Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017
We evaluated the performance of three global evapotranspiration (ET) models at local, regional, and global scales using the multiple sets of leaf area index (LAI) and meteorological data from 1982 to 2017 and investigated the uncertainty in ET simulations from the model structure and forcing data. T...
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MDPI AG
2020-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/15/2473 |
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| author | Huiling Chen Gaofeng Zhu Kun Zhang Jian Bi Xiaopeng Jia Bingyue Ding Yang Zhang Shasha Shang Nan Zhao Wenhua Qin |
| author_facet | Huiling Chen Gaofeng Zhu Kun Zhang Jian Bi Xiaopeng Jia Bingyue Ding Yang Zhang Shasha Shang Nan Zhao Wenhua Qin |
| author_sort | Huiling Chen |
| collection | DOAJ |
| description | We evaluated the performance of three global evapotranspiration (ET) models at local, regional, and global scales using the multiple sets of leaf area index (LAI) and meteorological data from 1982 to 2017 and investigated the uncertainty in ET simulations from the model structure and forcing data. The three ET models were the Simple Terrestrial Hydrosphere model (SiTH) developed by our team, the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), and the MODerate Resolution Imaging Spectroradiometer (MODIS) ET algorithm (MOD16). Comparing the observed with simulated monthly ET by the three models over 43 Fluxnet sites, we found that SiTH overestimated ET for forests with mean slope from 1.25 to 1.67, but it performed better than the other two models over short vegetation. MOD16 and PT-JPL models simulated well for forests but poorly in dryland biomes (slope = 0.25~0.55; <i>R</i><sup>2</sup> = 0.02~0.46). At the catchment scale, all models performed well, except for some tropical and high latitudinal catchments, with NSE values lower than 0 and RMSE and MAE values far beyond their mean values. At the global scale, SiTH highly overestimated ET in tropics, while PT-JPL slightly underestimated ET between 30°N and 60°N and MOD16 underestimated ET between 15°S and 30°S. Generally, the PT-JPL provided the better performance than SiTH and MOD16 models. This study also revealed that the estimated ET by SiTH and especially PT-JPL model were influenced by the uncertainty in meteorological data, and the estimated ET was performed better using MERRA-2 datasets for PT-JPL and using ERA5 datasets for SiTH. While the estimated ET by MOD16 were relatively sensitive to LAI data. In addition, our results suggested that the GLOBMAP and GIMMS datasets were more suitable for long-term ET simulations than the GLASS dataset. |
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| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T18:02:14Z |
| publishDate | 2020-08-01 |
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| series | Remote Sensing |
| spelling | doaj.art-7452e884ba0a4974b2f4b5a8c04012522023-11-20T08:49:01ZengMDPI AGRemote Sensing2072-42922020-08-011215247310.3390/rs12152473Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017Huiling Chen0Gaofeng Zhu1Kun Zhang2Jian Bi3Xiaopeng Jia4Bingyue Ding5Yang Zhang6Shasha Shang7Nan Zhao8Wenhua Qin9Key Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaInstitute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaNorthwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, ChinaCollege of Arts and Science Department of Mathematics, Miami University, Oxford, OH 45056, USAKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaKey Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, ChinaWe evaluated the performance of three global evapotranspiration (ET) models at local, regional, and global scales using the multiple sets of leaf area index (LAI) and meteorological data from 1982 to 2017 and investigated the uncertainty in ET simulations from the model structure and forcing data. The three ET models were the Simple Terrestrial Hydrosphere model (SiTH) developed by our team, the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), and the MODerate Resolution Imaging Spectroradiometer (MODIS) ET algorithm (MOD16). Comparing the observed with simulated monthly ET by the three models over 43 Fluxnet sites, we found that SiTH overestimated ET for forests with mean slope from 1.25 to 1.67, but it performed better than the other two models over short vegetation. MOD16 and PT-JPL models simulated well for forests but poorly in dryland biomes (slope = 0.25~0.55; <i>R</i><sup>2</sup> = 0.02~0.46). At the catchment scale, all models performed well, except for some tropical and high latitudinal catchments, with NSE values lower than 0 and RMSE and MAE values far beyond their mean values. At the global scale, SiTH highly overestimated ET in tropics, while PT-JPL slightly underestimated ET between 30°N and 60°N and MOD16 underestimated ET between 15°S and 30°S. Generally, the PT-JPL provided the better performance than SiTH and MOD16 models. This study also revealed that the estimated ET by SiTH and especially PT-JPL model were influenced by the uncertainty in meteorological data, and the estimated ET was performed better using MERRA-2 datasets for PT-JPL and using ERA5 datasets for SiTH. While the estimated ET by MOD16 were relatively sensitive to LAI data. In addition, our results suggested that the GLOBMAP and GIMMS datasets were more suitable for long-term ET simulations than the GLASS dataset.https://www.mdpi.com/2072-4292/12/15/2473evapotranspirationLAIuncertaintySiTHMOD16PT-JPL |
| spellingShingle | Huiling Chen Gaofeng Zhu Kun Zhang Jian Bi Xiaopeng Jia Bingyue Ding Yang Zhang Shasha Shang Nan Zhao Wenhua Qin Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 Remote Sensing evapotranspiration LAI uncertainty SiTH MOD16 PT-JPL |
| title | Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 |
| title_full | Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 |
| title_fullStr | Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 |
| title_full_unstemmed | Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 |
| title_short | Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 |
| title_sort | evaluation of evapotranspiration models using different lai and meteorological forcing data from 1982 to 2017 |
| topic | evapotranspiration LAI uncertainty SiTH MOD16 PT-JPL |
| url | https://www.mdpi.com/2072-4292/12/15/2473 |
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