Rainfall Drought Simulating Using Stochastic SARIMA Models for Gadaref Region, Sudan

Moahmed Hassan, Hisham and Mahgoub Mohamed, Tariq (2014): Rainfall Drought Simulating Using Stochastic SARIMA Models for Gadaref Region, Sudan.

Abstract

Sudan is one of the countries which economy depends on rain fed agriculture and also facing recurring cycles of natural drought. For many decades, recurrent drought, with intermittent severe droughts, had become normal phenomenon in Sudan. This paper presents linear stochastic models known as multiplicative seasonal autoregressive integrated moving average model (SARIMA) used to simulate monthly rainfall in Gadaref station, Sudan. For the analysis, monthly rainfall data for the years 1971–2010 were used. The seasonality observed in ACF and PACF plots of monthly rainfall data was removed using first order seasonal differencing prior to the development of the SARIMA model. Interestingly, the SARIMA (0,0,5)x(1,0,1)12 model developed here was found to be most suitable for simulating monthly rainfall over the Gadaref station. This model is considered appropriate to forecast the monthly rainfall to assist decision makers establish priorities for water demand, storage and distribution.

• Item Type: MPRA Paper
• Language: English
• Keywords: Stochastic models,SARIMA,Sudan
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs; O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O10 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q2 - Renewable Resources and Conservation > Q25 - Water; Z - Other Special Topics > Z0 - General

References

Abramowitz, M., Stegun, A. (eds.), (1965). Handbook of Mathematical Formulas, Graphs, and Mathematical Tables. Dover Publications, Inc., New York, USA.

Box, G.E., Jenkins, G.M., (1970), Time Series Analysis; Forecasting and Control. Holden-Day series in time series analysis, San Francisco.

Durdu, O.F., (2010), Application of Linear Stochastic Models For Drought Forecasting in The Buyuk Menderes River Basin, Western Turkey, Stochastic Environmental Research and Risk Assessment, doi:10.1007/s00477-010-0366-3.

Elagib, N.A., M.G. Mansell., (2000), Recent Trends and Anomalies in Mean Seasonal and Annual Temperature Over Sudan. Journal of Arid Environment 45(3): 263-288. Etuk, E.H., Mohamed T.M., (2014). Time Series Analysis of Monthly Rainfall data for the Gadaref rainfall station, Sudan, by SARIMA Methods. International Journal of Scientific Research in Knowledge, 2(7), pp. 320-327.

Le Houérou, H.N. (2009): Bioclimatology and Biogeography of Africa. Verlag Berlin Heidelberg, Germany.

Mishra, A. K., Desai, V. R., (2005), Drought Forecasting Using Stochastic Models. Stochastic Environmental Research and Risk Assessment 19(5): 326-339.

Edwards, D.C., McKee, T.B., (1997). Characteristics of 20th Century Drought in the United States at Multiple Scales. Atmospheric Science Paper 634.

Cacciamani, C., Morgillo, A., Marchesi, S., Pavan, V. (2007). Monitoring and Forecasting Drought on a Regional Scale: Emilia-Romagna Region. Water Science and Technology Library 62(1): 29-48

Thom, H.C.S., (1958). A Note on the Gamma Distribution. Monthly Weather Rev. 86, 117–122.

Press WH, Flannery BP, Teukolsky SA, Vetterling WT. 1986. Numerical Recipes. Cambridge University Press: Cambridge.

P. Angelidis, F. Maris, N. Kotsovinos and V. Hrissanthou, (2012). Computation of Drought Index SPI with Alternative Distribution Functions”, Water Resour ManageVol. 26 p2453 – 2473.

McKee, T. B.; N. J. Doesken; and J. Kleist. (1993). “The relation of drought frequency and duration to time scales.” Proceedings of the Eighth Conference on AppliedClimatology; pp. 179–84. American Meteorological Society, Boston.

Tsakiris, G., Vangelis, H. (2004). Towards a Drought Watch System based on spatial SPI. Water Resources Management 18 (1): 1-12.

Mishra, A. K., Desai, V. R., (2005), Drought Forecasting Using Stochastic Models. Stochastic Environmental Research and Risk Assessment 19(5): 326-339.

Durdu, O.F., (2010), Application of Linear Stochastic Models For Drought Forecasting in The Buyuk Menderes River Basin, Western Turkey, Stochastic Environmental Research and Risk Assessment, doi:10.1007/s00477-010-0366-3.