A physical-based two-source evapotranspiration model with Monin–Obukhov similarity theory

References

• Alfieri, J. G., W. P. Kustas, J. H. Prueger, L. E. Hipps, S. R. Evett, J. B. Basara, C. M. U. Neale, et al. 2012. “On the Discrepancy between Eddy Covariance and Lysimetry-based Surface Flux Measurements under Strongly Advective Conditions.” Advances in Water Resources 50 :62–78. doi:10.1016/j.advwatres.2012.07.008.
   Web of Science ®Google Scholar
• Alkhaier, F., Z. Su, and G. N. Flerchinger. 2012. “Reconnoitering the Effect of Shallow Groundwater on Land Surface Temperature and Surface Energy Balance Using MODIS and SEBS.” Hydrology and Earth System Sciences 16 (7): 1833–1844. doi:10.5194/hess-16-1833-2012.
   Web of Science ®Google Scholar
• Allen, R. 1996. “Assessing Integrity of Weather Data for Reference Evapotranspiration Estimation.” Journal of Irrigation and Drainage Engineering 122 (2): 2. doi:10.1061/(ASCE)0733-9437(1996)122:2(97).
   Web of Science ®Google Scholar
• Allen, R., A. Irmak, R. Trezza, J. M. H. Hendrickx, W. Bastiaanssen, and J. Kjaersgaard. 2011. “Satellite-based ET Estimation in Agriculture Using SEBAL and METRIC.” Hydrological Processes 25 (26): 4011–4027. doi:10.1002/hyp.8408.
   Web of Science ®Google Scholar
• Allen, R., M. Tasumi, and R. Trezza. 2007. “Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (Metric)—model.” Journal of Irrigation and Drainage Engineering 133 (4): 380–394. doi:10.1061/(ASCE)0733-9437(2007)133:4(380).
   Web of Science ®Google Scholar
• Anderson, M. C. 1997. “A Two-Source Time-Integrated Model for Estimating Surface Fluxes Using Thermal Infrared Remote Sensing.” Remote Sensing of Environment 60 (2): 195–216. doi:10.1016/S0034-4257(96)00215-5.
   Web of Science ®Google Scholar
• Arnqvist, J., and H. Bergström. 2015. “Flux-profile Relation with Roughness Sublayer Correction.” Quarterly Journal of the Royal Meteorological Society 141 (689): 1191–1197. doi:10.1002/qj.2426.
   Web of Science ®Google Scholar
• Badgley, G., J. B. Fisher, C. Jiménez, K. P. Tu, and R. Vinukollu. 2015. “On Uncertainty in Global Terrestrial Evapotranspiration Estimates from Choice of Input Forcing Datasets.” Journal of Hydrometeorology 16 (4): 1449–1455. doi:10.1175/jhm-d-14-0040.1.
   Web of Science ®Google Scholar
• Bai, J., L. I. Jia, S. Liu, Z. Xu, G. Hu, M. Zhu, L. Song, et al. 2015. “Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes.” IEEE Geoscience and Remote Sensing Letters 12 (5): 943–947. doi:10.1109/lgrs.2014.2368580.
   Web of Science ®Google Scholar
• Bai, Y., X. Li, S. Zhou, X. Yang, K. Yu, M. Wang, S. Liu, et al. 2019. “Quantifying Plant Transpiration and Canopy Conductance Using Eddy Flux Data: An Underlying Water Use Efficiency Method.” Agricultural and Forest Meteorology 271 :375–384. doi:10.1016/j.agrformet.2019.02.035.
   Web of Science ®Google Scholar
• Bastiaanssen, W. G. M., M. Menenti, R. A. Feddes, and A. A. M. Holtslag. 1998. “A Remote Sensing Surface Energy Balance Algorithm for Land (SEBAL). 1. Formulation.” Formulation. Journal of Hydrology 212-213: 198–212. doi:10.1016/S0022-1694(98)00253-4.
   Web of Science ®Google Scholar
• Bhattarai, N., S. B. Shaw, L. J. Quackenbush, J. Im, and R. Niraula. 2016. “Evaluating Five Remote Sensing-Based Single-source Surface Energy Balance Models for Estimating Daily Evapotranspiration in a Humid Subtropical Climate.” International Journal of Applied Earth Observation and Geoinformation 49: 75–86. doi:10.1016/j.jag.2016.01.010.
   Web of Science ®Google Scholar
• Bisquert, M., J. M. Sánchez, R. López-Urrea, and V. Caselles. 2016. “Estimating High Resolution Evapotranspiration from Disaggregated Thermal Images.” Remote Sensing of Environment 187: 423–433. doi:10.1016/j.rse.2016.10.049.
   Web of Science ®Google Scholar
• Brutsaert, W. 1999. “Aspects of Bulk Atmospheric Boundary Layer Similarity under Free-convective Conditions.” Reviews of Geophysics 37 (4): 439–451. doi:10.1029/1999rg900013.
   Web of Science ®Google Scholar
• Brutsaert, W. 2005. Hydrology: An Introduction. New York, NY: Cambridge University Press. ISBN: 9780521824798 doi.10.1017/CBO9780511808470.
   Google Scholar
• Burchard- Levine, Vicente, Héctor Nieto, David Riaño, Mirco Migliavacca, Tarek S. El-Madany, Oscar Perez-Priego, Arnaud Carrara, and M. Pilar Martín. 2019. “Adapting the thermal-based two-source energy balance model to estimate energy fluxes in a complex tree-grass ecosystem..” Hydrology and Earth System Sciences Discussions org/10.5194/hess-2019-354.
   Google Scholar
• Byun, K., U. W. Liaqat, and M. Choi. 2014. “Dual-model Approaches for Evapotranspiration Analyses over Homo- and Heterogeneous Land Surface Conditions.” Agricultural and Forest Meteorology 197: 169–187. doi:10.1016/j.agrformet.2014.07.001.
   Web of Science ®Google Scholar
• Cammalleri, C., G. Rallo, C. Agnese, G. Ciraolo, M. Minacapilli, and G. Provenzano. 2013. “Combined Use of Eddy Covariance and Sap Flow Techniques for Partition of ET Fluxes and Water Stress Assessment in an Irrigated Olive Orchard.” Agricultural Water Management 120 :89–97. doi:10.1016/j.agwat.2012.10.003.
   Web of Science ®Google Scholar
• Chen, J. M., and J. Liu. 2020. “Evolution of Evapotranspiration Models Using Thermal and Shortwave Remote Sensing Data.” Remote Sensing of Environment 237: 111594. doi:10.1016/j.rse.2019.111594.
   PubMed Web of Science ®Google Scholar
• Chen, X., Z. Su, Y. Ma, and E. M. Middleton. 2019. “Optimization of a Remote Sensing Energy Balance Method over Different Canopy Applied at Global Scale.” Agricultural and Forest Meteorology 279: 107633. doi:10.1016/j.agrformet.2019.107633.
   Web of Science ®Google Scholar
• Chen, X., Z. Su, Y. Ma, K. Yang, J. Wen, and Y. Zhang. 2013. “An Improvement of Roughness Height Parameterization of the Surface Energy Balance System (SEBS) over the Tibetan Plateau.” Journal of Applied Meteorology and Climatology 52 (3): 607–622. doi:10.1175/jamc-d-12-056.1.
   Web of Science ®Google Scholar
• Chen, X., Z. Su, Y. Ma, S. Liu, Q. Yu, and Z. Xu. 2014. “Development of a 10-year (2001–2010) 0.1° Data Set of Land-surface Energy Balance for Mainland China.” Atmospheric Chemistry and Physics 14 (23): 13097–13117. doi:10.5194/acp-14-13097-2014.
   Web of Science ®Google Scholar
• Cook, D. R., and R. C. Sullivan, 2019. “Energy Balance Bowen Ratio (EBBR) Instrument Handbook”. United States. USDOE Office of Environmental Management. In: Energy, U.D.o. (Ed.). DOI:10.2172/1020562
   Google Scholar
• Crago, R., and W. Brutsaert. 1996. “Daytime Evaporation and the Self-preservation of the Evaporative Fraction and the Bowen Ratio.” Journal of Hydrology 178 (1–4): 241–255. doi:10.1016/0022-1694(95)02803-X.
   Web of Science ®Google Scholar
• Deguchi, A., S. Hattori, and H.-T. Park. 2006. “The Influence of Seasonal Changes in Canopy Structure on Interception Loss: Application of the Revised Gash Model.” Journal of Hydrology 318 (1–4): 80–102. doi:10.1016/j.jhydrol.2005.06.005.
   Web of Science ®Google Scholar
• Ershadi, A., M. McCabe, J. P. Evans, and J. P. Walker. 2013. “Effects of Spatial Aggregation on the Multi-scale Estimation of Evapotranspiration.” Remote Sensing of Environment 131: 51–62. doi:10.1016/j.rse.2012.12.007.
   Web of Science ®Google Scholar
• Farah, H. O., W. G. M. Bastiaanssen, and R. A. Feddes. 2004. “Evaluation of the Temporal Variability of the Evaporative Fraction in a Tropical Watershed.” International Journal of Applied Earth Observation and Geoinformation 5 (2): 129–140. doi:10.1016/j.jag.2004.01.003.
   Google Scholar
• Fisher, J. B., F. Melton, E. Middleton, C. Hain, M. Anderson, R. Allen, M. F. McCabe, et al. 2017. “The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources.” Water Resources Research 53 (4): 2618–2626. doi:10.1002/2016WR020175.
   Web of Science ®Google Scholar
• Gibson, L., Z. Munch, and J. Engelbrecht. 2011. “Particular Uncertainties Encountered in Using a Pre-packaged SEBS Model to Derive Evapotranspiration in a Heterogeneous Study Area in South Africa.” Hydrology and Earth System Sciences 15 (1): 295–310. doi:10.5194/hess-15-295-2011.
   Web of Science ®Google Scholar
• Gokmen, M., Z. Vekerdy, A. Verhoef, W. Verhoef, O. Batelaan, and C. van der Tol. 2012. “Integration of Soil Moisture in SEBS for Improving Evapotranspiration Estimation under Water Stress Conditions.” Remote Sensing of Environment 121 :261–274. doi:10.1016/j.rse.2012.02.003.
   Web of Science ®Google Scholar
• Gowda, P. H., J. L. Chavez, P. D. Colaizzi, S. R. Evett, T. A. Howell, and J. A. Tolk. 2008. “ET Mapping for Agricultural Water Management: Present Status and Challenges.” Irrigation Science 26 (3): 223–237. doi:10.1007/s00271-007-0088-6.
   Web of Science ®Google Scholar
• Gowda, P. H., T. A. Howell, G. Paul, P. D. Colaizzi, T. H. Marek, B. Su, K. S. Copeland et al. 2013. “Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation.” Vadose Zone Journal 12 (3): 3. DOI:10.2136/vzj2012.0110.
   Web of Science ®Google Scholar
• Hess, A., B. Wadzuk, and A. Welker. 2017. “Evapotranspiration in Rain Gardens Using Weighing Lysimeters.” Journal of Irrigation and Drainage Engineering 143 (6): 04017004. doi:10.1061/(ASCE)IR.1943-4774.0001157.
   Web of Science ®Google Scholar
• Hsieh, C.-I., G. Katul, and T.-W. Chi. 2000. “An Approximate Analytical Model for Footprint Estimation of Scalar fluxes in Thermally stratified Atmospheric flows.” Advances in Water Resources 23 (7): 765–772. doi:10.1016/S0309-1708(99)00042-1.
   Web of Science ®Google Scholar
• Hssaine, B. A., O. Merlin, Z. Rafi, J. Ezzahar, L. Jarlan, S. Khabba, S. Er-Raki, et al. 2018. “Calibrating an Evapotranspiration Model Using Radiometric Surface Temperature, Vegetation Cover Fraction and Near-surface Soil Moisture Data.” Agricultural and Forest Meteorology 256-257 :104–115. doi:10.1016/j.agrformet.2018.02.033.
   Web of Science ®Google Scholar
• Huang, C., Y. Li, J. Gu, L. Lu, and X. Li. 2015. “Improving Estimation of Evapotranspiration under Water-Limited Conditions Based on SEBS and MODIS Data in Arid Regions.” Remote Sensing 7 (12): 16795–16814. doi:10.3390/rs71215854.
   Web of Science ®Google Scholar
• Janssen, T., K. Fleischer, S. Luyssaert, K. Naudts, and H. Dolman. 2020. “Drought Resistance Increases from the Individual to the Ecosystem Level in Highly Diverse Neotropical Rainforest: A Meta-analysis of Leaf, Tree and Ecosystem Responses to Drought.” Biogeosciences 17 (9): 2621–2645. doi:10.5194/bg-17-2621-2020.
   Web of Science ®Google Scholar
• Jia, L., G. Xi, S. Liu, C. Huang, Y. Yan, and G. Liu. 2009. “Regional Estimation of Daily to Annual Regional Evapotranspiration with MODIS Data in the Yellow River Delta Wetland.” Hydrology and Earth System Sciences 13 (10): 1775–1787. DOI:10.5194/hess-13-1775-2009.
   Web of Science ®Google Scholar
• Jia, Z., S. Liu, Z. Xu, Y. Chen, and M. Zhu. 2012. “Validation of Remotely Sensed Evapotranspiration over the Hai River Basin, China”. Journal of Geophysical Research: Atmospheres 117(D13). (D13):n/a-n/a. doi:10.1029/2011jd017037.
   Google Scholar
• Jung, M., M. Reichstein, P. Ciais, S. I. Seneviratne, J. Sheffield, M. L. Goulden, G. Bonan, et al. 2010. “Recent Decline in the Global Land Evapotranspiration Trend Due to Limited Moisture Supply.” Nature 467 (7318): 951–954. doi:10.1038/nature09396.
   PubMed Web of Science ®Google Scholar
• Khan, M. S., U. W. Liaqat, J. Baik, M. Choi. 2018. “Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach..”Agricultural and Forest Meteorology 252 : 256–268.org/10.1016/j.agrformet.2018.01.022.
   Web of Science ®Google Scholar
• Khan, M. S., Baik M. Choi. 2020. Inter-comparison of evapotranspiration datasets over heterogeneous landscapes across Australia.“Advances in Space Research” 66 no. 3: 533–545. org/10.1016/j.asr.2020.04.037.
   Web of Science ®Google Scholar
• Konings, A. G., A. P. Williams, and P. Gentine. 2017. “Sensitivity of Grassland Productivity to Aridity Controlled by Stomatal and Xylem Regulation.” Nature Geoscience 10 (4): 284–288. doi:10.1038/ngeo2903.
   Web of Science ®Google Scholar
• Kool, D., N. Agam, N. Lazarovitch, J. L. Heitman, T. J. Sauer, and A. Ben-Gal. 2014. “A Review of Approaches for Evapotranspiration Partitioning.” Agricultural and Forest Meteorology 184 :56–70. doi:10.1016/j.agrformet.2013.09.003.
   Web of Science ®Google Scholar
• Kurc, S. A., and E. E. Small. 2004. “Dynamics of Evapotranspiration in Semiarid Grassland and Shrubland Ecosystems during the Summer Monsoon Season, Central New Mexico.” Water Resources Research 40 (9): 9. doi:10.1029/2004wr003068.
   Web of Science ®Google Scholar
• Kustas, W. P., C. S. T. Daughtry, and P. J. V. Oevelen. 1993. “Analytical Treatment of the Relationships between Soil Heat Flux/Net Radiation Ratio and Vegetation Indices.” Remote Sensing of Environment 46 (3): 319–330. 10.1016/0034-4257(93)90052-Y
   Web of Science ®Google Scholar
• Kustas, W. P., and C. S. T. Daughtry. 1990. “Estimation of the Soil Heat Flux/net Radiation Ratio from Spectral Data.” Agricultural and Forest Meteorology 49 (3): 205–223. doi:10.1016/0168-1923(90)90033-3.
   Web of Science ®Google Scholar
• Kustas, W. P., and J. M. Norman. 1999a. “Evaluation of Soil and Vegetation Heat Flux Predictions Using a Simple Two-source Model with Radiometric Temperatures for Partial Canopy Cover.” Agricultural and Forest Meteorology 94: 13–29. doi.org/10.1016/S0168-1923(99)00005-2.
   Google Scholar
• Kustas, W. P., and J. M. Norman. 1999b. “Reply to Comments about the Basic Equations of Dual-source Vegetation–atmosphere Transfer Models.” Agricultural and Forest Meteorology 94 (3–4): 275–278. doi:10.1016/S0168-1923(99)00012-X.
   Web of Science ®Google Scholar
• Kustas, W. P., K. S. Humes, J. M. Norman, and M. S. Moran. 1996. “Single- and Dual-Source Modeling of Surface Energy Fluxes with Radiometric Surface Temperature.” Journal of Applied Meteorology 35 (1): 110–121. doi:10.1175/1520-0450(1996)035<0110:SADSMO>2.0.CO;2.
   Google Scholar
• Kwon, H., J.-H. Lee, Y.-K. Lee, J.-W. Lee, S.-W. Jung, and J. Kim. 2009. “Seasonal Variations of Evapotranspiration Observed in a Mixed Forest in the Seolmacheon Catchment.” Korean Journal of Agricultural and Forest Meteorology 11 (1): 39–47. doi:10.5532/KJAFM.2009.11.1.039.
   Google Scholar
• Lang, D., J. Zheng, J. Shi, F. Liao, X. Ma, W. Wang, X. Chen, et al. 2017. “A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China.” Water 9 (10): 10. doi:10.3390/w9100734.
   Web of Science ®Google Scholar
• Lee, D., J. Kim, K.-S. Lee, and S. Kim. 2010. “Partitioning of Catchment Water Budget and Its Implications for Ecosystem Carbon Exchange.” Biogeosciences 7 (6): 1903–1914. doi:10.5194/bg-7-1903-2010.
   Web of Science ®Google Scholar
• Legates, D. R., and G. J. McCabe. 1999. “Evaluating the Use of “Goodness-of-fit” Measures in Hydrologic and Hydroclimatic Model Validation.” Water Resources Research 35 (1): 233–241. doi:10.1029/1998wr900018.
   Web of Science ®Google Scholar
• Li, F., W. P. Kustas, J. H. Prueger, C. M. U. Neale, and T. J. Jackson. 2005. “Utility of Remote Sensing–Based Two-Source Energy Balance Model under Low- and High-Vegetation Cover Conditions.” Journal of Hydrometeorology 6: 878–891. doi.org/10.1175/JHM464.1.
   Web of Science ®Google Scholar
• Li, X., P. Gentine, C. Lin, S. Zhou, Z. Sun, Y. Zheng, J. Liu, et al. 2019. “A Simple and Objective Method to Partition Evapotranspiration into Transpiration and Evaporation at Eddy-covariance Sites.” Agricultural and Forest Meteorology 265 :171–182. doi:10.1016/j.agrformet.2018.11.017.
   Web of Science ®Google Scholar
• Li, Y., C. Huang, J. Hou, J. Gu, G. Zhu, and X. Li. 2017. “Mapping Daily Evapotranspiration Based on Spatiotemporal Fusion of ASTER and MODIS Images over Irrigated Agricultural Areas in the Heihe River Basin, Northwest China.” Agricultural and Forest Meteorology 244-245 :82–97. doi:10.1016/j.agrformet.2017.05.023.
   Web of Science ®Google Scholar
• Li, Y., J. Zhou, H. Wang, D. Li, R. Jin, Y. Zhou, Q. Zhou, et al. 2015. “Integrating Soil Moisture Retrieved from L-band Microwave Radiation into an Energy Balance Model to Improve Evapotranspiration Estimation on the Irrigated Oases of Arid Regions in Northwest China.” Agricultural and Forest Meteorology 214-215 :306–318. doi:10.1016/j.agrformet.2015.08.260.
   Web of Science ®Google Scholar
• Liaqat, U. W., and M. Choi. 2015. “Surface Energy Fluxes in the Northeast Asia Ecosystem: SEBS and METRIC Models Using Landsat Satellite Images.” Agricultural and Forest Meteorology 214-215: 60–79. doi:10.1016/j.agrformet.2015.08.245.
   Web of Science ®Google Scholar
• Liaqat, U. W., and M. Choi. 2017. “Accuracy Comparison of Remotely Sensed Evapotranspiration Products and Their Associated Water Stress Footprints under Different Land Cover Types in Korean Peninsula.” Journal of Cleaner Production 155: 93–104. doi:10.1016/j.jclepro.2016.09.022.
   Web of Science ®Google Scholar
• Long, D., and V. P. Singh. 2012a. “A Modified Surface Energy Balance Algorithm for Land (M-SEBAL) Based on A Trapezoidal Framework.” Water Resources Research 48 (2): 2. doi:10.1029/2011wr010607.
   Google Scholar
• Long, D., and V. P. Singh. 2012b. “A Two-source Trapezoid Model for Evapotranspiration (TTME) from Satellite Imagery.” Remote Sensing of Environment 121: 370–388. doi:10.1016/j.rse.2012.02.015.
   Web of Science ®Google Scholar
• Lu, J., Z.-L. Li, R. Tang, B.-H. Tang, H. Wu, F. Yang, J. Labed, et al. 2012. “Evaluating the SEBS-estimated Evaporative Fraction from MODIS Data for a Complex Underlying Surface.” Hydrological Processes: N/a-n/a. doi:10.1002/hyp.9440.
   Web of Science ®Google Scholar
• Ma, W., Z. Wei, P. Wang, and J. Asanuma. 2020. “Transpiration and Evaporation of Grassland Using Land Surface modelling.” Hydrological Processes 34 (17): 3656–3668. doi:10.1002/hyp.13792.
   Web of Science ®Google Scholar
• Ma, Y., S. Liu, L. Song, Z. Xu, Y. Liu, T. Xu, Z. Zhu, et al. 2018. “Estimation of Daily Evapotranspiration and Irrigation Water Efficiency at a Landsat-like Scale for an Arid Irrigation Area Using Multi-source Remote Sensing Data.” Remote Sensing of Environment 216 :715–734. doi:10.1016/j.rse.2018.07.019.
   Web of Science ®Google Scholar
• Marshall, M., P. Thenkabail, T. Biggs, and K. Post. 2016. “Hyperspectral Narrowband and Multispectral Broadband Indices for Remote Sensing of Crop Evapotranspiration and Its Components (Transpiration and Soil Evaporation).” Agricultural and Forest Meteorology 218-219: 122–134. doi:10.1016/j.agrformet.2015.12.025.
   Web of Science ®Google Scholar
• Massman, W. J. 1996. “An Analytical One-Dimensional Model of Momentum Transfer by Vegetation of Arbitrary Structure.” Boundary-Layer Meteorology 83 (3): 407–421. doi:10.1023/A:1000234813011.
   Web of Science ®Google Scholar
• Massman, W. J., J. M. Forthofer, and M. A. Finney. 2017. “An Improved Canopy Wind Model for Predicting Wind Adjustment Factors and Wildland Fire Behavior.” Canadian Journal of Forest Research 47 (5): 594–603. doi:10.1139/cjfr-2016-0354.
   Google Scholar
• Mastrotheodoros, T., C. Pappas, P. Molnar, P. Burlando, T. F. Keenan, P. Gentine, C. M. Gough, and S. Fatichi. 2017. “Linking Plant Functional Trait Plasticity and the Large Increase in Forest Water Use Efficiency.” Journal of Geophysical Research: Biogeosciences 122 (9): 2393–2408. doi:10.1002/2017jg003890.
   Web of Science ®Google Scholar
• Mecikalski, J. R., G. R. Diak, M. C. Anderson, and J. M. Norman. 1999. “Estimating Fluxes on Continental Scales Using Remotely Sensed Data in an Atmospheric–Land Exchange Model.” Journal of Applied Meteorology 38 (9): 1352–1369. doi:10.1175/1520-0450(1999)038<1352:EFOCSU>2.0.CO;2.
   Google Scholar
• Michel, D., C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens et al. 2016. “The WACMOS-ET Project – Part 1: Tower-scale Evaluation of Four Remote-sensing-based Evapotranspiration Algorithms.” Hydrology and Earth System Sciences 20 (2): 803–822. DOI:10.5194/hess-20-803-2016.
   Web of Science ®Google Scholar
• Miralles, D. G., C. Jiménez, M. Jung, D. Michel, A. Ershadi, M. F. McCabe, M. Hirschi et al. 2016. “The WACMOS-ET project – Part 2: Evaluation of Global Terrestrial Evaporation Data Sets.” Hydrology and Earth System Sciences 20 (2): 823–842. DOI:10.5194/hess-20-823-2016.
   Web of Science ®Google Scholar
• Miralles, D. G., P. Gentine, S. I. Seneviratne, and A. J. Teuling. 2019. “Land-atmospheric Feedbacks during Droughts and Heatwaves: State of the Science and Current Challenges.” Annals of the New York Academy of Sciences 1436 (1): 19. doi:10.1111/nyas.13912.
   PubMed Web of Science ®Google Scholar
• Miralles, D. G., T. R. H. Holmes, R. A. M. De Jeu, J. H. Gash, A. G. C. A. Meesters, and A. J. Dolman. 2011. “Global Land-surface Evaporation Estimated from Satellite-based Observations.” Hydrology and Earth System Sciences 15 (2): 453–469. doi:10.5194/hess-15-453-2011.
   Web of Science ®Google Scholar
• Monin, A. S., and A. M. L. Obukhov. 1954. “Basic Laws of Turbulent Mixing in the Surface Layer of the Atmosphere.” Contrib. Geophys. Inst. Acad. Sci. USSR 151 (163): e187.
   Google Scholar
• Montoro, A., F. Mañas, and R. López-Urrea. 2016. “Transpiration and Evaporation of Grapevine, Two Components Related to Irrigation Strategy.” Agricultural Water Management 177: 193–200. doi:10.1016/j.agwat.2016.07.005.
   Web of Science ®Google Scholar
• Mu, Q., M. Zhao, and S. Running. 2011. “MODIS Global Evapotranspiration Project (MOD16)”. NASA/EOS
   Google Scholar
• Norman, J. M., W. P. Kustas, J. H. Prueger, and G. R. Diak. 2000. “Surface Flux Estimation Using Radiometric Temperature: A Dual-temperature-difference Method to Minimize Measurement Errors.” Water Resources Research 36 (8): 2263–2274. doi:10.1029/2000wr900033.
   Web of Science ®Google Scholar
• Norman, J. M., W. P. Kustas, and K. S. Humes. 1995. “Source Approach for Estimating Soil and Vegetation Energy Fluxes in Observations of Directional Radiometric Surface Temperature.” Agricultural and Forest Meteorology 77 (3–4): 263–293. doi:10.1016/0168-1923(95)02265-Y.
   Web of Science ®Google Scholar
• Pradhan, R., N. Singh, and R. P. Singh. 2019. “Onset of Summer Monsoon in Northeast India Is Preceded by Enhanced Transpiration.” Scientific Reports 9 (1): 18646. doi:10.1038/s41598-019-55186-8.
   PubMedGoogle Scholar
• Purdy, A. J., J. B. Fisher, M. L. Goulden, and J. S. Famiglietti. 2016. “Ground Heat Flux: An Analytical Review of 6 Models Evaluated at 88 Sites and Globally.” Journal of Geophysical Research: Biogeosciences 121 (12): 3045–3059. doi:10.1002/2016jg003591.
   Web of Science ®Google Scholar
• Qin, Z., A. Karnieli, and P. Berliner. 2001. “A Mono-window Algorithm for Retrieving Land Surface Temperature from Landsat TM Data and Its Application to the Israel-Egypt Border Region.” International Journal of Remote Sensing 22 (18): 3719–3746. doi:10.1080/01431160010006971.
   Web of Science ®Google Scholar
• Rahman, M. M., and W. Zhang. 2019. “Validation of Satellite-Derived Sensible Heat Flux for TERRA/MODIS Images over Three Different Landscapes Using Large Aperture Scintillometer and Eddy Covariance Measurements.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12 (9): 3327–3337. doi:10.1109/jstars.2019.2928880.
   Web of Science ®Google Scholar
• Rigden, A. J., and G. D. Salvucci. 2017. “Stomatal Response to Humidity and CO 2 Implicated in Recent Decline in US Evaporation.” Global Change Biology 23 (3): 1140–1151. doi:10.1111/gcb.13439.
   PubMed Web of Science ®Google Scholar
• Sánchez, J. M., W. P. Kustas, V. Caselles, and M. C. Anderson. 2008. “Modelling Surface Energy Fluxes over Maize Using a Two-source Patch Model and Radiometric Soil and Canopy Temperature Observations.” Remote Sensing of Environment 112 (3): 1130–1143. doi:10.1016/j.rse.2007.07.018.
   Web of Science ®Google Scholar
• Song, L., Z. Bian, W. P. Kustas, S. Liu, Q. Xiao, H. Nieto, Z. Xu, et al. 2020. “Estimation of Surface Heat Fluxes Using Multi-angular Observations of Radiative Surface Temperature.” Remote Sensing of Environment 239 :111674. doi:10.1016/j.rse.2020.111674.
   Web of Science ®Google Scholar
• Su, Z. 2002. “The Surface Energy Balance System (SEBS) for Estimation of Turbulent Heat Fluxes.” Hydrology and Earth System Sciences 6 (1): 85–99. doi:10.5194/hess-6-85-2002.
   Web of Science ®Google Scholar
• Su, Z. B. 2001. A Surface Energy Balance System (SEBS) for Estimation of Turbulent Heat Fluxes from Point to Continental Scale. Spectra Workshop. Publications of the National Remote Sensing Board (BCRS), USP-2: 01-02.
   Google Scholar
• Talsma, C. J., S. P. Good, C. Jimenez, B. Martens, J. B. Fisher, D. G. Miralles, M. F. McCabe, et al. 2018. “Partitioning of Evapotranspiration in Remote Sensing-based Models.” Agricultural and Forest Meteorology 260-261 :131–143. doi:10.1016/j.agrformet.2018.05.010.
   Web of Science ®Google Scholar
• Tasumi, M., R. Allen, and R. Trezza. 2008. “At-Surface Reflectance and Albedo from Satellite for Operational Calculation of Land Surface Energy Balance.” Journal of Hydrologic Engineering 13 (2): 51–63. doi:10.1061/(ASCE)1084-0699(2008)13:2(51).
   Web of Science ®Google Scholar
• Taylor, G. I., 1938. “The Spectrum of Turbulence”. Proceedings of the Royal Society of London. Series A-Mathematical and Physical Sciences, 164( 919): 476–490.
   Google Scholar
• Taylor, K. E. 2001. “Summarizing Multiple Aspects of Model Performance in a Single Diagram.” Journal of Geophysical Research: Atmospheres 106 (D7): 7183–7192. doi:10.1029/2000jd900719.
   Web of Science ®Google Scholar
• Tilahun, K. 2006. “Analysis of Rainfall Climate and Evapo-transpiration in Arid and Semi-arid Regions of Ethiopia Using Data over the Last Half a Century.” Journal of Arid Environments 64 (3): 474–487. doi:10.1016/j.jaridenv.2005.06.013.
   Web of Science ®Google Scholar
• Timmermans, J., Z. Su, C. V. D. Tol, A. Verhoef, and W. Verhoef. 2013. “Quantifying the Uncertainty in Estimates of Surface–atmosphere Fluxes through Joint Evaluation of the SEBS and SCOPE Models.” Hydrology and Earth System Sciences 17 (4): 1561–1573. doi:10.5194/hess-17-1561-2013.
   Web of Science ®Google Scholar
• Trezza, R., R. Allen, and M. Tasumi. 2013. “Estimation of Actual Evapotranspiration along the Middle Rio Grande of New Mexico Using MODIS and Landsat Imagery with the METRIC Model.” Remote Sensing 5 (10): 5397–5423. doi:10.3390/rs5105397.
   Web of Science ®Google Scholar
• Twine, T. E., W. P. Kustas, J. M. Norman, D. R. Cook, P. R. Houser, T. P. Meyers, J. H. Prueger et al. 2000. “Correcting Eddy-covariance Flux Underestimates over a Grassland.” Agricultural and Forest Meteorology 103 (3): 279–300. DOI:10.1016/S0168-1923(00)00123-4.
   Web of Science ®Google Scholar
• Wang, Y., X. Li, and S. Tang. 2013. “Validation of the SEBS-derived Sensible Heat for FY3A/VIRR and TERRA/MODIS over an Alpine Grass Region Using LAS Measurements.” International Journal of Applied Earth Observation and Geoinformation 23: 226–233. doi:10.1016/j.jag.2012.09.005.
   Web of Science ®Google Scholar
• Webster, E., D. Ramp, and R. T. Kingsford. 2017. “Incorporating an Iterative Energy Restraint for the Surface Energy Balance System (SEBS).” Remote Sensing of Environment 198: 267–285. doi:10.1016/j.rse.2017.06.012.
   Web of Science ®Google Scholar
• Xue, J., K. M. Bali, S. Light, T. Hessels, and I. Kisekka. 2020. “Evaluation of Remote Sensing-based Evapotranspiration Models against Surface Renewal in Almonds.” Tomatoes and Maize. Agricultural Water Management 238. doi:10.1016/j.agwat.2020.106228.
   Google Scholar
• Yang, X., B. Yong, L. Ren, Y. Zhang, and D. Long. 2017. “Multi-scale Validation of GLEAM Evapotranspiration Products over China via ChinaFLUX ET Measurements.” International Journal of Remote Sensing 38 (20): 5688–5709. doi:10.1080/01431161.2017.1346400.
   Web of Science ®Google Scholar
• Yang, Y., M. Anderson, F. Gao, C. Hain, A. Noormets, G. Sun, R. Wynne, V. Thomas, and L. Sun. 2018a. “Investigating Impacts of Drought and Disturbance on Evapotranspiration over a Forested Landscape in North Carolina, USA Using High Spatiotemporal Resolution Remotely Sensed Data.” Remote Sensing of Environment. doi:10.1016/j.rse.2018.12.017.
   Web of Science ®Google Scholar
• Yang, Y., H. Su, R. Zhang, J. Tian, and L. Li. 2015. “An Enhanced Two-source Evapotranspiration Model for Land (ETEML): Algorithm and Evaluation.” Remote Sensing of Environment 168: 54–65. doi:10.1016/j.rse.2015.06.020.
   Web of Science ®Google Scholar
• Yang, Y., J. Qiu, R. Zhang, S. Huang, S. Chen, H. Wang, J. Luo, et al. 2018b. “Intercomparison of Three Two-Source Energy Balance Models for Partitioning Evaporation and Transpiration in Semiarid Climates.” Remote Sensing 10 (7): 7. doi:10.3390/rs10071149.
   Web of Science ®Google Scholar
• Yang, Y., and S. Shang. 2013. “A Hybrid Dual-source Scheme and Trapezoid Framework-based Evapotranspiration Model (HTEM) Using Satellite Images: Algorithm and Model Test.” Journal of Geophysical Research: Atmospheres 118 (5): 2284–2300. doi:10.1002/jgrd.50259.
   Web of Science ®Google Scholar
• Yao, Y., S. Liang, J. Yu, J. Chen, S. Liu, Y. Lin, J.B. Fisher, T.R. McVicar, J. Cheng, K. Jia, and X. Zhang. 2017. “A Simple Temperature Domain Two-source Model for Estimating Agricultural Field Surface Energy Fluxes from Landsat Images.” Journal of Geophysical Research: Atmospheres 122 (10): 5211–5236. doi:10.1002/2016jd026370.
   Web of Science ®Google Scholar
• Yu, B., S. Shang, W. Zhu, P. Gentine, and Y. Cheng. 2019. “Mapping Daily Evapotranspiration over a Large Irrigation District from MODIS Data Using a Novel Hybrid Dual-source Coupling Model.” Agricultural and Forest Meteorology 276-277: 107612. doi:10.1016/j.agrformet.2019.06.011.
   Web of Science ®Google Scholar
• Zhang, S., H. Chen, Y. Fu, H. Niu, Y. Yang, and B. Zhanget. 2019. “Fractional Vegetation Cover Estimation of Different Vegetation Types in the Qaidam Basin.” Sustainability 11 :3. doi:10.3390/su11030864.
   Web of Science ®Google Scholar
• Zhao, J., X. Chen, J. Zhang, H. Zhao, and Y. Song. 2019. “Higher Temporal Evapotranspiration Estimation with Improved SEBS Model from Geostationary Meteorological Satellite Data.” Scientific Reports 9 (1): 14981. doi:10.1038/s41598-019-50724-w.
   PubMedGoogle Scholar
• Zhao, T., W. Zhang, Y. Zhang, Z. Liu, and X. Chen. 2020. “Significant Spatial Patterns from the GCM Seasonal Forecasts of Global Precipitation.” Hydrology and Earth System Sciences 24 (1): 1–16. doi:10.5194/hess-24-1-2020.
   Web of Science ®Google Scholar