| 摘 要： |
Surface evapotranspiration (ET) is a vital process that connects the water cycle, energy budget, and carbon cycle between the land and atmosphere. ET measurements using the eddy covariance (EC) technique typically encounter large gaps. In this study, a physics-based full-factorial scheme for filling gaps in ET from EC observations is proposed based on the decoupling model of the Penman-Monteith equation, which mechanically interconnects the full range of ET influential factors from the atmosphere, vegetation, and soil. The new method was tested and intercompared with four typical gap-filling methods, i.e., marginal distribution sampling, mean diurnal variation, constant reference evaporative fraction, and constant evaporative fraction, using the data collected at 136 sites from AmeriFlux, FLUXNET, and Tibetan Plateau Data Center over the crop, grass, forest, and other remaining land-cover types. The validation results showed that (1) the full-factorial scheme performed well for filling the artificially randomly generated hourly and daily gaps of the EC-based ET measurements, with a root mean square error (RMSE) of 28.8-96.1 W/m(2) for the hourly gaps and an RMSE of 19.9-38.7 W/m(2) for the daily gaps, (2) for filling the hourly gaps, the accuracy decreased with the increase in the gap length; for filling the daily gaps, the accuracy decreased with the increase in the gap length at first and then remained almost unchanged, (3) the full-factorial scheme outperformed the four typical methods for filling both the hourly and daily gaps, and (4) all five gap-filling methods presented the best performance at the grass sites, followed by the crop, and the worst performance at the forest sites. In conclusion, the proposed full-factorial scheme can produce reasonable gap-filled hourly and daily ET and is superior to the existing typical gap-filling methods. Therefore, it could be a good candidate for filling the ET gaps in EC measurements. |
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