American Society of Civil Engineers


Artificial Models for Interbasin Flow Prediction in Southern Turkey


by M. Erol Keskin, (Prof., Fac. of Engrg.-Arch., Suleyman Demirel Univ., Isparta 32260, Turkey. E-mail: merol@mmf.sdu.edu.tr) and Dilek Taylan, (Fac. of Engrg.-Arch., Suleyman Demirel Univ., Isparta 32260, Turkey. E-mail: edilek@mmf.sdu.edu.tr)

Journal of Hydrologic Engineering, Vol. 14, No. 7, July 2009, pp. 752-758, (doi:  http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000051)

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Document type: Technical Note
Discussion: by Gürol Yıldırım E-mail: yildirimg3@itu.edu.tr and et al.    (See full record)
Closure:(See full record)
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 35-year 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.


ASCE Subject Headings:
Hydrologic models
Water flow
River basins
Predictions
Turkey