Future changes in meteorological drought characteristics over Bangladesh projected by the CMIP5 multi-model ensemble

Abstract

Drought is an inconspicuous natural disaster. In a warmer world, the severity and coverage of drought are expected to change, and it is essential to study these changes at smaller scale. This study detected changes in drought frequency, severity, and intensity in Bangladesh from a bias-corrected CMIP-5 multi-model projection of 11 members under a business-as-usual RCP8.5 scenario. We have used two well-known meteorological drought indices, Standardized Precipitation Index (SPI) and Standardized Precipitation and Evaporation Index (SPEI). SPI is solely based on precipitation, while SPEI considers climatic water balance and incorporates the effect of temperature. Two different methods of estimation of potential evapotranspiration (PET), namely Thornthwaite and Hargreaves methods, are explored. SPEI-based drought identification is found to have high sensitivity among these PET estimation methods. In Bangladesh, SPI-based analysis suggests virtually no change in the long-term drought (12-monthly) condition and a minor change in short-term (6-monthly or less) droughts. SPEI evaluated with Hargreaves method projects a similar scenario for long-term droughts but an increase in both drought frequency and severity in short timescales. At seasonal scale, winter and pre-monsoon are projected to be potentially more affected by water stress in the future. A spatially coherent shift in wet-dry regime is also found over the northern part of Bangladesh under the warming world.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Ahmadalipour A, Moradkhani H, Demirel MC (2017) A comparative assessment of projected meteorological and hydrological droughts: elucidating the role of temperature. J Hydrol 553:785–797

    Article  Google Scholar 

  2. Bayissa Y, Maskey S, Tadesse T, van Andel S, Moges S, van Griensven A, Solomatine D (2018) Comparison of the performance of six drought indices in characterizing historical drought for the Upper Blue Nile Basin, Ethiopia. Geosciences 8(3):81

    Article  Google Scholar 

  3. Brammer H (1987) Drought in Bangladesh: lessons for planners and administrators. Disasters 11(1):21–29

    Article  Google Scholar 

  4. Dai A (2013) Increasing drought under global warming in observations and models. Nat Clim Chang 3:52–58

    Article  Google Scholar 

  5. Dash BK, Rafiuddin M, Khanam F, Islam MN (2012) Characteristics of meteorological drought in Bangladesh. Nat Hazards 64(2):1461–1474

    Article  Google Scholar 

  6. Duan K, Mei Y (2014) Comparison of meteorological, hydrological and agricultural drought responses to climate change and uncertainty assessment. Water Resour Manag 28(14):5039–5054

    Article  Google Scholar 

  7. Dutta D, Kundu A, Patel NR (2013) Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto International 28(3):192–209

    Article  Google Scholar 

  8. Fahad MG, Islam AS, Nazari R, Hasan MA, Islam GMT, Bala SK (2018) Regional changes of precipitation and temperature over Bangladesh using bias corrected multi-model ensemble projections considering high emission pathways. Int J Climatol 38(4):1634–1648

    Article  Google Scholar 

  9. Giorgi F, Gutowski WJ Jr (2015) Regional dynamical downscaling and the CORDEX initiative. Annu Rev Environ Resour 40:467–490

    Article  Google Scholar 

  10. Grillakis MG, Koutroulis AG, Tsanis IK (2013) Multi-segment statistical bias correction of daily GCM precipitation output. J Geophys Res-Atmos 118(8):3150–3162

    Article  Google Scholar 

  11. Hao ZC, AghaKouchak A (2013) A multivariate standardized drought index: a parametric multi-index model. Adv Water Resour 57:12–18

    Article  Google Scholar 

  12. Hargreaves, G. H. (1994) Defining and using reference evapotranspiration. J Irrig Drain Eng

  13. He B, Wu J, Lü A, Cui X, Zhou L, Liu M, Zhao L (2013) Quantitative assessment and spatial characteristic analysis of agricultural drought risk in China. Nat Hazards 66(2):155–166

    Article  Google Scholar 

  14. IPCC 2019: Summary for policymakers. In: Climate change and land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.- O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, M. Belkacemi, J. Malley, (eds.)]

  15. Karim Z, Iqbal A (2001) Impact of land degradation in Bangladesh: changing scenario in agricultural land use

  16. Khan M, Islam A, Das M, Mohammed K, Bala S, Islam G (2019) Observed trends in climate extremes over Bangladesh from 1981 to 2010 Climate Research. Inter-Research Science Center 77:45–61. https://doi.org/10.3354/cr01539

    Article  Google Scholar 

  17. Khan MJU, Islam AKMS, Bala SK, Islam GMT (2020) Changes in climate extremes over Bangladesh at 1.5 °C, 2 °C, and 4 °C of global warming with high-resolution regional climate modeling. Theoretical and Applied Climatology, Springer Science and Business Media LLC, 2020. https://doi.org/10.1007/s00704-020-03164-w

  18. Lee MH, Im ES, Bae DH (2019) A comparative assessment of climate change impacts on drought over Korea based on multiple climate projections and multiple drought indices. Clim Dyn 53(1–2):389–404

    Article  Google Scholar 

  19. Lorenzo-Lacruz J, Vicente-Serrano SM, López-Moreno JI, Beguería S, García-Ruiz JM, Cuadrat JM (2010) The impact of droughts and water management on various hydrological systems in the headwaters of the Tagus River (central Spain). J Hydrol 386(1–4):13–26

    Article  Google Scholar 

  20. Marcos-Garcia P, Lopez-Nicolas A, Pulido-Velazquez M (2017) Combined use of relative drought indices to analyze climate change impact on meteorological and hydrological droughts in a Mediterranean basin. J Hydrol 554:292–305

    Article  Google Scholar 

  21. McKee TB, Doesken, NJ and Kleist J (1993) The relationship of drought frequency and duration to time scales. In Proceedings of the Eighth Conference on Applied Climatology, Boston, MA, USA 179–184

  22. Mohammed K, Islam AS, Islam GMT, Alferi L, Bala SK, Khan MJU (2017) Impact of high-end climate change on floods and low flows of the Brahmaputra River. J Hydrol Eng 22(10). https://doi.org/10.1061/28ASCE/29HE.1943-5584.0001567

  23. Mohammed K, Islam AS, Islam GMT, Alferi L, Bala SK, Khan MJU (2018) Future floods in Bangladesh under 1.5°C, 2°C and 4°C global warming scenarios. J Hydrol Eng 23(12):04018050

    Article  Google Scholar 

  24. Mondol MAH, Ara I, Das SC (2017) Meteorological drought index mapping in Bangladesh using standardized precipitation index during 1981-2010. Advances in Meteorology, Hindawi Publishing Corporation, 2017, pp.1–17

  25. Monteith JL (1965). Evaporation and environment. In Symposia of the society for experimental biology (Vol. 19, pp. 205-234). Cambridge University Press (CUP) Cambridge

  26. Nam WH, Choi JY, Yoo SH, Jang MW (2012) A decision support system for agricultural drought management using risk assessment. Paddy Water Environ 10(3):197–207

    Article  Google Scholar 

  27. Oloruntade AJ, Mohammad TA, Ghazali AH, Wayayok A (2017) Analysis of meteorological and hydrological droughts in the Niger-South Basin, Nigeria. Glob Planet Chang 155:225–233

    Article  Google Scholar 

  28. Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, Church JA, Clarke L, Dahe Q, Dasgupta P and Dubash NK (2014) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC).

  29. Paulo AA, Rosa RD, Pereira LS (2012) Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in Portugal. Nat Hazards Earth Syst Sci 12:1481–1491

    Article  Google Scholar 

  30. Penman HL (1948) Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A Mathematical and Physical Sciences 193(1032):120–145

    Google Scholar 

  31. Rahman MR (2013) Agro-spatial diversity in Bangladesh—a special reference to climate change and crop diversification in Rajshahi division. J Geo-Environment 10

  32. Rahman MR, Lateh H (2016) Meteorological drought in Bangladesh: assessing, analysing and hazard mapping using SPI, GIS and monthly rainfall data. Environ Earth Sci 75(12):1–20

    Article  Google Scholar 

  33. Rahman MA, Yunsheng L, Sultana N, Ongoma V (2019) Analysis of reference evapotranspiration (ET 0) trends under climate change in Bangladesh using observed and CMIP5 data sets. Meteorog Atmos Phys 131(3):639–655

    Article  Google Scholar 

  34. Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, Kindermann G, Nakicenovic N, Rafaj P (2011) RCP 8.5 - a scenario of comparatively high greenhouse gas emissions. Clim Chang 109(1–2):33

    Article  Google Scholar 

  35. Saha A, Ghosh S, Sahana AS, Rao EP (2014) Failure of CMIP5 climate models in simulating post-1950 decreasing trend of Indian monsoon. Geophys Res Lett 41(20):7323–7330

    Article  Google Scholar 

  36. Shahid S (2010) Rainfall variability and the trends of wet and dry periods in Bangladesh. Int J Climatol 30(15):2299–2313

    Article  Google Scholar 

  37. Shahid S, Behrawan H (2008) Drought risk assessment in the western part of Bangladesh. Nat Hazards 46(3):391–413

    Article  Google Scholar 

  38. Sharmila S, Joseph S, Sahai AK, Abhilash S, Chattopadhyay R (2015) Future projection of Indian summer monsoon variability under climate change scenario: an assessment from CMIP5 climate models. Glob Planet Chang 124:62–78

    Article  Google Scholar 

  39. Shaw R & Nguyen H (Eds.) (2011) Droughts in Asian monsoon region (Vol 8). Emerald Group Publishing

  40. Sheffield J, Andreadis K, Wood E, Lettenmaier D (2009) Global and continental drought in the second half of the twentieth century: severity-area-duration analysis and temporal variability of large-scale events. J Climatol 22:1962–1981

    Article  Google Scholar 

  41. Sheffield J, Wood EF, Roderick ML (2012) Little change in global drought over the past 60 years. Nature, Springer Nature 491:435–438

    Google Scholar 

  42. Solomon S, Dahe Q, Martin M, Chen Z, Marquis M, Averyt KB, Tignor M, and Miller HL, (2007) Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change

  43. Tallaksen, L.M., Van Lanen, H.A.J. (Eds.) (2004) Hydrological drought: processes and estimation methods for streamflow and groundwater. Elsevier

  44. Tate EL, Gustard A (2000) Drought definition: a hydrological perspective in drought and drought mitigation in Europe. Springer Netherlands pp 23–48

  45. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94

    Article  Google Scholar 

  46. Van Loon AF, Van Dijk AI, Tallaksen LM, Teuling AJ, Hannah DM, Van Lanen HA (2016) Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches. Hydrology and Earth System Sciences, Copernicus GmbH 20:3631

    Article  Google Scholar 

  47. Vicente-Serrano SM, Begueria S, Lopez-Moreno JI (2010) A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718

    Article  Google Scholar 

  48. Vörösmarty CJ, Green P, Salisbury J, Lammers RB (2000) Global water resources: vulnerability from climate change and population growth. Science 289(5477):284–288

    Article  Google Scholar 

  49. Wada Y, Van Beek LP, Wanders N, Bierkens MF (2013) Human water consumption intensifies hydrological drought worldwide. Environ Res Lett 8(3):034036

    Article  Google Scholar 

  50. Wilhite DA (2000) Drought as a natural hazard: concepts and definitions

  51. Wilhite DA, Sivakumar MVK, Pulwarty R (2014) Managing drought risk in a changing climate: the role of national drought policy. Weather Clim Extrem 3:4–13

    Article  Google Scholar 

  52. Xu C-Y, Singh V (2001) Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrological processes, Wiley Online Library, 15, 305–319

Download references

Funding

The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no. 603864 (HELIX: High-End cLimate Impacts and eXtremes; http://www.helixclimate.eu).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jamal Uddin Khan.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Highlights

• Multi-model ensemble projections of meteorological drought over Bangladesh

• Hargreaves method underestimates droughts compared to the Thornthwaite method due to the low climate sensitivity in the DTR

• Short spell drought (< 6 months) is also projected to become more severe in the future

• In the pre-monsoon season, a spatially coherent dry-wet regime shift is projected between near and far future

• Drought severity will continue to increase in the south-west region throughout the century

• The north-west region will become wetter while the south-central region will become drier by the end of the century

Electronic supplementary material

ESM 1

(DOCX 1004 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Khan, J.U., Islam, A.K.M.S., Das, M.K. et al. Future changes in meteorological drought characteristics over Bangladesh projected by the CMIP5 multi-model ensemble. Climatic Change 162, 667–685 (2020). https://doi.org/10.1007/s10584-020-02832-0

Download citation

Keywords

  • Climatic change
  • Drought
  • RCM
  • RCP
  • SPI
  • SPEI
  • Multi-model ensemble