Artificial Models for Interbasin Flow Prediction in Southern Turkey
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Volume 14, Issue 7
Abstract
The aim of this study was to develop an optimum flow prediction method, based on the adaptive neural-based fuzzy inference system (ANFIS) and artificial neural network (ANN). Each methodology was applied to river flow predicting in Manavgat Stream in the southern part of Turkey. In application, Manavgat Stream flows were predicted from Dalaman Stream, Alara Stream, and Göksu Stream flows. Each stream is located in different catchments. For monthly streamflow predictions, data were taken from the General Directorate of Electrical Power Resources Survey and Development Administration. Used data covered a period (1969–2003) for monthly streamflows. The ANFIS and ANN models had only one output with three input variables. Comparison of the ANFIS and ANN models showed a better agreement between the ANFIS model estimations and measurements of monthly flows than ANN. With the help of the ANFIS model for interbasin flow prediction, it was possible to estimate missing or unmeasured data.
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Published In
Journal of Hydrologic Engineering
Volume 14 • Issue 7 • July 2009
Pages: 752 - 758
Copyright
© 2009 ASCE.
History
Received: Oct 4, 2007
Accepted: Nov 5, 2008
Published online: Feb 19, 2009
Published in print: Jul 2009
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