Estimation of evapotranspiration by the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith temperature (PMT) and Hargreaves-Samani (HS) models under temporal and spatial criteria - a case study in Duero basin (Spain)

Moratiel Yugueros, Ruben ORCID: https://orcid.org/0000-0002-9920-3937, Bravo Rubio, Raquel, Saa Requejo, Antonio ORCID: https://orcid.org/0000-0002-0329-0934, Tarquis Alfonso, Ana Maria ORCID: https://orcid.org/0000-0003-2336-5371 and Almorox Alonso, Javier ORCID: https://orcid.org/0000-0003-1523-0979 (2020). Estimation of evapotranspiration by the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith temperature (PMT) and Hargreaves-Samani (HS) models under temporal and spatial criteria - a case study in Duero basin (Spain). "Natural Hazards and Earth Systems Sciences", v. 20 (n. 3); pp. 859-875. ISSN 1561-8633. https://doi.org/10.5194/nhess-20-859-2020.

Descripción

Título: Estimation of evapotranspiration by the Food and Agricultural Organization of the United Nations (FAO) Penman-Monteith temperature (PMT) and Hargreaves-Samani (HS) models under temporal and spatial criteria - a case study in Duero basin (Spain)
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Natural Hazards and Earth Systems Sciences
Fecha: 27 Marzo 2020
ISSN: 1561-8633
Volumen: 20
Número: 3
Materias:
ODS:
Palabras Clave Informales: Accuracy; Calibration; Climate; COEFFICIENTS; Crop evapotranspiration; Equation; LIMITED WEATHER DATA; Trends; Variables; Water-Use
Escuela: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Departamento: Producción Agraria
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The evapotranspiration-based scheduling method is the most common method for irrigation programming in agriculture. There is no doubt that the estimation of the reference evapotranspiration (ETo) is a key factor in irrigated agriculture. However, the high cost and maintenance of agrometeorological stations and high number of sensors required to estimate it make it non-plausible, especially in rural areas. For this reason, the estimation of ETo using air temperature, in places where wind speed, solar radiation and air humidity data are not readily available, is particularly attractive. A daily data record of 49 stations distributed over Duero basin (Spain), for the period 20002018, was used for estimation of ETo based on seven models against Penman-Monteith (PM) FAO 56 (FAO - Food and Agricultural Organization of the United Nations) from a temporal (annual or seasonal) and spatial perspective. Two Hargreaves-Samani (HS) models, with and without calibration, and five Penman-Monteith temperature (PMT) models were used in this study. The results show that the models' performance changes considerably, depending on whether the scale is annual or seasonal. The performance of the seven models was acceptable from an annual perspective (R-2 > 0.91, NSE > 0.88, MAE < 0.52 and RMSE < 0.69 mm d(-1); NSE - Nash-Sutcliffe model efficiency; MAE - mean absolute error; RMSE - root-mean-square error). For winter, no model showed good performance. In the rest of the seasons, the models with the best performance were the following three models: PMTCHU (Penman-Monteith temperature with calibration of Hargreaves empirical coefficient - k(RS), average monthly value of wind speed, and average monthly value of maximum and minimum relative humidity), HSC (Hargreaves-Samani with calibration of k(RS)) and PMTCHU (Penman-Monteith temperature without calibration of k(RS), average monthly value of wind speed and average monthly value of maximum and minimum relative humidity). The HSc model presents a calibration of the Hargreaves empirical coefficient (k(RS)). In the PMTCUH model, k(RS) was calibrated and average monthly values were used for wind speed and maximum and minimum relative humidity. Finally, the PMTCUH model is like the PMTCUH model except that k(RS) was not calibrated. These results are very useful for adopting appropriate measures for efficient water management, especially in the intensive agriculture in semi-arid zones, under the limitation of agrometeorological data.

Proyectos asociados

Tipo
Código
Acrónimo
Responsable
Título
Gobierno de España
AGL2016-77282-C3-2-R
PRECISOST
Sin especificar
Sin especificar
Comunidad de Madrid
S2018/BAA-4330
AGRISOST-CM
Sin especificar
Sin especificar

Más información

ID de Registro: 91720
Identificador DC: https://oa.upm.es/91720/
Identificador OAI: oai:oa.upm.es:91720
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/6230219
Identificador DOI: 10.5194/nhess-20-859-2020
URL Oficial: https://nhess.copernicus.org/articles/20/859/2020/
Depositado por: iMarina Portal Científico
Depositado el: 31 Oct 2025 15:47
Ultima Modificación: 31 Oct 2025 19:04