Quantification of the Flood Discharge Following the 2023 Kakhovka Dam Breach Using Satellite Remote Sensing

Abstract Fourteen months post the Ukrainian‐Russian war outbreak, the Kakhovka Dam collapsed, leading to weeks of catastrophic flooding. Yet, scant details exist regarding the reservoir draining process. By using a new technique for processing gravimetric satellite orbital observations, this study succeeded in recovering continuous changes in reservoir mass with a temporal resolution of 2–5 days. By integrating these variations with satellite imagery and altimetry data into a hydrodynamic model, we derived the effective width and length of the breach and the subsequent 30‐day evolution of the reservoir discharge. Our model reveals that the initial volumetric flow rate is m 3 /s, approximately 28 times the average flow of the Dnipro River. After 30 days, the water level in the reservoir had dropped by m and its water volume was almost completely depleted by km 3 . In addition, this event provides a rare opportunity to examine the discharge coefficient—a key modeling parameter—of giant reservoirs, which we find to be 0.8–1.0, significantly larger than the ∼0.6 value previously measured in the laboratory, indicating that this parameter may be related to the reservoir scale. This study demonstrates a paradigm of utilizing multiple remote sensing techniques to address observational challenges posed by extreme hydrological events.

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Publication Details

Journal
Water Resources Research
Published
2025-03-01
DOI
https://doi.org/10.1029/2024wr038314
Citations
6
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
6.63

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article

Quantification of the Flood Discharge Following the 2023 Kakhovka Dam Breach Using Satellite Remote Sensing

Shuang Yi, Shin‐Chan Han, Nico Sneeuw, Hao‐si Li et al.
6 citations
Water Resources Research
Flood Risk Assessment and Management
6.63
article

Quantification of the Flood Discharge Following the 2023 Kakhovka Dam Breach Using Satellite Remote Sensing

Shuang Yi, Shin‐Chan Han, Nico Sneeuw, Hao‐si Li, In‐Young Yeo, Chunqiao Song, Christopher McCullough, Chunyu Yuan
article en
6 citations

Abstract

Abstract Fourteen months post the Ukrainian‐Russian war outbreak, the Kakhovka Dam collapsed, leading to weeks of catastrophic flooding. Yet, scant details exist regarding the reservoir draining process. By using a new technique for processing gravimetric satellite orbital observations, this study succeeded in recovering continuous changes in reservoir mass with a temporal resolution of 2–5 days. By integrating these variations with satellite imagery and altimetry data into a hydrodynamic model, we derived the effective width and length of the breach and the subsequent 30‐day evolution of the reservoir discharge. Our model reveals that the initial volumetric flow rate is m 3 /s, approximately 28 times the average flow of the Dnipro River. After 30 days, the water level in the reservoir had dropped by m and its water volume was almost completely depleted by km 3 . In addition, this event provides a rare opportunity to examine the discharge coefficient—a key modeling parameter—of giant reservoirs, which we find to be 0.8–1.0, significantly larger than the ∼0.6 value previously measured in the laboratory, indicating that this parameter may be related to the reservoir scale. This study demonstrates a paradigm of utilizing multiple remote sensing techniques to address observational challenges posed by extreme hydrological events.

Water Resources ResearchVol. 61(3)
University of Stuttgart (DE), Nanjing University of Chinese Medicine (CN), Jet Propulsion Laboratory (US), Chinese Academy of Sciences (CN), Nanjing Institute of Geography and Limnology (CN), University of Chinese Academy of Sciences (CN), University of Newcastle Australia (AU)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 3%
Flood Risk Assessment and Management
6.63
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