Environmental Research Letters (Jan 2023)

On the role of climate change in the 2018 flooding event in Kerala

  • Manish Kumar Dhasmana,
  • Arpita Mondal,
  • Mariam Zachariah

DOI
https://doi.org/10.1088/1748-9326/ace6c0
Journal volume & issue
Vol. 18, no. 8
p. 084016

Abstract

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The extreme precipitation during August 2018 in Kerala, India was catastrophic, triggering one of the worst floods in history. There is growing evidence of human-induced climate change in driving hydroclimatic extremes across the globe. However, whether and to what degree the 2018 flooding event in Kerala was influenced by climate change has yet to be fully understood. To this end, we present the first formal attribution analysis of the event, using the probabilistic event attribution (PEA) framework. Three methods using (i) Historical and HistoricalNat runs from CMIP6 (general circulation models-based method), (ii) observed records from 1901–2018 for two periods, split at 1950 (time-slice method) and (iii) observations that are scaled to 1901 and 2018 climates (scaling method), are considered for quantifying the risk ratio (RR) of the event. Using an objective approach, the 2018 precipitation event is defined by the return period of the 4 day cumulative precipitation over the Periyar River Basin (PRB), during 15–18 August, 2018. The subsequent flood event is characterized by the return period of the 1 day maximum streamflow at one of the outlets of the PRB, where maximum impact during the event was reported. The results from multiple methods are consistent, suggesting that the event is exceptionally less likely to have been caused by anthropogenic climate change, with RR for the precipitation and flood events ranging from 0.31 to 0.82 and 0.55 to 0.8, respectively. The role of wet antecedent soil moisture conditions, which is found to be the primary driving factor of floods in the PRB, is also found to be unchanged between simulations with and without climate change. Our results highlight the challenges in unequivocal discerning of the climate change signal on regional hydrological events and emphasize the importance of better consideration of local confounding interventions in PEA studies.

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