Monthly runoff model for kemer dam with radial based artificial neural networkss Radyal Tabanh Yapay Sinir Aǧ;lari• ile Kemer Baraji• Ayli•k Aki•mlari•ni•n Modellenmesi

Okkan U., DALKILIÇ H. Y.

Teknik Dergi/Technical Journal of Turkish Chamber of Civil Engineers, cilt.23, sa.2, ss.5957-5966, 2012 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 2
  • Basım Tarihi: 2012
  • Dergi Adı: Teknik Dergi/Technical Journal of Turkish Chamber of Civil Engineers
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.5957-5966
  • Anahtar Kelimeler: Kemer dam, Monthly runoff model, Radial based artificial neural networks
  • Erzincan Binali Yıldırım Üniversitesi Adresli: Evet

Özet

It is very important to make reliable runoff estimations and runoff modeling studies when planning and designing water resources systems. In the study presented, a Radial Based Artificial Neural Network (RBANN) model is developed and applied to the monthly flows of Kemer Dam reservoir in the Biiyuk Menderes Basin. The best radial based neural network model which requires monthly areal precipitation, temperature and a month before areal precipitation as the input data, is trained by using 225 months of runoff data observed between March 1979 and October 1997. The model is then tested by 97 months of runoff data recorded between December 1997 and December 2005. When the statistics of the long term and seasonal term recorded and modeled runoff are compared, it can be seen that the developed model successfully represents the monthly runoff input to Kemer reservoir and can be used to forecast the monthly runoff in a watershed.