Best arima models for forecasting inflow of hit station

Joint Authors

Shathir, Adnan Khalaf
Salih, Layla Ali Muhammad

Source

Basrah Journal for Engineering Sciences

Issue

Vol. 16, Issue 1 (30 Jun. 2016), pp.62-71, 10 p.

Publisher

University of Basrah College of Engineering

Publication Date

2016-06-30

Country of Publication

Iraq

No. of Pages

10

Main Subjects

Earth Sciences, Water and Environment
Materials Science , Minerals

Abstract EN

Time series analysis for hydrological phenomena has an important role in water resources engineering.

In this study, seven models of ARIMA family are tested for forecasting the monthly discharge at Hit station on Euphrates river in Iraq.

The statistical analyses were done for models with help of IBM SPSS statistics 21 software, The number of observations used is equal to 480 reading, start from October 1932 and end at September 1972, this period represents the near-natural stream flow of the river before the construction of dams in Syria and Turkey.

Statistical tests such as T-test and F-test were used to detect any change in Mean and Variance at 95% significant probability level.

Results showed that the best model is (2,0,1)×(0,1,1)12 which gives minimum error and good agreement between observed and forecast discharge

American Psychological Association (APA)

Shathir, Adnan Khalaf& Salih, Layla Ali Muhammad. 2016. Best arima models for forecasting inflow of hit station. Basrah Journal for Engineering Sciences،Vol. 16, no. 1, pp.62-71.
https://search.emarefa.net/detail/BIM-724379

Modern Language Association (MLA)

Shathir, Adnan Khalaf& Salih, Layla Ali Muhammad. Best arima models for forecasting inflow of hit station. Basrah Journal for Engineering Sciences Vol. 16, no. 1 (2016), pp.62-71.
https://search.emarefa.net/detail/BIM-724379

American Medical Association (AMA)

Shathir, Adnan Khalaf& Salih, Layla Ali Muhammad. Best arima models for forecasting inflow of hit station. Basrah Journal for Engineering Sciences. 2016. Vol. 16, no. 1, pp.62-71.
https://search.emarefa.net/detail/BIM-724379

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 71

Record ID

BIM-724379