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

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