Abstract
Abstract. In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents, for the first time, an attribution of this precipitation-induced flooding to anthropogenic climate change from a combined meteorological and hydrological perspective. Experiments were conducted with three observational datasets and two climate models to estimate changes in the extreme 10-day precipitation event frequency over the Brahmaputra basin up to the present and, additionally, an outlook to 2 ∘C warming since pre-industrial times. The precipitation fields were then used as meteorological input for four different hydrological models to estimate the corresponding changes in river discharge, allowing for comparison between approaches and for the robustness of the attribution results to be assessed. In all three observational precipitation datasets the climate change trends for extreme precipitation similar to that observed in August 2017 are not significant, however in two out of three series, the sign of this insignificant trend is positive. One climate model ensemble shows a significant positive influence of anthropogenic climate change, whereas the other large ensemble model simulates a cancellation between the increase due to greenhouse gases (GHGs) and a decrease due to sulfate aerosols. Considering discharge rather than precipitation, the hydrological models show that attribution of the change in discharge towards higher values is somewhat less uncertain than in precipitation, but the 95 % confidence intervals still encompass no change in risk. Extending the analysis to the future, all models project an increase in probability of extreme events at 2 ∘C global heating since pre-industrial times, becoming more than 1.7 times more likely for high 10-day precipitation and being more likely by a factor of about 1.5 for discharge. Our best estimate on the trend in flooding events similar to the Brahmaputra event of August 2017 is derived by synthesizing the observational and model results: we find the change in risk to be greater than 1 and of a similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach. This study shows that, for precipitation-induced flooding events, investigating changes in precipitation is useful, either as an alternative when hydrological models are not available or as an additional measure to confirm qualitative conclusions. Besides this, it highlights the importance of using multiple models in attribution studies, particularly where the climate change signal is not strong relative to natural variability or is confounded by other factors such as aerosols.
Highlights
In August 2017 Bangladesh faced one of the worst river flooding events in recent history, with record high water levels, and the Ministry of Disaster Management and Relief reported that the floods were the worst in at least 40 years
The LISFLOOD model shows that a discharge value with a return period of 4 years in the actual scenario would increase to 5.4 years in the natural climate scenario, while it would reduce to 3.1 years in the greenhouse gases (GHGs)-only scenario
7 Conclusions In August 2017, following heavy rains, Bangladesh faced one of their worst river flooding events in recent history, with record high water levels leading to inundation of river basin areas in the northern parts of the country, impacting millions of people who are highly exposed and vulnerable to unusual flooding
Summary
In August 2017 Bangladesh faced one of the worst river flooding events in recent history, with record high water levels, and the Ministry of Disaster Management and Relief reported that the floods were the worst in at least 40 years. Due to heavy local rainfall, as well as water flow from the upstream hills in India, the various rivers in northern Bangladesh burst their banks. This led to the inundation of river basin areas in the northern parts of Bangladesh, starting on 12 August and affecting over 30 districts. At least 2292 schools were damaged, affecting education for weeks, and 13 035 cases of waterborne illnesses were reported in the aftermath of the floods
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