Reference crop evapotranspiration in distinct agricultural regions of Southern Brazil: a comparison of improved empirical models
The FAO56 Penman-Monteith model is globally accepted for the accurate determination of reference evapotranspiration (ETo). However, a lack of appropriate data encouraged the improved model’s approach to estimate ETo. This study compared the performance of 10 empirical models of ETo estimation (Penma...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Brasil |
| Institución: | Universidade Federal de Viçosa (UFV) |
| Repositorio: | Engenharia na Agricultura |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.periodicos.ufv.br:article/12418 |
| Acceso en línea: | https://periodicos.ufv.br/reveng/article/view/12418 |
| Access Level: | acceso abierto |
| Palabra clave: | FAO-56 Multi-climatic models Soil-plant-atmosphere system water balance Spatiotemporal models crop evapotranspiration multi-climatic models soil-plant-atmosphere system water balance spatiotemporal models |
| Sumario: | The FAO56 Penman-Monteith model is globally accepted for the accurate determination of reference evapotranspiration (ETo). However, a lack of appropriate data encouraged the improved model’s approach to estimate ETo. This study compared the performance of 10 empirical models of ETo estimation (Penman, Priestley & Taylor, Tanner & Pelton, Makkink, Jensen & Haise, Hargreaves & Samani, Camargo, Benevides & Lopes, Turc, and Linacre) contrasted with the FAO56 model in two regions in Southern Brazil. Data were collected from automatic stations of the Brazilian National Institute of Meteorology (INMET) from December 21, 2019, to February 28, 2021. The determination coefficient (R²), mean square error (nRMSE), mean bias error (MBE), Willmott index (d), and Pearson’s correlation coefficient (r), clustering, and Principal Component Analysis (PCA) were performed. For the different regions, the radiation-based model proposed by Penman was the best alternative for estimating ETo. The model showed the most appropriated values for R2 (0.9015) and r (0.9494). The clustering and PCA analyses indicated the interrelations of the meteorological data and the combination of the models according to the parameters used for the determination of ETo. |
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