Using logistic regression to model the risk of sewer overflows triggered by compound flooding with application to sea level rise

Coastal wastewater and storm water systems can be overwhelmed during high precipitation events, particularly when compounded by surge that blocks spillways drainage ways. Sea level rise (SLR) brings increased risk of such compound flooding triggering sanitary sewer overflows (SSO) which release waste into the local environment. A logistic regression model was developed to better predict this in southern Pinellas County, FL. Model variables were selected from 2000 2017 cumulative coastal levels using both objective subjective criteria. The 2 day (P2) 90 (P90) precipitation, maximum (W2) identified as significant predictors p-value their coefficients, but required an interaction term P2*W2 for fidelity. correctly hindcasted all 6 SSOs 2017. SLR represented a range values up 0.5 m added W2. For number SSO days factor 42–52 individual events ~15. Subtracting recent W2 reduced probability some suggesting already is increasing rate SSOs.