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Combination of limited meteorological data for predicting reference crop evapotranspiration using artificial neural network method

A. Elbeltagi ; A. Nagy ; S. Mohammed ; C.B. Pande ; M. Kumar ; S.A. Bhat ; J. Zsembeli ; L. Huzsvai ; J. Tamás ; E. Kovács ; E. Harsányi ; C. Juhász |

Dans Agronomy (vol. 12, n. 2, February 2022)

Reference crop evapotranspiration (ETo) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was [...]

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