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Evaluation of the temporal reconstruction methods for MODIS-based continuous daily actual evapotranspiration estimation

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Listed:
  • Hu, Xinyu
  • Zhao, Jinfeng
  • Sun, Shikun
  • Jia, Chengru
  • Zhang, Fuyao
  • Ma, Yizhe
  • Wang, Kaixuan
  • Wang, Yubao

Abstract

Monitoring continuous daily actual evapotranspiration (ET) is very useful for managing regional water resources and understanding vegetation water consumption and water use efficiency. However, the research on remote sensing-based temporal reconstruction methods for mapping continuous daily ET is still limited, lacking comparative evaluations and mechanism discussions. In the study, four reconstruction methods, including two interpolation methods (the reference evaporative fraction (ETrF) and evaporative fraction (EF) method) and two calibration methods (the advection-aridity (AA) and modified Katerji-Perrier (KP) method), were systematically evaluated to reconstruct continuous daily ET from discrete daily ET based on MODIS products and atmospheric data. Meanwhile, an additional test using in situ measurements as a perfect proxy for the retrievals on satellite overpass dates was added as a baseline case that is independent of remotely sensed ET error. The internal coupling mechanism between each model’s simulations and the underlying surface physical and atmospheric driving factors were also analyzed using the sensitivity and uncertainty analysis methods. The results demonstrated that the interpolation methods performed better and had a higher potential for improvement as the quality of remote sensing ET inputs improved. Although the underestimation errors in the remote sensing-based ET estimates propagated to subsequent reconstructions and caused underestimation to a certain extent, the four methods could still effectively simulate continuous daily ET. Among them, the EF method with a simple calculation process, which used reference quantity directly related to solar radiation, had the best performance based on in situ with an R2 of 0.8233 and an NRMSE of 0.0889. Given remote sensing estimates, the AA method was the best due to the compensation effects, with an R2 of 0.7267 and an NRMSE of 0.1442. As all methods showed high sensitivity to ET of satellite overpass days, its accuracy should be a top priority for continuous daily ET reconstruction work.

Suggested Citation

  • Hu, Xinyu & Zhao, Jinfeng & Sun, Shikun & Jia, Chengru & Zhang, Fuyao & Ma, Yizhe & Wang, Kaixuan & Wang, Yubao, 2023. "Evaluation of the temporal reconstruction methods for MODIS-based continuous daily actual evapotranspiration estimation," Agricultural Water Management, Elsevier, vol. 275(C).
    • Handle: RePEc:eee:agiwat:v:275:y:2023:i:c:s0378377422005388
    DOI: 10.1016/j.agwat.2022.107991
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    References listed on IDEAS

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    1. Hao, Pengyu & Di, Liping & Guo, Liying, 2022. "Estimation of crop evapotranspiration from MODIS data by combining random forest and trapezoidal models," Agricultural Water Management, Elsevier, vol. 259(C).
    2. James M. Murphy & David M. H. Sexton & David N. Barnett & Gareth S. Jones & Mark J. Webb & Matthew Collins & David A. Stainforth, 2004. "Quantification of modelling uncertainties in a large ensemble of climate change simulations," Nature, Nature, vol. 430(7001), pages 768-772, August.
    3. 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.
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