Mapping individual and combined hazard potential within a city is key to understanding how urban populations may disproportionately exposed to hazards at different times of the year. Using a Topographic Wetness Index (TWI) and an Urban Heat Index (UHI) to model winter flood and summer heat hazard potential respectively, this research uses a geographic information system (GIS) to develop a combined index, and tests for relationships between sociodemographic variables and environmental hazard potential. Along with data from the American Community Survey, and tax lot information, index values are summarized by census block groups, and tested against sociodemographic and biophysical variables for correlations. An exploratory regression identifies unique combinations of variables that produce the highest degree of explanation across all census block groups. Spatial models, including a spatial error model, spatial lag model and a geographically weighted regression (GWR) model further tests how relationships vary across Portland, and identifies areas that may face acute impacts from flooding and heat. Results show combined sewer pipe density, green space, impervious surface, population density, and percentage of population without higher education explained 69% of the variation of the combined hazard potential. GWR further identified how these variables were non-stationary across space in their relationship with the combined hazard index and explained 80% of the variation of combined hazard potential. Our findings offer practitioners and researchers a dual-hazard perspective for assessing the role of socioeconomic conditions when designing resilient infrastructure.