Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau

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Abstract = R 2 = 0.86 and 0.87), resulting in a higher simulation accuracy than all six existing algorithms. We used five soil moisture datasets and five precipitation datasets to further investigate the impact of moisture constraint uncertainty on the improved P-LSH algorithm. The ET estimates of the improved P-LSH algorithm, driven by the GLDAS_Noah soil moisture, performed best compared with those driven by other soil moisture and precipitation datasets, while ET estimates driven by various precipitation datasets generally showed a high and stable accuracy. These results suggest that high-quality soil moisture can optimally express moisture supply to ET, and that more accessible precipitation data can serve as a substitute for soil moisture as an indicator of moisture status for its robust performance in barren evaporation.

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Improved soil evaporation remote sensing retrieval algorithms and associated uncertainty analysis on the Tibetan Plateau ; volume:27 ; number:2 ; year:2023 ; pages:363-383 ; extent:21
Hydrology and earth system sciences ; 27, Heft 2 (2023), 363-383 (gesamt 21)

Creator: Feng, Jin
Zhang, Ke
Zhan, Huijie
Chao, Lijun

DOI: 10.5194/hess-27-363-2023

URN: urn:nbn:de:101:1-2023033008202031222856

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:46 AM CEST

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Feng, Jin
Zhang, Ke
Zhan, Huijie
Chao, Lijun

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