Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

[摘要] Gravity Recovery and Climate Experiment (GRACE) and itssuccessor GRACE Follow-on (GRACE-FO) satellite provide terrestrial waterstorage anomaly (TWSA) estimates globally that can be used to monitor floodin various regions at monthly intervals. However, the coarse temporalresolution of GRACE and GRACE-FO satellite data has been limiting theirapplications at finer temporal scales. In this study, TWSA estimates havebeen reconstructed and then temporally downscaled into daily values based onthree different learning-based models, namely a multi-layer perceptron (MLP)model, a long-short term memory (LSTM) model and a multiple linear regression(MLR) model. Furthermore, a new index incorporating temporally downscaledTWSA estimates combined with daily average precipitation anomalies isproposed to monitor the severe flood events at sub-monthly timescales forthe Yangtze River basin (YRB), China. The results indicated that (1) the MLPmodel shows the best performance in reconstructing the monthly TWSA with root mean squareerror (RMSE)  =  10.9 mm per month and Nash–Sutcliffe efficiency (NSE)  =  0.89 during the validation period; (2) the MLPmodel can be useful in temporally downscaling monthly TWSA estimates intodaily values; (3) the proposed normalized daily flood potential index(NDFPI) facilitates robust and reliable characterization of severe floodevents at sub-monthly timescales; (4) the flood events can be monitored bythe proposed NDFPI earlier than traditional streamflow observations withrespect to the YRB and its individual subbasins. All these findings canprovide new opportunities for applying GRACE and GRACE-FO satellite data toinvestigations of sub-monthly signals and have important implications forflood hazard prevention and mitigation in the study region.

[学科分类] 妇产科学