Uncovering the Drivers of Urban Flood Reports: An Environmental and Socioeconomic Analysis Using 311 Data

Cities use 311 platforms for residents to report flooding, offering insight into flood-prone areas. The combined role of environmental and socioeconomic factors shaping these reports remains unexplored. This study analyzes five years of 311 flood reports in Norfolk, VA, using a logistic regression model to identify salient predictors and assess their influence on flood reporting. The model includes environmental variables (precipitation, tide level, and topographic wetness index) and socioeconomic indicators (race, income, and education). The model performed well with an area under the receiver operator characteristic (ROC) curve (AUC) of 0.8. Permutation-based feature importance revealed precipitation as the most important predictor (AUC contribution: 0.27), followed by the percentage of Black residents (0.02); tide only contributed ~0.01. The influence of the percentage of Hispanics was also ~0.01. Increases in the percentage of Black residents were associated with increased reporting, while the converse was true for a higher percentage of Hispanic residents. Higher reporting in Norfolk from locations with more Black residents is distinct from findings in other cities, suggesting Norfolk may have more effective communication with these residents about 311 reporting. However, lower reporting in locations with more Hispanic residents suggests Norfolk could improve outreach to non-native speakers, for example, by adding Spanish language options to their 311 platform.