Browse > Article
http://dx.doi.org/10.4491/eer.2016.075

Monthly rainfall forecast of Bangladesh using autoregressive integrated moving average method  

Mahmud, Ishtiak (Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology)
Bari, Sheikh Hefzul (Department of Civil Engineering, Leading University)
Rahman, M. Tauhid Ur (Department of Civil Engineering, Military Institute of Science and Technology)
Publication Information
Environmental Engineering Research / v.22, no.2, 2017 , pp. 162-168 More about this Journal
Abstract
Rainfall is one of the most important phenomena of the natural system. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. Rainfall forecasting could play a significant role in the planning and management of water resource systems also. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. A validation check for each station was performed on residual series. Residuals were found white noise at almost all stations. Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. The predicted results from the selected models were compared with the observed data to determine prediction precision. We found that selected models predicted monthly rainfall with a reasonable accuracy. Therefore, year-long rainfall can be forecasted using these models.
Keywords
ARIMA model; Bangladesh; Forecast; Monthly rainfall; Time series;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Shahid S. Rainfall variability and the trends of wet and dry periods in Bangladesh. Int. J. Climatol. 2010;30:2299-2313.   DOI
2 You Q, Kang S, Aguilar E, Yan Y. Changes in daily climate extremes in the eastern and central Tibetan Plateau during 1961-2005. J. Geophys. Res-Atmos. 2008;113:D07101.
3 Mortuza MR, Selmi S, Khudri MM, Ankur AK, Rahman MM. Evaluation of temporal and spatial trends in relative humidity and dew point temperature in Bangladesh. Arab. J Geosci. 2014;7:5037-5050.   DOI
4 Alexandersson H. A homogeneity test applied to precipitation data. J. Climatol. 1986;6:661-675.   DOI
5 Von Neumann J. Distribution of the ratio of the mean square successive difference to the variance. Ann. Math. Statist. 1941;12:367-395.   DOI
6 Buishand TA. The analysis of homogeneity of long-term rainfall records in the Netherlands. KNMI Scientific Report WR 81-7, De Bilt, The Netherlands; 1981.
7 Box GE, Jenkins GM. Time series analysis: Forecasting and control. Rev. ed. San Francisco: Holden-Day; 1976.
8 Mishra AK, Desai VR. Drought forecasting using stochastic models. Stoch. Environ. Res Ris. Assess. 2005;19:326-339.   DOI
9 Rahman M, Islam AHMS, Nadvi SYM, Rahman RM. Comparative study of ANFIS and ARIMA model for weather forecasting in Dhaka. Informatics, Electronics & Vision (ICIEV), 2013 International Conference on, Dhaka; 2013. p. 1-6.
10 Johnson LA, Montgomery DC. Forecasting and time series analysis. New York: McGraw-Hill; 1976.
11 Dizon CQ. ARMA modeling of a stochastic process appropriate for the angat reservoir. Philipp. Eng. J. 2007;28:1-20.
12 Pettitt AN. A non-parametric approach to the change-point problem. J. Roy. Stat. Soc. C-App. 1979;28:126-135.
13 Box G, Jenkins G, Reinsel G. Time series analysis: Forecasting & control [Internet]. 3rd ed. New Jersy: Prentice Hall; c1994 [cited 23 February 2016]. Available from: http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20&path=ASIN/0130607746.
14 Chow VT, Maidment DR, Mays LW. Applied hydrology [Internet]. New York: Mcgraw-Hill Book Company; c1988 [cited 23 February 2016]. Available from: http://documentatiecentrum.watlab.be/imis.php?module=ref&refid=127685&basketaction=add.
15 Rashid HE. Geography of Bangladesh. 2nd ed. Dhaka: Univ. Press Ltd.; 1991. p. 545.
16 Ljung GM, Box GEP. On a measure of lack of fit in time series models. Biometrika 1978;65:297-303.   DOI
17 Momani PENM. Time series analysis model for rainfall data in Jordan: Case study for using time series analysis. Am. J. Environ. Sci. 2009;5:599-604.   DOI
18 Mahsin M, Akhter Y, Begum M. Modeling rainfall in Dhaka division of Bangladesh using time series analysis. J. Math. Model. Appl. 2012;1:67-73.
19 Bari SH, Rahman MT, Hussain MM, Ray S. Forecasting monthly precipitation in Sylhet city using ARIMA model. Civil Environ. Res. 2015;7:69-77.