1Professor, Department of Civil Engineering, S.V. University College of Engineering, Tirupati, Andhra Pradesh, India.
2Principal, Siddhartha Institute of Engineering and Technology, Narayanavanam Road, Puttur, Andhra Pradesh, India.
*E-mail id: mallikarjuna_perugu@yahoo.co.in
The study presents the development of artificial neural network (ANN) models for estimating daily reference evapotranspiration (ET0) at Tirupati, Nellore, Rajahmundry, Anakapalli and Rajendranagar regions of Andhra Pradesh. The performance of neural networks with input climatic parameters mostly influencing the regions was evaluated by comparing ET0 estimated using FAO-56 Penman–Monteith method. The optimal ANN (4-3-1) for Tirupati and Nellore regions and ANN (4-4-1) for Rajahmundry, Anakapalli and Rajendranagar regions showed a satisfactory performance in the ET0 estimation. These ANN models may therefore be adopted for estimating ET0 in the study area with reasonable degree of accuracy.
Reference evapotranspiration, Artificial neural network, Multiple and partial correlation coefficients, Performance evaluation
