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Performance of Different Surface Incoming Solar Radiation Models and Their Impacts on Reference Evapotranspiration

Author

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  • Ali Mokhtari

    (Iranian Space Agency)

  • Hamideh Noory

    (University of Tehran)

  • Majid Vazifedoust

    (University of Guilan)

Abstract

Reference evapotranspiration (ET0) from FAO-Penman-Monteith equation is highly sensitive to the surface incoming solar radiation (SISR) and therefore accurate estimate of this parameter would result in more accurate estimation of ET0. In this study, the accuracy of three main approaches for SISR estimation including empirical models (Angstrom and Hargreaves-Samani), physically-based data assimilation models (Global Land Data Assimilation System-Noah, GLDAS/Noah, and National Centers of Environmental Predictions/National Center for Atmospheric Research, NCEP/NCAR), and a satellite observation model (Satellite Application Facility on Climate Monitoring, CM-SAF) were evaluated using ground-based measurements from 2012 to 2015. Then SISR outputs from introduced approaches were implemented in FAO-Penman-Monteith equation for ET0 estimation on daily and monthly basis. The Angstrom calibrated model was the most accurate model with a coefficient of determination (R2) of 0.9 and standard error of estimate (SEE) of 2.58 MJ. m−2. d−1, and GLDAS/Noah, Hargreaves-Samani, NCEP/NCAR, and CM-SAF, had lower accuracy, respectively. However, the lack of the meteorological data and required empirical coefficients are the main limitations of applying the empirical models, however, satellite-based approaches are more practical for operational purposes. The results indicated that, in spite of slight overestimation in warm months, GLDAS/Noah model had better performance with R2=0.87 and SEE = 3.5 MJ. m−2. d−1 in case of lack of meteorological data. The accuracy of ET0 derived from FAO-Penman-Monteith equation was directly depended on the accuracy of SISR estimation. The ET0 estimation error was related to SISR estimation error with a fourth-degree function and had a linear relationship with SISR error at daily and monthly scales, respectively.

Suggested Citation

  • Ali Mokhtari & Hamideh Noory & Majid Vazifedoust, 2018. "Performance of Different Surface Incoming Solar Radiation Models and Their Impacts on Reference Evapotranspiration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(9), pages 3053-3070, July.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:9:d:10.1007_s11269-018-1974-9
    DOI: 10.1007/s11269-018-1974-9
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    References listed on IDEAS

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    1. C.-Y. Xu & V. Singh, 2002. "Cross Comparison of Empirical Equations for Calculating Potential Evapotranspiration with Data from Switzerland," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(3), pages 197-219, June.
    2. Alireza Sharifi & Yagob Dinpashoh, 2014. "Sensitivity Analysis of the Penman-Monteith reference Crop Evapotranspiration to Climatic Variables in Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5465-5476, December.
    3. Goyal, R. K., 2004. "Sensitivity of evapotranspiration to global warming: a case study of arid zone of Rajasthan (India)," Agricultural Water Management, Elsevier, vol. 69(1), pages 1-11, September.
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    2. Xiang, Keyu & Li, Yi & Horton, Robert & Feng, Hao, 2020. "Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review," Agricultural Water Management, Elsevier, vol. 232(C).
    3. Santos, Jannaylton Everton Oliveira & Cunha, Fernando França da & Filgueiras, Roberto & Silva, Gustavo Henrique da & Castro Teixeira, Antônio Heriberto de & Santos Silva, Francisco Charles dos & Sediy, 2020. "Performance of SAFER evapotranspiration using missing meteorological data," Agricultural Water Management, Elsevier, vol. 233(C).
    4. Nouri, Milad & Homaee, Mehdi, 2022. "Reference crop evapotranspiration for data-sparse regions using reanalysis products," Agricultural Water Management, Elsevier, vol. 262(C).
    5. Paredes, P. & Pereira, L.S., 2019. "Computing FAO56 reference grass evapotranspiration PM-ETo from temperature with focus on solar radiation," Agricultural Water Management, Elsevier, vol. 215(C), pages 86-102.

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