Integrating multi-sensor observations and rainfall-runoff inundation modeling for mapping flood extents over the Nile River basin: example from the 2020 flooding in Sudan

Understanding the dynamics of flooding events is crucial to mitigate flood risks, particularly in developing nations like Sudan. This study combines multi-sensor approaches with Rainfall-Runoff-Inundation (RRI) modeling to predict flood inundation extent over the Nile River Basin (NRB). Building upon the RRI model, we firstly simulated the streamflow over the Blue Nile basin and the White Nile basin. Our results show a good agreement between the observed and the simulated streamflow at both daily and monthly scales, e.g. NSE = 0.72 and R-2 = 0.85 for daily simulations at Khartoum station. Further, we compared the inundation extents from the RRI model with derived inundation maps from different satellite images (Sentinel-1, Sentinel-2, Landsat-8, and MODIS). The results indicate the potential to overcome the limitation of data scarcity in developing regions and hence provide a supportive assessment tool for flood risk maps in the NRB.

Automated summary

Understanding the dynamics of flooding events is crucial in developing nations like Sudan. This study combines multi-sensor approaches with RRI modeling to predict flood inundation extent over the Nile River Basin, providing a supportive assessment tool for flood risk maps in developing regions.