Hydrological modeling using distributed rainfall data to represent the flow in urban watersheds

Abstract

Hydrological models are one of the most effective ways of assessing water behavior and flood risk, although the quality of their results is determined by the input data representativity, especially rainfall. Normally, only rain gauge data is used, unable to represent rain spatial variability. Aiming to reduce the model’s uncertainties, hydrological model performance was evaluated in determining the runoff based on distributed rainfall data applied in an urban watershed with macro drainage structures. A distributed rainfall data, derived from a conditional merging of radar and field measurements, was used as the hydrological model’s input data, and led to very accurate runoff results. The analysis of the results demonstrated that to model urban watersheds with accuracy, distributed rainfall data is required, as well as knowledge about the sewage and drainage systems, reinforcing the need to use tools that are compatible with the site complexity.