Application of linear stochastic models to monthly streamflow data of Rahad River, Sudan
by Tariq Mahgoub Mohamed; Ette Harrison Etuk
International Journal of Hydrology Science and Technology (IJHST), Vol. 7, No. 2, 2017

Abstract: Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Linear stochastic models known as multiplicative seasonal autoregressive integrated moving average (SARIMA) model were used to simulate and forecast monthly streamflow of Rahad River, Sudan. For the analysis, monthly streamflow data for the years 1972 to 2009 were used. A visual inspection of the time plot gives the expected impression of a generally horizontal trend and 12-month seasonal periodicity. The seasonality observed in auto correlation function (ACF) and partial auto correlation function (PACF) plots of monthly streamflow data was removed using first order seasonal differencing prior to the development of the SARIMA model. Interestingly, the SARIMA (2, 0, 0) × (0, 1, 1)₁₂ model developed was found to be most suitable for simulating monthly streamflow for Rahad River. The model was found appropriate to forecast three years of monthly streamflow and assist decision makers to establish priorities for water demand.

Online publication date: Sun, 14-May-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Hydrology Science and Technology (IJHST):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com