Flood Analysis in Karkheh River Basin using Stochastic Model

Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh


This study analyzed the annual streamflow of Karkheh River in Karkheh river basin in the west of Iran for flood forecasting using stochastic models. For this purpose, we collected annual stremflow (peak and maximum discharge) during the period from 1958 to 2015 in Jelogir Majin hydrometric station (upstream of Karkheh dam reservoir). A time series model (stochastic model or ARIMA) has three stages consists of: model identification, parameter estimation and diagnostic check. Model identification was done by visual inspection on the Autocorrelation and Partial Autocorrelation Function. Three types of ARIMA(p,d,q) models (0,1,1), (1,1,1) and (4,1,1) suggested for the studied series. The suggested model parameters were computed using the Maximum Likelihood (ML), Conditional Least Square (CLS) and Unconditional Least Square (ULS) methods. In model verification, the chosen criterion for model parsimony was the Akaike Information Criteria (AIC) and the diagnostic checks include independence of residuals. The best ARIMA model for this series was (4,1,1), with their AIC values of 88.9 and 77.8 for annual peak and maximum streamflow respectively. Forecast series up to a lead time of ten years future (2006 to 2015) were generated using the accepted ARIMA models. Model accuracy was checked by comparing the predicted and observation series by coefficient of determination (R2). Results show that the ARIMA model was adequate for the flood analysis in Karkheh River and the forecast of the series in short time at future.


Stochastic Model; Flood Analysis; Maximum Likelihood; Karkheh River Basin.


Adeli, A., Fathi, M., Moghadam, Habib Musavi Jahromi, H., "Using Stochastic Models to Produce Artificial Time Series and Inflow Prediction: A Case Study of Talog Dam Reservoir, Khuzestan Province, Iran." International Bulletin of Water Resources and Development, 2015, Issue 5.

Chakraborty, SH., Denis, D.M., and Sherring, A., "Development of Time Series Autoregressive Model for Prediction of Rainfall and Runoff in Kelo Watershed Chhattisgarh". International Journal of Advances in Engineering Science and Technology, 2009, Vol. 2, No. 2, pp. 153-163.

Ghanbarpour, M.R., Abbaspour, K.C., Jalalvand, G., and ashtiani moghaddam, G., "Stochastic Modeling of Surface Stream Flow at Different Time Scales: Sangsoorakh Karst Basin, Iran" Journal of Cave and Karst Studies, 2010, Vol. 72, No. 1, pp. 1–10.

Hamidi machekposhti, K., Sedghi, H., Telvari, A., Babazadeh, H., "Forecasting by Stochastic Models to Inflow of Karkheh Dam at Iran" Civil Engineering Journal, 2017, Vol. 3, No. 5, pp. 340-350.

Huang Y.F., Mirzaei M., and Yap W.K. "Flood Analysis in Langat River Basin using Stochastic Model" International Journal of GEOMATE, 2016, Vol. 11, No. 27, pp. 2796-2803.

Mohamed, T.M., and Etuk, E.H., "Application of Linear Stochastic Models to Monthly Streamflow Data" Journal of Scientific and Engineering Research, 2017, Vol. 4, No. 4, pp. 322-326

Montgomery D.C., Jennings C.L., and Kulahci M., Introduction to time series analysis and forecasting, John Wiley & Sons, Inc., 2008.

Muhammad A.R., Xiaohui, Y., Ozgur, K., and Valetin, C., "Application of time series models for Streamflow Forecasting" Civil and Environmental Research, 2017, Vol. 9, No. 3.

Mujumdar, P.P., and D. Nagesh Kumar, D., "Stochastic models of streamflow: some case studies". Hydrological Sciences Journal, 2009, Vol. 35, No. 4, pp. 395-410.

Musa J.J., "Stochastic Modelling of Shiroro River Stream flow Process." American Journal of Engineering Research (AJER), 2013, Vol. No.6, pp. 49-54.

Nguyen, V.T.V., Nguyen, T.D., and Cung, A., "A statistical approach to downscaling of sub-daily extreme rainfall processes for climate-related impact studies in urban areas." Water science and technology: water supply, 2007, Vol.7 .No. 2, pp. 183-192.

Nigam, R., Nigam, S., and Mittal, S.K., "The river runoff forecast based on the modelling of time series." Russian Meteorology and Hydrology, 2014, Vol. 39, Issue 11, pp. 750-761.

O'Connel, P.E., ARIMA Model in Synthetic Hydrology: Mathematical Model for Surface Hydrology. John Wiley, NY, USA. 1977.

Otache Y. Martins, M. A. Sadeeq, I. E. Ahaneku, "ARMA Modelling of Benue River Flow Dynamics: Comparative Study of PAR Model." Open Journal of Modern Hydrology, 2011, Vol. 1, pp. 1-9.

Shakeel, A.M., Idrees, A.M., Naeem H.M., and Sarwar, B.M., "Time Series Modelling of Annual Maximum Flow of River Indus at Sukkur" Pakistan Journal of Agricultural Sciences, 1993, Vol. 30, No. 1.

Sherring, A., Hafizishtiyaq, A., Mishra, A.K., and Mohd A.A, "Stochastic Time Series Model for Prediction of Annual Rainfall and Runoff for Lidder Catchment of South Kashmir." Journal of Soil and Water Conservation, 2009, Vol. 8, No. 4, pp. 11-15.

Srikanthan, R., McMohan, T.A., and Irish J.L., "Time series analysis of annual flows of Australian streams." Journal of Hydrology, 1983, Vol. 66, pp. 213-226.

Stojković, M., Prohaska, S., and Plavšić, J., "Stochastic structure of annual discharges of large European rivers." J. Hydrology and Hydromechanics, 2015, Vol. 63, No. 1, pp. 63–70.

Tian, P., Zhao, G.J., Li, J., and Tian, K., "Extreme Value Analysis of Stream flow Time Series in Poyang Lake Basin, China." Water Science and Engineering, 2011, Vol.4, No.2, pp. 121-132.

Vijayakumar, N., Vennila, S., "A comparative analysis of forecasting reservoir inflow using ARMA model and Holt winters exponential smoothening technique." International Jour. of Innovation in Science and Mathematics, 2016, Vol. 4, No. 2, pp. 85-90.

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DOI: 10.21859/cej-030915


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