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Reference crop evapotranspiration for data-sparse regions using reanalysis products

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  • Nouri, Milad
  • Homaee, Mehdi

Abstract

Reasonable estimation of reference evapotranspiration (ETo) requires some climatic inputs which might be missing in areas with sparse data recording. This study aimed to assess performance of FAO56 Penman-Monteith (PM-ETo) fed by ERA5, MERRA2 and GLDAS2 outputs in estimating daily and monthly ETo under data limitation. The accuracy of PM-ETo calculated by interpolated factors and the temperature-based PM-ETo (PMT) was also studied. Additionally, performance of PM-ETo fed by the bias-corrected reanalysis products against the PMT with updated constant, i.e. recalibrated PMT, was investigated. Climatic data required to run PM-ETo were collected from 146 stations over Iran for 25 years. Results revealed that ERA5 provides more realistic daily and monthly ETo estimates relative to MERRA2 and GLDAS2 in 84% of cases. Furthermore, ERA5 surpassed the others in producing daily and monthly wind speed, vapor pressure deficit and mean temperature for the majority of locations. The average relative Mean Bias Error (rMBE) of − 7.3% and 8.1% at monthly scale and of − 11.1% and 9.8% at daily scale were found for MERRA2- and GLDAS2-estimated ETo, respectively, indicating ETo overestimation and underestimation by MERRA2 and GLDAS2, respectively. The ERA5 provided more satisfactory results, with normalized Root Mean Square Error of 15.2% and 22.7% for daily and monthly steps, respectively, relative to PMT for approximately 70% of sites. Moreover, ETo estimated by ERA5 had a smaller nRMSE than that simulated using the interpolated variables in around 60% of the sites. Therefore, under temperature data availability or existence of nearby sites, application of ERA5 is better suited to estimate ETo in our study area. The PM-ETo fed by bias-corrected ERA5 outputs also outperformed recalibrated PMT, illustrating that bias-correction seems to be a more accurate modification when complete datasets are available at least for a limited time. Overall, ERA5 products are robust surrogates for simulating ETo under data limitation on different temporal resolutions which is needed for decision making and planning processes.

Suggested Citation

  • Nouri, Milad & Homaee, Mehdi, 2022. "Reference crop evapotranspiration for data-sparse regions using reanalysis products," Agricultural Water Management, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:agiwat:v:262:y:2022:i:c:s0378377421005965
    DOI: 10.1016/j.agwat.2021.107319
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    References listed on IDEAS

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    1. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).
    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. Jeong, D.I. & St-Hilaire, A. & Gratton, Y. & Bélanger, C. & Saad, C., 2017. "A guideline to select an estimation model of daily global solar radiation between geostatistical interpolation and stochastic simulation approaches," Renewable Energy, Elsevier, vol. 103(C), pages 70-80.
    4. Martinez-Cob, A. & Tejero-Juste, M., 2004. "A wind-based qualitative calibration of the Hargreaves ET0 estimation equation in semiarid regions," Agricultural Water Management, Elsevier, vol. 64(3), pages 251-264, February.
    5. Ohlendorf, Nils & Schill, Wolf-Peter, 2020. "Frequency and duration of low-wind-power events in Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(8).
    6. Raziei, Tayeb & Pereira, Luis S., 2013. "Estimation of ETo with Hargreaves–Samani and FAO-PM temperature methods for a wide range of climates in Iran," Agricultural Water Management, Elsevier, vol. 121(C), pages 1-18.
    7. 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.
    8. Nouri, Milad & Homaee, Mehdi & Bannayan, Mohammad & Hoogenboom, Gerrit, 2017. "Towards shifting planting date as an adaptation practice for rainfed wheat response to climate change," Agricultural Water Management, Elsevier, vol. 186(C), pages 108-119.
    9. Allen, Richard G. & Pereira, Luis S. & Howell, Terry A. & Jensen, Marvin E., 2011. "Evapotranspiration information reporting: I. Factors governing measurement accuracy," Agricultural Water Management, Elsevier, vol. 98(6), pages 899-920, April.
    10. Gavilan, P. & Lorite, I.J. & Tornero, S. & Berengena, J., 2006. "Regional calibration of Hargreaves equation for estimating reference ET in a semiarid environment," Agricultural Water Management, Elsevier, vol. 81(3), pages 257-281, March.
    11. Gruber, Katharina & Klöckl, Claude & Regner, Peter & Baumgartner, Johann & Schmidt, Johannes, 2019. "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil," Energy, Elsevier, vol. 189(C).
    12. Nouri, Milad & Homaee, Mehdi & Bannayan, Mohammad & Hoogenboom, Gerrit, 2016. "Towards modeling soil texture-specific sensitivity of wheat yield and water balance to climatic changes," Agricultural Water Management, Elsevier, vol. 177(C), pages 248-263.
    13. Olauson, Jon, 2018. "ERA5: The new champion of wind power modelling?," Renewable Energy, Elsevier, vol. 126(C), pages 322-331.
    14. 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.
    15. Pelosi, A. & Chirico, G.B., 2021. "Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?," Agricultural Water Management, Elsevier, vol. 258(C).
    16. 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.
    17. Slavisa Trajkovic & Srdjan Kolakovic, 2009. "Evaluation of Reference Evapotranspiration Equations Under Humid Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(14), pages 3057-3067, November.
    18. Allen, Richard G. & Pruitt, William O. & Wright, James L. & Howell, Terry A. & Ventura, Francesca & Snyder, Richard & Itenfisu, Daniel & Steduto, Pasquale & Berengena, Joaquin & Yrisarry, Javier Basel, 2006. "A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO56 Penman-Monteith method," Agricultural Water Management, Elsevier, vol. 81(1-2), pages 1-22, March.
    19. 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.
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    1. Pelosi, A., 2023. "Performance of the Copernicus European Regional Reanalysis (CERRA) dataset as proxy of ground-based agrometeorological data," Agricultural Water Management, Elsevier, vol. 289(C).
    2. Nouri, Milad & Homaee, Mehdi & Pereira, Luis S. & Bybordi, Mohammad, 2023. "Water management dilemma in the agricultural sector of Iran: A review focusing on water governance," Agricultural Water Management, Elsevier, vol. 288(C).

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