A Hybrid Wavelet and Neuro-Fuzzy Model for Forecasting the Monthly Streamflow Data

Alpaslan Yarar ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2014, vol. 28, issue 2, 553-565

Abstract: Researchers have studied to forecast the streamflow in order to develop the water usage policy. They have used not only traditional methods, but also computer aided methods. Some black-box models, like Adaptive Neuro Fuzzy Inference Systems (ANFIS), became very popular for the hydrologic engineering, because of their rapidity and less variation requirements. Wavelet Transform has become a useful tool for the analysis of the variations in time series. In this study, a hybrid model, Wavelet-Neuro Fuzzy (WNF), has been used to forecast the streamflow data of 5 Flow Observation Stations (FOS), which belong to Sakarya Basin in Turkey. In order to evaluate the accuracy performance of the model, Auto Regressive Integrated Moving Average (ARIMA) model has been used with the same data sets. The comparison has been made by Root Mean Squared Errors (RMSE) of the models. Results showed that hybrid WNF model forecasts the streamflow more accurately than ARIMA model. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Streamflow modeling; Wavelet; Anfis; ARIMA (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11269-013-0502-1 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:28:y:2014:i:2:p:553-565

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-013-0502-1

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().