient. The Pearson's correlation coefficient of 0.115 showed a weak positive relationship, which indicates that high flood risk is associated with slightly longer selling times, though the effect is limited and other factors like price, condition, and demand matter as well. Qualitative results show that homebuyer behavior is shaped by past hazard experience, income, and physical condition of the property. Climate risk, particularly flood risk score, does not directly affect property prices in isolation; rather, insurance costs serve as the primary channel through which risk influences property values. Results report that buyers’ concerns focus less on risk itself and more on the financial implications of required insurance premiums. The findings show the importance of considering the influence of climate risk in housing decisions.

This poster describes a study exploring the experiences of older adults in the United States and other countries using longitudinal health and retirement surveys to assess possible risk factors for loneliness and social isolation with likely implications for disaster planning in local communities. To build upon last year's analysis of survey instrument questions used across a broader scope of countries, this research now uses the findings from those instruments across countries including the United States, England, India, Chile, and Northern Ireland from the Gateway to Global Aging as well as from the National Health and Aging Trends Study and the National Social Life, Health and Aging Project, among others. Although each of these countries faces a very different spectrum of hazards and demonstrates different approaches to emergency management, aging populations are a continued trend shared between them. Last year's project helped to highlight the potential variances between different cultures’ conceptions of loneliness and social isolation regarding the categorization of questions asked. This year’s research explores potential cultural differences in survey responses to overlapping or differing questions related or impacting social isolation and loneliness. Uncertainties regarding the magnitude and types of natural hazards in addition to shifts in funding approaches mean that household resilience takes on further economic significance for many local communities. The increased share of older adults in populations living on their own necessitates a better understanding of social connectivity as well as the constraints and challenges faced by older adults to help communities better allocate resources for disaster preparedness.

This project aims to influence United States climate and labor discourse and action to center care and domestic workers as holders of critical knowledge and experiences regarding climate-related disasters. Care work—elder care, childcare, care for disabled people, domestic work, and more—is life-sustaining work that too often is invisibilized, unpaid, and under-resourced. Care workers also serve as first responders during climate emergencies but are excluded from federal resource allocation, decision-making power, and benefits. To address this issue, we will conduct interviews with care workers and complete a review of gray literature to collate testimony, build evidence, and support clear recommendations for policymakers. Care work is overwhelmingly done by immigrant women, women of color, and gender-expansive people of color. Care workers continue to struggle and mobilize for fair pay, anti-discrimination protections, and basic labor rights. For migrant care workers, the fear of deportation or detention often prevents them from seeking or accessing resources, further marginalizing these communities in unionizing or labor rights struggles. To advance racial, gender, immigrant, and economic justice, care infrastructure must experience meaningful public investment that creates the conditions for well-paid, safe and healthy, and dignified care jobs. In turn, we intend for recommendations from this project to be focused on creating safer working conditions and honoring care workers’ expertise as workers on the frontlines of climate impacts. This poster presentation will highlight emergent themes of this timely research.

This poster describes research developing two complementary artificial intelligence (AI) agents that link long-term recovery measurement with documented recovery practice using outputs grounded in official sources. Disaster recovery unfolds over years, and trajectories vary widely by locality, local government capacity, and longstanding disparities. Yet recovery is often operationalized through administrative timelines or program windows, such as periods during which federal assistance is authorized, which may not reflect whether households, neighborhoods, or infrastructure systems have substantively recovered. The first agent focuses on recovery measurement. It estimates place-based recovery trajectories by synthesizing longitudinal evidence, including aggregated and microdata from the U.S. Census Bureau, parcel and property records, satellite imagery, and selected social media signals. The agent draws on Recovery Support Functions (RSFs) to organize these sources into recovery dimensions and to identify cases where measured recovery patterns diverge from administrative timeframes. The second agent supports practitioners as they plan and carry out recovery activities by grounding responses to practice-oriented recovery questions in a curated corpus of official disaster recovery guidance and providing references for verification. We evaluate the measurement agent by checking whether estimated trajectories respond to changes in key indicators over time, and we evaluate the guidance agent by checking whether each answer is supported by retrieved passages and their document references. Together, these agents aim to strengthen how long-term recovery is assessed and communicated across communities and to connect recovery measurement to actionable, documented recovery practice.

This poster describes a study examining the longitudinal recovery trajectories of food insecurity in the Houston Metropolitan Area following the COVID-19 outbreak, utilizing data from CrowdSource Rescue, a nonprofit disaster relief service. Framing food insecurity through the lens of social vulnerability and resilience, we analyzed 37,555 service requests collected between March 2020 and December 2023. We employed Zero-Inflated Beta Regression to identify community characteristics predicting service usage and Growth Mixed Models to classify distinct recovery patterns. Results reveal that social vulnerability indicators, specifically race (Black and Hispanic populations), low income, unemployment, lack of vehicle access, and lower educational attainment, were strong predictors of both the likelihood and intensity of service utilization. The longitudinal analysis identified two divergent recovery trajectories: a “Highly Impacted and Slower Recovery” (HISR) class and a “Lower Impacted and Quicker Recovery” (LIQR) class. Communities in the HISR group were characterized by entrenched social vulnerabilities and persistent need, whereas LIQR communities rebounded more rapidly. Additionally, the LIQR took around 12 months to recover an 80% deficit, while the HISR took approximately 30 months to reach the same level. These findings underscore the critical role of adaptive nonprofit interventions and suggest that disaster recovery policies must account for structural inequalities to build long-term community resilience.

Ensuring the safety of nuclear power plants under earthquake hazards is a critical concern for the safe nuclear operation, as these facilities must maintain structural integrity under rare but intense ground motions. Seismic fragility analysis plays a central role in seismic probabilistic risk assessment, providing a quantitative measure of the probability of structural failure across different seismic intensity levels. The soil also exhibits significant spatial variability, which has an important impact on evaluating the seismic performance of nuclear power plants under earthquake hazard conditions. It is critical to incorporate both seismic and geotechnical uncertainties into probabilistic analyses of nuclear power plants. The poster aims to present a probabilistic framework for risk and fragility analysis for nuclear power plants equipped with periodic foundations under earthquake hazards, considering the combined uncertainties of ground motions and soil properties using Monte Carlo simulations. The seismic fragility curve is defined based on the variability of the performance of the nuclear power plants under different seismic hazard levels in a probabilistic manner. The seismic isolation performance of a layered periodic foundation composed of rubber and concrete materials is investigated through seismic fragility analysis. The results demonstrate that periodic foundations can enhance the seismic resilience of nuclear power plants under the uncertain seismic excitations and complex geotechnical conditions. The derived fragility curves for different seismic hazard levels in probabilistic manners can provide useful references for risk-informed design and management for enhancing the resilience of nuclear power plants in the face of earthquake hazards.

Consistent visitation from caregivers is critical for the well-being of nursing home (NHs) residents, yet extreme weather events increasingly threaten these vital connections. This poster describes a study aiming to examine how neighborhood climate vulnerability impacts caregiver visitation to NHs during extreme weather events. We analyzed 480 Florida-based NHs certified by the Centers for Medicare and Medicaid Services to determine the association between climate vulnerability in caregiver neighborhoods and NH visitation changes during and following Hurricane Ian (2022). Caregiver neighborhoods were identified through data-driven estimation of catchment areas based on recurrent visitation patterns over the prior two months. The outcome measure was the percentage change in visitation during Hurricane Ian compared to the prior eight-week average. We utilized the Climate Vulnerability Index to evaluate environmental, social, economic, and infrastructural factors, employing quantile regression models adjusted

This project describes an empirical modeling methodology using the City of Norfolk in southeastern Virginia to indicate areas of higher risk based on built infrastructure, property exposure, and temporal records of previous losses. Under this new empirical modeling methodology, a risk score is defined as the properties that may be at higher risk from future flooding events based on elevation differences, the number of flood insurance payouts a property has received, and whether a property has an active flood insurance policy. Results make evident how the methodology can be used to characterize a community's risk and highlight higher risk hotspots that can in turn be used for future resilience planning and hazard mitigation.

Asteroids are low probability-high consequence hazards. Since humanity has not experienced an asteroid impact in modern times, our understanding of asteroids in the emergency management context is limited. Our capabilities to address this risk remain grounded in conceptual theory. This poster describes a study which aimed to critically evaluate the presence of near-Earth objects (NEOs) in emergency management research and doctrine. A systematic literature search was conducted in emergency management related journals for articles relating to NEOs. Both qualitative and quantitative studies were subjected to meta-synthesis to uncover the deeper level of insights between the studies. The 123 articles resulted in 481 quotes, 42 codes, and four categories that inform two overarching themes. Our limited exposure is reflected within our policy and knowledge, as much of the literature only cursory mentions asteroids as hazards. While we understand that NEOs can be catastrophic, the exact principles on how to respond remain unknown. Instead, our conceptual knowledge attempts to coerce this unique hazard into preexisting concepts and standard operating procedures, which may hinder response and preparedness due to its scale and intense complexities. 

Near-Earth Objects (NEOs) are a low probability-high consequence hazard with potentially catastrophic impacts. The Chelyabinsk impact in 2013 and asteroid 2024 YR4 have brought planetary defense to the fore. There is, however, limited research that addresses perception of NEO risk, meaning that preparedness initiatives are based on differing understanding of the risks faced and limited modern experience, which compromises response efficacy. Preparedness begins at the local level and requires a global collaborative effort as the impacts of a NEO strike could overwhelm community lifelines, infrastructure, and local capabilities. As this poster describes, the aim of this proposed study is to critically evaluate how the public, emergency managers, and NEO subject matter experts perceive the risk of NEOs. The proposed study is informed by an inductive system of logic, social construction philosophy, web-based self-completed questionnaires, semi-structured interviews, and qualitative content analysis methodology. First, members of the public will be snowball sampled to participate in a web-based self-completed questionnaire relating to their knowledge, perception, and conceptualization of NEO risk. Second, local and state-level emergency managers and NEO subject matter experts will be snowball sampled for semi-structured interviews relating to their knowledge, perception, and conceptualization of NEO risk. Third, the resultant data will be analyzed using computer-assisted qualitative content analysis to determine differences in NEO risk perception and knowledge between the three participant groups. This proposed study will highlight the differences between the general public, emergency managers, and NEO subject matter experts to enhance planetary defense.

Natural hazards are substantial threats to the safety, economic well-being, and resources of U.S. communities. National assessments of societal exposure to natural hazards provide managers, planners, and policymakers at multiple scales with insights on where targeted studies, preparedness and mitigation plans, and outreach efforts may be warranted. The U.S. Geological Survey (USGS) has recently completed several national studies of societal exposure to natural hazards that may support local, county, state, territorial, and tribal risk-reduction planning. One national assessment in collaboration with the Federal Emergency Management Agency (FEMA) estimates population exposure, evacuation potential, and average annualized losses from earthquake-generated tsunami sources that threaten U.S. coastal communities. Another national study focuses on variations in earthquake-hazard exposure to U.S. residential populations with potential access and functional needs. A third national study characterizes landslide-haza

Extreme heat events have become increasingly frequent and intense due to climate change, posing significant risks to public health, labor safety, and urban operations. Local governments, positioned at the forefront of climate adaptation, play a critical role in implementing policies and coordinating resources to manage heat-related risks and enhance urban climate resilience. However, differences in governance strategies, institutional design, and policy instruments among local governments result in varying governance approaches and outcomes, which require systematic examination. This poster describes a study aiming to analyze the governance strategies, institutional arrangements, and challenges faced by local governments in responding to extreme heat events. It adopts literature review and comparative case study methods, selecting local governments that have implemented innovative heat governance policies. The study examines their institutional frameworks and policy instruments, including the establishment of Chief Heat Officer positions and the implementation of Heat Action Plans, and compares their governance structures and practices. Through cross-case comparative analysis, this study identifies key factors influencing the effectiveness of local heat governance from the perspectives of governance structures, collaborative mechanisms, and policy instruments. Based on these findings, the study proposes policy recommendations to strengthen local government capacity in managing extreme heat risks. This research contributes to the advancement of climate adaptation and local governance and provides practical insights for developing effective heat resilience policies.

Hazard mitigation planning efforts have the potential to shift prevailing paradigms toward addressing environmental justice (EJ) concerns and supporting disproportionately affected marginalized communities. However, substantial variation exists in the extent to which EJ considerations are integrated across different components of the mitigation planning process. Drawing on the theoretical concept of EJ, this poster describes a study analyzing 500 hazard mitigation plans from counties across the United States using a computational approach. Findings indicated that regarding human-centered EJ, greater emphasis has been placed on recognizational than on procedural and distributional by counties in the sample. This means counties are paying more attention to identifying risks but do not view participation from communities as important. In terms of environment, this emphasis shifts to distributional instead recognizational, demonstrating that localities are investing less into assessing environmental risks and focusing more on actions. This study extends the theoretical concept of EJ into examining counties’ work in hazard mitigation planning. Its findings show an uneven integration of EJ in different stages of planning work, pointing out missed opportunities in these efforts. Methodologically, this research provides insights into effective evaluations of large amounts of plan documents, particularly those enabled by federal mandates such as the Disaster Mitigation Act of 2000.  We developed an EJ-focused dictionary grounded in definitions, examples, and evidence drawn from academic literature and professional organizations, tested them on policy data, and conducted human validation to ensure analytical rigor.

While there are multiple disaster archives for singular events, including Hurricane Katrina and Hurricane Harvey, a large-scale repository of oral histories and narratives that spans disasters has not yet been organized. Our team has begun to elicit and organize narratives and oral histories from disasters across the world to develop a cross-cultural disaster archive. In this poster, we focus on describing the development of the archive, from generating an interview protocol to testing the protocol and data analysis strategies. We also discuss the different sampling strategies that will be used to populate the archive. As we work toward a public release, we envision an archive of disaster narratives that provides the opportunity for researchers to engage with oral histories and narratives of these events.

Concern about flood risk has increased worldwide in recent years. In Japan, climate change–induced increases in heavy rainfall have intensified river flooding. During the July 2020 heavy rainfall event, continuous torrential rain struck the Kuma River basin, causing severe damage in Kumamoto Prefecture, including 65 fatalities and more than 4,500 houses that were partially or completely destroyed. As flood risks are expected to further increase under climate change, the importance of ex ante flood mitigation measures, such as residential mobility, adaptive housing strategies, and insurance coverage for residential properties against flood disasters, has become increasingly recognized. This poster describes a study focusing on the purchase of insurance coverage for residential properties against flood disasters, including both private insurance and mutual aid–based schemes, as an ex ante risk management measure. The objective is to investigate the determinants and causal structure of decisions to purchase s

Buyouts seek to remove people from high-risk landscapes and convert the built environment to open space, with the understanding that local governments will manage them in ways that reflect community preferences and maximize ecological services. In practice, however, most land uses on post-buyout open space are developed ad hoc and without community input, resulting in land uses with limited social or ecological benefits. Using a socio-ecological systems (SES) lens that integrates the physical environment, ecosystems, social processes, and biodiversity, this poster describes a study that is among the first to examine the social and ecological dimensions of buyout property management across six counties in central Texas. Our approach includes four specific tasks: identifying ecosystem services in the six buyout land subtypes; quantifying ecological services using field and geospatial data; surveying peripheral communities to understand their perceptions of and engagement with the buyout properties; and interviewing key stakeholders to explore buyout property management challenges and best practices. Preliminary results suggest that consistent with previous studies, most buyout sites are vacant lots; fewer than 10% are used as gardens or for informal purposes. Despite the low utility of the open space, most surveyed residents felt the open space was well maintained; however, nuances exist regarding how the open space is currently used and valued. The findings from this study will serve as a guide for policymakers to better plan for buyout land uses, integrating community participation and preferences, and to formulate policies for future flood adaptation by conserving local ecosystem services.

Flooding is the most common and costly natural disaster in the United States. Climate change, rising sea levels, and changing precipitation patterns are increasing the number and intensity of extreme flooding events. Water treatment plants are often located next to rivers, making water treatment and distribution systems particularly vulnerable to flooding. Much of water infrastructure in the United States is aging, further compounding their vulnerability. Beyond physical damage that can halt water distribution, flood water can also contaminate drinking water, thus presenting both short-term disruptions and long-term public health risk, especially for marginalized populations as well as those residents who depend on private wells. In this poster, we assess the impact of Hurricane Helene on the drinking water systems and its distributive consequence in inland areas of Virginia and North Carolina. We identify data about public drinking systems and private wells, operational status, flood damage, socioeconomic

Research has revealed that heat events can adversely affect mental health, while the co-occurrence of heat with other hazards such as drought and wildfire can lead to impacts exceeding those of single disasters. Given the urgent need for adaptive strategies to extreme weather events and public health burden reduction, the role of greenspace has received increasing attention. However, evidence on the association between complex heat hazard exposure (e.g., recurring heat events, compound heat with other weather extremes) and mental health is limited, and the specific mechanisms through which greenspace may affect the mental health impacts of heat hazards are not well understood. This poster describes a study aiming to assess the association between complex heat disasters and mental health and to examine the moderating role of greenspace in this relationship. We measured heat-related hazards exposure, hospital visits for mental disorders, and enhanced vegetation index in Texas between 2015 and 2022. Our data analysis methods included a time-series analysis. The results suggest that complex heat disasters were associated with greater risks of mental diseases compared to single heat hazards. It is also indicated that higher levels of greenery could mitigate the mental health risks associated with heat-related hazards, with more pronounced protective effects for complex heat disasters. This study can provide evidence to guide disaster preparedness and public health strategies to support individual and community well-being and inform urban planning policies by highlighting greenspace as a modifiable factor in addressing the adverse mental health impacts of complex climate disasters.

This poster highlights a visualization-driven framework for assessing flood risk at youth camps in Texas, emphasizing fine-scale analysis from individual buildings to aggregated county patterns. Many camps span multiple land parcels, making boundary delineation critical for accurate risk estimation. To address this, we developed a Python-based “ripple effect” tool that integrates parcel data to reconstruct complete camp boundaries, ensuring comprehensive exposure analysis. Using the U.S. Army Corps of Engineers' National Structure Inventory (NSI), we examine building-level attributes such as construction year, location relative to 100-year and 500-year floodplains, and foundation type to evaluate structural vulnerability. These details allow us to move beyond parcel-level mapping and quantify usable land within flood zones, providing insight into how design and age influence resilience. Results are visualized through a GIS dashboard that enables parents and stakeholders to search for any licensed youth camp and review its flood risk before making enrollment decisions. This interactive platform enhances transparency and demonstrates how hazard data can be transformed into actionable tools for public use. At a broader scale, we aggregate findings to rank counties and reveal spatial patterns, including concentrations of risk along Texas’ Flash Flood Alley. By combining advanced geospatial techniques, building-level vulnerability metrics, and public-facing visualization, this work introduces a scalable approach for integrating hazard data into decision-making for youth-serving institutions.