Seven centuries of reconstructed Brahmaputra River discharge demonstrate underestimated high discharge and flood hazard frequency

Mukund P. Rao (), Edward R. Cook, Benjamin I. Cook, Rosanne D. D’Arrigo, Jonathan G. Palmer, Upmanu Lall, Connie A. Woodhouse, Brendan M. Buckley, Maria Uriarte, Daniel A. Bishop, Jun Jian and Peter J. Webster
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Mukund P. Rao: Lamont-Doherty Earth Observatory of Columbia University
Edward R. Cook: Lamont-Doherty Earth Observatory of Columbia University
Benjamin I. Cook: NASA Goddard Institute for Space Studies
Rosanne D. D’Arrigo: Lamont-Doherty Earth Observatory of Columbia University
Jonathan G. Palmer: University of New South Wales
Upmanu Lall: Columbia University
Connie A. Woodhouse: University of Arizona
Brendan M. Buckley: Lamont-Doherty Earth Observatory of Columbia University
Maria Uriarte: Columbia University
Daniel A. Bishop: Lamont-Doherty Earth Observatory of Columbia University
Jun Jian: Dalian Maritime University
Peter J. Webster: Georgia Institute of Technology

Nature Communications, 2020, vol. 11, issue 1, 1-10

Abstract: Abstract The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309–2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956–1986 C.E.) ranks amongst the driest of the past seven centuries (13th percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24–38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.

Date: 2020
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DOI: 10.1038/s41467-020-19795-6

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