From Rainfall to Rumors: Interpreting the 2024 Bangladesh Floods Through Numbers, Narratives, and Information Gaps

Abstract When severe floods struck southeastern Bangladesh in August 2024, competing explanations emerged. Meteorological analysis revealed that extreme precipitation was exacerbated by the Madden‐Julian Oscillation and jet stream dynamics. However, alternative narratives proliferated on social media, particularly claims that India deliberately released water from upstream dams. This study synthesizes hydrometeorological data and social media analysis to examine the divergence between scientific evidence and social narratives. Despite hydrometeorological explanations, misinformation attributing floods to intentional dam releases gained traction because it aligned with existing sentiments in Bangladesh. While these narratives did not appear to materially impact disaster response in 2024, similar patterns elsewhere demonstrate the potential harm. Effective flood management requires aligning scientific data with narratives that motivate collective action. We argue that both India and Bangladesh face mutual vulnerabilities that give misinformation its power but can also facilitate cooperation. Drawing on the water diplomacy literature, we propose a pilot flood early warning initiative on the Feni and Gomati rivers, combining data sharing with community‐based outreach through locally trusted individuals and institutions, as a practical first step toward strengthening transboundary flood preparedness, countering divisive misinformation, and achieving a flood‐resilient system.

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Publication Details

Journal
Water Resources Research
Published
2026-05-01
DOI
https://doi.org/10.1029/2025wr042679
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

From Rainfall to Rumors: Interpreting the 2024 Bangladesh Floods Through Numbers, Narratives, and Information Gaps

N. Rabb, KT Smith, A. R. Ganguly, P. Das et al.
Water Resources Research
Flood Risk Assessment and Management
article

From Rainfall to Rumors: Interpreting the 2024 Bangladesh Floods Through Numbers, Narratives, and Information Gaps

N. Rabb, KT Smith, A. R. Ganguly, P. Das, S. Islam
article en

Abstract

Abstract When severe floods struck southeastern Bangladesh in August 2024, competing explanations emerged. Meteorological analysis revealed that extreme precipitation was exacerbated by the Madden‐Julian Oscillation and jet stream dynamics. However, alternative narratives proliferated on social media, particularly claims that India deliberately released water from upstream dams. This study synthesizes hydrometeorological data and social media analysis to examine the divergence between scientific evidence and social narratives. Despite hydrometeorological explanations, misinformation attributing floods to intentional dam releases gained traction because it aligned with existing sentiments in Bangladesh. While these narratives did not appear to materially impact disaster response in 2024, similar patterns elsewhere demonstrate the potential harm. Effective flood management requires aligning scientific data with narratives that motivate collective action. We argue that both India and Bangladesh face mutual vulnerabilities that give misinformation its power but can also facilitate cooperation. Drawing on the water diplomacy literature, we propose a pilot flood early warning initiative on the Feni and Gomati rivers, combining data sharing with community‐based outreach through locally trusted individuals and institutions, as a practical first step toward strengthening transboundary flood preparedness, countering divisive misinformation, and achieving a flood‐resilient system.

Water Resources ResearchVol. 62(5)
Tufts University (US), Northeastern University (US), Pacific Northwest National Laboratory (US), California State University Los Angeles (US)
National Science Foundation, National Aeronautics and Space Administration, Strategic Environmental Research and Development Program
Climate action
Openalex Percentile: Top 6%
Flood Risk Assessment and Management
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