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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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Social and environmental vulnerability to flooding: Investigating cross-scale hypotheses
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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- PAR ID:
- 10483663
- Publisher / Repository:
- HydroShare
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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