Artificial neural network models of daily pan evaporation

KESKİN M. E., TERZİ Ö.

Journal of Hydrologic Engineering, cilt.11, sa.1, ss.65-70, 2006 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11 Sayı: 1
  • Basım Tarihi: 2006
  • Doi Numarası: 10.1061/(asce)1084-0699(2006)11:1(65)
  • Dergi Adı: Journal of Hydrologic Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.65-70
  • Anahtar Kelimeler: Evaporation, Hydrologic models, Lakes, Neural network, Turkey
  • Isparta Uygulamalı Bilimler Üniversitesi Adresli: Hayır

Özet

Artificial neural network (ANN) models are proposed as an alternative approach of evaporation estimation for Lake Eǧirdir. This study has three objectives: (1) to develop ANN models to estimate daily pan evaporation from measured meteorological data; (2) to compare the ANN models to the Penman model; and (3) to evaluate the potential of ANN models. Meteorological data from Lake Eǧirdir consisting of 490 daily records from 2001 to 2002 are used to develop the model for daily pan evaporation estimation. The measured meteorological variables include daily observations of air and water temperature, sunshine hours, solar radiation, air pressure, relative humidity, and wind speed. The results of the Penman method and ANN models are compared to pan evaporation values. The comparison shows that there is better agreement between the ANN estimations and measurements of daily pan evaporation than for other model. © 2006 ASCE.