Upper Indus Basin (UIB) region has faced seasonal and sometimes unpredictable disastrous flow in their tributaries and contributing one of the world’s largest Indus River System. As these streams emerged from high mountains of Hindukush, Karakorum and Himalaya ranges, and formed as a lifeline for the local population of which90% is accommodate by Indus River system source. A little change in the regional climate may cause floods and outburst flows in the river and affects the lives, regional ecosystem and long part of the Karakoram highway. On the other hand, the shortage of water in Pakistan can create an alarming condition in future because a huge amount of eastern glaciers is shrinking. According to UN-ICC 2011 report Pakistan is in top of the four risky countries which adversely affected by climate change and especially worst hit by bi-catastrophes in 2010.During summer, intensifications of temperature may dissimilar for different locations/altitudes but it affects the glaciated areas. Moreover, the summer river flow and precipitation in previous winter and spring seasons has significant correlation shows their influence in the UIB region. Consequently, it may also be responsible for fluctuation in the seasonal/regular flows of UIB Rivers. To study these variations this paper analyses two types of data, mean monthly and 4-times moving average of monthly for long-term forecast. They belong to two different rivers Ghizer-Gilgit at Gilgit and Ghizer-Gilgit-Hunza at Alam stations. Both types of data illustrate a strong seasonal cycle. Therefore, seasonal autoregressive integrated moving average (SARIMA) models of time series method have been used. The five selected SARIMA models explore 90% and more river flow forecast. Moreover, the result with 4-times moving average is more accurate than simple data.
Hewitt K. Tributary glacier surges: An exceptional concentration at panmah glacier, karakoramhimalaya. J Glaciol 2007; 53: 181-188. http://dx.doi.org/10.3189/172756507782202829
Tahir AA, Chevallier P, Arnaud Y, Ahmad B. Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan. Hydrol Earth Syst Sci. Discuss 2011; 8: 2821-2860. http://dx.doi.org/10.5194/hessd-8-2821-2011
Konecny F. 2 A daily stream?ow model based on a jump-diffusion process. New uncertainty concepts in hydrology and water resources 2007; 225.
Fowler HJ, Archer DR. Conflicting signals of climatic change in the upper Indus basin. J Climate 2005; 19: 4276-4293. http://dx.doi.org/10.1175/JCLI3860.1
Anthes RA. Meterology, 7/e, Upper Saddle River, NJ: Prentice-Hall, 1997; pp. 31-50
Minarik B, Martinka K. Reduction of uncertainties in the flood estimation in the Czechoslovak section of Danube river. In Flood Hydrology, Springer Netherlands, 1987; pp. 187-195. http://dx.doi.org/10.1007/978-94-009-3957-8_15
Browning Keith A, Robert J. Gurney. Global energy and water cycles. Cambridge University Press 1999.
Hassan SA, Ansari MRK. Nonlinear analysis of seasonality and stochasticity of the Indus River. Hydrol Sci J 2010; 55: 250-265. http://dx.doi.org/10.1080/02626660903546167
Eastham J, Kirby M, Mainuddin M, Thomas M. Simple water use accounting of the Indus Basin. Challenge Program on Water & Food 2008.
Archer DR, Fowler HJ. Using meteorological data to forecast seasonal runoff on the River Jhelum, Pakistan. Journal of Hydrology 2008; 361: 10-23. http://dx.doi.org/10.1016/j.jhydrol.2008.07.017
Salas JD. Analysis and modeling of hydrologic time series. Handbook of hydrology 1993; pp. 1-72.
Chatfield C. The analysis of time series: an introduction. CRC press 2013.
Archer D. Contrasting hydrological regimes in the upper Indus Basin. Journal of Hydrology 2003; 274: 198-210. http://dx.doi.org/10.1016/S0022-1694(02)00414-6
Tong H. Non-linear time series: a dynamical system approach. Oxford University Press 1990.
Pandit SM, Shien-Ming W. Time series and system analysis with pplications. New York: Wiley 1983.
Box GE, Jenkins GM. Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco, California, USA 1994.
Solomatine DP, Velickov S, Wust JC. Predicting water levels and currents in the North Sea using chaos theory and neural networks. In proceedings of the congress-international association for hydraulic research 2001; pp. 353-359.
Makridakis S, Wheelwright SC, Hyndman RJ. Forecasting methods and applications. John Wiley & Sons 2008.
EViews (7.0v) EViews software available from: http:// www.eviews.com. Quantitative Micro Software (QMS), Irvine, California, USA 2010.
Akaike H. A new look at the statistical model identification. IEEE Transaction on Automatic Control 1974; 19: 716-723. http://dx.doi.org/10.1109/TAC.1974.1100705
Schwartz G. Estimating the dimensions of a model. Ann. Statist 1978; 6: 461-464. http://dx.doi.org/10.1214/aos/1176344136
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