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Article

Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

1
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
2
School of Civil & Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430072, China
3
Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(15), 3023; https://doi.org/10.3390/rs13153023
Submission received: 2 July 2021 / Revised: 29 July 2021 / Accepted: 29 July 2021 / Published: 1 August 2021

Abstract

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.
Keywords: GRACE Follow-On; CaMa-Flood model; discharge estimation; flood monitoring; Yangtze River basin GRACE Follow-On; CaMa-Flood model; discharge estimation; flood monitoring; Yangtze River basin
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MDPI and ACS Style

Xiong, J.; Guo, S.; Yin, J.; Gu, L.; Xiong, F. Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin. Remote Sens. 2021, 13, 3023. https://doi.org/10.3390/rs13153023

AMA Style

Xiong J, Guo S, Yin J, Gu L, Xiong F. Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin. Remote Sensing. 2021; 13(15):3023. https://doi.org/10.3390/rs13153023

Chicago/Turabian Style

Xiong, Jinghua, Shenglian Guo, Jiabo Yin, Lei Gu, and Feng Xiong. 2021. "Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin" Remote Sensing 13, no. 15: 3023. https://doi.org/10.3390/rs13153023

APA Style

Xiong, J., Guo, S., Yin, J., Gu, L., & Xiong, F. (2021). Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin. Remote Sensing, 13(15), 3023. https://doi.org/10.3390/rs13153023

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