Abstract
The analysis of detailed characteristics of rainfall is of utmost importance for understanding water resources, irrigation, and agriculture. This study investigated detailed characteristics of rainfall of Bangladesh from 1966 to 2019. Rainfall features like the precipitation concentration index (PCI) and seasonality index (SI) were estimated to characterize spatial patterns of rainfall regimes, and innovative trend analysis (ITA) and percent bias (PBIAS) were used to detect the trend, and its reliability was tested by using the Mann–Kendall (MK) or modified Mann–Kendall (mMK) test. The magnitude of changes was computed by using Sen’s slope estimator (Q), and discrete wavelet transform (DWT) was employed to find out the dominant periodicity of the trend of annual series. SI and PCI revealed that rainfall is mainly seasonal and markedly with the long dry season, and the distribution of rainfall is irregular for the major portion of Bangladesh. The result of ITA and PBIAS showed a similar trend for all the stations and time scales. ITA showed that 23 stations experienced significant (α = < 0.05) increasing (39.13%) and decreasing (39.13%) trends in annual rainfall. For the seasonal scale, post-monsoon rainfall is dominated by significant increasing trend (60.87%), whereas winter rainfall is dominated by significant decreasing trend (65.28%); besides, both decreasing and increasing trends were found in pre-monsoon and monsoon in Bangladesh. The analysis of DWT confirmed that 4- to 16-year periodic cycle was the dominant component for annual rainfall. The results of detailed analysis of rainfall will be helpful for policymakers and scientists to focus on regional-scale planning about flood and drought situation of the country that will be ultimately helpful for agricultural development and environmental planning.
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References
Adarsh S, Janga Reddy M (2015) Trend analysis of rainfall in four meteorological subdivisions of southern India using nonparametric methods and discrete wavelet transforms. Int J Climatol 35(6):1107–1124. https://doi.org/10.1002/joc.4042
Agrawala S, Ota T, Ahmed AU, Smith J, Van Aalst M (2003) Development and climate change in Bangladesh: focus on coastal flooding and the Sundarbans (1-49). OECD, Paris
Ahasan MN, Chowdhary MA, Quadir DA (2010) Variability and trends of summer monsoon rainfall over Bangladesh. J Hydrol Meteorol 7(1):1–17. https://doi.org/10.3126/jhm.v7i1.5612
Ahmad I, Zhang F, Tayyab M, Anjum MN, Zaman M, Liu J, Farid HU, Saddique Q (2018) Spatiotemporal analysis of precipitation variability in annual, seasonal and extreme values over upper Indus River basin. Atmos Res 213:346–360. https://doi.org/10.1016/j.atmosres.2018.06.019
Ahmed R, Kim IK (2003) Patterns of daily rainfall in Bangladesh during the summer monsoon season: case studies at three stations. Phys Geogr 24(4):295–318. https://doi.org/10.2747/0272-3646.24.4.295
Alam MT, Iskander SM (2013) Climate change impact: climate type, vegetation type, rainfall intensity over three decades in Bangladesh. IOSR J Environ Sci Toxicol Food Technol 4(6):56–59
Anderson RL (1954) The problem of autocorrelation in regression analysis. J Am Stat Assoc 49(265):113–129
Araghi A, Baygi MM, Adamowski J, Malard J, Nalley D, Hasheminia SM (2015) Using wavelet transforms to estimate surface temperature trends and dominant periodicities in Iran based on gridded reanalysis data. Atmos Res 155:52–72. https://doi.org/10.1016/j.atmosres.2014.11.016
Ay M, Kisi O (2015) Investigation of trend analysis of monthly total precipitation by an innovative method. Theor Appl Climatol 120(3–4):617–629. https://doi.org/10.1007/s00704-014-1198-8
Bari SH, Rahman MTU, Hoque MA, Hussain MM (2016) Analysis of seasonal and annual rainfall trends in the northern region of Bangladesh. Atmos Res 176:148–158. https://doi.org/10.1016/j.atmosres.2016.02.008
Basher MA, Stiller-Reeve MA, Islam AS, Bremer S (2018) Assessing climatic trends of extreme rainfall indices over northeast Bangladesh. Theor Appl Climatol 134(1–2):441–452. https://doi.org/10.1007/s00704-017-2285-4
Brammer H (2002) Land use and land use planning in Bangladesh. University Press Ltd., Dhaka
Chatterjee S, Khan A, Akbari H, Wang Y (2016) Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901–2002), West Bengal, India. Atmos Res 182:54–75. https://doi.org/10.1016/j.atmosres.2016.07.010
Chu PS, Chen YR, Schroeder TA (2010) Changes in precipitation extremes in the Hawaiian Islands in a warming climate. J Clim 23(18):4881–4900. https://doi.org/10.1175/2010JCLI3484.1
Cui L, Wang L, Lai Z, Tian Q, Liu W, Li J (2017) Innovative trend analysis of annual and seasonal air temperature and rainfall in the Yangtze River Basin, China during 1960–2015. J Atmos Sol Terr Phys 164:48–59. https://doi.org/10.1016/j.jastp.2017.08.001
Das J, Bhattacharya SK (2018) Trend analysis of long-term climatic parameters in Dinhata of Koch Bihar district, West Bengal. Spat Inf Res 26:1–10. https://doi.org/10.1007/s41324-018-0173-3
Das J, Mandal T, Saha P (2019) Spatio-temporal trend and change point detection of winter temperature of North Bengal, India. Spat Inf Res 27:411–424. https://doi.org/10.1007/s41324-019-00241-9
Das J, Mandal T, Saha P, Bhattacharya SK (2020a) Variability and trends of rainfall using non-parametric approaches: a case study of semi-arid area. Mausam 75(1):33–44
Das J, Rahman AS, Mandal T, Saha P (2020b) Exploring driving forces of large-scale unsustainable groundwater development for irrigation in lower Ganga River basin in India. Environ Dev Sustain:1–21. https://doi.org/10.1007/s10668-020-00917-5
Das J, Rahman ATMS, Mandal T, Saha P (2020c) Challenges for sustainable groundwater management for large scale irrigation under changing climate in lower Ganga River Basin in India. Groundw Sustain Dev 100449:100449. https://doi.org/10.1016/j.gsd.2020.100449
Das J, Gayen A, Saha P, Bhattacharya SK (2020d) Meteorological drought analysis using standardized precipitation index over Luni Basin in Rajasthan, India. SN Appl Sci 2. https://doi.org/10.1007/s42452-020-03321-w
Fathian F, Dehghan Z, Bazrkar MH, Eslamian S (2016) Trends in hydrological and climatic variables affected by four variations of the Mann-Kendall approach in Urmia Lake basin, Iran. Hydrol Sci J 61(5):892–904. https://doi.org/10.1080/02626667.2014.932911
Feng X, Porporato A, Rodriguez-Iturbe I (2013) Changes in rainfall seasonality in the tropics. Nat Clim Chang 3(9):811–815. https://doi.org/10.1038/nclimate1907
Ghaemi A, Rezaie-Balf M, Adamowski J, Kisi O, Quilty J (2019) On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction. Agric For Meteorol 278:107647. https://doi.org/10.1016/j.agrformet.2019.107647
Gilbert RO (1987) Statistical methods for environmental pollution monitoring. Van Nostrand Reinhold Company, New York
Girma A, Qin T, Wang H, Yan D, Gedefaw M, Abiyu A,Batsuren D (2020) Study on Recent Trends of Climate Variability Using Innovative Trend Analysis: The Case of the upper Huai River Basin. Polish Journal of Environmental Studies 29 (3):2199-2210
Gocic M, Trajkovic S (2013) Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia. Glob Planet Chang 100:172–182. https://doi.org/10.1016/j.gloplacha.2012.10.014
Haktanir T, Citakoglu H (2014) Trend, independence, stationarity, and homogeneity tests on maximum rainfall series of standard durations recorded in Turkey. J Hydrol Eng 19(9):05014009. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000973
Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204(1–4):182–196. https://doi.org/10.1016/S0022-1694(97)00125-X
Hamilton JP, Whitelaw GS, Fenech A (2001) Mean annual temperature and total annual precipitation trends at Canadian biosphere reserves. Environ Monit Assess 67(1–2):239–275. https://doi.org/10.1023/A:1006490707949
Huang Y, Wang H, Xiao W, Chen L, Yan D, Zhou Y, Jiang D, Yang M (2018) Spatial and temporal variability in the precipitation concentration in the upper reaches of the Hongshui river basin, southern China. Adv Meteorol 2018:1–19. https://doi.org/10.1155/2018/4329757
IPCC (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
Islam T, Neelim A (2010a) Assessing fluctions of temperature, in climate change in Bangladesh: a closer look into temperature and rainfall data. The University Press Limited, Bangladesh, p 80
Islam T, Neelim A (2010b) Climate change in Bangladesh: a closer look into temperature and rainfall data. University Press, Dhaka
Joshi N, Gupta D, Suryavanshi S, Adamowski J, Madramootoo CA (2016) Analysis of trends and dominant periodicities in drought variables in India: a wavelet transform based approach. Atmos Res 182:200–220. https://doi.org/10.1016/j.atmosres.2016.07.030
Kamruzzaman M, Rahman ATMS, Ahmed MS, Kabir ME, Mazumder QH, Rahman MS, Jahan CS (2018) Spatio-temporal analysis of climatic variables in the western part of Bangladesh. Environ Dev Sustain 20(1):89–108. https://doi.org/10.1007/s10668-016-9872-x
Karl TR, Trenberth KE (2003) Modern global climate change. Science 302(5651):1719–1723. https://doi.org/10.1126/science.1090228
Kendall MG (1975) Rank correlation measures, vol 202. Charles Griffin, London, p 15
Kisi O (2015) An innovative method for trend analysis of monthly pan evaporations. J Hydrol 527:1123–1129. https://doi.org/10.1016/j.jhydrol.2015.06.009
Kisi O, Ay M (2014) Comparison of Mann–Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey. J Hydrol 513:362–375. https://doi.org/10.1016/j.jhydrol.2014.03.005
Kumar KN, Rajeevan M, Pai DS, Srivastava AK, Preethi B (2013) On the observed variability of monsoon droughts over India. Weather Clim Extr 1:42–50. https://doi.org/10.1016/j.wace.2013.07.006
Li X, Jiang F, Li L, Wang G (2011) Spatial and temporal variability of precipitation concentration index, concentration degree and concentration period in Xinjiang, China. Int J Climatol 31(11):1679–1693. https://doi.org/10.1002/joc.2181
Lopez B, Baran N, Bourgine B (2015) An innovative procedure to assess multi-scale temporal trends in groundwater quality: example of the nitrate in the Seine–Normandy basin, France. J Hydrol 522:1–10. https://doi.org/10.1016/j.jhydrol.2014.12.002
Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674–693. https://doi.org/10.1109/34.192463
Mallick DL (2008) Growing environmental and climate refugees in Bangladesh: urgent actions are required. In C40 Tokyo Conference on Climate Change—adaptation measures for sustainable low carbon cities pp. 22-24
Mandal T, Das J, Rahman, ATMS Saha P (2020) Rainfall insight in Bangladesh and India: climate change and environmental perspective. In Habitat, Ecology and Ekistics: Case Studies of Human-Environment Interactions in India. Springer, Singapore. https://doi.org/10.1007/978-3-030-49115-4_3
Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3): 245–259. doi:10.2307/1907187
Markus M, Demissie M, Short MB, Verma S, Cooke RA (2013) Sensitivity analysis of annual nitrate loads and the corresponding trends in the lower Illinois River. J Hydrol Eng 19(3):533–543
Merino A, López L, Hermida L, Sánchez JL, García-Ortega E, Gascón E, Fernández-González S (2015) Identification of drought phases in a 110-year record from Western Mediterranean basin: trends, anomalies and periodicity analysis for Iberian Peninsula. Glob Planet Chang 133:96–108. https://doi.org/10.1016/j.gloplacha.2015.08.007
Michiels P, Gabriels D, Hartmann R (1992) Using the seasonal and temporal precipitation concentration index for characterizing the monthly rainfall distribution in Spain. Catena 19(1):43–58. https://doi.org/10.1016/0341-8162(92)90016-5
Nalley D, Adamowski J, Khalil B (2012) Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954–2008). J Hydrol 475:204–228. https://doi.org/10.1016/j.jhydrol.2012.09.049
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 transform. Atmos Res 132:375–398. https://doi.org/10.1016/j.atmosres.2013.06.011
Nievergelt Y (2001) Wavelets made easy. Birkhäuser, Boston
Nunes AN, Lourenço L (2015) Precipitation variability in Portugal from 1960 to 2011. J Geogr Sci 25(7):784–800. https://doi.org/10.1007/s11442-015-1202-y
Oliver JE (1980) Monthly precipitation distribution: a comparative index. Prof Geogr 32(3):300–309. https://doi.org/10.1111/j.0033-0124.1980.00300.x
Palizdan N, Falamarzi Y, Huang YF, Lee TS (2017) Precipitation trend analysis using discrete wavelet transform at the Langat River Basin, Selangor, Malaysia. Stoch Env Res Risk A 31(4):853–877. https://doi.org/10.1007/s00477-016-1261-3
Partal T, Küçük M (2006) Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region (Turkey). Phys Chem Earth Parts A/B/C 31(18):1189–1200. https://doi.org/10.1016/j.pce.2006.04.043
Pathak P, Kalra A, Ahmad S, Bernardez M (2016) Wavelet-aided analysis to estimate seasonal variability and dominant periodicities in temperature, precipitation, and streamflow in the Midwestern United States. Water Resour Manag 30(13):4649–4665. https://doi.org/10.1007/s11269-016-1445-0
Pearson ES, Hartley HO (1966) Biometrika tables for statisticians, vol 1, 3rd edn. Cambridge University Press, London
Percival DB, Walden AT (2000) Wavelet methods for time series analysis, 1106. Cambridge University Press, New York
Protić M, Shamshirband S, Petković D, Abbasi A, Kiah MLM, Unar JA, Živković L, Raos M (2015) Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm. Energy 87:343–351. https://doi.org/10.1016/j.energy.2015.04.109
Pour SH, Wahab AKA, Shahid S, Ismail ZB (2020) Changes in reference evapotranspiration and its driving factors in peninsular Malaysia. Atmospheric Research 246:105096
Pryor SC, Schoof JT (2008) Changes in the seasonality of precipitation over the contiguous USA. J Geophys Res-Atmos 113(D21). https://doi.org/10.1029/2008JD010251
Rahman MR, Salehin M, Matsumoto J (1997) Trends of monsoon rainfall pattern in Bangladesh. Bangladesh J Water Resour 14(18):121–138
Rahman A, Jiban Md JH, Munna SA (2015) Regional variation of temperature and rainfall in Bangladesh: estimation of trend. Open J Stat 5:652–657. https://doi.org/10.4236/ojs.2015.57066
Rahman A. T. M. S, Kamruzzaman MD, Jahan CS, Mazumder QH, Hossain A (2016) Evaluation of spatio-temporal dynamics of water table in NW Bangladesh: an integrated approach of GIS and Statistics. Sustainable Water Resources Management 2 (3):297–312
Rahman A. T. M. S, Jahan CS,Mazumder QH, Kamruzzaman Md, Hosono T, (2017) Drought analysis and its implication in sustainable water resource management in Barind area, Bangladesh. Journal of the Geological Society of India 89 (1):47–56
Rahman MA, Yunsheng L, Sultana N (2017a) Analysis and prediction of rainfall trends over Bangladesh using Mann–Kendall, Spearman’s rho tests and ARIMA model. Meteorog Atmos Phys 129(4):409–424. https://doi.org/10.1007/s00703-016-0479-4
Rahman M, Kamal S, Billah M (2017b) Prediction and trends of rainfall variability over Bangladesh. Sci J Appl Mathematics Stat 5(1):54–59. https://doi.org/10.11648/j.sjams.20170501.18
Rahman ATMS, Ahmed SM, Adnan MA, Kamruzzaman M, Khalek MA, Mazumder QH, Jahan CS (2018) Modeling the changes in water balance components of the highly irrigated western part of Bangladesh. Hydrol Earth Syst Sci 22(8):4213–4228. https://doi.org/10.5194/hess-22-4213-2018
Rashid H (1991) Geography of Bangladesh. The University Press Limited, Dhaka
Roushangar K, Alizadeh F (2018) Identifying complexity of annual precipitation variation in Iran during 1960–2010 based on information theory and discrete wavelet transform. Stoch Env Res Risk A 32(5):1205–1223. https://doi.org/10.1007/s00477-017-1430-z
Sa’adi Z, Shahid S, Ismail T, Chung ES, Wang XJ (2019) Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann–Kendall test. Meteorog Atmos Phys 131(3):263–277. https://doi.org/10.1007/s00703-017-0564-3
Salahuddin A, Isaac RH, Curtis S, Matsumoto J (2006) Teleconnections between the sea surface temperature in the Bay of Bengal and monsoon rainfall in Bangladesh. Glob Planet Chang 53(3):188–197. https://doi.org/10.1016/j.gloplacha.2006.06.001
Sanderson M, Ahmed R (1979) Pre-monsoon rainfall and its variability in Bangladesh: a trend surface analysis. Hydrol Sci J 24(3):277–287. https://doi.org/10.1080/02626667909491867
Sang YF (2012) A practical guide to discrete wavelet decomposition of hydrologic time series. Water Resour Manag 26(11):3345–3365. https://doi.org/10.1007/s11269-012-0075-4
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389
Sen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17(9):1042–1046. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000556
Serencam U (2019) Innovative trend analysis of total annual rainfall and temperature variability case study: Yesilirmak region, Turkey. Arab J Geosci 12(23):704. https://doi.org/10.1007/s12517-019-4903-1
Shahid S (2010) Recent trends in the climate of Bangladesh. Clim Res 42(3):185–193. https://doi.org/10.3354/cr00889
Shahid S (2011) Trends in extreme rainfall events of Bangladesh. Theor Appl Climatol 104(3–4):489–499. https://doi.org/10.1007/s00704-010-0363-y
Shahid S, Khairulmaini OS (2009) Spatio-temporal variability of rainfall over Bangladesh during the time period 1969-2003. Asia-Pac J Atmos Sci 45(3):375–389
Shenify M, Danesh AS, Gocić M, Taher RS, Wahab AWA, Gani A, Shamshirband S, Petković D (2016) Precipitation estimation using support vector machine with discrete wavelet transform. Water Resour Manag 30(2):641–652. https://doi.org/10.1007/s11269-015-1182-9
Sneyers S (1990) On the statistical analysis of series of observations. Technical note no 5 143, WMO No 725 415 Secretariat of the World Meteorological Organization, Geneva
Suhaila J, Yusop Z (2018) Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia. Meteorog Atmos Phys 130(5):565–581. https://doi.org/10.1007/s00703-017-0537-6
Tayyab M, Zhou J, Dong X, Ahmad I, Sun N (2019) Rainfall-runoff modeling at Jinsha River basin by integrated neural network with discrete wavelet transform. Meteorog Atmos Phys 131(1):115–125. https://doi.org/10.1007/s00703-017-0546-5
Tosunoglu F, Kisi O (2017) Trend analysis of maximum hydrologic drought variables using Mann–Kendall and Şen’s innovative trend method. River Res Appl 33(4):597–610. https://doi.org/10.1002/rra.3106
Trenberth KE, Fasullo JT, Shepherd TG (2015) Attribution of climate extreme events. Nat Clim Chang 5(8):725–730. https://doi.org/10.1038/nclimate2657
Van Scheltinga CT, Quadir DA, Ludwig F (2015) Baseline study climate change–Bangladesh Delta Plan. Bangladesh Delta Plan
Walsh RPD, Lawler DM (1981) Rainfall seasonality: description, spatial patterns and change through time. Weather 36(7):201–208. https://doi.org/10.1002/j.1477-8696.1981.tb05400.x
Wang Y, Sen OL, Wang B (2003) A highly resolved regional climate model (IPRC-RegCM) and its simulation of the 1998 severe precipitation event over China. Part I: model description and verification of simulation. J Clim 16(11):1721–1738. https://doi.org/10.1175/1520-0442(2003)016<1721:AHRRCM>2.0.CO;2
Wu H, Qian H (2017) Innovative trend analysis of annual and seasonal rainfall and extreme values in Shaanxi, China, since the 1950s. Int J Climatol 37(5):2582–2592. https://doi.org/10.1002/joc.4866
Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16(9):1807–1829. https://doi.org/10.1002/hyp.1095
Zhang Q, Xu CY, Gemmer M, Chen YD, Liu C (2009) Changing properties of precipitation concentration in the Pearl River basin, China. Stoch Env Res Risk A 23(3):377–385. https://doi.org/10.1007/s00477-008-0225-7
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The authors acknowledge the Bangladesh Agricultural Council for providing the rainfall data. Also, the authors would like to thank anonymous reviewers and editor for their helpful comments.
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Jayanta Das: Conceptualization, methodology, Formal analysis, writing—reviewing, editing and supervision. Tapash Mandal: Writing—original draft, contributed to data analysis. ATM Sakiur Rahman: Conceived and designed the analysis, collected the data, programming, editing and supervision. Piu Saha: Writing— original draft and performed the analysis.
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Das, J., Mandal, T., Rahman, A.T.M.S. et al. Spatio-temporal characterization of rainfall in Bangladesh: an innovative trend and discrete wavelet transformation approaches. Theor Appl Climatol 143, 1557–1579 (2021). https://doi.org/10.1007/s00704-020-03508-6
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DOI: https://doi.org/10.1007/s00704-020-03508-6