Integrating total water level data and visual evidence to assess coastal flooding in San Diego County

Abstract. Coastal flooding in Southern California poses a growing threat to communities and infrastructure, exacerbated by climate change and sea level rise. Total water level (TWL), the combination of sea level, tides, and wave runup, is increasingly used to forecast coastal flooding, but validating the thresholds at which flood impacts occur remains a challenge. This study examines the relationship between modeled TWL and photographic or video evidence of flooding in San Diego County from 2010 to 2024. We integrate model output from the Coastal Data Information Program with visual records from community monitoring programs to assess spatial and seasonal variations in flood occurrence. We also evaluate the influence of atmospheric rivers and El Niño conditions. Atmospheric river days were associated with an increase in the likelihood of observed flooding, and El Niño winters showed a positive but weaker correlation. Overall results demonstrate a robust but imprecise correlation between modeled TWL and observed flood impacts, with uncertainty driven largely by convenience sampling in the visual dataset. Despite these limitations, modeled TWL is shown to be a useful proxy for flood risk. Our findings underscore the need for systematic flood impact documentation to refine threshold estimates and improve flood forecasting and coastal management.