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Temperature-Based Approaches for Estimating Reference Evapotranspiration.
- Source :
- Journal of Irrigation & Drainage Engineering; Jul2005, Vol. 131 Issue 4, p316-323, 8p, 3 Charts, 1 Graph
- Publication Year :
- 2005
-
Abstract
- The Food and Agriculture Organization of the United Nations (FAO) has proposed using the Penman–Monteith (FAO-56 PM) method as the standard method for estimating reference evapotranspiration (ET<subscript>0</subscript>), and for evaluating other methods. The basic obstacle to widely using this method is the numerous required data that are not available at many weather stations. The maximum and minimum air temperatures constitute a set of minimum data necessary for the estimation of ET<subscript>0</subscript>. The basic goal of the paper is to examine whether it is possible to attain the reliable estimation of ET<subscript>0</subscript> only on the basis of the temperature data. This goal was reached by the evaluation of the reliability of four temperature-based approaches [radial basis function (RBF) network, Thornthwaite, Hargreaves, and reduced set Penman–Monteith methods] as compared to the FAO-56 PM method. The seven weather stations selected for this study are located in Serbia (Southeast Europe). The Thornthwaite, Hargreaves, and reduced set Penman–Monteith methods mostly underestimated or overestimated ET<subscript>0</subscript> obtained by the FAO-56 PM method. In this study, methods were calibrated using the standard FAO-56 PM method. However, the RBF network better predicted FAO-56 PM ET<subscript>0</subscript> than calibrated temperature-based methods at most locations. It gives reliable results in all locations and it has proven to be the most adjustable to the local climatic conditions. These results are of significant practical use because the adaptive temperature-based RBF network can be used when relative humidity, radiation, and wind speed data are not available. [ABSTRACT FROM AUTHOR]
- Subjects :
- EVAPOTRANSPIRATION
TEMPERATURE
ARTIFICIAL neural networks
CALIBRATION
Subjects
Details
- Language :
- English
- ISSN :
- 07339437
- Volume :
- 131
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Journal of Irrigation & Drainage Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 17636714
- Full Text :
- https://doi.org/10.1061/(ASCE)0733-9437(2005)131:4(316)