A Novel Flood Probability Index Based on Radar Rainfall and Soil Moisture Estimates for a Small Vegetated Watershed in Southeast Brazil

Floods result from intense and/or prolonged rainfall that exceeds the soil’s infiltration capacity, generating surface runoff and increasing river discharge. These events can cause substantial societal damage and may even lead to fatalities. In this study, we analyzed flood events in Lençóis Paulista, southeastern Brazil, between 2016 and 2024, by evaluating estimated precipitation and soil moisture conditions to develop a flood prediction index for the city. Precipitation estimates were derived from reflectivity data provided by the Bauru weather radar, while soil moisture estimates were obtained from the Joint UK Land Environment Simulator (JULES) land surface model, operated at IPMet-Unesp. Although the index was not developed based on formal hydrological modeling or physical process simulation, the analysis of these variables within the Lençóis River sub-basins revealed that elevated soil moisture in the days preceding flood events was a key contributing factor. This is consistent with the increased susceptibility of wetter soils to surface runoff generation. Based on the identification of relevant variables, we developed the Flood Probability Index (FPI) using data from only nine flood events and applied it to classify the likelihood of flooding in the city. The index produced satisfactory results, highlighting its potential as a tool for flood prediction and early warning for the local population.