Preprints
https://doi.org/10.5194/hess-2022-168
https://doi.org/10.5194/hess-2022-168
 
10 May 2022
10 May 2022
Status: a revised version of this preprint is currently under review for the journal HESS.

Downscaling and monitoring the extreme flood events in the Yangtze River Basin based on GRACE/GRACE-FO satellites data

Jingkai Xie1, Yue-Ping Xu1, Hongjie Yu1, Yan Huang2, and Yuxue Guo1 Jingkai Xie et al.
  • 1Institute of Hydrology and Water Resources, Zhejiang University, Hangzhou, 310058, China
  • 2Changjiang Water Resources Commission of the Ministry of Water Resources, Wuhan, 43000, China

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

Jingkai Xie et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-168', Anonymous Referee #1, 23 May 2022
    • AC1: 'Reply on RC1', Jingkai Xie, 02 Aug 2022
  • CC1: 'Comment on hess-2022-168', Abhishek Abhi, 24 May 2022
    • AC2: 'Reply on CC1', Jingkai Xie, 02 Aug 2022
  • RC2: 'Comment on hess-2022-168', Anonymous Referee #2, 01 Jun 2022
    • AC3: 'Reply on RC2', Jingkai Xie, 02 Aug 2022

Jingkai Xie et al.

Jingkai Xie et al.

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Short summary
Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers around the world. In this study, we propose a new index incorporating satellites observations combined with meteorological data to monitor the extreme flood event at sub-monthly time scales for the Yangtze River Basin (YRB), China. The conclusions drawn from this study can provide important implications of flood hazard prevention and water resource management over this region.