Articles | Volume 26, issue 22
https://doi.org/10.5194/hess-26-5933-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5933-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2022
Research article |
| 25 Nov 2022
| 25 Nov 2022
Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data
Jingkai Xie
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Hongjie Yu
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Yan Huang
Changjiang Water Resources Commission of the Ministry of Water
Resources, Wuhan, 43000, China
Yuxue Guo
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
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Cited
14 citations as recorded by crossref.
- Evaluating flood potential in the Mahanadi River Basin, India, using Gravity Recovery and Climate Experiment (GRACE) data and topographic flood susceptibility index under non-stationary framework S. Bhere & M. Reddy 10.1007/s11356-024-32105-7
- Assessing and attributing flood potential in Brazil using GPS 3D deformation X. Yang et al. 10.1016/j.rse.2024.114535
- Spatiotemporal Variability of Current and Future Sub‐Daily Rainfall in Japan Using State‐Of‐The‐Art High‐Quality Data Sets W. Zhao et al. 10.1029/2022WR034305
- Spatial downscaling of GRACE terrestrial water storage anomalies for drought and flood potential assessment G. Yin et al. 10.1016/j.jhydrol.2025.133144
- Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al. 10.1038/s41467-023-38966-9
- Deep learning-aided temporal downscaling of GRACE-derived terrestrial water storage anomalies across the Contiguous United States M. Uz et al. 10.1016/j.jhydrol.2024.132194
- Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows X. Yu et al. 10.1016/j.ejrh.2025.102244
- Exploring the utility of GRACE measurements for characterizing karst systems at a continental scale C. Orazulike et al. 10.1016/j.jhydrol.2024.132578
- Downscaling and Gap-Filling GRACE-Based Terrestrial Water Storage Anomalies in the Qinghai–Tibet Plateau Using Deep Learning and Multi-Source Data J. Chen et al. 10.3390/rs17081333
- The Flow of the Yangtze River Inverted From a Continuous Global Navigation Satellite System Station R. Zou et al. 10.1029/2023GL104481
- Long short-term memory exploitation of satellite gravimetry to infer floods O. Sorkhabi & J. Awange 10.1016/j.jag.2025.104562
- High-resolution groundwater storage anomalies in the Middle and Lower Yangtze River Basin of China using machine learning fusion of in-situ wells, satellite gravity and hydrological model L. Hu et al. 10.1016/j.jenvman.2025.124322
- Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin C. Xiao et al. 10.3390/rs15123192
- Exploring potential drivers of terrestrial water storage anomaly trends in the Yangtze River Basin (2002–2019) J. Wang et al. 10.1016/j.ejrh.2025.102264
14 citations as recorded by crossref.
- Evaluating flood potential in the Mahanadi River Basin, India, using Gravity Recovery and Climate Experiment (GRACE) data and topographic flood susceptibility index under non-stationary framework S. Bhere & M. Reddy 10.1007/s11356-024-32105-7
- Assessing and attributing flood potential in Brazil using GPS 3D deformation X. Yang et al. 10.1016/j.rse.2024.114535
- Spatiotemporal Variability of Current and Future Sub‐Daily Rainfall in Japan Using State‐Of‐The‐Art High‐Quality Data Sets W. Zhao et al. 10.1029/2022WR034305
- Spatial downscaling of GRACE terrestrial water storage anomalies for drought and flood potential assessment G. Yin et al. 10.1016/j.jhydrol.2025.133144
- Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al. 10.1038/s41467-023-38966-9
- Deep learning-aided temporal downscaling of GRACE-derived terrestrial water storage anomalies across the Contiguous United States M. Uz et al. 10.1016/j.jhydrol.2024.132194
- Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows X. Yu et al. 10.1016/j.ejrh.2025.102244
- Exploring the utility of GRACE measurements for characterizing karst systems at a continental scale C. Orazulike et al. 10.1016/j.jhydrol.2024.132578
- Downscaling and Gap-Filling GRACE-Based Terrestrial Water Storage Anomalies in the Qinghai–Tibet Plateau Using Deep Learning and Multi-Source Data J. Chen et al. 10.3390/rs17081333
- The Flow of the Yangtze River Inverted From a Continuous Global Navigation Satellite System Station R. Zou et al. 10.1029/2023GL104481
- Long short-term memory exploitation of satellite gravimetry to infer floods O. Sorkhabi & J. Awange 10.1016/j.jag.2025.104562
- High-resolution groundwater storage anomalies in the Middle and Lower Yangtze River Basin of China using machine learning fusion of in-situ wells, satellite gravity and hydrological model L. Hu et al. 10.1016/j.jenvman.2025.124322
- Applying Reconstructed Daily Water Storage and Modified Wetness Index to Flood Monitoring: A Case Study in the Yangtze River Basin C. Xiao et al. 10.3390/rs15123192
- Exploring potential drivers of terrestrial water storage anomaly trends in the Yangtze River Basin (2002–2019) J. Wang et al. 10.1016/j.ejrh.2025.102264
Latest update: 08 May 2025
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 satellite observations combined with meteorological data to monitor extreme flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The conclusions drawn from this study provide important implications for flood hazard prevention and water resource management over this region.
Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers...
