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Performance of SAFER evapotranspiration using missing meteorological data

Author

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  • Santos, Jannaylton Everton Oliveira
  • Cunha, Fernando França da
  • Filgueiras, Roberto
  • Silva, Gustavo Henrique da
  • Castro Teixeira, Antônio Heriberto de
  • Santos Silva, Francisco Charles dos
  • Sediyama, Gilberto Chohaku

Abstract

The Simple Algorithm for Evapotranspiration Retrieving (SAFER) can be used to estimate surface evapotranspiration. In the process of SAFER parameterization, the reference evapotranspiration (ETo) calculated by the Penman-Monteith (PM) method was included. However, methodologies for estimating ETo that use fewer meteorological variables should be sought, mainly to increase the applicability of the method in regions where there are no complete weather stations. Thus, the objective of this study was to evaluate the impact of the ETo calculated with estimated data on the calculation of surface evapotranspiration using SAFER (ETSAFER) in the Brazilian semiarid region. The study was carried out in areas of centre pivots cultivated with sugarcane located in the public irrigated perimeter of Jaíba, MG, Brazil. ETo and its impact on ETSAFER were analysed using meteorological data from a station belonging to the National Institute of Meteorology (INMET) as well as data from 19 images of the Landsat 8 satellite from 2013, 2014 and 2016. The ETSAFER responses were analysed from the calculations of ETo estimated by the Hargreaves-Samani (HS) and PM methods with missing data including single absences of solar radiation (RS), wind speed (U2), relative humidity (RH) and combined absences of U2 and RH, U2, RH and RS, RS and U2, and RS and RH. The temporal and spatial variability of ETSAFER for sugarcane crops was assessed. RS was the parameter that most affected ETo and, consequently, ETSAFER. ETSAFER was underestimated when calculated using the ETo estimated by PM with missing RS data and overestimated when the ETo was calculated by HS. In the absence of single or combined data of U2 and RH, it is recommended to estimate ETo by PM with missing data for the calculation of ETSAFER. It is not advised to use the ETo obtained by the HS method for calculating ETSAFER in semiarid regions.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:agiwat:v:233:y:2020:i:c:s0378377419320785
    DOI: 10.1016/j.agwat.2020.106076
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    1. Elnmer, Ayat & Khadr, Mosaad & Kanae, Shinjiro & Tawfik, Ahmed, 2019. "Mapping daily and seasonally evapotranspiration using remote sensing techniques over the Nile delta," Agricultural Water Management, Elsevier, vol. 213(C), pages 682-692.
    2. Singh Rawat, Kishan & Kumar Singh, Sudhir & Bala, Anju & Szabó, Szilárd, 2019. "Estimation of crop evapotranspiration through spatial distributed crop coefficient in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 213(C), pages 922-933.
    3. Bingham, N. H., 1996. "The sample mid-range and interquartiles," Statistics & Probability Letters, Elsevier, vol. 27(2), pages 131-136, April.
    4. Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
    5. 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.
    6. 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.
    7. Olivera-Guerra, Luis & Merlin, Olivier & Er-Raki, Salah & Khabba, Saïd & Escorihuela, Maria Jose, 2018. "Estimating the water budget components of irrigated crops: Combining the FAO-56 dual crop coefficient with surface temperature and vegetation index data," Agricultural Water Management, Elsevier, vol. 208(C), pages 120-131.
    8. 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.
    9. Rahimzadegan, Majid & Janani, AdelehalSadat, 2019. "Estimating evapotranspiration of pistachio crop based on SEBAL algorithm using Landsat 8 satellite imagery," Agricultural Water Management, Elsevier, vol. 217(C), pages 383-390.
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