Possibility of Flood Modelling by Utilizing Global Precipitation Data in Developing Country: A Case Study on Bengawan Solo River, Indonesia

Abstract

In Indonesia 75.7 million people are exposed to high flood risk. Flood model in Indonesia is limited due to the unavailability of adequate information. Precipitation data is one of the key aspects for flood modelling, but the gauge rainfall observation only covers a limited area. This study aims to investigate the possibility of global precipitation data in determining the RRI Model parameters and to understand most suitable rainfall product in area with insufficient gauge observations. We compare two global precipitation datasets, GSMaP and ERA5, with rain gauges from 57 stations. The global precipitation data still have low correlation for flood modeling. Although both GSMaP and ERA5 are still unable to represent the rainfall distribution, ERA5 is proven to have lower error, performed better correlation, and resulted in better discharge prediction. ERA5 might have the potential to be utilized for parameter optimization in watersheds with insufficient ground rainfall observations.