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Analysis of reference evapotranspiration (ET0) trends under climate change in Bangladesh using observed and CMIP5 data sets

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Abstract

ET0 is an important hydro-meteorological phenomenon, which is influenced by changing climate like other climatic parameters. This study investigates the present and future trends of ET0 in Bangladesh using 39 years’ historical and downscaled CMIP5 daily climatic data for the twenty-first century. Statistical Downscaling Model (SDSM) was used to downscale the climate data required to calculate ET0. Penman–Monteith formula was applied in ET0 calculation for both the historical and modelled data. To analyse ET0 trends and trend changing patterns, modified Mann–Kendall and Sequential Mann–Kendall tests were, respectively, done. Spatial variations of ET0 trends are presented by inverse distance weighting interpolation using ArcGIS 10.2.2. Results show that RCP8.5 (2061–2099) will experience the highest amount of ET0 totals in comparison to the historical and all other scenarios in the same time span of 39 years. Though significant positive trends were observed in the mid and last months of year from month-wise trend analysis of representative concentration pathways, significant negative trends were also found for some months using historical data in similar analysis. From long-term annual trend analysis, it was found that major part of the country represents decreasing trends using historical data, but increasing trends were observed for modelled data. Theil–Sen estimations of ET0 trends in the study depict a good consistency with the Mann–Kendall test results. The findings of the study would contribute in irrigation water management and planning of the country and also in furthering the climate change study using modelled data in the context of Bangladesh.

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References

  • Ahmed R, Karmakar S (1993) Arrival and withdrawal dates of the summer monsoon in Bangladesh. Int J Climatol 137:727–740. https://doi.org/10.1002/joc.3370130703

    Article  Google Scholar 

  • Ahmed R, Kim I (2003) Patterns of daily rainfall in Bangladesh during the summer monsoon season: case studies at three stations. Phys Geogr 24:295–318

    Article  Google Scholar 

  • Ahmad I, Tang D, Wang T, Wang M, Wagan B (2015) Precipitation trends over time using Mann-Kendall and Spearman’s rho tests in swat river basin, Pakistan. Adv Meteorol. https://doi.org/10.1155/2015/431860

    Google Scholar 

  • Alexandersson H (1986) A homogeneity test applied to precipitation data. Int J Climatol 6:661–675

    Article  Google Scholar 

  • Ali A (1996) Vulnerability of Bangladesh to climate change and sea level rise through tropical cyclones and storm surges. Water Air Soil Pollut 92:171–179

    Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome 300(9):D05109

    Google Scholar 

  • Amarasinghe UA, Sharma BR, Muthuwatta L, Khan ZH (2014) Water for food in Bangladesh: outlook to 2030. Colombo, Sri Lanka: International Water Management Institute (IWMI). 32p. IWMI Research Report 158. http://doi.org/10.5337/2014.213

  • Attarod P, Kheirkhah F, Sigaroodi SK, Sadeghi SMM (2015) Sensitivity of Reference Evapotranspiration to Global Warming in the Caspian Region, North of Iran. J Agr Sci Tech 17:869–883

    Google Scholar 

  • Ayub R, Miah MM (2011) Effects of change in temperature on reference crop evapotranspiration (ETo) in the northwest region of Bangladesh. In: The fourth annual paper meet and 1st civil engineering congress, December, 2011, Dhaka, pp 978–984

  • Bayazit M, Önöz B (2008) To prewhiten or not to prewhiten in trend analysis? Hydrol Sci J 52:611–624. https://doi.org/10.1623/hysj.52.4.611

    Article  Google Scholar 

  • Blain GC (2013) The Mann–Kendall test: the need to consider the interaction between serial correlation and trend. Agric Eng. https://doi.org/10.4025/actasciagron.v35i4.16006

    Google Scholar 

  • Buishand TA (1982) Some methods for testing the homogeneity of rainfall records. J Hydrol 58:11–27

    Article  Google Scholar 

  • Bultot F, Dupriez GL, Gellens D (1988) Estimated annual regime of energy balance components, evapotranspiration and soil moisture for a drainage basin in case of a CO2 doubling. Clim Chang 12:39–56. https://doi.org/10.1007/BF00140263

    Article  Google Scholar 

  • Climate Change Cell (2008) Economic modeling of climate change adaptation needs for physical infrastructures in Bangladesh Department of Environment, Ministry of Environment and Forests, Component 4b. Comprehensive Disaster Management Programme, Ministry of Food and Disaster Management, Bangladesh

    Google Scholar 

  • Das GA, Singh BM, Albert X, Mark O (2005) Water sector of Bangladesh in the context of integrated water resources management: a review. Int J Water Resour D 21:385–398. https://doi.org/10.1080/07900620500037818

    Article  Google Scholar 

  • Ericksen NJ, Ahmad QK, Chowdhury AR (1996) Socio-economic implications of climate change for Bangladesh. The implications of climate and sea-level change for Bangladesh. Springer, Netherlands, pp 205–287

    Chapter  Google Scholar 

  • Gleick PH (1986) Methods for evaluating the regional hydrologic impacts of global climatic changes. J Hydrol 88:97–116. https://doi.org/10.1016/0022-1694(86)90199-X

    Article  Google Scholar 

  • Goyal RK (2004) Sensitivity of evapotranspiration to global warming: a case study of arid zone of Rajasthan (India). Agric Water Manag 69:1–11. https://doi.org/10.1016/j.agwat.2004.03.014

    Article  Google Scholar 

  • Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204:182–196. https://doi.org/10.1016/S0022-1694(97)00125-X

    Article  Google Scholar 

  • Haylock MR, Cawley GC, Harpham C, Wilby RL, Goodess CM (2006) Downscaling heavy precipitation over the UK: a comparison of dynamical and statistical methods and their future scenarios. Int J Climatol 26:1397–1415. https://doi.org/10.1002/joc.1318

    Article  Google Scholar 

  • Hirsch RM, Slack JR (1984) A nonparametric trend test for seasonal data with serial dependence. Water Resour Res 20:727–732. https://doi.org/10.1029/WR020i006p00727

    Article  Google Scholar 

  • Immerzeel W (2008) Historical trends and future predictions of climate variability in the Brahmaputra basin. Int J Climatol 28:243–254. https://doi.org/10.1002/joc.1528

    Article  Google Scholar 

  • IPCC (2007) Climate change 2007: impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 976

    Google Scholar 

  • IPCC (2013) Climate change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. http://doi.org/10.1017/CBO9781107415324

  • Ji F, Wu Z, Huang J, Chassignet EP (2014) Evolution of land surface air temperature trend. Nat Clim Chang 4:462–466. https://doi.org/10.1038/nclimate2223

    Article  Google Scholar 

  • Jones P (1999) The Instrumental Data Record: Its accuracy and use in attempts to identify the “CO2 Signal”. Analysis of climate variability. Springer, Berlin, pp 53–76

  • Karim MF, Mimura N (2008) Impacts of climate change and sea-level rise on cyclonic storm surge floods in Bangladesh. Glob Environ Chang 18:490–500. https://doi.org/10.1016/j.gloenvcha.2008.05.002

    Article  Google Scholar 

  • Karim NN, Talukder MSU, Hassan AA, Khair MA (2008) Temporal trend of reference crop evapotranspiration due to changes of climate in North Central hydrological region of Bangladesh. J Agric Eng 34/AE:91–100

    Google Scholar 

  • Karl R, Williams CN Jr (1987) An approach to adjusting climatological time series for discontinuous inhomogeneities. J Climatol Appl Meteorol 26:1744–1763

    Article  Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Griffin and Co, London

    Google Scholar 

  • Khalil AA (2013) Effect of climate change on evapotranspiration in Egypt. Researcher 55:7–12. https://doi.org/10.9780/22307850

    Google Scholar 

  • Kumar S, Merwade V, Kam J, Thurner K (2009) Stream flow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. J Hydrol 374:171–183. https://doi.org/10.1016/j.jhydrol.2009.06.012

    Article  Google Scholar 

  • Kundu S, Khare D, Mondal A (2017) Future changes in rainfall, temperature and reference evapotranspiration in the central India by least square support vector machine. Geosci Front 8:583–596. https://doi.org/10.1016/j.gsf.2016.06.002

    Article  Google Scholar 

  • Lorentzen T (2014) Statistical analysis of temperature data sampled at Station-M in the Norwegian Sea. J Mar Syst 130:31–45. https://doi.org/10.1016/j.jmarsys.2013.09.009

    Article  Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259. http://doi.org/0012-9682(194507)13:3<245:NTAT>2.0.CO;2-U

  • Martin P, Rosenberg NJ, Kenney MMS (1989) Sensitivity of evapotranspiration in wheat field, afforest and a grassland to change in climate and direct effect of carbon dioxide. Clim Chang 14:117–151

    Article  Google Scholar 

  • Mirza MMQ (2002) Global warming and changes in the probability of occurrence of floods in Bangladesh and implications. Glob Environ Chang 12:127–138. https://doi.org/10.1016/S0959-3780(02)00002-X

    Article  Google Scholar 

  • Mojid MA, Rannu RP, Karim NN (2015) Climate change impacts on reference crop evapotranspiration in northwest hydrological region of Bangladesh. Int J Climatol 35:4041–4046. https://doi.org/10.1002/joc.4260

    Article  Google Scholar 

  • Moratiel R, Durán JM, Snyder RL (2010) Responses of reference evapotranspiration to changes in atmospheric humidity and air temperature in Spain. Clim Res 44:27–40. https://doi.org/10.3354/cr00919

    Article  Google Scholar 

  • Nalley D, Adamowski J, Khalil B, Ozga-Zielinski B (2013) Trend detection in surface air temperature in Ontario and Quebec, Canada during 1967–2006 using the discrete wavelet transforms. Atmos Res 132:375–398. https://doi.org/10.1016/j.atmosres.2013.06.011

    Article  Google Scholar 

  • Nemec J, Schaake J (1982) Sensitivity of water resources system to climate variation. Hydrol Sci J 27:327–343. https://doi.org/10.1080/02626668209491113

    Article  Google Scholar 

  • Nick FM, Vieli A, Howat IM, Joughin I (2009) Large scale changes in Greenland outlet glacier dynamics triggered at the terminus. Nat Geosci 2:110–114. https://doi.org/10.1038/ngeo394

    Article  Google Scholar 

  • Önöz B, Bayazit M (2012) Block bootstrap for Mann–Kendall trend test of serially dependent data. Hydrol Process 26:3552–3560. https://doi.org/10.1002/hyp.8438

    Article  Google Scholar 

  • Peterson TC, Easterling DR, Karl TR, Groisman P, Nicholls N, Plummer N, Torok S, Auer I, Boehm R, Gullett D, Vincent L, Heino R, Tuomenvirta H, Mestre O, Szentimrey T, Salinger J, Førland EJ, Hanssen-Bauer I, Alexandersson H, Jones P, Parker D (1998) Homogeneity adjustments of in situ atmospheric climate data: a review. Int J Climatol 18:1493–1517. https://doi.org/10.1002/(SICI)1097-0088(19981115)18:13<1493:AID-JOC329>3.0.CO;2-T

  • Rabby YW, Shogib RI, Hossain L (2015) Analysis of temperature change in capital city of Bangladesh. J Environ Treat Tech 3:55–59

    Google Scholar 

  • Radziejewski M, Zbigniew WK (2004) Detectability of changes in hydrological records/Possibilité de détecter les changements dans les chroniques hydrologiques. Hydrol Sci J 49:39–51

    Article  Google Scholar 

  • Rahman MR, Lateh H (2015) Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model. Theor Appl Climatol. https://doi.org/10.1007/s00704-015-1688-3

    Google Scholar 

  • Rahman MA, Yunsheng L, Sultana N (2017) Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman’s rho tests and ARIMA model. Meteorol Atmos Phys 129:409–424. https://doi.org/10.1007/s00703-016-0479-4

    Article  Google Scholar 

  • Rashid HE (1991) Geography of Bangladesh. University Press Ltd, Dhaka

    Google Scholar 

  • Rosenberg NJ, Kenney MMS, Martin P (1989) Evapotranspiration in greenhouse warmed world: a review and a simulation. Agric For Meteorol 47:303–320. https://doi.org/10.1016/0168-1923(89)90102-0

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389

    Article  Google Scholar 

  • Shahid S (2010) Rainfall variability and the trends of wet and dry periods in Bangladesh. Int J Climatol 30:2299–2313. https://doi.org/10.1002/joc.2053

    Article  Google Scholar 

  • Shahid S (2011) Impact of climate change on irrigation water demand of dry season Boro rice in northwest Bangladesh. Clim Chang 105:433–453. https://doi.org/10.1007/s10584-010-9895-5

    Article  Google Scholar 

  • Solomon S, Qin D, Manning M, Alley RB, Berntsen T, Bindoff NL, Chen Z, Chidthaisong A, Gregory JM, Hegerl GC, Heimann M, Hewitson B, Hoskins BJ, Joos F, Jouzel J, Kattsov V, Lohmann U, Matsuno T, Molina M, Nicholls N, Overpeck J, Raga G, Ramaswamy V, Ren J, Rusticucci M, Somerville R, Stocker TF, Whetton P, Wood RA, Wratt D (2007) Technical summary. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate CHANGE 2007: THE PHYSICAL SCIENCE BASIS. Contribution of Working Group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

  • Sun S, Chen H, Wang G, Li J, Mu M, Yan G, Xu B, Huang J, Wang J, Zhang F, Zhu S (2016) Shift in potential evapotranspiration and its implications for dryness/wetness over Southwest China. J Geophys Res Atmos 121:9342–9355. https://doi.org/10.1002/2016JD025276

    Article  Google Scholar 

  • Sun S, Chen H, Ju W, Wang G, Sun G, Huang J, Ma H, Gao C, Hua W, Yan G (2017a) On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China. Clim Dyn 48:3779–3797. https://doi.org/10.1007/s00382-016-3302-5

    Article  Google Scholar 

  • Sun S, Wang G, Huang J, Mu M, Yan G, Liu C, Gao C, Li X, Yin Y, Zhang F, Zhu S, Hua W (2017b) Spatial pattern of reference evapotranspiration change and its temporal evolution over Southwest China. Theor Appl Climatol 130:979–992. https://doi.org/10.1007/s00704-016-1930-7

    Article  Google Scholar 

  • Theil H (1950) A rank-invariant method of linear and polynomial regression analysis. I, II, III. Nederl Akad Wetensch Proc 53:386–392, 521–525, 1397–1412

  • van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque J-F, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK (2011) The representative concentration pathways: an overview. Clim Chang 109:5–31. https://doi.org/10.1007/s10584-011-0148-z

    Article  Google Scholar 

  • Wetterhall F, Halldin S, Xu CY (2007) Seasonality properties of four statistical-downscaling methods in central Sweden. Theor Appl Climatol 87:123–137. https://doi.org/10.1007/s00704-005-0223-3

    Article  Google Scholar 

  • Wilby RL, Dawson CW (2007) User’s Manual for SDSM 4.2—a decision support tool for the assessment of regional climate change impacts. Loughborough University, UK. http://co-public.lboro.ac.uk/cocwd/SDSM/SDSMManual.pdf. Accessed 20 Oct 2016

  • Wilby RL, Harris I (2006) A framework for assessing uncertainties in climate change impacts: low flow scenarios for the River Thames, UK. Water Resour Res 42:W02419. http://doi.org/10.1029/2005WR004065

  • Wilby RL, Wigley TML, Conway D, Jones PD, Hewitson BC, Main J, Wilks DS (1998) Statistical downscaling of general circulation model output: a comparison of methods. Water Resour Res 34:2995–3008. https://doi.org/10.1029/98WR02577

    Article  Google Scholar 

  • Yaseen M, Bhatti HA, Rientjes T, Nabi G, Latif M (2013) Temporal and spatial variations in summer flows of upper Indus Basin, Pakistan. In: Proceedings of the 72nd annual session of Pakistan engineering congress, December, 2013, pp 315–334

  • Yaseen M, Bhatti HA, Rientjes T, Nabi G, Latif M (2014) Assessment of recent temperature trends in Mangla watershed. J Himalayan Earth Sci 47:107–121

    Google Scholar 

  • Zhao J, Xu Z, Zuo D, Wang X (2015) Temporal variations of reference evapotranspiration and its sensitivity to meteorological factors in Heihe River Basin, China. Water Sci Eng 8:1–8. https://doi.org/10.1016/j.wse.2015.01.004

    Article  Google Scholar 

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Acknowledgements

The authors would like to express their gratitude to Chinese Government Scholarship Council (CSC) and to Nanjing University of Information Science and Technology (NUIST) for different forms of supports. The authors are also thankful to Bangladesh Meteorological Department (BMD) for providing climate data used in this study. Special thanks go to the anonymous reviewers who contributed much in improving the quality of this paper.

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Correspondence to Mohammad Atiqur Rahman.

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Rahman, M.A., Yunsheng, L., Sultana, N. et al. Analysis of reference evapotranspiration (ET0) trends under climate change in Bangladesh using observed and CMIP5 data sets. Meteorol Atmos Phys 131, 639–655 (2019). https://doi.org/10.1007/s00703-018-0596-3

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