Daily reference crop evapotranspiration with reduced data sets in the humid environments of Azores islands using estimates of actual vapor pressure, solar radiation, and wind speed

  • P. Paredes
  • J. C. Fontes
  • E. B. Azevedo
  • L. S. Pereira
Original Paper


Reference crop evapotranspiration (ETo) estimations using the FAO Penman-Monteith equation (PM-ETo) require a set of weather data including maximum and minimum air temperatures (T max, T min), actual vapor pressure (e a), solar radiation (R s), and wind speed (u 2). However, those data are often not available, or data sets are incomplete due to missing values. A set of procedures were proposed in FAO56 (Allen et al. 1998) to overcome these limitations, and which accuracy for estimating daily ETo in the humid climate of Azores islands is assessed in this study. Results show that after locally and seasonally calibrating the temperature adjustment factor a d used for dew point temperature (T dew) computation from mean temperature, ETo estimations shown small bias and small RMSE ranging from 0.15 to 0.53 mm day−1. When R s data are missing, their estimation from the temperature difference (T maxT min), using a locally and seasonal calibrated radiation adjustment coefficient (k Rs), yielded highly accurate ETo estimates, with RMSE averaging 0.41 mm day−1 and ranging from 0.33 to 0.58 mm day−1. If wind speed observations are missing, the use of the default u 2 = 2 m s−1, or 3 m s−1 in case of weather measurements over clipped grass in airports, revealed appropriated even for the windy locations (u 2 > 4 m s−1), with RMSE < 0.36 mm day−1. The appropriateness of procedure to estimating the missing values of e a, R s, and u 2 was confirmed.


PM-ETo equation Actual vapor pressure from temperature Solar radiation from temperature Default wind speed 



The first author thanks the postdoctoral fellowship (SFRH/BPD/102478/2014) provided by FCT. The support of FCT through the research unit LEAF (UID/AGR/04129/2013) is acknowledged. The support to the third author by the project PROAAcXXIs (PO Açores 01-0145-FEDER-000037) is also acknowledged. Data were provided through the PROAAcXXIs project from Secretaria Regional do Ambiente e do Mar, Azores, Instituto Português do Mar e da Atmosfera (IPMA) and from the Eastern North Atlantic (ENA) Graciosa Island facility from the Atmospheric Radiation Measurement (ARM) Program sponsored by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division.


  1. Abraha MG, Savage MJ (2008) Comparison of estimates of daily solar radiation from air temperature range for application in crop simulations. Agric For Meteorol 148(3):401–416. CrossRefGoogle Scholar
  2. Aladenola OO, Madramootoo CA (2014) Evaluation of solar radiation estimation methods for reference evapotranspiration estimation in Canada. Theor Appl Climatol 118(3):377–385. CrossRefGoogle Scholar
  3. Allen RG (1996) Assessing integrity of weather data for reference evapotranspiration estimation. J Irrig Drain Eng 122(2):97–106. CrossRefGoogle Scholar
  4. Allen RG (1997) Self-calibrating method for estimating solar radiation from air temperature. J Hydrol Eng 2(2):56–67. CrossRefGoogle Scholar
  5. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration. Guidelines for computing crop water requirements. Irrigation and drainage paper 56. FAO, Rome 300 pGoogle Scholar
  6. Almorox J, Senatore A, Quej VH, Mendicino G (2016) Worldwide assessment of the Penman–Monteith temperature approach for the estimation of monthly reference evapotranspiration. Theor Appl Climatol.
  7. Annandale JG, Jovanovic NZ, Benadé N, Allen RG (2002) Software for missing data error analysis of Penman-Monteith reference evapotranspiration. Irrig Sci 21:57–67CrossRefGoogle Scholar
  8. Azevedo EB, Pereira LS, Itier B (1999) Modelling the local climate in island environments: water balance applications. Agric Water Manag 40(2-3):393–403. CrossRefGoogle Scholar
  9. Barceló AM, Nunes LF (2012) Climate atlas of the archipelagos of the Canary Islands, Madeira and the Azores. Air temperature and precipitation (1971-2000). State Meteorological Agency of Spain, Madrid, and Institute of Meteorology of Portugal, Lisbon 78pGoogle Scholar
  10. Bandyopadhyay A, Bhadra A, Raghuwanshi NS, Singh R (2008) Estimation of monthly solar radiation from measured air temperature extremes. Agric For Meteorol 148(11):1707–1718. CrossRefGoogle Scholar
  11. Cropper TE, Hanna E (2014) An analysis of the climate of Macaronesia, 1865–2012. Int J Climatol 34(3):604–622. CrossRefGoogle Scholar
  12. Eisenhauer JG (2003) Regression through the origin. Teach Stat 25(3):76–80. CrossRefGoogle Scholar
  13. Elias RB, Gil A, Silva L, Fernández-Palacios JM, Azevedo EB, Reis F (2016) Natural zonal vegetation of the Azores Islands: characterization and potential distribution. Phytocoenologia 46(2):107–123. CrossRefGoogle Scholar
  14. Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. J Irrig Drain Eng 108:225–230Google Scholar
  15. Jabloun M, Sahli A (2008) Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data: application to Tunisia. Agric Water Manag 95(6):707–715. CrossRefGoogle Scholar
  16. Jensen DT, Hargreaves GH, Temesgen B, Allen RG (1997) Computation of ETo under nonideal conditions. J Irrig Drain Eng 123(5):394–400. CrossRefGoogle Scholar
  17. Kimball JS, Running SW, Nemani R (1997) An improved method for estimating surface humidity from daily minimum temperature. Agric For Meteorol 85:87–98CrossRefGoogle Scholar
  18. Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World map of the Köppen-Geiger climate classification updated. Meteorol Z 15(3):259–263. CrossRefGoogle Scholar
  19. Kwon H, Choi M (2011) Error assessment of climate variables for FAO-56 reference evapotranspiration. Meteorog Atmos Phys 112(1-2):81–90. CrossRefGoogle Scholar
  20. Lawrence MG (2005) The relationship between relative humidity and the dewpoint temperature in moist air. A simple conversion and applications. Bull Am Meteorol Soc 86(2):225–233CrossRefGoogle Scholar
  21. Lecina S, Martınez-Cob A, Perez PJ, Villalobos FJ, Baselga JJ (2003) Fixed versus variable bulk canopy resistance for reference evapotranspiration estimation using the Penman–Monteith equation under semiarid conditions. Agric Water Manage 60:181–198CrossRefGoogle Scholar
  22. Legates DR, McCabe GJ Jr (1999) Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour Res 35(1):233–241. CrossRefGoogle Scholar
  23. Liu Y, Pereira LS (2001) Calculation methods for reference evapotranspiration with limited weather data. J Hydraul Eng 3:11–17 (in Chinese)Google Scholar
  24. Lyra GB, Zanetti SS, Santos AAR, de Souza JL, Lyra GB, Oliveira-Júnior JF, Lemes MAM (2016) Estimation of monthly global solar irradiation using the Hargreaves–Samani model and an artificial neural network for the state of Alagoas in northeastern Brazil. Theor Appl Climatol 125(3-4):743–756. CrossRefGoogle Scholar
  25. Martí P, Zarzo M, Vanderlinden K, Girona J (2015) Parametric expressions for the adjusted Hargreaves coefficient in Eastern Spain. J Hydrol 529:1713–1724. CrossRefGoogle Scholar
  26. Martins DS, Paredes P, Raziei T, Pires C, Cadima J, Pereira LS (2017) Assessing reference evapotranspiration estimation from reanalysis weather products. An application to the Iberian Peninsula. Int J Climatol 37(5):2378–2397. CrossRefGoogle Scholar
  27. Mendicino G, Senatore A (2013) Regionalization of the Hargreaves coefficient for the assessment of distributed reference evapotranspiration in Southern Italy. J Irrig Drain Eng 139(5):349–362. CrossRefGoogle Scholar
  28. Miranda PMA, Valente MA, Tomé AR, Trigo R, Coelho MFES, Aguiar A, Azevedo EB (2006) O clima de Portugal nos séculos XX e XXI. In: Santos FD, Miranda PMA (eds) Alterações Climáticas em Portugal - Cenários. Impactes e Medidas de Adaptação. Gradiva, Lisboa, pp 45–113 (In Portuguese)Google Scholar
  29. Monteith JL (1965) Evaporation and environment. In: The state and movement of water in living organisms, 19th Symp. of Soc. Exp. Biol., Cambridge University Press, Cambridge, pp. 205–234Google Scholar
  30. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900.  10.13031/2013.23153 CrossRefGoogle Scholar
  31. Nandagiri L, Kovoor GM (2005) Sensitivity of the food and agriculture organization Penman–Monteith evapotranspiration estimates to alternative procedures for estimation of parameters. J Irrig Drain Eng 131(3):238–248. CrossRefGoogle Scholar
  32. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models: part 1. A discussion of principles. J Hydrol 10(3):282–290. CrossRefGoogle Scholar
  33. Paredes P, Fontes JC, Azevedo EB, Pereira LS (2017) Daily reference crop evapotranspiration in the humid environments of Azores islands using reduced data sets. Accuracy of FAO PM temperature and Hargreaves-Samani methods. Theor Appl Climatol.
  34. Penman HL (1948) Natural evaporation from open water, bare soil and grass. Proc Royal Soc Ser A London 193(1032):120–145. CrossRefGoogle Scholar
  35. Pereira LS (2017) Water, agriculture and food: challenges and issues. Water Resour Manag 31(10):2985–2999. CrossRefGoogle Scholar
  36. Pereira LS, Allen RG, Smith M, Raes D (2015) Crop evapotranspiration estimation with FAO56: past and future. Agric Water Manag 147:4–20. CrossRefGoogle Scholar
  37. Pereira LS, Cai LG, Hann MJ (2003) Farm water and soil management for improved water use in the North China Plain. Irrig Drain 52(4):299–317CrossRefGoogle Scholar
  38. Pereira LS, Perrier A, Allen RG, Alves I (1999) Evapotranspiration: review of concepts and future trends. J Irrig Drainage Eng 125(2):45–51. CrossRefGoogle Scholar
  39. Popova Z, Kercheva M, Pereira LS (2006) Validation of the FAO methodology for computing ETo with missing climatic data. Application to South Bulgaria. Irrig Drain 55(2):201–215. CrossRefGoogle Scholar
  40. Raziei T, Pereira LS (2013) Estimation of ETo with Hargreaves-Samani and FAO-PM temperature methods for a wide range of climates in Iran. Agric Water Manag 121:1–18. CrossRefGoogle Scholar
  41. Ren X, Qu Z, Martins DS, Paredes P, Pereira LS (2016) Daily reference evapotranspiration for hyper-arid to moist sub-humid climates in Inner Mongolia, China: I. Assessing temperature methods and spatial variability. Water Resour Manag 30(11):3769–3791. CrossRefGoogle Scholar
  42. Samani Z (2000) Estimating solar radiation and evapotranspiration using minimum climatological data. J Irrig Drain Eng 126:265–267CrossRefGoogle Scholar
  43. Santos FD, Valente MA, Miranda PMA, Aguiar A, Azevedo EB, Tomé AR, Coelho F (2004) Climate change scenarios in the Azores and Madeira islands. World Resource Rev 16:473–491Google Scholar
  44. Sentelhas PC, Gillespie TJ, Santos EA (2010) Evaluation of FAO Penman–Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada. Agric Water Manag 97(5):635–644. CrossRefGoogle Scholar
  45. Slatyer RO, McIlroy IC (1961) Evaporation and the principles of its measurement. In: Practical micrometeorology, CSIRO (Australia) and UNESCO, ParisGoogle Scholar
  46. Smith M, Allen R, Monteith J, Perrier A, Pereira LS, Segeren A (1991) Report of the expert consultation on procedures for revision of FAO guidelines for prediction of crop water requirements. UN-FAO, Rome 54pGoogle Scholar
  47. Steduto P, Todorovic M, Caliandro A, Rubino P (2003) Daily reference evapotranspiration estimates by the Penman–Monteith equation in Southern Italy. Constant vs. variable canopy resistance. Theor Appl Climatol 74(3-4):217–225. CrossRefGoogle Scholar
  48. Tabari H (2010) Evaluation of reference crop evapotranspiration equations in various climates. Water Resour Manag 24(10):2311–2337. CrossRefGoogle Scholar
  49. Temesgen B, Allen RG, Jensen DT (1999) Adjusting temperature parameters to reflect well-watered conditions. J Irrig Drai Eng 125(1):26–33. CrossRefGoogle Scholar
  50. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94. CrossRefGoogle Scholar
  51. Todorovic M, Karic B, Pereira LS (2013) Reference evapotranspiration estimate with limited weather data across a range of Mediterranean climates. J Hydrol 481:166–176CrossRefGoogle Scholar
  52. Trajkovic S, Kolakovic S (2009) Estimating reference evapotranspiration using limited weather data. J Irrig Drain Eng 135(4):443–449. CrossRefGoogle Scholar
  53. Turbet M, Forget F, Head IIIJW, Wordsworth R (2017) 3D modelling of the climatic impact of outflow channel formation events on early Mars. Icarus 288:10–36. CrossRefGoogle Scholar
  54. UNEP (1997) World atlas of desertification, 2nd edn. United Nations Environment Programme, Arnold 182 pGoogle Scholar
  55. Vanderlinden K, Giráldez JV, Van Meirvenne M (2004) Assessing reference evapotranspiration by the Hargreaves method in southern Spain. J Irrig Drain Eng 130(3):184–191. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2017

Authors and Affiliations

  • P. Paredes
    • 1
  • J. C. Fontes
    • 2
  • E. B. Azevedo
    • 3
  • L. S. Pereira
    • 1
  1. 1.Centro de Investigação em Agronomia, Alimentos, Ambiente e Paisagem (LEAF), Instituto Superior de AgronomiaUniversidade de LisboaLisbonPortugal
  2. 2.Instituto de Investigação e Tecnologias Agrárias e do Ambiente, Faculdade de Ciências Agrárias e do AmbienteUniversidade dos AçoresAngra do HeroísmoPortugal
  3. 3.Grupo de Estudos do Clima, Meteorologia e Mudanças Globais, Instituto de Investigação e Tecnologias Agrárias e do Ambiente, Faculdade de Ciências Agrárias e do AmbienteUniversidade dos AçoresAngra do HeroísmoPortugal

Personalised recommendations