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Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula

Author

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  • Tomas-Burguera, Miquel
  • Vicente-Serrano, Sergio M.
  • Grimalt, Miquel
  • Beguería, Santiago

Abstract

The standard approach for computing reference crop evapotranspiration (ETo) is the FAO-56 Penman-Monteith (FAO-PM) method, which requires data on air temperature, radiation, air humidity and wind speed. Unlike air temperature the other variables are less frequently available, hindering the application of FAO-PM. A lot of efforts exist to find the best method to estimate FAO-PM ETo when some variables are not available. The FAO-56 manual recommends to estimate the missing variables based on those currently observed (PM-R), or use the less demanding Hargreaves and Samani method (HS). Additionally, if the missing variables are measured at nearby stations, spatial interpolation can be used to estimate the missing data previous to applying FAO-PM (PM-IC). This paper focuses on the comparison, at the monthly time scale, of the performance of these methods to in the Iberian Peninsula. By using 53 weather stations with all data to calculate FAO-PM, data scarcity scenarios are simulated and the mentioned methods are tested (PM-R, HS, PM-IC)PM-IC yielded consistently the best results according to a number of tests. It yielded the lowest mean absolute error (MAE) at 7.56mm/month, while PM-R yielded values of 10.15mm/month and HS 9.36mm/month and biased results. PM-IC was also best at reproducing the long-term variability and trends in ETo. A good and unbiased estimation of monthly ETo time series are required for irrigation planning and crop design.

Suggested Citation

  • Tomas-Burguera, Miquel & Vicente-Serrano, Sergio M. & Grimalt, Miquel & Beguería, Santiago, 2017. "Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula," Agricultural Water Management, Elsevier, vol. 182(C), pages 103-116.
    • Handle: RePEc:eee:agiwat:v:182:y:2017:i:c:p:103-116
    DOI: 10.1016/j.agwat.2016.12.013
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    2. Paredes, P. & Pereira, L.S. & Almorox, J. & Darouich, H., 2020. "Reference grass evapotranspiration with reduced data sets: Parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables," Agricultural Water Management, Elsevier, vol. 240(C).
    3. Sergio M. Vicente‐Serrano & Tim R. McVicar & Diego G. Miralles & Yuting Yang & Miquel Tomas‐Burguera, 2020. "Unraveling the influence of atmospheric evaporative demand on drought and its response to climate change," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(2), March.
    4. Vásquez, Cristina & Célleri, Rolando & Córdova, Mario & Carrillo-Rojas, Galo, 2022. "Improving reference evapotranspiration (ETo) calculation under limited data conditions in the high Tropical Andes," Agricultural Water Management, Elsevier, vol. 262(C).
    5. Yang, Yang & Cui, Yuanlai & Bai, Kaihua & Luo, Tongyuan & Dai, Junfeng & Wang, Weiguang & Luo, Yufeng, 2019. "Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts," Agricultural Water Management, Elsevier, vol. 211(C), pages 70-80.
    6. Zhang, Zixiong & Gong, Yicheng & Wang, Zhongjing, 2018. "Accessible remote sensing data based reference evapotranspiration estimation modelling," Agricultural Water Management, Elsevier, vol. 210(C), pages 59-69.
    7. Yang, Yang & Luo, Yufeng & Wu, Conglin & Zheng, Hezhen & Zhang, Lei & Cui, Yuanlai & Sun, Ningning & Wang, Li, 2019. "Evaluation of six equations for daily reference evapotranspiration estimating using public weather forecast message for different climate regions across China," Agricultural Water Management, Elsevier, vol. 222(C), pages 386-399.
    8. Paredes, Paula & Martins, Diogo S. & Pereira, Luis Santos & Cadima, Jorge & Pires, Carlos, 2018. "Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes," Agricultural Water Management, Elsevier, vol. 210(C), pages 340-353.
    9. Nouri, Milad & Homaee, Mehdi, 2022. "Reference crop evapotranspiration for data-sparse regions using reanalysis products," Agricultural Water Management, Elsevier, vol. 262(C).

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