Application of SARIMA model to forecasting monthly flows in Waterval River, South Africa

Kassahun Birhanu Tadesse, Megersa Olumana Dinka

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


Knowledge of future river flow information is fundamental for development and management of a river system. In this study, Waterval River flow was forecastedby SARIMA model using GRETL statistical software. Mean monthly flows from 1960 to 2016 were used for modelling and forecasting. Different unit root and Mann-Kendall trend analysis proved the stationarity of the observed flow time series. Based on seasonally differenced correlogram characteristics, different SARIMA models were evaluated; their parameters were optimized, and diagnostic check up of forecasts was made using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AI) and Hannan-Quinn (HQ) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 model was selected for Waterval River flow forecasting. Comparison of forecast performance of SARIMA models with that of computational intelligent forecasting techniques was recommended for future study.

Original languageEnglish
Pages (from-to)229-236
Number of pages8
JournalJournal of Water and Land Development
Issue number1
Publication statusPublished - 1 Dec 2017


  • heteroscedasticity
  • stationarity test
  • trend analysis
  • validation
  • white noise

ASJC Scopus subject areas

  • Environmental Engineering
  • Geography, Planning and Development
  • Development
  • Water Science and Technology
  • Agricultural and Biological Sciences (miscellaneous)


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