Flood exposure and household green stormwater infrastructure adoption

Abstract Decentralized green stormwater infrastructure (GSI) on private property offers promise for mitigating urban flood risk, but adoption depends on social, economic, and perceptual factors. We integrate household survey responses, census data, parcel feasibility measures, and flood hazard maps to assess how flood risk aligns with GSI adoption across 234 Austin tracts. Regression-based propensity scores predict structural and rain-catching adoption probabilities, which we analyze using global and local Moran’s I and co-location tests. Results reveal weak or negative citywide correlations between flood exposure and predicted probability adoption, while latent factors (awareness, pro-environmental attitudes, personal norms, and social capital) display moderate-to-strong positive associations. Although a few central hotspots align high exposure with high adoption, many high-risk, lower-income, majority-minority neighborhoods show low adoption rates. We reject the hypothesis that exposure alone drives adoption and emphasize socio-economic and perceptual and behavioral barriers as primary determinants. These findings support outreach to underserved communities and incentives to ensure effective, inclusive GSI implementation.

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Publication Details

Journal
Environmental Research Communications
Published
2026-01-30
DOI
https://doi.org/10.1088/2515-7620/ae3ff0
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
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article

Flood exposure and household green stormwater infrastructure adoption

Koorosh Azizi, R. Patrick Bixler
Environmental Research Communications
Flood Risk Assessment and Management
article

Flood exposure and household green stormwater infrastructure adoption

Koorosh Azizi, R. Patrick Bixler
article en

Abstract

Abstract Decentralized green stormwater infrastructure (GSI) on private property offers promise for mitigating urban flood risk, but adoption depends on social, economic, and perceptual factors. We integrate household survey responses, census data, parcel feasibility measures, and flood hazard maps to assess how flood risk aligns with GSI adoption across 234 Austin tracts. Regression-based propensity scores predict structural and rain-catching adoption probabilities, which we analyze using global and local Moran’s I and co-location tests. Results reveal weak or negative citywide correlations between flood exposure and predicted probability adoption, while latent factors (awareness, pro-environmental attitudes, personal norms, and social capital) display moderate-to-strong positive associations. Although a few central hotspots align high exposure with high adoption, many high-risk, lower-income, majority-minority neighborhoods show low adoption rates. We reject the hypothesis that exposure alone drives adoption and emphasize socio-economic and perceptual and behavioral barriers as primary determinants. These findings support outreach to underserved communities and incentives to ensure effective, inclusive GSI implementation.

Environmental Research CommunicationsVol. 8(2)
Tennessee State University (US), The University of Texas at Austin (US)
Sustainable cities and communities
Openalex Percentile: Top 81%
Flood Risk Assessment and Management
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