Inferring the joint operation of high Aswan dam and Toshka depression using multi-sensor satellite approach

Remote sensing observations with high spatial and temporal resolutions have been successful in overcoming the challenge of data availability in ungauged basins. In this study, we applied a Multi-Sensor Satellite (MSS) approach to understand the reservoir operation in the Nile river basin (NRB) with the focus on the joint operation of High Aswan Dam (HAD) and Toshka depression, located in the southwestern part of HAD. The MSS data, which integrates Landsat (5-8), Sentinel-2A, MODIS with hydrological model outputs, are used in a water balance model to derive the operation of HAD reservoir and Toshka depression. The results show that the MSS approach has a reasonable skill when modelling the Toshka inflow (i.e. HAD spillway outflow) with a Relative Error and R2 of −19.14% and 0.79, respectively (for the period 1998–2002). Overall, our study provides a framework that harnesses free available sensors to infer the operation of lakes and reservoirs in the NRB

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 R2 = 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