Water Productivity Journal (WPJ) Quarterly Publication

Document Type : Original Research Paper


1 Assistant Professor (study-leave), Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh; Ph.D. Student, Civil Engineering, Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA - 22904, USA

2 Professor, Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh.

3 Professor of Hydroinformatics, UNESCO-IHE Institute for Water Education, P.O. Box 3015, 2601 DA, Delft, The Netherlands

4 Research Assistant, Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh



Introduction: Monsoon rains in August 1917 in Bangladesh affected close to 6.9 million people in Bangladesh. Rising waters began on August 11 and by August 15, one third of the country was submerged.
The floods killed at least 115 people and forced close to 200,000 people from their homes. In some parts of the country, up to 80% of sanitation and water facilities were affected. Many shelter centres lacked the ability to provide adequate food, water, hygiene and protection, putting children, adolescent girls and women at risk. Most of the affected people were farm labourers, relying on agriculture to meet their basic needs. The extent of the disaster increased the risks of serious disease outbreaks; children dropping out of school; and violence, neglect, abuse and exploitation of children and women.
Pre-monsoon (March-May) flash flood in the northeast Haor region of Bangladesh has drawn much attention due to its early onset, high frequency, and adverse impact on the Boro crop. To understand its past changes and future occurrences, a trend analysis is carried out on the observed 3 - hourly water level data and daily rainfall data of the Haor region using the Mann-Kendall test, Trend-Free Pre-Whitening test, and Sens slope estimator.
Material and methods: This study was conducted in the north-eastern region of Bangladesh covers approximately 24,500 km2, bounded by the international border with India to the north and east, the Old Brahmaputra River to the west, and the Nasirnagar to Madhabpur and Meghna River to the south. This region is comprised of the floodplains of the Meghna River and its tributaries. The larger portion of this region is the Haor basin and is characterized by numerous large, deeply flooded depressions.
The Mann Kendall Trend Test is used to analyze data collected over time for consistently increasing or decreasing trends (monotonic) in Y values. It is a non-parametric test, which means it works for all distributions, but your data should have no serial correlation. If your data does follow a normal distribution, you can run simple linear regression instead. The test can be used to find trends for as few as four samples. However, with only a few data points, the test has a high probability of not finding a trend when one would be present if more points were provided. The more data points you have the more likely the test is going to find a true trend (as opposed to one found by chance). The minimum number of recommended measurements is therefore at least 8 to 10.
Results: Later, statistical trend analysis is conducted using the Mann-Kendall test and Sen’s slope. However, Lag-1 autocorrelation was determined before statistical trend analysis. The stations having no autocorrelation were directly investigated by the MK test, whereas the stations showing significant autocorrelation were analyzed through TFPWMK. Here, TFPWMK was preferred to PWMK because PWMK deals with the influence of serial correlation on the MK test but does not address the interaction between a trend and autocorrelation process. There can be a case where a trend exists in a time series even though the time series does not comprise an autocorrelation process, and in such a situation, the use of PWMK can be erroneous.
Conclusion: Although trend analysis can be extremely helpful in many applications—from climate change to sociological analysis—it’s important to keep in mind that it is not foolproof. In particular:
All data (unless gathered through a population census) is liable to sampling error. The extent of this problem will increase when coarse sampling methods (e.g. convenience sampling) are used. Data is likely subject to measurement error; random, systematic, or external; trends in this error may be mistaken as trends in the actual data. “Phantom”, short term trends exist even in the most random of number sequences, so trends should be followed out as long as possible. Also, finding no trend may mean there is no trend, but it may just as likely mean that your data is insufficient to illuminate a trend which does in fact exist.
A statistically significant increasing trend is found for the relative water level. The trend in rainfall is increasing, though it is not statistically significant. From the observed record, the peak of the flash floods is found to be arriving early in late March-early April (instead of late April-early May), coinciding with the harvesting period of the Boro crop. The early arrival of the flash flood can cause catastrophic damage to the Boro crop in future flash floods. None of the current Boro varieties BRRI dhan28, BRRI 36, BRRI dhan69, BRRI dhan88 are safer to save Boro from early flash floods experienced in recent years. To escape the Boro crop from an early flash flood, Boro varieties with a shorter growth duration should be introduced. This helps crop productivity.


Main Subjects

Ahmed, A.U. (2006). Bangladesh climate change impacts and vulnerability: a synthesis. Climate Change Cell, Department of Environment, Bangladesh.
Basher, Md., Stiller-Reeve, M., Islam, A.S. & Scott, B. (2018). Assessing extreme rainfall trends over the northeast regions of Bangladesh. Theoretical and Applied Climatology, 134(1-12): 441-452.
Biswas, J.K. (2017). Boro Rice for Haor Area: Some Suggestions. Daily Sun. Available at: https://www.daily-sun.com/printversion/details/269361/Boro-Rice-for-Haor-Area:-Some-Suggestions (Accessed on 1 June 2021)
BRRI. (2021). Bangladesh Rice Knowledge Bank (BRKB). Bangladesh Rice Research Institute (BRRI). Available at: 
http://knowledgebank-brri.org/brri-rice-varieties/boro-rice-varieties/ (Accessed on 30 May 2021).
Burn, D.H. & Hag, E.M.A. (2001). Climate change impact using hydrologic variables. Report for CCAF project, Environment Canada.
Burn, D.H. (1994). Hydrologic effects of climatic change in West Central Canada. Journal of Hydrology, 160(1-4): 53-70.
BWDB. (2006). Mathematical Modelling with Hydrological Studies and Terrestrial Survey under the Haor Rehabilitation Scheme. Bangladesh Water Development Board, Bangladesh.
Center for Environmental and Geographic Information Services (CEGIS). (2012). Master Plan of Haor Area. Vol.1, Summary Report, Government of People’s Republic of Bangladesh, Ministry of Water Resources, Bangladesh Haor and Wetland Development Board, Bangladesh.
Chang, C.K., Ghani, A., Puay, H.T. & Othman, M.A. (2017). Homogeneity testing and trends analysis in long term rainfall data for Sungai Pahang River Basin over 40 years records. In: Proceedings of the 37th IAHR World Congress, Kuala Lumpur, Malaysia.
Douglas, E.M.,Vogel, R.M. & Kroll, C.N. (2000). Trends in floods and low flows in the United States: impact of spatial correlation. Journal of Hydrology, 240(1-2): 90-105.
FFWC (Flood Forecasting and Warning Centre). (2020). Bangladesh water development board. Available at: http://www.ffwc.gov.bd/ (Accessed January 19, 2020).
Gadedjisso-Tossou, A., Adjegan, K.I. & Kablan, A.K.M. (2021). Rainfall and Temperature Trend Analysis by Mann-Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo. Sci, 3(1): 17.
Gan, T.Y. & Kwong, Y.T.J. (1991). Identification of warming trends in northern Alberta and southern northwest territories by the non-parametric Kendall’s test. In: Using Hydrometric Data to Detect and Monitor Climatic Change. Proceedings of NHRI Workshop, No. 8: 43-56.
Gan, T.Y. (1998). Hydroclimatic trends and possible climatic warming in the Canadian Prairies. Water Resources Research, 34(11): 3009-3015.
Hamed, K.H. (2008). Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis. Journal of Hydrology, 349(3-4): 350-363.
Kendall, M.G. (1975). Rank Correlation Methods, 4th edition, Charles Griffin, London, UK.
Khalequzzaman, M. (2019). Early flash floods in the haor region: A new normal? Daily Star. Available at:        
https://www.thedailystar.net/opinion/environment/news/early-flash-floods-the-haor-region-new-normal-1726942 (Accessed May 5, 2019).
Khan, M.J.U., Islam, A.S., Das, M.K., Mohammed, K., Bala, S.K. & Islam, G.T. (2019). Observed trends in climate extremes over Bangladesh from 1981 to 2010. Climate Research, 77(1): 45-61.
Khan, M.N.H., Mia, M.Y. & Hossain, M.R. (2012). Impacts of flood on crop production in Haor areas of two Upazillas in Kishoregonj. Journal of Environmental Science and Natural Resources, 5(1): 193-198.
Kocsis, T., Kovács-Székely, I. & Anda, A. (2020). Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely, Western Hungary. Theoretical and Applied Climatology, 139(3): 849-859.
Kumar, S., Merwade, V., Kam, J. & Thurner, K. (2009). Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology, 374(1-2): 171-183.
Lettenmaier, D.P., Wood, E.F. & Wallis, J.R. (1994). Hydro-climatological trends in the continental United States, 1948-88. Journal of Climate, 7(4): 586-607.
Mallick, J., Talukdar, S., Alsubih, M., Salam, R., Ahmed, M., Kahla, N.B. & Shamimuzzaman, M. (2021). Analysing the trend of rainfall in Asir region of Saudi Arabia using the family of Mann-Kendall tests, innovative trend analysis, and detrended fluctuation analysis. Theoretical and Applied Climatology, 143(1): 823-841.
Mann, H.B. (1945). Non-Parametric Tests against Trend. Econmetrica, 13: 245-259.
Meshram, S.G., Kahya, E., Meshram, C., Ghorbani, M.A., Ambade, B. & Mirabbasi, R. (2020). Long-term temperature trend analysis associated with agriculture crops. Theoretical and Applied Climatology, 140: 1139-1159.   
DOI: 10.1007/s00704-020-03137-z
Mirabbasi, R., Ahmadi, F. & Jhajharia, D. (2020). Comparison of parametric and non-parametric methods for trend identification in groundwater levels in Sirjan plain aquifer, Iran. Hydrology Research, 51(6): 1455-1477. DOI: 10.2166/nh.2020.041
Mondal, A., Kundu, S. & Mukhopadhyay, A. (2012). Rainfall trend analysis by Mann-Kendall test: A case study of north-eastern part of Cuttack district, Orissa. International Journal of Geology, Earth and Environmental Sciences, 2(1): 70-78.
National Weather Service (NWS). (2016). The National Oceanic and Atmospheric Administration (NOAA). U.S. Department of Commerce, USA.
NIRAPAD. (2017). Bangladesh: Flash Flood Situation. Available at:     
https://reliefweb.int/report/bangladesh/bangladesh-flash-flood-situation-april-19-2017 (April 19, 2017).
Northeast Regional Water Management Plan, Bangladesh Flood Action Plan - 6 (NERP FAP - 6). (1995). Wetland Resources Specialist Study, Northeast Regional Water Management Plan. Bangladesh Flood Action Plan 6, Bangladesh.
Nowreen, S., Murshed, S.B., Islam, A.S., Bhaskaran, B. & Hasan, M.A. (2015). Changes of rainfall extremes around the haor basin areas of Bangladesh using multi-member ensemble RCM. Theoretical and Applied Climatology, 119(1-2): 363-377.
Pettitt, AN. (1979). A non-parametric approach to the change-point problem. Appl Stat, 28(2): 126-135.
Rashid, M.M. & Yasmeen, R. (2017). Cold injury and flash flood damage in boro rice cultivation in Bangladesh: A Review. Bangladesh Rice Journal, 21(1): 13-25.
Roy, B., Islam, A.K.M.S., Islam, G.T., Khan, M.J.U., Bhattacharya, B., Ali, M.H., Khan, A.S., Hossain, M.S., Sarker, G.C. & Pieu, N.M. (2019). Frequency Analysis of Flash Floods for Establishing New Danger Levels for the Rivers in the Northeast Haor Region of Bangladesh. Journal of Hydrologic Engineering, 24(4): 05019004.
DOI: https://ascelibrary.org/doi/abs/10.1061/(ASCE)HE.1943-5584.0001760
Sattari, M.T., Mirabbasi, R., Jarhan, S., Shaker Sureh, F. & Ahmad, S. (2020). Trend and abrupt change analysis in water quality of Urmia Lake in comparison with changes in lake water level. Environmental Monitoring and Assessment, 192: 623. DOI: 10.1007/s10661-020-08577-8
Sen, P.K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American statistical association, 63(324): 1379-1389.
Shahid, S. (2009). Spatio-temporal variability of rainfall over Bangladesh during
the time period 1969-2003. Asia-Pacific Journal of Atmospheric Science, 45(3): 375-389.
Shahid, S. (2010). Rainfall variability and the trends of wet and dry periods in Bangladesh. International Journal of Climatology, 30(15): 2299-2313.
Shahid, S. (2011). Trends in extreme rainfall events of Bangladesh. Theoretical and applied climatology, 104(3-4): 489-499.
Stocker, T.F., Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V. & Midgley, P.M. (2013). IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Sultana, T. (2015). Flash flood forecasting using estimated precipitation by global satellite mapping in the north-east region of Bangladesh. M.Sc. thesis, Dept. of Water Resources Engineering, Bangladesh Univ. of Engineering and Technology, Bangladesh.
Tabari, H., Somee, B.S. & Zadeh, M.R. (2011). Testing for long-term trends in climatic variables in Iran. Atmospheric Research, 100(1): 132-140.
Thiel, H. (1950). A rank-invariant mathod of linear and ploynomial regression analysis III’. Proceedings Koninklijke Nederlandse Akademie Van Wetenschappen, pp. 1897-1912.
Von Storch, H. (1995). Misuses of statistical analysis in climate research. In: Analysis of Climate Variability: Applications of Statistical Techniques, von Storch H. & Navarra A. (eds). Springer-Verlag: Berlin, Germany, pp. 11-26.
Yue, S., Pilon, P., Phinney, B. & Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological processes, 16(9): 1807-1829.
Yusoff, S.H.M., Hamzah, F.M., Jaafar, O. & Tajudin, H. (2021). Long Term Trend Analysis of Upstream and Middle-Stream River in Langat Basin, Selangor, Malaysia. Sains Malaysiana, 50(3): 629-644.
Zhang, X., Harvey, K.D., Hogg, W.D. & Yuzyk, T.R. (2001). Trends in Canadian streamflow. Water Resources Research, 37(4): 987-998.
Zhang, X., Vincent, L.A., Hogg, W.D. & Niitsoo, A. (2000). Temperature and precipitation trends in Canada during the 20th century. Atmosphere–Ocean, 38(3): 395-429.