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1. Spatial Accessibility Analysis of Emergency Shelters with a Consideration of Sea Level Rise in Northwest Florida

   https://doi.org/10.3390/su151310263  

   Yang, Jieya; Alisan, Onur; Ma, Mengdi; Ozguven, Eren Erman; Huang, Wenrui; Vijayan, Linoj (July 2023, Sustainability)

   Hurricane-induced storm surge and flooding often lead to the closures of evacuation routes, which can be disruptive for the victims trying to leave the impacted region. This problem becomes even more challenging when we consider the impact of sea level rise that happens due to global warming and other climate-related factors. As such, hurricane-induced storm surge elevations would increase nonlinearly when sea level rise lifts, flooding access to highways and bridge entrances, thereby reducing accessibility for affected census block groups to evacuate to hurricane shelters during hurricane landfall. This happened with the Category 5 Hurricane Michael which swept the east coast of Northwest Florida with long-lasting damage and impact on local communities and infrastructure. In this paper, we propose an integrated methodology that utilizes both sea level rise (SLR) scenario-informed storm surge simulations and floating catchment area models built in Geographical Information Systems (GIS). First, we set up sea level rise scenarios of 0, 0.5, 1, and 1.5 m with a focus on Hurricane Michael’s impact that led to the development of storm surge models. Second, these storm surge simulation outputs are fed into ArcGIS and floating catchment area-based scenarios are created to study the accessibility of shelters. Findings indicate that rural areas lost accessibility faster than urban areas due to a variety of factors including shelter distributions, and roadway closures as spatial accessibility to shelters for offshore populations was rapidly diminishing. We also observed that as inundation level increases, urban census block groups that are closer to the shelters get extremely high accessibility scores through FCA calculations compared to the other block groups. Results of this study could guide and help revise existing strategies for designing emergency response plans and update resilience action policies. 

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2. Geographical Information Systems-Based Assessment of Evacuation Accessibility to Special Needs Shelters Comparing Storm Surge Impacts of Hurricane Irma (2017) and Ian (2022)

   https://doi.org/10.3390/geographies5010002  

   Yang, Jieya; Kocatepe, Ayberk; Alisan, Onur; Ozguven, Eren Erman (March 2025, Geographies)

   Research on hurricane impacts in Florida’s coastal regions has been extensive, yet there remains a gap in comparing the effects and potential damage of different hurricanes within the same geographical area. Additionally, there is a need for reliable discussions on how variations in storm surges during these events influence evacuation accessibility to hurricane shelters. This is especially significant for rural areas with a vast number of aging populations, whose evacuation may require extra attention due to their special needs (i.e., access and functional needs). Therefore, this study aims to address this gap by conducting a comparative assessment of storm surge impacts on the evacuation accessibility of southwest Florida communities (e.g., Lee and Collier Counties) affected by two significant hurricanes: Irma in 2017 and Ian in 2022. Utilizing the floating catchment area method and examining Replica’s OD Matrix data with Geographical Information Systems (GISs)-based technical tools, this research seeks to provide insights into the effectiveness of evacuation plans and identify areas that need enhancements for special needs sheltering. By highlighting the differential impacts of storm surges on evacuation accessibility between these two hurricanes, this assessment contributes to refining disaster risk reduction strategies and has the potential to inform decision-making processes for mitigating the impacts of future coastal hazards. 

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3. Planning for Special Needs Shelters: A Hurricane Track Uncertainty-Based Approach Integrating Coastal Inundation and Accessibility

   Yang, J. (January 2023, Transportation Research Board Conference)

   Storm surge and evacuation traffic under the observed track of Hurricane Michael (2018) showed clear accessibility and evacuation challenges for Panama City, Florida although the city was not hit directly. Since a possible Hurricane Michael track within National Hurricane Center (NHC)'s forecasted hurricane cone was Panama City, this paper tries to answer the following questions: What if Hurricane Michael hit Panama City directly? How would the special needs populations and their accessibility to Special Needs Shelters (SpNS) be impacted, and what could have been done to alleviate this impact? A previously validated storm surge model was used to predict storm surge inundations under this different hurricane track. Based on the impact of these coastal inundations, a GIS-based optimization methodology was developed to evaluate the accessibility and siting of special needs shelters. Results indicate that if Hurricane Michael had shifted to Panama City in 2018, most of the coastal region of Panama City would have been inundated, compelling residents to evacuate. The possible landfall of Michael in this simulation would also lead to a maximum storm surge of 5 to 6 m on the coast, which is above FEMA's 100-year flood elevation. In addition, the only evacuation route out of Panama City area, when the bridges with their access roads were flooded, was US 231. This would have been life-threatening since there is only one SpNS in the north of the city accessible by this roadway. The proposed analysis studies the accessibility of this SpNS shelter and provides a reasonable approach for SpNS shelter siting or repurposing regular shelters for this purpose based on the hypothesized travel time most likely to be experienced on roadway networks based on the impact of Hurricane Michael. Emergency plans can be updated by the results of this optimization model, which can locate additional sites or shelter locations while minimizing the travel costs and integrating the impact of storm surge modeling and transportation accessibility analysis. 

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4. Estuarine response to storm surge and sea-level rise associated with channel deepening: a flood vulnerability assessment of southwest Louisiana, USA

   https://doi.org/10.1007/s11069-023-05841-1  

   Mansur, Maqsood; Hopkins, Julia; Chen, Qin (February 2023, Natural Hazards)

   Abstract This study investigates the sensitivity of the Calcasieu Lake estuarine region to channel deepening in southwest Louisiana in the USA. We test the hypothesis that the depth increase in a navigational channel in an estuarine region results in the amplification of the inland penetration of storm surge, thereby increasing the flood vulnerability of the region. We run numerical experiments using the Delft3D modeling suite (validated with observational data) with different historic channel depth scenarios. Model results show that channel deepening facilitates increased water movement into the lake–estuary system during a storm surge event. The inland peak water level increases by 37% in the presence of the deepest channel. Moreover, the peak volumetric flow rate increases by 291.6% along the navigational channel. Furthermore, the tidal prism and the volume of surge prism passing through the channel inlet increase by 487% and 153.3%, respectively. In our study, the presence of the deepest channel results in extra 56.72 km²of flooded area (approximately 12% increase) which is an indication that channel deepening over the years has rendered the region more vulnerable to hurricane-induced flooding. The study also analyzes the impact of channel deepening on storm surge in estuaries under different future sea-level rise (SLR) scenarios. Simulations suggest that even the most conservative scenario of SLR will cause an approximately 51% increase in flooded area in the presence of the deepest ship channel, thereby suggesting that rising sea level will cause increased surge penetration and increased flood risk. 

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5. Probabilistic tropical cyclone surge hazard under future sea-level rise scenarios: A case study in the Chesapeake Bay region

   https://doi.org/10.1061/9780784484852.117  

   K. Kim, J.-W. Lee (January 2023, 2023 World Environmental & Water Resources Congress)

   Storm surge flooding caused by tropical cyclones is a devastating threat to coastal regions, and this threat is growing due to sea-level rise (SLR). Therefore, accurate and rapid projection of the storm surge hazard is critical for coastal communities. This study focuses on developing a new framework that can rapidly predict storm surges under SLR scenarios for any random synthetic storms of interest and assign a probability to its likelihood. The framework leverages the Joint Probability Method with Response Surfaces (JPM-RS) for probabilistic hazard characterization, a storm surge machine learning model, and a SLR model. The JPM probabilities are based on historical tropical cyclone track observations. The storm surge machine learning model was trained based on high-fidelity storm surge simulations provided by the U.S. Army Corps of Engineers (USACE). The SLR was considered by adding the product of the normalized nonlinearity, arising from surge-SLR interaction, and the sea-level change from 1992 to the target year, where nonlinearities are based on high-fidelity storm surge simulations and subsequent analysis by USACE. In this study, this framework was applied to the Chesapeake Bay region of the U.S. and used to estimate the SLR-adjusted probabilistic tropical cyclone flood hazard in two areas: One is an urban Virginia site, and the other is a rural Maryland site. This new framework has the potential to aid in reducing future coastal storm risks in coastal communities by providing robust and rapid hazard assessment that accounts for future sea-level rise. 

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