Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives
<p>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 w...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-03-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/23/1409/2019/hess-23-1409-2019.pdf |
| _version_ | 1818678270012424192 |
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| author | S. Philip S. Sparrow S. F. Kew K. van der Wiel N. Wanders N. Wanders R. Singh A. Hassan K. Mohammed H. Javid H. Javid K. Haustein F. E. L. Otto F. Hirpa R. H. Rimi A. K. M. S. Islam D. C. H. Wallom G. J. van Oldenborgh |
| author_facet | S. Philip S. Sparrow S. F. Kew K. van der Wiel N. Wanders N. Wanders R. Singh A. Hassan K. Mohammed H. Javid H. Javid K. Haustein F. E. L. Otto F. Hirpa R. H. Rimi A. K. M. S. Islam D. C. H. Wallom G. J. van Oldenborgh |
| author_sort | S. Philip |
| collection | DOAJ |
| description | <p>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 <span class="inline-formula"><sup>∘</sup></span>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.</p>
<p>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 <span class="inline-formula"><sup>∘</sup></span>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.</p> |
| first_indexed | 2024-12-17T09:12:35Z |
| format | Article |
| id | doaj.art-a9e77c0eb71f4919a87ba364bbb97bd8 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-17T09:12:35Z |
| publishDate | 2019-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-a9e77c0eb71f4919a87ba364bbb97bd82022-12-21T21:55:08ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382019-03-01231409142910.5194/hess-23-1409-2019Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectivesS. Philip0S. Sparrow1S. F. Kew2K. van der Wiel3N. Wanders4N. Wanders5R. Singh6A. Hassan7K. Mohammed8H. Javid9H. Javid10K. Haustein11F. E. L. Otto12F. Hirpa13R. H. Rimi14A. K. M. S. Islam15D. C. H. Wallom16G. J. van Oldenborgh17Royal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsOxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UKRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the NetherlandsDepartment of Physical Geography, Utrecht University, Utrecht, the NetherlandsDepartment of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USARed Cross Red Crescent Climate Centre, The Hague, the NetherlandsRed Cross Red Crescent Climate Centre, The Hague, the NetherlandsOxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UKOxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UKEnvironmental Change Institute, Oxford University Centre for the Environment, Oxford, UKEnvironmental Change Institute, Oxford University Centre for the Environment, Oxford, UKEnvironmental Change Institute, Oxford University Centre for the Environment, Oxford, UKSchool of Geography and the Environment, University of Oxford, Oxford, UKEnvironmental Change Institute, Oxford University Centre for the Environment, Oxford, UKInstitute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka, BangladeshOxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UKRoyal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands<p>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 <span class="inline-formula"><sup>∘</sup></span>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.</p> <p>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 <span class="inline-formula"><sup>∘</sup></span>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.</p>https://www.hydrol-earth-syst-sci.net/23/1409/2019/hess-23-1409-2019.pdf |
| spellingShingle | S. Philip S. Sparrow S. F. Kew K. van der Wiel N. Wanders N. Wanders R. Singh A. Hassan K. Mohammed H. Javid H. Javid K. Haustein F. E. L. Otto F. Hirpa R. H. Rimi A. K. M. S. Islam D. C. H. Wallom G. J. van Oldenborgh Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives Hydrology and Earth System Sciences |
| title | Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives |
| title_full | Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives |
| title_fullStr | Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives |
| title_full_unstemmed | Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives |
| title_short | Attributing the 2017 Bangladesh floods from meteorological and hydrological perspectives |
| title_sort | attributing the 2017 bangladesh floods from meteorological and hydrological perspectives |
| url | https://www.hydrol-earth-syst-sci.net/23/1409/2019/hess-23-1409-2019.pdf |
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