TY - JOUR
T1 - Hydrologic utility of satellite precipitation products in flood prediction
T2 - A meta-data analysis and lessons learnt
AU - Hinge, Gilbert
AU - Hamouda, Mohamed A.
AU - Long, Di
AU - Mohamed, Mohamed M.
N1 - Funding Information:
This research was funded by the national water and energy center, United Arab Emirates University, through the Asian University Alliance (AUA) program, grants number 31R281-AUA-NWEC-4-2020, 12R023-AUA-NWEC-4-2020, and 12R019-NWEC-6-2020.
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/9
Y1 - 2022/9
N2 - 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.
AB - 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.
KW - Flood
KW - Hydrologic prediction
KW - Hydrological model
KW - Satellite precipitation product
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U2 - 10.1016/j.jhydrol.2022.128103
DO - 10.1016/j.jhydrol.2022.128103
M3 - Review article
AN - SCOPUS:85132931424
SN - 0022-1694
VL - 612
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 128103
ER -