Hydrology and Earth System Sciences | 2019
Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives
Abstract
Abstract. In August 2017 Bangladesh faced one of its worst river flooding events in\nrecent history. This paper presents, for the first time, an attribution of this\nprecipitation-induced flooding to anthropogenic climate change from a\ncombined meteorological and hydrological perspective. Experiments were\nconducted with three observational datasets and two climate models to\nestimate changes in the extreme 10-day precipitation event frequency over the\nBrahmaputra basin up to the present and, additionally, an outlook to 2\u2009 ∘ C warming since pre-industrial times.\nThe precipitation fields were then used as meteorological input for four\ndifferent hydrological models to estimate the corresponding changes in river\ndischarge, allowing for comparison between approaches and for the robustness\nof the attribution results to be assessed. In all three observational precipitation datasets the climate change trends\nfor extreme precipitation similar to that observed in August 2017 are not\nsignificant, however in two out of three series, the sign of this\ninsignificant trend is positive. One climate model ensemble shows a\nsignificant positive influence of anthropogenic climate change, whereas the\nother large ensemble model simulates a cancellation between the increase due\nto greenhouse gases (GHGs) and a decrease due to sulfate aerosols. Considering\ndischarge rather than precipitation, the hydrological models show that\nattribution of the change in discharge towards higher values is somewhat less\nuncertain than in precipitation, but the 95\u2009% confidence intervals still\nencompass no change in risk. Extending the analysis to the future, all models\nproject an increase in probability of extreme events at 2\u2009 ∘ C global\nheating since pre-industrial times, becoming more than 1.7\xa0times more likely\nfor high 10-day precipitation and being more likely by a factor of about 1.5 for\ndischarge. Our best estimate on the trend in flooding events similar to the\nBrahmaputra event of August\xa02017 is derived by synthesizing the observational\nand model results: we find the change in risk to be greater than 1 and of\na similar order of magnitude (between\xa01 and 2) for both the meteorological and\nhydrological approach. This study shows that, for precipitation-induced\nflooding events, investigating changes in precipitation is useful, either as\nan alternative when hydrological models are not available or as an\nadditional measure to confirm qualitative conclusions. Besides this, it highlights\nthe importance of using multiple models in attribution studies, particularly\nwhere the climate change signal is not strong relative to natural variability\nor is confounded by other factors such as aerosols.