Affiliations:
College of Business and Economics, California State University, Los Angeles, United States
Wildfire poses a growing risk to California’s electric grid. In Riverside County, fires ignited near overhead distribution lines and substations lead to power outages and public safety shutoffs, which place a disproportionate burden on disadvantaged communities. This study develops an energy-aware decision-support framework to identify census tracts where wildfire hazard severity overlaps with social and infrastructure vulnerability. Data were obtained from the Riverside County GIS portal, CalEnviroScreen 4.0, and U.S. Census and American Community Survey variables, including income, age, disability, housing conditions, and transportation access. An Infrastructure Risk Index (IRI) was constructed by normalizing and aggregating indicators of sensitivity, adaptive capacity, and exposure, and then integrating wildfire hazard severity to prioritize at-risk assets. Results from a two-sample t-test show that IRI values are significantly higher in areas classified as high and very high wildfire hazard zones, confirming a strong association between fire risk and social vulnerability. The resulting spatial outputs provide actionable guidance for utilities and emergency managers, including vegetation management near power lines, targeted inspections of transformers and switches, equitable placement of emergency resources, and informed funding decisions. The framework can incorporate near–real-time data, such as weather conditions or sensor inputs, and user-defined alert thresholds to support proactive maintenance. By prioritizing under-resourced communities, this approach contributes to improved grid resilience, enhanced public safety, and more equitable wildfire risk mitigation in Riverside County.
Wildfire risk, Electric grid resilience, Social vulnerability, Infrastructure risk index, Decision-support framework
https://doi.org/10.21833/ijaas.2026.03.021
Sultan, V., Ruiz, S., & Wilson, D. T. (2026). GIS-based wildfire risk and social vulnerability mapping for smart grid resilience in Riverside County. International Journal of Advanced and Applied Sciences, 13(3), 207–211. https://doi.org/10.21833/ijaas.2026.03.021