Browse > Article
http://dx.doi.org/10.4491/eer.2015.115

Analysis of drought in Northwestern Bangladesh using standardized precipitation index and its relation to Southern oscillation index  

Nury, Ahmad Hasan (Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology)
Hasan, Khairul (Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology)
Publication Information
Environmental Engineering Research / v.21, no.1, 2016 , pp. 58-68 More about this Journal
Abstract
The study explored droughts using the Standardized Precipitation Index (SPI) in the northwestern region of Bangladesh, which is the drought prone area. In order to assess the trend and variability of monthly rainfall, as well as 3-month scale SPI, non-parametric Mann-Kendall (MK) tests and continuous wavelet transform were used respectively. The effect of climatic parameters on the drought in this region was also evaluated using SPI, with the Southern Oscilation Index (SOI) by means of the wavelet coherence technique, a relatively new and powerful tool for describing processes. The MK test showed no statistically significant monthly rainfall trends in the selected stations, whereas the seasonal MK test showed a declining rainfall trend in Bogra, Ishurdi, Rangpur and Sayedpur stations respectively. Sen's slope of six stations also provided a decreasing rainfall trend. The trend of the SPI, as well as Sen's slope indicated an increasing dryness trend in this area. Dominant periodicity of 3-month scale SPI at 8 to 16 months, 16 to 32 months, and 32 to 64 months were observed in the study area. The outcomes from this study contribute to hydrologists to establish strategies, priorities and proper use of water resources.
Keywords
Drought; Mann-Kendall test; Rainfall; SPI; Sen's slope; Wavelet coherence; Wavelet power spectrum;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Wilhite, DA. Drought: A global assessment. Hazards and disasters: A series of definitive major works. 7th ed. London: Routledge Publishers; 2000.
2 Climate Change Cell. Department of Environment, Ministry of Environment and Forests, Bangladesh [Internet]. c2009 [cited 2014 Dec 21]. Available from: http://www.climatechangecell-bd.org/.
3 Hamed KH. Trend detection in hydrologic data: The Mann-Kendall trend test under the scaling hypothesis. J. Hydrol. 2008;349:350-363.   DOI
4 Zhang Q, Xu CY, Zhang Z, Chen YD, Liu CL. Spatial and temporal variability of precipitation over China, 1951-2005. Theor. Appl. Climatol. 2008;95:53-68.
5 Kizza M, Rodhe A, Xu CY, Ntale HK, Halldin S. Temporal rainfall variability in the Lake Victoria Basin in East Africa during the twentieth century. Theor. Appl. Climatol. 2009;98:119-135.   DOI
6 Lima MIP, Carvalho SCP, Lima JLMP, Coelho MFES. Trends in precipitation: analysis of long annual and monthly time series from mainland Portugal. Adv. Geosci. 2010;25:155-160.   DOI
7 Ngongondo C, Xu CY, Gottschalk L, Alemaw B. Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region. Theor. Appl. Climatol. 2011;106:79-83.   DOI
8 Afzal M, Mansell MG, Gagnon AS. Trends and variability in daily precipitation in Scotland. Procedia Environ. Sci. 2011;6:15-26.   DOI
9 Ramazanipour M, Roshani M. Test and trend analysis of precipitation and discharge in the north of Iran (Case Study: Polroud Basin). World Appl. Sci. J. 2011;14:1286-1289.
10 Shahid S. Trends in extreme rainfall events of Bangladesh. Theor. Appl. Climatol. 2011;104:489-499.   DOI
11 Yanming Z, Jun W, Xinhua W. Study on the change trend of precipitation and temperature in Kunming city based on mann-kendall analysis. In: Tianbiao Z, eds. Future computer, communication, control and automation of advances in intelligent and soft computing. Springer Berlin Heidelberg; 2011. p. 505-513.
12 Taxak AK, Murumkar AR, Arya DS. Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India. Weather Clim. Extremes 2014;4:50-61.   DOI
13 Markovic D, Koch M. Wavelet and scaling analysis of monthly precipitation extremes in Germany in the 20th century: Interannual to interdecadal oscillations and the North Atlantic Oscillation influence. Water Resour. Res. 2005;41:1-13.
14 Nakken M. Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns. Environ. Model. Softw. 1999;14:283-295.   DOI
15 Jury MR, Melice JL, Analysis of Durban rainfall and Nile river flow (1871-1999). Theor. Appl. Climatol. 2000;67:161-169.   DOI
16 Kim S. Wavelet analysis of precipitation variability in northern California. U.S.A. KSCE J. Civ. Eng. 2004;8:471-477.   DOI
17 Xu Y, Li S, Cai Y. Wavelet analysis of rainfall variation in the Hebei Plain. Sci. China Earth Sci. 2005;48:2241-2250.   DOI
18 Kang S, Lin H. Wavelet analysis of hydrological and water quality signals in an agricultural watershed. J. Hydrol. 2007;338:1-14.   DOI
19 Echer MPS, Echer E, Nordemann DJ, Rigozo NR, Prestes A. Wavelet analysis of a centennial (1895-1994) southern Brazil rainfall series (Pelotas, $31^{\circ}4633″W). Clim. Change 2008;87:489-497.   DOI
20 Kun FS, Sheng WC, Ting W, et al. Multiple time scale analysis of climate variation in Macau during the last 100 years. J. Trop. Meteorol. 2012;18:21-30.
21 McKee TB, Doeskin NJ, Kieist J. The relationship of drought frequency and duration to time scales. In: Eighth Conference on Applied Climatology; 1993 Jan 17-22; Anaheim, California.
22 Wilhite DA, Glantz MH. Understanding: the drought phenomenon: The role of definitions. Water Int. 1985;10:111-120.   DOI
23 Quiring SM, Papakryiakou TM. An evaluation of agricultural drought indices for the Canadian prairies. Agric. For. Meteorol. 2003;118:49-62.   DOI
24 Hayes MJ, Svoboda MD, Wilhite DA, Vanyarkho OV. Monitoring the 1996 drought using the standardized precipitation index. Bull. Am. Meteorol. Soc. 1999;80:429-437.   DOI
25 Richard R, Heim Jr. A review of twentieth-century drought indices used in the United States. Bull. Am. Meteorol. Soc. 2002;83:1149-1165.   DOI
26 Bonaccorso B, Bordi I, Cancelliere A, Sutera A. Spatial variability of drought: An analysis of the SPI in sicily. Water Resour. Manage. 2003;17:273-296.   DOI
27 Livada I, Assimakopoulos VD. Spatial and temporal analysis of drought in Greece using the Standardized Precipitation Index (SPI). Theor. Appl. Climatol. 2007;89:143-153.   DOI
28 Patel NR, Chopra P, Dadhwal VK. Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorol. Appl. 2007;14:329-336.   DOI
29 Komuscu AU. Using the SPI to analyze spatial and temporal patterns of drought in Turkey. Drought Network News 1999;11:7-13.
30 Sigdel M, Ikeda M. Spatial and temporal analysis of drought in Nepal using standardized precipitation index and its relationship with climate indices. J. Hydrol. Meteorol. 2010;7:59-74.
31 Mishra AK, Desai VR. Drought forecasting using stochastic models. Stoch. Env. Res. Risk. A. 2005;19:326-339.   DOI
32 Edwards DC, McKee TB. Characteristics of 20th century drought in the United States at multiple time scales. Climatology Report No. 97-2. Colorado State University, Ft. Collins, CO; 1997.
33 Kendall MG. Rank correlation methods.4th ed. Charles Griffin: London; 1975.
34 Svoboda M, Hayes M, Wood D. World meteorological organization standardized precipitation index user guide [Internet]. Geneva: c2012 [cited 2014 Dec 21]. Available from: http://www.wamis.org/agm/pubs/SPI/WMO_1090_EN.pdf.
35 Vermes L. How to work out a drought mitigation strategy (An ICID Guide). DVWK Guidelines for water management; 1998.
36 Mann HB. Nonparametric tests against trend. Econometrica 1945;13:245-259.   DOI
37 Hirsch RM, Slack JR, Smith RA. Techniques of trend analysis for monthly water quality analysis. Water Resour. Res. 1982;18:107-121.   DOI
38 Yue S, Pilon PJ, Phinney B. Canadian stream flow trend detection: impacts of serial and cross correlation. J. Hydrol. Sci. 2003;48:51-64.   DOI
39 Sen PK. Estimates of the regression coefficient based on Kendall's Tau. J. Am. Statist. Assoc. 1968;63:1379-1389.   DOI
40 Yue S, Pilon PJ, Phinney B, Cavadias G. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol. Processes 2002;16:1807-1829.   DOI
41 Torrence C, Compo GP. A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 1998;79:618.
42 Lau KM, Weng H. Climate signal detection using wavelet transform: How to make a time series sing. Bull. Am. Meteorol. Soc. 1995;76:2391-2402.   DOI
43 Wang B, Wang Y. Temporal structure of the southern oscillation as revealed by waveform and wavelet analysis. J. Climatol. 1996;9:1586-1598.   DOI
44 Beecham S, Chowdhury RK. Statistical behaviour of Adelaide's rainfall-is climate change detectable? World Env. Water Resour. Congress 2008;1-13.
45 Fraedrich K, Jiang J, Gerstengarbe F-W, Werner PC. Multiscale detection of abrupt climate changes: application to river Nile flood levels. Int. J. Climatol. 1997;17:1301-1315.   DOI
46 Torrence C, Webster PJ. Interdecadal changes in the ENSO monsoon system. J. Climate 1999;12:2679-2690.   DOI
47 Kirkup H, Pitman AJ, Hogan J, Brierley G. An initial analysis of river discharge and rainfall in coastal new South Wales, Australia using wavelet transforms. Aust. Geogr. Stud. 2001;39:313-334.   DOI
48 Beecham S, Chowdhury RK. Temporal characteristics and variability of point rainfall: a statistical and wavelet analysis. Int. J. Climatol. 2010;30:458-473.
49 Chui CK, Wang JZ. An analysis of cardinal-spline wavelets. J. Apporx. Theory 1993;72:54-68.   DOI
50 Torrence C, Webster PJ. The annual cycle of persistence in the El Nio Southern. Q. J. Roy. Meteor. SOC 1998;124:1985-2004.
51 Helsel DR, Hirsch RM. Statistical methods in water resources. In: Techniques of water resources investigations of the US Geological Survey. Reston: USGS; 2002.
52 Islam ARMT, Tasnuva A, Islam MT, Haque MR. Management approach to disaster scenario in Bangladesh: An overview. Int. J. Sci. Res. Pub. 2014;4:1-7.
53 Dewan AM, Nishigaki M, Komatsu M. Floods in Bangladesh: A comparative hydrological investigation on two catastrophic events. J. Fac. Env. Sci. Tech. 2003;8:53-62.
54 Jahangir AATM, Sayedur RM, Saadat AHM. Monitoring meteorological and agricultural drought dynamics in Barind region Bangladesh using standard precipitation index and Markov chain model. Int. J. Geomat. Geosci. 2013;3:511-524.
55 Aceituno P. El Nino, the southern oscillation, and ENSO: Confusing names for a complex ocean-atmosphere interaction. Bull. Am. Meteorol. Soc. 1992;73:483-485.   DOI
56 Edossa DC, Woyessa YE, Welderufael WA. Analysis of droughts in the central region of South Africa and their association with SST anomalies. Int. J. Atoms. Sci. 2014;2014:1-8.
57 Keka IA, Martin I, Rahman M, Banu DA. Analysis of drought in Eastern part of Bangladesh. Daffodil Int. Univ. J. Sci. Tech. 2012;7:20-27.
58 Schubert SD, Suarez MJ, Pegion PJ, Koster RD, Bacmeister JT. Potential predictability of long-term drought and pluvial conditions in the United States Great Plains. J. Clim. 2008;21:802-816.   DOI
59 Malik KM. Drought in central south-west Asia [dissertation]. Toronto: York University; 2010.
60 Rahman MD, Begum M. Application of non parametric test for trend detection of rainfall in the largest Island of Bangladesh. ARPN J. Earth Sci. 2013;2:40-44.
61 Hasan Z, Akhter S, kabir A. Analysis of rainfall trends in the South-east Bangladesh. J. Env. 2014;3:51-56.
62 Dey NC, Alam MS, Sajjan AK, et al. Assessing environmental and health impact of drought in the Northwest Bangladesh. J. Env. Sci. Nat. Resour. 2011;4:89-97