Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration
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 val...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2019/6253832 |
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| author | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Shaohui Chen Weimin Wang Lijun Yang Hong Liang |
| author_facet | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Shaohui Chen Weimin Wang Lijun Yang Hong Liang |
| author_sort | Suhua Liu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2247e498e12145f890aefb631627a9ea |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-2247e498e12145f890aefb631627a9ea2025-02-03T01:29:56ZengWileyAdvances in Meteorology1687-93091687-93172019-01-01201910.1155/2019/62538326253832Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous EvapotranspirationSuhua Liu0Hongbo Su1Renhua Zhang2Jing Tian3Shaohui Chen4Weimin Wang5Lijun Yang6Hong Liang7School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaDepartment of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Florida, FL 33431, USAKey Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaShenzhen Environmental Monitoring Center, Shenzhen 518049, ChinaShenzhen Environmental Monitoring Center, Shenzhen 518049, ChinaShenzhen Environmental Monitoring Center, Shenzhen 518049, ChinaEvapotranspiration (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.http://dx.doi.org/10.1155/2019/6253832 |
| spellingShingle | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Shaohui Chen Weimin Wang Lijun Yang Hong Liang Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration Advances in Meteorology |
| title | Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration |
| title_full | Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration |
| title_fullStr | Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration |
| title_full_unstemmed | Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration |
| title_short | Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration |
| title_sort | based on the gaussian fitting method to derive daily evapotranspiration from remotely sensed instantaneous evapotranspiration |
| url | http://dx.doi.org/10.1155/2019/6253832 |
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