Estimation of the pan evaporation coefficient in cold and dry climate conditions via the M5 regression tree model

In this study, class A pan coefficient (Kp) values were simulated via the M5 tree model, by using daily meteorological data of four stations in the East Azerbaijan province, which has arid and cold climate in the northwest of Iran. Firstly, the FAO-24 and FAO-56 methods, which are commonly used to c...

Descripción completa

Detalles Bibliográficos
Autores: Taghi Sattari, Mohammad, Ahmadi̇far, Vahdat, Deli̇rhasanni̇a, Reza, Apaydín, Halit
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:México
Institución:UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
Repositorio:Atmósfera
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/52777
Acceso en línea:https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52777
Access Level:acceso abierto
Palabra clave:class a pan
data mining
decision tree
evapotranspiration
pan coefficient
Descripción
Sumario:In this study, class A pan coefficient (Kp) values were simulated via the M5 tree model, by using daily meteorological data of four stations in the East Azerbaijan province, which has arid and cold climate in the northwest of Iran. Firstly, the FAO-24 and FAO-56 methods, which are commonly used to calculate Kp values, were taken into consideration in the study. The Kp values calculated in the second stage were assumed to be observed values and were taken as the outputs of the M5 model. Four different training datasets consisting of 66, 70, 75 and 80% of the original data were tested. The best results were obtained when 70% of the data was used for training and 30% for testing. Results indicated that a Kp value was easily simulated with simple linear equations with high accuracy rate (R2 = 0.99) in all the stations. Furthermore, the Kp value was easily simulated using only two meteorological variables (relative humidity and wind speed), without the need for complex tables and equations. The most important finding of this study was the easy estimation of the Kp with a number of linear functions obtained from the M5 model; as a result, the simulated Kp can help us to calculate evapotranspiration accurately for more effective irrigation planning. The proposed method offers advantages as it is simpler and easier than the existing approaches in the literature.