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Comparison of evapotranspiration upscaling methods from instantaneous to daytime scale for tea and wheat in southeast China

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  • Yan, Haofang
  • Li, Mi
  • Zhang, Chuan
  • Zhang, Jianyun
  • Wang, Guoqing
  • Yu, Jianjun
  • Ma, Jiamin
  • Zhao, Shuang

Abstract

Accurately converting instantaneous evapotranspiration (λETi) at satellite over-passing time into daily evapotranspiration (λETd) is a key issue of applying remotely sensed data to estimate regional evapotranspiration (λET) from remote sensing satellites, which plays an important role for effective water resource management. The scaling methods that take advantage of the relationship between λET and other environmental factors and can be used to convert λETi into λETd. In this study, five scaling methods of converting λETi into λETd, including the evaporative fraction method (Eva-f method), revised evaporative fraction method (R-Eva-f method), crop coefficient method (Kc-ET0 method), revised crop coefficient method (R-Kc-ET0 method) and direct canopy resistance method (Direct-rc method), were evaluated based on the detailed meteorological data measured from 2016 to 2018 in a tea field and 2018 to 2020 in a wheat field in southeast China. The estimated λETd was compared with the measured λETd by the Bowen ratio energy balance (BREB) method. The results indicated that the Eva-f and R-Eva-f methods with the mean root mean square error (RMSE) and coefficient of efficiency (ε) equaled 9.02 W m−2 and 0.92; 12.06 W m−2 and 0.89, respectively, were superior to the Kc-ET0, R-Kc-ET0 and Direct-rc method; the Kc-ET0 method with the mean RMSE and ε equaled 20.62 W m−2 and 0.79 was also a good option for simulating the λETd of tea and wheat; while the R-Kc-ET0 method simulated the λETd well for the wheat with mean RMSE and ε equaled 36.29 W m−2 and 0.71, but significantly overestimated the tea λETd with the mean RMSE and ε values of 39.61 W m−2 and 0.59 for tea; the Direct-rc method overestimated λETd of tea and wheat for the most of intervals with the mean RMSE and ε of 39.58 W m−2 and 0.62, and was not recommended to use in the present study areas.

Suggested Citation

  • Yan, Haofang & Li, Mi & Zhang, Chuan & Zhang, Jianyun & Wang, Guoqing & Yu, Jianjun & Ma, Jiamin & Zhao, Shuang, 2022. "Comparison of evapotranspiration upscaling methods from instantaneous to daytime scale for tea and wheat in southeast China," Agricultural Water Management, Elsevier, vol. 264(C).
  • Handle: RePEc:eee:agiwat:v:264:y:2022:i:c:s0378377422000117
    DOI: 10.1016/j.agwat.2022.107464
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    References listed on IDEAS

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    1. Xue, Jingyuan & Bali, Khaled M. & Light, Sarah & Hessels, Tim & Kisekka, Isaya, 2020. "Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize," Agricultural Water Management, Elsevier, vol. 238(C).
    2. Qiu, Rangjian & Du, Taisheng & Kang, Shaozhong & Chen, Renqiang & Wu, Laosheng, 2015. "Assessing the SIMDualKc model for estimating evapotranspiration of hot pepper grown in a solar greenhouse in Northwest China," Agricultural Systems, Elsevier, vol. 138(C), pages 1-9.
    3. Filgueiras, Roberto & Almeida, Thomé Simpliciano & Mantovani, Everardo Chartuni & Dias, Santos Henrique Brant & Fernandes-Filho, Elpídio Inácio & da Cunha, Fernando França & Venancio, Luan Peroni, 2020. "Soil water content and actual evapotranspiration predictions using regression algorithms and remote sensing data," Agricultural Water Management, Elsevier, vol. 241(C).
    4. Chen, Shu & Xu, Jijun & Li, Qingqing & Tan, Xuezhi & Nong, Xizhi, 2019. "A copula-based interval-bistochastic programming method for regional water allocation under uncertainty," Agricultural Water Management, Elsevier, vol. 217(C), pages 154-164.
    5. Lecina, S. & Martinez-Cob, A. & Perez, P. J. & Villalobos, F. J. & Baselga, J. J., 2003. "Fixed versus variable bulk canopy resistance for reference evapotranspiration estimation using the Penman-Monteith equation under semiarid conditions," Agricultural Water Management, Elsevier, vol. 60(3), pages 181-198, May.
    6. Huang, Song & Yan, Haofang & Zhang, Chuan & Wang, Guoqing & Acquah, Samuel Joe & Yu, Jianjun & Li, Lanlan & Ma, Jiamin & Opoku Darko, Ransford, 2020. "Modeling evapotranspiration for cucumber plants based on the Shuttleworth-Wallace model in a Venlo-type greenhouse," Agricultural Water Management, Elsevier, vol. 228(C).
    7. Yan, Haofang & Acquah, Samuel Joe & Zhang, Chuan & Wang, Guoqing & Huang, Song & Zhang, Hengnian & Zhao, Baoshan & Wu, Haimei, 2019. "Energy partitioning of greenhouse cucumber based on the application of Penman-Monteith and Bulk Transfer models," Agricultural Water Management, Elsevier, vol. 217(C), pages 201-211.
    8. Pozníková, Gabriela & Fischer, Milan & van Kesteren, Bram & Orság, Matěj & Hlavinka, Petr & Žalud, Zdeněk & Trnka, Miroslav, 2018. "Quantifying turbulent energy fluxes and evapotranspiration in agricultural field conditions: A comparison of micrometeorological methods," Agricultural Water Management, Elsevier, vol. 209(C), pages 249-263.
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