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Estimating Regional Evapotranspiration Using a Satellite-Based Wind Speed Avoiding Priestley–Taylor Approach
Wind speed (u) is a significant constraint in the evapotranspiration modeling over the highly heterogeneous regional surface due to its high temporal-spatial variation. In this study, a satellite-based Wind Speed Avoiding Priestley–Taylor (WAPT) algorithm was proposed to estimate the regional actual evapotranspiration by employing a u-independent theoretical trapezoidal space to determine the pixel Priestley–Taylor (PT) parameter Φ. The WAPT model was comprehensively evaluated with hydro-meteorological observations in the arid Heihe River Basin in northwestern China. The results show that the WAPT model can provide reliable latent heat flux estimations with the root-mean-square error (RMSE) of 46.0 W/m2 across 2013–2018 for 5 long-term observation stations and the RMSE of 49.6 W/m2 in the growing season in 2012 for 21 stations with intensive observations. The estimation by WAPT has a higher precision in the vegetation growing season than in the non-growing season. The estimation by WAPT has a closer agreement with the ground observations for vegetation-covered surfaces (e.g., corn and wetland) than that for dry sites (e.g., Gobi, desert, and desert steppe).
Estimating Regional Evapotranspiration Using a Satellite-Based Wind Speed Avoiding Priestley–Taylor Approach
Wind speed (u) is a significant constraint in the evapotranspiration modeling over the highly heterogeneous regional surface due to its high temporal-spatial variation. In this study, a satellite-based Wind Speed Avoiding Priestley–Taylor (WAPT) algorithm was proposed to estimate the regional actual evapotranspiration by employing a u-independent theoretical trapezoidal space to determine the pixel Priestley–Taylor (PT) parameter Φ. The WAPT model was comprehensively evaluated with hydro-meteorological observations in the arid Heihe River Basin in northwestern China. The results show that the WAPT model can provide reliable latent heat flux estimations with the root-mean-square error (RMSE) of 46.0 W/m2 across 2013–2018 for 5 long-term observation stations and the RMSE of 49.6 W/m2 in the growing season in 2012 for 21 stations with intensive observations. The estimation by WAPT has a higher precision in the vegetation growing season than in the non-growing season. The estimation by WAPT has a closer agreement with the ground observations for vegetation-covered surfaces (e.g., corn and wetland) than that for dry sites (e.g., Gobi, desert, and desert steppe).
Estimating Regional Evapotranspiration Using a Satellite-Based Wind Speed Avoiding Priestley–Taylor Approach
Jingjing Sun (Autor:in) / Wen Wang (Autor:in) / Xiaogang Wang (Autor:in) / Dui Huang (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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British Library Conference Proceedings | 2014
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