A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm
Abstract
1. Introduction
2. Data and Methodology
2.1. Study Area and Data
2.2. Methodology
3. Results
3.1. Evaluation of Yearly Scale ET Data
3.2. Evaluation of Seasonal-Scale ET Data
3.3. Evaluation of Monthly-Scale ET Data
3.4. Overall Evaluation of Five ET Products
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Name | Acronyms | Temporal Coverage | Resolution | Algorithm | Key Equations | Limitations | References |
---|---|---|---|---|---|---|---|
Actual evapotranspiration reconstruction | Recon | April 2002 to September 2013 | Monthly, 0.125° | Simple water balance | | The resolution of Grace satellite is coarse, and the accuracy of ET in small watershed is affected. | Wan et al. (2015) |
Process-based land surface evapotranspiration/heat flux | P-LSH | January 1982 to December 2013 | Monthly, 0.5° | Modified Penman-Monteith | No considered canopy interception | K. Zhang et al. (2015) | |
Penman–Monteith–Leuning | PML | July 2002 to August 2019 | 8 day, 500 m | Modified Penman-Monteith-Leuning | Soil evaporation simplifies the physical process. | Y Q. Zhang et al. (2019) | |
Moderate-resolution imaging spectroradiometer | MODIS | January 2000 to Present | 8 day, 500 m | Penman-Monteith-Leuning | Biome Properties Look-Up Table is an empirical value. Unused flux tower data calibration parameters. | Mu et al. (2011) | |
Model tree ensemble | MTE | January 1982 to December 2008 | Monthly, 0.5° | TRIAL + ERROR | No specific equation | No physical process | Jung et al. (2011) |
Global land evaporation amsterdam model | GLEAM | 1980 to 2020 | Monthly, 0.25° | Modified Priestley-Taylor | Simplified impedance | Martens et al. (2017) |
Five ET datasets vs. Recon | Bias (mm/year) | RMSE (mm/year) | R |
---|---|---|---|
P-LSH vs. Recon | −22.94 | 92.62 | 0.92 |
PML vs. Recon | 17.73 | 83.44 | 0.93 |
MODIS vs. Recon | -106.71 | 145.90 | 0.89 |
MTE vs. Recon | 99.45 | 126.39 | 0.95 |
GLEAM vs Recon | 23.18 | 87.78 | 0.92 |
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Chao, L.; Zhang, K.; Wang, J.; Feng, J.; Zhang, M. A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm. Remote Sens. 2021, 13, 2414. https://doi.org/10.3390/rs13122414
Chao L, Zhang K, Wang J, Feng J, Zhang M. A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm. Remote Sensing. 2021; 13(12):2414. https://doi.org/10.3390/rs13122414
Chicago/Turabian StyleChao, Lijun, Ke Zhang, Jingfeng Wang, Jin Feng, and Mengjie Zhang. 2021. "A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm" Remote Sensing 13, no. 12: 2414. https://doi.org/10.3390/rs13122414
APA StyleChao, L., Zhang, K., Wang, J., Feng, J., & Zhang, M. (2021). A Comprehensive Evaluation of Five Evapotranspiration Datasets Based on Ground and GRACE Satellite Observations: Implications for Improvement of Evapotranspiration Retrieval Algorithm. Remote Sensing, 13(12), 2414. https://doi.org/10.3390/rs13122414