Analysis of Rainfall Trends in the South-East Bangladesh
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1 Research Paper Analysis of Trends in the South-East Bangladesh Zaheed Hasan 1, Sabiha Akhter 2 and Alamgir Kabir 3 1 Ph.D., Department of Geography, Environment and Population, University of Adelaide, Australia 2 Ph.D., Department of Economics, La Trobe University, Melbourne, Australia 3 M.Sc., University of Adelaide, Australia zaheedhasan@yahoo.com 1 ; sabiha_akhter2000@yahoo.com 2 ; makabirce@yahoo.com 3 Abstract This paper explores annual and seasonal trends of rainfall in the South-East part of coastal Bangladesh over the period between 1980 and Non-parametric- Mann-Kendall and Sen s test estimate is applied for detecting and estimating rainfall trends respectively. An assessment of rainfall data indicate amount of annual rainfall in South-East Bangladesh is increasing although this trend is not statistically significant. Seasonal analysis reveals least amount of rainfall occurs in winter and it is getting drier. However, trends analysis indicates the other three seasons, e.g. Monsoon, Rainy Monsoon and Post Monsoon, are becoming wetter. It is important to note that among all the seasons rainfall in Monsoon is increasing significantly (significant at p= 0.05 level) and the rate of increase is 8.5 mm/year. Keywords:, Bangladesh, Trend analysis, Mann-Kendall Test, Sen s Test, Annual Trend, Seasonal Trend 1. Introduction is a significant factor in the coastal Bangladesh, especially for the communities of farmers and fishermen whose livelihood entirely depend on natural resources (Shahid, 2010). is a crucial factor for the whole farming process from sowing seeds to harvesting crops. Moreover erratic rainfall can trigger various disasters, e.g. floods and landslides, water logging, erosion and salinity intrusion (Matsumoto, 1989). Various studies have indicated due to climate change; rainfall pattern is most likely to change in Bangladesh (Paudyal, 2002; Harvey et al, 2006 and Ali, 2007). The Inter-Governmental Panel of Climate Change (IPCC) 2007) has predicted the temperature and rainfall in Bangladesh will increase steadily till the end of this century. Islam (2009) in a study has projected by 2018; annual rainfall in Bangladesh will increase at least 5.3%. In the context of climate change and disaster management, it is, therefore important to understand the rainfall trends. The study reports recent trends of annual and seasonal rainfall in the coastal region of South-East part of Bangladesh. 2. Data and Study Area For this study, daily rainfall data over the period between 1980 and 2011 of the five weather stations situated in the South-East part of Bangladesh was obtained from the Bangladesh Meteorological Department (BMD). We used this data set to calculate monthly, seasonal and annual rainfall totals and to do the trend analyses. Figure 1 and Table 1 show the specific locations of the five weather stations and data period of rainfall used in this study. Homogeneity analysis of the data set is performed in monthly total rainfall data for all the five weather stations. We do a graphical analysis and the Kruskal-Wallies test to check the homogeneity of the data set. The monthly total rainfall of all the five weather stations has been the basis to calculate the regional average and the regional precipitateon series. 3. Methodology From the daily precipitation data we calculated the month- Available online at 51
2 ly total rainfall. The annual and the seasonal rainfalls were calculated from the monthly total rainfall. The regional average precipitation index was developed from the mean monthly rainfall of the five whether stations in the South- East Bangladesh. Figure 2 summarise stepwise methodology of the study. The non-parametric model Mann-Kendall test was applied to calculate the seasonal and the annual rainfall series to investigate the rainfall trends and the Sen s test method was used to estimate magnitude of the rainfall changes. Mann-Kendall and Sen s tests were done by using the Microsoft Excel template MAKESENS, which was developed by the Finnish Meteorological department for detecting and estimating trends in the time series. MAKESENS is widely used software for detecting and researching rainfall trends (Río et al, 2011; Nasher, 2013; Nenwiinia & Kabandab, 2013 and Tudose et al, 2013). Readers are referred to the article written by MÄÄTTÄ et al (2002) and to visit the website of the Finnish Meteorological Institutes to get more information on the MAKESENS application for trend calculation. For this study we divided the seasons of Bangladesh into four categories as suggested by Islam & Uyeda (2007). Table 2 describes the seasons and the respective months. Figure 1. Study Area and Location of the Meteorological s* * IAEA (2010) Table 1. s and Data Period General Location SE B gladesh Name Lats. Longs. Period of Record Used Chittagong Cox s Bazar Feni Sandwip Teknaf SE: South East; B gladesh: Bangladesh; Lats: Latitude; Longs:. Longitudes Figure 2. The Stepwise Data Organization and the Analytical Tools Used in this Study Table 2. Seasons of Bangladesh Seasons Dry Winter Season Monsoon Season Rainy Monsoon Season Monsoon Season 4. Results and Discussion Months December, January, February March, April, May June, July, August, September October, November, December 4.1. Basis Increasing Trend of Annual Table 3 shows that in Chittagong division the annual mean amount of rainfall varies by location. Mean annual rainfall in Chittagong Division during the period between 1980 and 2011 varies from 2934 to 4195 mm. During the same period the highest and the lowest amount of annual rainfall was recorded in Teknaf and Chittagong stations respectively. Teknaf which is situated in the furthest South-Eastern part of Bangladesh also received 43% higher annual rainfall than Chittagong. in Chittagong division increased gradually from North to South. The Mann-Kendall test results revealed upward trend in annual rainfall in four out of five weather stations (Chittagong, Cox s Bazar, Teknaf and Shanwip) and a downward trend of annual rainfall in Feni. Annual rainfall in Teknaf is increasing significantly. Sen s slope estimate rate of increase in annual rainfall in Teknaf is mm per year (Table 4) Seasonal Trends Available online at 52
3 Figure 3 summarises 32 years ( ) seasonal trend of mean rainfall in Chittagong Division for the five weather stations. Figure 3 shows the lowest amount of rainfall occurs during winter and the highest during rainy Monsoon seasons. Mean rainfall during winter varies from 40 to 330 mm (Table 4). Table 3. Descriptive Statistics of the Annual in Chittagong Division, Period Mean Std. Dev. Range Min Max Teknaf Cox s Bazar Sandwip Feni Chittagong N(Years of observation)=32 years, *mm=millimetre Figure 3. Seasonal Trend of in the Chittagong Division Table 4. Mann-Kendall and Sen s Test Results of Annual Trends in the Five s MK Test (Test Z) Trend Result Sen s Slope Estimate Change in (mm/y) Chittagong 0.28 NS 4.64 Cox s Bazar 1.38 NS Teknaf 2.06 Sig Feni NS Shandwip 1.59 NS mm= Millimetre; MK: Mann-Kendall; NS: Not Significant; Sig.: Significant; : Upward; :Downward Each year after winter; rainfall gradually increases. In the Monsoon season the range of rain-fall varies between 85 and 1200 mm. In Teknaf the lowest amount of mean rainfall occurs in the Monsoon season and the highest amount occurs in Sandwip. increases sharply after the Monsoon. The highest amount of rainfall occurred during the rainy monsoon season and it varied between 2000 and 3500 mm. In the rainy Monsoon season maximum amount of rainfall occurs in Teknaf (mean rainfall 3500 mm), and Cox s Bazar and Sandwip receive a little more than 2500 mm of rainfall, Chittagong and Feni received almost a similar amount of rainfall i.e mm. After rainy-monsoon season, rainfall decreases sharply and during the Monsoon season, rainfall varies in between mm (Table 5). Table 5. Seasonal Mean, Standard Deviation and Range of in Various s (Period between 1980 and 2011) Chittagong Cox s Bazar Teknaf Feni Sandwip Season Mean RF SD RF Min RF Range Max RF Winter Winter Winter Winter Winter : Monsoon; SD: Standard Deviation; : RF Table 6 shows that there is an upward trend of rainfall during rainy Monsoon and post Monsoon in Cox s Bazar, Teknaf and Sandwip. Monsoon rainfall is increasing significantly in Cox s Bazar and Teknaf and the rate of increase is 7-8 mm/year. Monsoon rainfall is decreaseng in Feni, Chittagong and Sandwip. A decreasing trend of Available online at 53
4 Monsoon rainfall is significant in Feni and the rate of decrease is 9 mm/year. In Chittagong, Cox Bazar, Teknaf, and Sawndip there are increasing trends of rainfall during rainy Monsoon. The increasing rate is statistically significant for Sandwip and it is increasing at the rate of 19 mm/year. in winter is decreasing in all the areas. Table 6. Seasonal Trend of all the Five s Chittagong Cox s Bazar Teknaf Feni Sandwip Season MK Test Trend Result (Test Z) Sen s Slope Estimate Change in (mm/y) Winter NS NS NS NS 0.02 Winter NS Sig NS NS 2.47 Winter 0.10 NS Sig NS NS 5.10 Winter NS Sig NS NS 5.10 Winter NS NS Sig NS 4.86 : Monsoon; MK: Mann-Kendall; NS: Not Significant; Sig.: Significant; : Upward; :Downward 4.2. Regional Trend Analysis Table 7 shows the seasonal mean rainfall in the South-East part of Bangladesh between the period of 1980 and 2011 and Figure 4 shows seasonal percentage of mean annual rainfall. 76% of total annual rainfall occurs during the rainy Monsoon season (Figure 4). Maximum amount of rainfall during rainy Monsoon season is 3270 mm. The Monsoon season receives the second highest amount of rainfall after the rainy Monsoon. 14% of the total annual rainfall occurs during the pre-monsoon season and the mean rainfall is 500 mm/season. 9% of the total means rainfall occurs during the post-monsoon season. The lowest amount of rainfall occurs during the winter i.e. 1% of the total annual rainfall. Table 7. Seasonal in the South East Part of Bangladesh (Period between 1980 and 2011) Region SE B gladesh Season Mean SD Range Min Maxi Rainfal l Winter B gladesh: Bangladesh; : Monsoon; SD: Standard Deviation Figure 4. Season Wise Percentage of Mean Annual in the South East Bangladesh (Period between 1980 and 2011) The Mann-Kendall test shows an upward trend of rainfall during Monsoon, rainy Monsoon and Post Monsoon seasons and a downward trend of rainfall in winter season. However, the results are not statistically significant. It is Available online at 54
5 important to note that the amount of increase in rainfall during rainy monsoon is quite high i.e. 11 mm/year/season. Winter receives the lowest amount of rainfall-showing the downward trend of rainfall. Winters are getting drier. 5. Conclusion The following conclusions can be deduced from the study: Annual rainfall in Chittagong Division is increasing. However, the trend is not statistically significant. In the South-East Bangladesh, 76% of the total annual rainfall occurs during rainy monsoon seasons. 14% and 9% of the total annual rainfall occurs in Monsoon and Monsoon seasons respectively. Winter receives the lowest amount of rainfall i.e. 1% of the annual rainfall. in Monsoon season is increasing significantly in most of the areas. The rate of increase is in between 8-9 mm/year. This is quite significant because 14% of the total annual rainfall occurs during Monsoon season. during winter is decreasing in all the areas in the South-East Bangladesh. Winter is becoming drier. The southern part of Chittagong Division likely to receive more rainfall compare to the northern part. Acknowledgement We would like to express our sincere gratitude and appreciation to the Bangladesh Meteorological Department for providing data and valuable information. A special thanks to Ms Angela Jessep from the La Trobe University, Melbourne, Australia for suggestions, constructive critiques and continued supports. We thank all our reviewers for their comments and suggestions. References Ali, A.M.S. (2007) September 2004 flood event in South Western Bangladesh: a study of its nature, causes, and human perception and adjustments to a new hazard. Natural Hazards, 40, pp Finnish Meteorological Institutes (n.d.) MAKESENS- Application for Trend Calculation [Internet], Finnish Meteorological Institutes. Available from < [Accessed on 3 rd December 2014]. Harvey, C.F., Ashfaque, K.N., Yu, W., Badruzzaman, A., Ali, M.A., Oates, P.M., Michael, H.A., Neumann, R.B., Beckie, R., and Islam, S. (2006) Groundwater dynamics and arsenic contamination in Bangladesh. Chemical Geology, 228, pp IPCC (2007) Climate Change 2007: Synthesis Report. IPCC. IAEA (2010) Bangladesh; General Information [Internet], Vienna, International Atomic Energy Agency. Available from: < [Accessed on 1 st October 2014). Islam, M.N. (2009) and temperature scenario for Bangladesh. The Open Atmospheric Science Journal, 3, pp Islam, M.N., and Uyeda, H. (2007) Use of TRMM in determining the climatic characteristics of rainfall over Bangladesh. Remote Sensing of Environment, 108, pp Määttä, A., Salmi, T., Anttila, P., and Ruoho-Airola, T. (2002) Makesens 1.0. Excel Template for the Calculation of Trend Statistics of Annual Time Series. Finnish Meteorological Institute, Helsinki, Finland. Matsumoto, J. (1989) Synoptic features of heavy monsoon rainfall in 1987 related to the severe flood in Bangladesh. Japanese Progress in Climatology, pp Nasher, N.R. (2013) Impact of Climate Variability on Temperature and Trend in Bangladesh: A case of two cities. European Journal of Climate Change, 11, pp Nenwiinia, S., and Kabandab, T.A. (2013) Trends and Variability Assessment of in Vhembe South Africa. J. Hum. Ecol., 42, pp Paudyal, G.N. (2002) Forecasting and warning of waterrelated disasters in a complex hydraulic setting-the case of Bangladesh. Hydrological Sciences Journal, 47, S5-S18. Río, S.D., Herrero, L., Fraile, R., and Penas, A. (2011) Spatial distribution of recent rainfall trends in Spain ( ). International Journal of Climatology, 31, pp Shahid, S. (2010) variability and the trends of wet and dry periods in Bangladesh. International Journal of Climatology, 30, pp Tudose, C., Croitoru, A., and Haidu, I. (2013) Some Asp- Available online at 55
6 ects on rainfall maximum intensity in North Western Romania. In: 13th SGEM Geo Conference on Energy and Clean Technologies, June 16-22, SGEM, pp Available online at 56
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