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1. Social and environmental vulnerability to flooding: Investigating cross-scale hypotheses

   https://doi.org/10.4211/hs.45624efce89d42beb6db58adc83309ba  

   Hinojos, Selena; Grady, Caitlin (June 2023, HydroShare)

   Flooding is a natural hazard that touches nearly all facets of the globe and is expected to become more frequent and intensified due to climate and land-use change. However, flooding does not impact all individuals equally. Therefore, understanding how flooding impacts distribute across populations of different socioeconomic and demographic backgrounds is vital. One approach to reducing flood risk on people is using indicators, such as social vulnerability indices and flood exposure metrics, to inform decision-making for flood risk management. However, such indicators can face the scale and zonal effect produced by the Modifiable Areal Unit Problem (MAUP). This study investigates how the U.S. Census block group, tract, and county scale selection impacts social vulnerability and flood exposure outcomes within coastal Virginia, USA. Here we show how (1) scale selection can obstruct our understanding of drivers of vulnerability, (2) increasingly aggregated scales significantly undercount highly vulnerable populations, and (3) hotspot clusters of social vulnerability and flood exposure can identify variable priority areas for current and future flood risk reduction. Study results present considerations about using such indicators, given the real-life consequences that can occur due to the MAUP. The results of this work warrant understanding the implications of scale selection on research methodological approaches and what this means for practitioners and policymakers that utilize such information to help guide flood mitigation strategies. 

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2. Relating social, ecological, and technological vulnerability to future flood exposure at two spatial scales in four U.S. cities

   https://doi.org/10.1016/j.scs.2023.104880  

   Sauer, Jason; Pallathadka, Arun; Ajibade, Idowu; Berbés-Blázquez, Marta; Chang, Heejun; Cook, Elizabeth M; Grimm, Nancy B; Iwaniec, David M; Lloyd, Robert; Post, Gregory C (December 2023, Sustainable Cities and Society)

   Flooding occurs at different scales and unevenly affects urban populations based on the broader social, ecological, and technological system (SETS) characteristics particular to cities. As hydrological models improve in spatial scale and account for more mechanisms of flooding, there is a continuous need to examine the re- lationships between flood exposure and SETS drivers of flood vulnerability. In this study, we related fine-scale measures of future flood exposure—the First Street Foundation’s Flood Factor and estimated change in chance of extreme flood exposure—to SETS indicators like building age, poverty, and historical redlining, at the parcel and census block group (CBG) scales in Portland, OR, Phoenix, AZ, Baltimore, MD, and Atlanta, GA. We used standard regression models and accounted for spatial bias in relationships. The results show that flood exposure was more often correlated with SETS variables at the parcel scale than at the CBG scale, indicating scale dependence. However, these relationships were often inconsistent among cities, indicating place-dependence. We found that marginalized populations were significantly more exposed to future flooding at the CBG scale. Combining newly-available, high-resolution future flood risk estimates with SETS data available at multiple scales offers cities a new set of tools to assess the exposure and multi-dimensional vulnerability of populations. These tools will better equip city managers to proactively plan and implement equitable interventions to meet evolving hazard exposure. 

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3. Spatiotemporal implications of flooding on relocation risk in rural and urban coastal municipalities

   https://doi.org/10.1016/j.landusepol.2023.106754  

   Bukvic, A.; Mitchell, A.; Shao, Y.; Irish, J.L. (September 2023, Land Use Policy)

   The research on coastal hazards predicts substantial adverse impacts of chronic and episodic flooding on populated coastal areas. Despite the growing evidence about anticipated flood risks, many coastal communities are still not adapting. The observed disconnect between science on physical impacts and adaptation decisionmaking in part reflects stakeholders’ inability to envision the implications of these impacts on socioeconomic systems and the built environment in their jurisdictions. This inertia is particularly apparent in the discourse on flood-driven displacement and relocation. There is a lack of knowledge about direct and indirect flood impacts on community attributes and services that contribute to relocation decision-making. This study holistically evaluates the flood exposure on municipal features vital for socioeconomic stability, livelihoods, and quality of life across spatiotemporal scales. As such, it uses a more nuanced approach to relocation risk assessment than those solely focused on direct inundation impacts. It measures flood exposure of land use, land cover, and sociocultural and economic dimensions that are important drivers of relocation in selected rural and urban areas. The approach uses a 50-year floodplain to delineate populated coastal locations exposed to 2% Annual Exceedance Probability (AEP) storm surge projections adjusted for 2030, 2060, and 2090 sea level rise (SLR) scenarios. It then evaluates the potential impacts of this flood exposure on different types of land uses and critical socioeconomic assets in rural (Dorchester and Talbot Counties, Maryland, USA) and urban (Cities of Hampton, Norfolk, Portsmouth, and Virginia Beach, Virginia, USA) settings. The results show that some urban land uses, such as open space, military and mixed-use, and rural residential and commercial areas, might experience significantly more flooding. There are also notable differences in the baseline flood exposure and the anticipated rate and acceleration in the future among selected communities with significant implications for relocation planning. 

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4. National‐Scale Flood Hazard Data Unfit for Urban Risk Management

   https://doi.org/10.1029/2024EF004549  

   Schubert, Jochen_E; Mach, Katharine_J; Sanders, Brett_F (July 2024, Earth's Future)

   Abstract Extreme flooding events are becoming more frequent and costly, and impacts have been concentrated in cities where exposure and vulnerability are both heightened. To manage risks, governments, the private sector, and households now rely on flood hazard data from national‐scale models that lack accuracy in urban areas due to unresolved drainage processes and infrastructure. Here we assess the uncertainties of First Street Foundation (FSF) flood hazard data, available across the U.S., using a new model (PRIMo‐Drain) that resolves drainage infrastructure and fine resolution drainage dynamics. Using the case of Los Angeles, California, we find that FSF and PRIMo‐Drain estimates of population and property value exposed to 1%‐ and 5%‐annual‐chance hazards diverge at finer scales of governance, for example, by 4‐ to 18‐fold at the municipal scale. FSF and PRIMo‐Drain data often predict opposite patterns of exposure inequality across social groups (e.g., Black, White, Disadvantaged). Further, at the county scale, we compute a Model Agreement Index of only 24%—a ∼1 in 4 chance of models agreeing upon which properties are at risk. Collectively, these differences point to limited capacity of FSF data to confidently assess which municipalities, social groups, and individual properties are at risk of flooding within urban areas. These results caution that national‐scale model data at present may misinform urban flood risk strategies and lead to maladaptation, underscoring the importance of refined and validated urban models. 

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5. Revealing hazard-exposure heterophily as a latent characteristic of community resilience in social-spatial networks

   https://doi.org/10.1038/s41598-023-31702-9  

   Liu, Chia-Fu; Mostafavi, Ali (December 2023, Scientific Reports)

   Abstract We present a latent characteristic in socio-spatial networks, hazard-exposure heterophily, to capture the extent to which populations with dissimilar hazard exposure could assist each other through social ties. Heterophily is the tendency of unlike individuals to form social ties. Conversely, populations in hazard-prone spatial areas with significant hazard-exposure similarity, homophily, would lack sufficient resourcefulness to aid each other to lessen the impact of hazards. In the context of the Houston metropolitan area, we use Meta’s Social Connectedness data to construct a socio-spatial network in juxtaposition with flood exposure data from National Flood Hazard Layer to analyze flood hazard exposure of spatial areas. The results reveal the extent and spatial variation of hazard-exposure heterophily in the study area. Notably, the results show that lower-income areas have lower hazard-exposure heterophily possibly caused by income segregation and the tendency of affordable housing development to be located in flood zones. Less resourceful social ties in hazard-prone areas due to their high-hazard-exposure homophily may inhibit low-income areas from better coping with hazard impacts and could contribute to their slower recovery. Overall, the results underscore the significance of characterizing hazard-exposure heterophily in socio-spatial networks to reveal community vulnerability and resilience to hazards. 

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