Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration

Liu, S; Su, H; Zhang, R; Tian, J; Chen, S; Wang, W; Yang, L; Liang, H

Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration

Liu, S Su, H Zhang, R Tian, J Chen, S Wang, W Yang, L Liang, H

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Publisher:: Hindawi Limited
Publication Type:: Journal Article
Citation:: Advances in Meteorology, 2019, 2019, pp. 1-13
Issue Date:: 2019-01-14

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Field	Value	Language
dc.contributor.author	Liu, S
dc.contributor.author	Su, H
dc.contributor.author	Zhang, R
dc.contributor.author	Tian, J
dc.contributor.author	Chen, S
dc.contributor.author	Wang, W
dc.contributor.author	Yang, L
dc.contributor.author	Liang, H
dc.date.accessioned	2022-03-18T05:57:23Z
dc.date.available	2022-03-18T05:57:23Z
dc.date.issued	2019-01-14
dc.identifier.citation	Advances in Meteorology, 2019, 2019, pp. 1-13
dc.identifier.issn	1687-9309
dc.identifier.issn	1687-9317
dc.identifier.uri	http://hdl.handle.net/10453/155354
dc.description.abstract	<jats:p>Evapotranspiration (ET) is a significant component in the water cycle, and the estimation of it is imperative in water resource management. Regional ET can be derived by using remote sensing technology which combines remote sensing inputs with ground-based measurements. However, instantaneous ET values estimated through remote sensing directly need to be converted into daily totals. In this study, we attempted to retrieve daily ET from remotely sensed instantaneous ET. The study found that the Gaussian fitting curve closely followed the ET measurements during the daytime and hence put forward the Gaussian fitting method to convert the remotely sensed instantaneous ET into daily ETs. The method was applied to the middle reaches of Heihe River in China. Daily ETs on four days were derived and evaluated with ET measurements from the eddy covariance (EC) system. The correlation between daily ET estimates and measurements showed high accuracy, with a coefficient of determination (<jats:italic>R</jats:italic><jats:sup>2</jats:sup>) of 0.82, a mean average error (MAE) of 0.41 mm, and a root mean square error (RMSE) of 0.46 mm. To make more scientific assessments, percent errors were calculated on the estimation accuracy, which ranged from 0% to 18%, with more than 80% of locations having the percent errors within 10%. Analyses on the relationship between daily ET estimates and land use status were also made to assess the Gaussian fitting method, and the results showed that the spatial distribution of daily ET estimates well demonstrated ET differences caused by land use types and was intimately linked with the vegetation pattern. The comparison between the Gaussian fitting method and the sine function method and the ETrF method indicated that results derived through the Gaussian fitting method had higher precision than that obtained by the sine function method and the ETrF method.</jats:p>
dc.language	en
dc.publisher	Hindawi Limited
dc.relation.ispartof	Advances in Meteorology
dc.relation.isbasedon	10.1155/2019/6253832
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0401 Atmospheric Sciences
dc.title	Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration
dc.type	Journal Article
utslib.citation.volume	2019
utslib.for	0401 Atmospheric Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-03-18T05:57:22Z
pubs.publication-status	Published
pubs.volume	2019

Abstract:

Evapotranspiration (ET) is a significant component in the water cycle, and the estimation of it is imperative in water resource management. Regional ET can be derived by using remote sensing technology which combines remote sensing inputs with ground-based measurements. However, instantaneous ET values estimated through remote sensing directly need to be converted into daily totals. In this study, we attempted to retrieve daily ET from remotely sensed instantaneous ET. The study found that the Gaussian fitting curve closely followed the ET measurements during the daytime and hence put forward the Gaussian fitting method to convert the remotely sensed instantaneous ET into daily ETs. The method was applied to the middle reaches of Heihe River in China. Daily ETs on four days were derived and evaluated with ET measurements from the eddy covariance (EC) system. The correlation between daily ET estimates and measurements showed high accuracy, with a coefficient of determination (R2) of 0.82, a mean average error (MAE) of 0.41 mm, and a root mean square error (RMSE) of 0.46 mm. To make more scientific assessments, percent errors were calculated on the estimation accuracy, which ranged from 0% to 18%, with more than 80% of locations having the percent errors within 10%. Analyses on the relationship between daily ET estimates and land use status were also made to assess the Gaussian fitting method, and the results showed that the spatial distribution of daily ET estimates well demonstrated ET differences caused by land use types and was intimately linked with the vegetation pattern. The comparison between the Gaussian fitting method and the sine function method and the ETrF method indicated that results derived through the Gaussian fitting method had higher precision than that obtained by the sine function method and the ETrF method.

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http://hdl.handle.net/10453/155354