Storm runoff prediction using rainfall radar map supported by global optimization methodology

Abstract

In Tokyo metropolitan area, flood risk is increasing due to social and environmental conditions including concentration of population and industry etc. Small urban watersheds are at a high risk of inundation by river flooding and/or inner water induced by heavy rainfall in a short time. To estimate river water level accurately in urban small rivers, it is critically important to conduct precise runoff analysis by using spatiotemporally distributed rainfall data. In this study, a runoff analysis was conducted with spatiotemporally densely distributed X-band MP Radar (X-band multi-parameter radar) data as input for storm events occurred in upper Kanda River, a typical urban small river in Tokyo. Then, SCE-UA method, one of global optimization methodologies, was applied to identify the parameters of the storm runoff model. The results revealed that urban storm runoff was predicted accurately using X-band MP radar map supported by optimized runoff model.