Hydrologic utility of satellite precipitation products in flood prediction: A meta-data analysis and lessons learnt

Abstract

• A meta-analysis on performance of satellite products was carried out. • The performance of SPP varies under different climate zones. • SPPs that use microwave algorithms were found to outperform the others. • Best performance was found after bias correction and model recalibration. This work summarizes lessons learnt on using satellite precipitation products (SPPs) for flood simulation and prediction and proposes ways forward in this field of research. A meta-analysis was carried out to review: effect of climate zone, topographical features, selection of hydrological models, and calibration procedures on SPPs forced hydrological model performance. SPPs performance was shown to be higher in temperate and tropical than in dry climates. Low lying and moderate elevations areas exhibited high-performance accuracy compared to higher latitudes landscapes. SPPs that use microwave algorithms were found to outperform the others. The best simulation and prediction results were found after bias correction and model recalibration. From a general standpoint, SPPs offer great potential for flood simulation and prediction, but the performance of SPPs needs to be enhanced for operational purposes. The present study discusses bias correction techniques, model recalibration, the importance of interaction between different types of SPPs and hydrological models, and other lessons learned and future directions of using SPPs for future flood applications.