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Comparison of radial basis function networks and empirical equations for converting from pan evaporation to reference evapotranspiration
Authors:Slavisa Trajkovic
Affiliation:Faculty of Civil Engineering, University of Nis, Aleksandra Medvedeva 14, 18000 Nis, Serbia
Abstract:Evapotranspiration (ET) is one of the major processes in the hydrological cycle, and its reliable estimation is essential to water resources management. Numerous equations have been developed for estimating ET, most of which are complex and require numerous items of weather data. In many areas, the necessary data are lacking, and simpler techniques are required. Evaporation pans are used throughout the world because of the simplicity of technique, low cost, and ease of application. In this study, the radial basis function (RBF) network is applied for pan evaporation to evapotranspiration conversions. The adaptive pan‐based RBF network was trained using daily Policoro data from 15 May 1981 to 23 December 1983. The RBF network obtained, Christiansen, FAO‐24 pan, and FAO‐56 Penman–Monteith equations were verified in comparison with lysimeter measurements of grass evapotranspiration using daily Policoro data from 25 February to 18 December 1984. Based on summary statistics, the RBF network ranked first with the lowest RMSE value (0·433 mm day?1). The RBF network obtained on the basis of the daily data from Policoro, Italy and pan‐based equations were further tested using mean monthly data collected in Novi Sad, Serbia, and Kimberly, Idaho, USA. The overall results favoured use of the RBF network for pan evaporation to evapotranspiration conversions. The use of the RBF network is very simple and does not require any knowledge of ANNs. Users require only code (RBF network), Epan data and corresponding Ra data. Copyright © 2009 John Wiley & Sons, Ltd.
Keywords:class A pan  evaporation  evapotranspiration  lysimeters  neural networks
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