Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS
Abstract
1. Introduction
2. Materials and Methods
2.1. Overview of the Study Area
2.2. Data Collection and Processing
2.2.1. Landsat Data
2.2.2. MODIS Data
2.2.3. Meteorological Data
2.2.4. Actual ET Measured by Large-Weighted Lysimeter and the DEM Data
2.3. The Surface Energy Balance System (SEBS) Model
2.3.1. Parameters of SEBS Model
2.3.2. Evaporation Ratio
2.3.3. Evapotranspiration Time Scale Expansion
2.3.4. Accuracy Verification Methods
2.4. Model Performance Statistics
3. Results
3.1. Comparison of ET Estimation Results to Measured ET
3.2. Comparison of ET Modeled by SEBS and Measured by Large-Weighted Lysimeter
3.3. The Influence Factors for Calculating Spatial ET
3.4. The Spatial Distribution of Modeled ET
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Liu, C.; Qiu, R.; Cui, N.; Zhang, B.; Wang, R.; Wang, Z.; Guo, W. Comparison of Surface Resistance-Based Models for Estimating Maize Evapotranspiration in a Humid Region of China. J. Am. Water Resour. Assoc. 2024, 60, 27–42. [Google Scholar] [CrossRef]
- Qiu, R.; Li, L.; Liu, C.; Wang, Z.; Zhang, B.; Liu, Z. Evapotranspiration Estimation Using a Modified Crop Coefficient Model in a Rotated Rice-Winter Wheat System. Agric. Water Manag. 2022, 264, 107501. [Google Scholar] [CrossRef]
- Kool, D.; Agam, N.; Lazarovitch, N.; Heitman, J.L.; Sauer, T.J.; Ben-Gal, A. A Review of Approaches for Evapotranspiration Partitioning. Agric. For. Meteorol. 2014, 184, 56–70. [Google Scholar] [CrossRef]
- Anderson, M.C.; Kustas, W.P.; Norman, J.M.; Diak, G.T.; Hain, C.R.; Gao, F.; Yang, Y.; Knipper, K.R.; Xue, J.; Yang, Y.; et al. A Brief History of the Thermal IR-Based Two-Source Energy Balance (TSEB) Model—Diagnosing Evapotranspiration from Plant to Global Scales. Agric. For. Meteorol. 2024, 350, 109951. [Google Scholar] [CrossRef]
- Su, Z. The Surface Energy Balance System (SEBS) for Estimation of Turbulent Heat Fluxes. Hydrol. Earth Syst. Sci. 2002, 6, 85–100. [Google Scholar] [CrossRef]
- Zhao, J.; Chen, X.L.; Zhang, J.; Zhao, H.G.; Song, Y.Y. Higher Temporal Evapotranspiration Estimation with Improved SEBS Model from Geostationary Meteorological Satellite Data. Sci. Rep. 2019, 9, 14981. [Google Scholar] [CrossRef]
- Kaya, Y. Evaluation of ICESat-2 Laser Altimetry for Inland Water Level Monitoring: A Case Study of Canadian Lakes. Water 2025, 17, 1098. [Google Scholar] [CrossRef]
- Huang, Z.; Sun, R.; Wang, H.; Wu, X. Trends and Innovations in Surface Water Monitoring via Satellite Altimetry: A 34-Year Bibliometric Review. Remote Sens. 2024, 16, 2886. [Google Scholar] [CrossRef]
- Liou, Y.A.; Kar, S.K. Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms-A Review. Energies 2014, 7, 2821–2849. [Google Scholar] [CrossRef]
- Derardja, B.; Khadra, R.; Abdelmoneim, A.A.A.; El-Shirbeny, M.A.; Valsamidis, T.; De Pasquale, V.; Deflorio, A.M.; Volden, E. Advancements in Remote Sensing for Evapotranspiration Estimation: A Comprehensive Review of Temperature-Based Models. Remote Sens. 2024, 16, 1927. [Google Scholar] [CrossRef]
- Hu, X.L.; Shi, L.S.; Lian, X.; Bian, J. Parameter Variability across Different Timescales in the Energy Balance-Based Model and Its Effect on Evapotranspiration Estimation. Sci. Total Environ. 2023, 871, 161919. [Google Scholar] [CrossRef]
- Dhungel, R.; Aiken, R.; Evett, S.R.; Colaizzi, P.D.; Marek, G.; Moorhead, J.E.; Baumhardt, R.L.; Brauer, D.; Kutikoff, S.; Lin, X.M. Energy Imbalance and Evapotranspiration Hysteresis Under an Advective Environment: Evidence From Lysimeter, Eddy Covariance, and Energy Balance Modeling. Geophys. Res. Lett. 2021, 48, e2020GL091203. [Google Scholar] [CrossRef]
- Liu, S.H.; Su, H.B.; Zhang, R.H.; Tian, J.; Chen, S.H.; Wang, W.Z. Regional Estimation of Remotely Sensed Evapotranspiration Using the Surface Energy Balance-Advection (SEB-A) Method. Remote Sens. 2016, 8, 644. [Google Scholar] [CrossRef]
- Mu, Q.; Heinsch, F.A.; Zhao, M.; Running, S.W. Development of a Global Evapotranspiration Algorithm Based on MODIS and Global Meteorology Data. Remote Sens. Environ. 2007, 111, 519–536. [Google Scholar] [CrossRef]
- El Masri, B.; Rahman, A.F.; Dragoni, D. Evaluating a New Algorithm for Satellite-Based Evapotranspiration for North American Ecosystems: Model Development and Validation. Agric. For. Meteorol. 2019, 268, 234–248. [Google Scholar] [CrossRef]
- Raoufi, R.; Beighley, E. Estimating Daily Global Evapotranspiration Using Penman-Monteith Equation and Remotely Sensed Land Surface Temperature. Remote Sens. 2017, 9, 1138. [Google Scholar] [CrossRef]
- Li, Y.; Hu, X.; Luo, Y.; Xu, Y.; Huang, P.; Yuan, D.; Song, C.; Cui, Y.; Xie, H. Spatiotemporal Variation in Rice Evapotranspiration under the Influence of Rice Expansion: A Case Study in the Sanjiang Plain, Northeast China. Paddy Water Environ. 2024, 22, 535–550. [Google Scholar] [CrossRef]
- Elhag, M. Inconsistencies of SEBS Model Output Based on the Model Inputs: Global Sensitivity Contemplations. J. Indian Soc. Remote Sens. 2016, 44, 435–442. [Google Scholar] [CrossRef]
- Liu, Z.; Fu, Y.H.; Shi, X.; Lock, T.R.; Kallenbach, R.L.; Yuan, Z. Soil Moisture Determines the Effects of Climate Warming on Spring Phenology in Grasslands. Agric. For. Meteorol. 2022, 323, 109039. [Google Scholar] [CrossRef]
- Yinglan, A.; Wang, G.Q.; Liu, T.X.; Xue, B.L.; Kuczera, G. Spatial Variation of Correlations between Vertical Soil Water and Evapotranspiration and Their Controlling Factors in a Semi-Arid Region. J. Hydrol. 2019, 574, 53–63. [Google Scholar] [CrossRef]
- Liu, C.; Sun, G.; McNulty, S.G.; Noormets, A.; Fang, Y. Environmental Controls on Seasonal Ecosystem Evapotranspiration/Potential Evapotranspiration Ratio as Determined by the Global Eddy Flux Measurements. Hydrol. Earth Syst. Sci. 2017, 21, 311–322. [Google Scholar] [CrossRef]
- Alam, M.S.; Lamb, D.W.; Rahman, M.M. In-Situ Partitioning of Evaporation and Transpiration Components Using a Portable Evapotranspiration Dome-A Case Study in Tall Fescue (Festuca Arundinacea). Agric. Water Manag. 2019, 213, 352–357. [Google Scholar] [CrossRef]
- Sun, X.M.; Zou, C.B.; Wilcox, B.P.; Stebler, E. Effect of Vegetation on the Energy Balance and Evapotranspiration in Tallgrass Prairie: A Paired Study Using the Eddy-Covariance Method. Bound.-Layer Meteorol. 2019, 170, 127–160. [Google Scholar] [CrossRef]
- Gwate, O.; Mantel, S.K.; Gibson, L.A.; Munch, Z.; Palmer, A.R. Exploring Dynamics of Evapotranspiration in Selected Land Cover Classes in a Sub-Humid Grassland: A Case Study in Quaternary Catchment S50E, South Africa. J. Arid. Environ. 2018, 157, 66–76. [Google Scholar] [CrossRef]
- Wagle, P.; Gowda, P.H.; Northup, B.K. Dynamics of Evapotranspiration over a Non-Irrigated Alfalfa Field in the Southern Great Plains of the United States. Agric. Water Manag. 2019, 223, 105727. [Google Scholar] [CrossRef]
- Hufkens, K.; Keenan, T.F.; Flanagan, L.B.; Scott, R.L.; Bernacchi, C.J.; Joo, E.; Brunsell, N.A.; Verfaillie, J.; Richardson, A.D. Productivity of North American Grasslands Is Increased under Future Climate Scenarios despite Rising Aridity. Nat. Clim. Chang. 2016, 29, 710–714. [Google Scholar] [CrossRef]
- Qiu, R.; Katul, G.G.; Zhang, L.; Qin, S.; Jiang, X. The Effects of Changing Environments, Abiotic Stresses, and Management Practices on Cropland Evapotranspiration: A Review. Rev. Geophys. 2025, 63, e2024RG000858. [Google Scholar] [CrossRef]
- Li, X.; An, C.; Li, X.; Wu, Q.; Chen, X.; Guo, J.; Gao, T.; Wang, H.; Dong, Z. Impacts of grazing intensity on soil properties and carbon content in Xilamuren Grassland. J. Environ. Manag. 2025, 386, 125773. [Google Scholar] [CrossRef]
- Irons, J.R.; Dwyer, J.L.; Barsi, J.A. The next Landsat Satellite: The Landsat Data Continuity Mission. Remote Sens. Environ. 2012, 122, 11–21. [Google Scholar] [CrossRef]
- Mu, Q.; Zhao, M.; Running, S.W. Improvements to a MODIS Global Terrestrial Evapotranspiration Algorithm. Remote Sens. Environ. 2011, 115, 1781–1800. [Google Scholar] [CrossRef]
- Chen, X.; Yu, S.; Zhang, H.; Li, F.; Liang, C.; Wang, Z. Estimating the Actual Evapotranspiration Using Remote Sensing and SEBAL Model in an Arid Environment of Northwest China. Water 2023, 15, 1555. [Google Scholar] [CrossRef]
- Funk, C.; Pete, P.; Martin, L.; Diego, P.; James, V.; Shraddhanand, S.; Gregory, H.; James, R.; Laura, H.; Andrew, H.; et al. The climate hazards infrared precipitation with stations-a new environmental record for monitoring extremes. Sci. Data 2015, 2, 150066. [Google Scholar] [CrossRef]
- Javadnia, E.; Mobasheri, M.R.; Kamali, G.A. MODIS NDVI Quality Enhancement Using ASTER Images. J. Agric. Sci. Technol. 2009, 11, 549–558. [Google Scholar]
- Al-Doski, J.; Hassan, F.M.; Mossa, H.A.; Najim, A.A. Incorporation of Digital Elevation Model, Normalized Difference Vegetation Index, and Landsat-8 Data for Land Use Land Cover Mapping. Photogramm. Eng. Remote Sens. 2022, 88, 507–516. [Google Scholar] [CrossRef]
- Khan, M.S.; Baik, J.; Choi, M. A Physical-Based Two-Source Evapotranspiration Model with Monin–Obukhov Similarity Theory. GIScience Remote Sens. 2021, 58, 88–119. [Google Scholar] [CrossRef]
- Huang, C.; Li, Y.; Gu, J.; Lu, L.; Li, X. Improving Estimation of Evapotranspiration under Water-Limited Conditions Based on SEBS and MODIS Data in Arid Regions. Remote Sens. 2015, 7, 16795–16814. [Google Scholar] [CrossRef]
- Liu, C.; Cui, N.; Gong, D.; Hu, X.; Feng, Y. Evaluation of Seasonal Evapotranspiration of Winter Wheat in Humid Region of East China Using Large-Weighted Lysimeter and Three Models. J. Hydrol. 2020, 590, 125388. [Google Scholar] [CrossRef]
- Feng, J.; Wang, W.; Che, T.; Xu, F. Performance of the Improved Two-Source Energy Balance Model for Estimating Evapotranspiration over the Heterogeneous Surface. Agric. Water Manag. 2023, 278, 108159. [Google Scholar] [CrossRef]
- Wang, Y.; Li, X.; Tang, S. Validation of the SEBS-Derived Sensible Heat for FY3A/VIRR and TERRA/MODIS over an Alpine Grass Region Using LAS Measurements. Int. J. Appl. Earth Obs. Geoinf. 2013, 23, 226–233. [Google Scholar] [CrossRef]
- Rihan, W.; Zhao, J.; Zhang, H.; Guo, X. Preseason Drought Controls on Patterns of Spring Phenology in Grasslands of the Mongolian Plateau. Sci. Total Environ. 2022, 838, 156018. [Google Scholar] [CrossRef]
- Mohammadian, M.; Arfania, R.; Sahour, H. Evaluation of SEBS Algorithm for Estimation of Daily Evapotranspiration Using Landsat-8 Dataset in a Semi-Arid Region of Central Iran. Open J. Geol. 2017, 7, 335–347. [Google Scholar] [CrossRef]
- Jahangir, M.; Arast, M. Remote sensing products for predicting actual evapotranspiration and water stress footprints under different land cover. J. Clean. Prod. 2020, 266, 121818. [Google Scholar] [CrossRef]
- Li, G.; Jing, Y.; Wu, Y.; Zhang, F. Improvement of Two Evapotranspiration Estimation Models Using a Linear Spectral Mixture Model over a Small Agricultural Watershed. Water 2018, 10, 474. [Google Scholar] [CrossRef]
- Wang, Y.; You, C.; Gao, Y.; Li, Y.; Niu, Y.; Shao, C.; Wang, X.; Xin, X.; Yu, G.; Han, X.; et al. Seasonal Variations and Drivers of Energy Fluxes and Partitioning along an Aridity Gradient in Temperate Grasslands of Northern China. Agric. For. Meteorol. 2023, 342, 109736. [Google Scholar] [CrossRef]
- Xu, X.; Li, X.; He, C.; Tian, W.; Tian, J. Development of a simple Budyko-based framework for the simulation and attribution of ET variability in dry regions. J. Hydrol. 2022, 610, 127955. [Google Scholar] [CrossRef]
- Zou, H.; Gao, G.; Fu, B. The relationship between grassland ecosystem and soil water in arid and semiarid areas: A review. Acta Ecol. Sin. 2016, 36, 3127–3136. [Google Scholar] [CrossRef]
Date | Measured ET (mm/day) | SEBS Model ET (mm/day) | MOD16A2 ET (mm/day) | Residual Error of SEBS (mm/day) | Relative Error of SEBS |
---|---|---|---|---|---|
05 JAN | 1.86 | 1.99 | 2.09 | 0.13 | 6.99% |
10 FEB | 2.37 | 2.56 | 2.89 | 0.19 | 8.02% |
06 MAR | 2.91 | 2.88 | 3.13 | 0.03 | 1.05% |
30 APR | 4.27 | 4.75 | 4.93 | 0.48 | 11.24% |
09 MAY | 4.15 | 4.77 | 4.62 | 0.62 | 14.94% |
26 JUN | 5.03 | 4.92 | 5.21 | −0.11 | −2.19% |
03 JUL | 6.59 | 6.40 | 6.94 | −0.19 | −2.88% |
21 AUG | 8.10 | 8.21 | 8.40 | 0.11 | 1.36% |
14 SEP | 6.11 | 6.02 | 5.93 | −0.09 | −1.47% |
07 OCT | 3.14 | 2.99 | 3.22 | −0.15 | −4.78% |
17 NOV | 2.39 | 2.70 | 3.07 | 0.31 | 12.97% |
03 DEC | 1.72 | 1.83 | 1.94 | 0.11 | 6.40% |
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Feng, Y.; Wang, L.; Liu, C.; Zhang, B.; Wang, J.; Zhang, P.; Wang, R. Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS. Hydrology 2025, 12, 205. https://doi.org/10.3390/hydrology12080205
Feng Y, Wang L, Liu C, Zhang B, Wang J, Zhang P, Wang R. Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS. Hydrology. 2025; 12(8):205. https://doi.org/10.3390/hydrology12080205
Chicago/Turabian StyleFeng, Yanlin, Lixia Wang, Chunwei Liu, Baozhong Zhang, Jun Wang, Pei Zhang, and Ranghui Wang. 2025. "Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS" Hydrology 12, no. 8: 205. https://doi.org/10.3390/hydrology12080205
APA StyleFeng, Y., Wang, L., Liu, C., Zhang, B., Wang, J., Zhang, P., & Wang, R. (2025). Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS. Hydrology, 12(8), 205. https://doi.org/10.3390/hydrology12080205