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