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Peer-reviewedCC BYProgress in Disaster Science

An integrated framework to assess social inequity and flood susceptibility: a case study of Harris County, Texas

  • Flavio Vata1
  • Marco Painho2
  • Ana Cristina Costa2
  • Carlos Granell3
  1. 1NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Lisboa, Portugal; Corresponding author at: NOVA IMS, Campus de Campolide, 1070-312 Lisboa. Portugal.
  2. 2NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Lisboa, Portugal
  3. 3Universitat Jaume I, Castelló, Spain
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Abstract

Flooding disproportionately affects marginalized communities, yet flood risk assessments rarely integrate social and environmental dimensions within a single spatial framework. This study develops an integrated methodology for assessing flood vulnerability in Harris County, Texas, by combining a Social Inequity Index (SII), built using Principal Component Analysis on socio-economic and demographic variables, with a Flood Susceptibility Map (FSM), built using the Analytic Hierarchy Process on environmental and topographic indicators. The two are integrated into a composite Flood Vulnerability Map (FVM) and examined using spatial statistics — hot spot analysis, Moran's I, and (Multiscale) Geographically Weighted Regression — to test whether, and where, social inequity and flood risk spatially coincide. Results show that flood susceptibility and social inequity are only weakly correlated at the county level ( r = 0.042), but exhibit meaningful localized overlap: 12.83% of census tracts ( n = 143) are simultaneously classified as hot spots for both flood susceptibility and social inequity, with Black, Hispanic, and elderly-disabled populations disproportionately represented in these zones. These findings suggest that county-wide statistical association is a poor proxy for compounded risk, and that spatially explicit, tract-level analysis is necessary to identify where equity-focused flood resilience investment is most needed.

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Cite

BibTeXRIS
BibTeX
@article{vata2026integrated,
  title = {{An integrated framework to assess social inequity and flood susceptibility: a case study of Harris County, Texas}},
  author = {Flavio Vata and Marco Painho and Ana Cristina Costa and Carlos Granell},
  journal = {Progress in Disaster Science},
  year = {2026},
  month = nov,
  doi = {10.1016/j.pdisas.2026.100776},
  url = {https://doi.org/10.1016/j.pdisas.2026.100776},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - An integrated framework to assess social inequity and flood susceptibility: a case study of Harris County, Texas
AU  - Flavio Vata
AU  - Marco Painho
AU  - Ana Cristina Costa
AU  - Carlos Granell
PY  - 2026
DA  - 2026/11/02
JO  - Progress in Disaster Science
DO  - 10.1016/j.pdisas.2026.100776
UR  - https://doi.org/10.1016/j.pdisas.2026.100776
AB  - Flooding disproportionately affects marginalized communities, yet flood risk assessments rarely integrate social and environmental dimensions within a single spatial framework. This study develops an integrated methodology for assessing flood vulnerability in Harris County, Texas, by combining a Social Inequity Index (SII), built using Principal Component Analysis on socio-economic and demographic variables, with a Flood Susceptibility Map (FSM), built using the Analytic Hierarchy Process on environmental and topographic indicators. The two are integrated into a composite Flood Vulnerability Map (FVM) and examined using spatial statistics — hot spot analysis, Moran's I, and (Multiscale) Geographically Weighted Regression — to test whether, and where, social inequity and flood risk spatially coincide. Results show that flood susceptibility and social inequity are only weakly correlated at the county level ( r = 0.042), but exhibit meaningful localized overlap: 12.83% of census tracts ( n = 143) are simultaneously classified as hot spots for both flood susceptibility and social inequity, with Black, Hispanic, and elderly-disabled populations disproportionately represented in these zones. These findings suggest that county-wide statistical association is a poor proxy for compounded risk, and that spatially explicit, tract-level analysis is necessary to identify where equity-focused flood resilience investment is most needed.
SN  - 2590-0617
ER  -