1427 citations as recorded by crossref.

1. A framework of correcting the angular effect of land surface temperature on evapotranspiration estimation in single-source energy balance models Y. Jiang et al. https://doi.org/10.1016/j.rse.2022.113306
2. Introduction to the GEOBIA 2010 special issue: From pixels to geographic objects in remote sensing image analysis E. Addink et al. https://doi.org/10.1016/j.jag.2011.12.001
3. Optimal Land Use at Developing Communities C. Palencia-Aguilar https://doi.org/10.1016/j.proeng.2015.06.102
4. Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales Y. Ryu et al. https://doi.org/10.1029/2011GB004053
5. Assessing relative soil moisture with remote sensing data: theory, experimental validation, and application to drought monitoring over the North China Plain Z. Su et al. https://doi.org/10.1016/S1474-7065(03)00010-X
6. Investigating the influence of roughness length for heat transport (zoh) on the performance of SEBAL in semi-arid irrigated and dryland agricultural systems G. Paul et al. https://doi.org/10.1016/j.jhydrol.2013.11.040
7. Preface: Land Surface Processes and Interactions—From HCMM to Sentinel Missions and Beyond Z. Su et al. https://doi.org/10.3390/rs9080788
8. A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement L. Yu et al. https://doi.org/10.5194/essd-14-3673-2022
9. Numerical simulation of methane spreading in porous media after leaking from an underground pipe J. Wang et al. https://doi.org/10.1108/HFF-01-2020-0007
10. Mapping regional distribution of land surface heat fluxes on the southern side of the central Himalayas using TESEBS P. Amatya et al. https://doi.org/10.1007/s00704-015-1466-2
11. Quantifying energy and water fluxes in dry dune ecosystems of the Netherlands B. Voortman et al. https://doi.org/10.5194/hess-19-3787-2015
12. An optimized surface aerodynamic temperature approach to estimate maize sensible heat flux and evapotranspiration E. Costa-Filho et al. https://doi.org/10.1016/j.agrformet.2021.108683
13. Analysis of land-atmosphere interactions and their influence on the energy and water cycle over the Tibetan Plateau Y. Ma et al. https://doi.org/10.1080/10095020.2024.2372504
14. Assessing a scheme of spatial-temporal thermal remote-sensing sharpening for estimating regional evapotranspiration K. Liu et al. https://doi.org/10.1080/01431161.2018.1434326
15. Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India A. Bala et al. https://doi.org/10.1080/10106049.2015.1076062
16. Evapotranspiration Everywhere, All the Time: Towards a Unified View From Earth Observation J. Fisher et al. https://doi.org/10.1111/gcb.70898
17. Estimating Evapotranspiration in a Post-Fire Environment Using Remote Sensing and Machine Learning P. Poon & A. Kinoshita https://doi.org/10.3390/rs10111728
18. An Assessment of Using Remote Sensing-based Models to Estimate Ground Surface Soil Heat Flux on the Tibetan Plateau during the Freeze-thaw Process C. Yang et al. https://doi.org/10.3390/rs12030501
19. Normalized Difference Latent Heat Index for Remote Sensing of Land Surface Energy Fluxes Y. Liou et al. https://doi.org/10.1109/TGRS.2018.2866555
20. A Comprehensive Clear-Sky Database for the Development of Land Surface Temperature Algorithms S. Ermida & I. Trigo https://doi.org/10.3390/rs14102329
21. A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture G. Petropoulos et al. https://doi.org/10.1177/0309133309338997
22. A Copernicus-based evapotranspiration dataset at 100 m spatial resolution over four Mediterranean basins P. Bartkowiak et al. https://doi.org/10.5194/essd-16-4709-2024
23. Evapotranspiration Estimation Using Remote Sensing Technology Based on a SEBAL Model in the Upper Reaches of the Huaihe River Basin L. Tan et al. https://doi.org/10.3390/atmos12121599
24. An Interpretable Machine Learning Approach to Remote Sensing-Based Estimation of Hourly Agricultural Evapotranspiration in Drylands Q. Zhuang et al. https://doi.org/10.3390/agriculture15212193
25. Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates E. Delogu et al. https://doi.org/10.3390/rs10111806
26. Global assessment of how averaging over spatial heterogeneity in precipitation and potential evapotranspiration affects modeled evapotranspiration rates E. Rouholahnejad Freund et al. https://doi.org/10.5194/hess-24-1927-2020
27. Assessing Terrain Effect on Evapotranspiration Using the SEBAL Model in Mountainous Regions W. Fu et al. https://doi.org/10.1109/JSTARS.2025.3539822
28. Investigating the temporal and spatial variations of water consumption in Urmia Lake River Basin considering the climate and anthropogenic effects on the agriculture in the basin M. Taheri et al. https://doi.org/10.1016/j.agwat.2018.11.013
29. Warming Effort and Energy Budget Difference of Various Human Land Use Intensity: Case Study of Beijing, China S. Zhou et al. https://doi.org/10.3390/land9090280
30. Effects of land-use/cover change on hydrological processes using a GIS/RS-based integrated hydrological model: case study of the East River, China K. Wang et al. https://doi.org/10.1080/02626667.2014.949723
31. Uncertainty Quantification in Land Surface Hydrologic Modeling: Toward an Integrated Variational Data Assimilation Framework A. Abdolghafoorian & L. Farhadi https://doi.org/10.1109/JSTARS.2016.2553444
32. Quantifying Evapotranspiration and Environmental Factors in the Abandoned Saline Farmland Using Landsat Archives L. Zhao et al. https://doi.org/10.3390/land14020283
33. Urban evapotranspiration estimation based on anthropogenic activities and modified Penman-Monteith model J. Chen et al. https://doi.org/10.1016/j.jhydrol.2022.127879
34. Comparison of Two Satellite‐Based Evapotranspiration Models of the Nagqu River Basin of the Tibetan Plateau M. Zou et al. https://doi.org/10.1002/2017JD027965
35. Land Use Classification: A Surface Energy Balance and Vegetation Index Application to Map and Monitor Irrigated Lands M. Pun et al. https://doi.org/10.3390/rs9121256
36. Carbon–water coupling in California almond orchards: a multi-scale assessment of ecosystem water use efficiency using eddy covariance and remote sensing S. Peddinti & I. Kisekka https://doi.org/10.1016/j.scitotenv.2025.179914
37. Responses of field evapotranspiration to the changes of cropping pattern and groundwater depth in large irrigation district of Yellow River basin L. Bai et al. https://doi.org/10.1016/j.agwat.2017.03.028
38. Assessing the Spatial Pattern of Irrigation Demand under Climate Change in Arid Area L. Wang et al. https://doi.org/10.3390/ijgi9090506
39. Deriving scaling factors using a global hydrological model to restore GRACE total water storage changes for China's Yangtze River Basin D. Long et al. https://doi.org/10.1016/j.rse.2015.07.003
40. Evaluating the accuracy of satellite-derived evapotranspiration estimates acquired during conditions of water stress S. Gokool et al. https://doi.org/10.1080/01431161.2019.1646940
41. Integrated Modeling System for Water Resources Management of Tarim River Basin Y. Huang et al. https://doi.org/10.1089/ees.2009.0359
42. Regional analysis of evapotranspiration changes in an arid river basin using satellite observations X. Zhu et al. https://doi.org/10.1080/15324982.2020.1853279
43. A comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration M. Mahour et al. https://doi.org/10.1016/j.isprsjprs.2017.02.004
44. Feasibility of Using the Two-Source Energy Balance Model (TSEB) with Sentinel-2 and Sentinel-3 Images to Analyze the Spatio-Temporal Variability of Vine Water Status in a Vineyard J. Bellvert et al. https://doi.org/10.3390/rs12142299
45. Comparison of evapotranspiration estimated by ETWatch with that derived from combined GRACE and measured precipitation data in Hai River Basin, North China J. Moiwo et al. https://doi.org/10.1080/02626667.2011.553617
46. Estimations of Regional Surface Energy Fluxes Over Heterogeneous Oasis–Desert Surfaces in the Middle Reaches of the Heihe River During HiWATER-MUSOEXE . Yanfei Ma et al. https://doi.org/10.1109/LGRS.2014.2356652
47. Evapotranspiration Estimate over an Almond Orchard Using Landsat Satellite Observations R. He et al. https://doi.org/10.3390/rs9050436
48. Validation and downscaling of Advanced Scatterometer (ASCAT) soil moisture using ground measurements in the Western Cape, South Africa J. Moller et al. https://doi.org/10.1080/02571862.2017.1318962
49. Estimation of Land Surface Heat Fluxes over the Tibetan Plateau Using GMS Data Y. Oku et al. https://doi.org/10.1175/JAM2456.1
50. METRIC-GIS: An advanced energy balance model for computing crop evapotranspiration in a GIS environment J. Ramírez-Cuesta et al. https://doi.org/10.1016/j.envsoft.2020.104770
51. Recent advance in earth observation big data for hydrology L. Chen & L. Wang https://doi.org/10.1080/20964471.2018.1435072
52. Improving the algorithms for the estimation of wet surface evaporation on the Tibetan Plateau C. Zhang et al. https://doi.org/10.1016/j.agrformet.2026.111030
53. Estimation of spatial surface energy fluxes and actual evapotranspiration over Ghataprabha river basin using remote sensing data S. Bangi et al. https://doi.org/10.1051/e3sconf/202345503008
54. Multi-Satellite Data of Land Surface Temperature, Lakes Area, and Water Level for Hydrological Model Calibration and Validation in the Yangtze River Basin C. Corbari et al. https://doi.org/10.3390/w11122621
55. First results of the earth observation Water Cycle Multi-mission Observation Strategy (WACMOS) Z. Su et al. https://doi.org/10.1016/j.jag.2013.08.002
56. A pixel-aligned co-registration and DSM-grid fusion framework for UAV multispectral and thermal imagery and point-cloud data: 3D Characterization of crop canopy water status L. Zhang et al. https://doi.org/10.1016/j.compag.2025.111290
57. Evaluation of Evapotranspiration over a Semiarid Region Using Multiresolution Data Sources S. Jamshidi et al. https://doi.org/10.1175/JHM-D-18-0082.1
58. A Distributed Hydrological Model Driven by Multi-Source Spatial Data and Its Application in the Ili River Basin of Central Asia M. Cai et al. https://doi.org/10.1007/s11269-014-0641-z
59. Estimation and validation of high-resolution evapotranspiration products for an arid river basin using multi-source remote sensing data J. Xiao et al. https://doi.org/10.1016/j.agwat.2024.108864
60. Tailoring the surface energy balance algorithm for land-improved (SEBALI) model using high-resolution land/use land cover for monitoring actual evapotranspiration Y. Mekonnen et al. https://doi.org/10.1016/j.agwat.2024.109058
61. Estimation of evapotranspiration of “soil-vegetation” system with a scheme combining a dual-source model and satellite data assimilation Y. Cui & L. Jia https://doi.org/10.1016/j.jhydrol.2021.127145
62. Monitoring satellite-based crop irrigation water requirements for maize, cotton and hay in distinct Mediterranean regions N. Dercas et al. https://doi.org/10.1016/j.agwat.2025.109719
63. High spatio-temporal monitoring of century-old biochar effects on evapotranspiration through the ETLook model: a case study with UAV and satellite image fusion based on additive wavelet transform (AWT) R. Heidarian Dehkordi et al. https://doi.org/10.1080/15481603.2021.2016262
64. Daily evapotranspiration assessment by means of residual surface energy balance modeling: A critical analysis under a wide range of water availability C. Cammalleri et al. https://doi.org/10.1016/j.jhydrol.2012.05.042
65. Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region V. Pellet et al. https://doi.org/10.5194/hess-23-465-2019
66. Applicability of the Surface Energy Balance System (SEBS) Model for Evapotranspiration in Tropical Rubber Plantation and Its Response to Influencing Factors J. Wang et al. https://doi.org/10.3390/f16121820
67. Global Land Surface Evapotranspiration Estimation From Meteorological and Satellite Data Using the Support Vector Machine and Semiempirical Algorithm M. Liu et al. https://doi.org/10.1109/JSTARS.2017.2788462
68. Nonlinear boundaries of land surface temperature–vegetation index space to estimate water deficit index and evaporation fraction X. Hu et al. https://doi.org/10.1016/j.agrformet.2019.107736
69. Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration? C. Corbari et al. https://doi.org/10.1080/02626667.2013.866709
70. Modeling the evapotranspiration of Lycium barbarum with drip irrigation based on the shuttleworth-wallace model in Ningxia, Northwest China B. Ma & J. He https://doi.org/10.1007/s00704-023-04520-2
71. Advances in thermal infrared remote sensing for land surface modeling W. Kustas & M. Anderson https://doi.org/10.1016/j.agrformet.2009.05.016
72. Water allocation and water consumption of irrigated agriculture and natural vegetation in the Aksu-Tarim river basin, Xinjiang, China N. Thevs et al. https://doi.org/10.1016/j.jaridenv.2014.05.028
73. Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites M. Chen et al. https://doi.org/10.1016/j.jhydrol.2016.02.026
74. Estimating the long-term daily evapotranspiration in the source region of the Yangtze River based on a universal trapezoid method Y. Li et al. https://doi.org/10.1016/j.ejrh.2026.103119
75. Estimation of evapotranspiration using all-weather land surface temperature and variational trends with warming temperatures for the River Source Region in Southwest China Y. Ma et al. https://doi.org/10.1016/j.jhydrol.2022.128346
76. Enhancing evapotranspiration estimates in composite terrain through the integration of satellite remote sensing and eddy covariance measurements A. Ghorbanpour et al. https://doi.org/10.1016/j.scitotenv.2025.178530
77. Quantifying bare soil evaporation and its relationship with groundwater depth X. Jin et al. https://doi.org/10.1080/01431161.2014.975374
78. Land surface energy partitioning revisited: A novel approach based on single depth soil measurement J. Yang & Z. Wang https://doi.org/10.1002/2014GL062041
79. Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches R. Vinukollu et al. https://doi.org/10.1016/j.rse.2010.11.006
80. Improvement of Two Evapotranspiration Estimation Models Using a Linear Spectral Mixture Model over a Small Agricultural Watershed G. Li et al. https://doi.org/10.3390/w10040474
81. Estimating sub-pixel temperatures using the triangle algorithm H. Yang et al. https://doi.org/10.1080/01431160903376373
82. Drought evolution, severity and trends in mainland China over 1961–2013 N. Yao et al. https://doi.org/10.1016/j.scitotenv.2017.10.327
83. Long-Term Regional Estimates of Evapotranspiration for Mexico Based on Downscaled ISCCP Data J. Sheffield et al. https://doi.org/10.1175/2009JHM1176.1
84. Evolving water science in the Anthropocene H. Savenije et al. https://doi.org/10.5194/hess-18-319-2014
85. A continuous satellite‐derived global record of land surface evapotranspiration from 1983 to 2006 K. Zhang et al. https://doi.org/10.1029/2009WR008800
86. Derivation of Geostationary Satellite Based Background Temperature and Its Validation with Ground Observation and Geographic Information D. Choi et al. https://doi.org/10.7780/kjrs.2015.31.6.8
87. Spatiotemporal Distribution Characteristics of Evapotranspiration Based on SEBAL Model and Remote Sensing 鹏. 乔 https://doi.org/10.12677/JWRR.2020.94043
88. Monitoring land degradation risk using ASTER data: The non-evaporative fraction as an indicator of ecosystem function M. García et al. https://doi.org/10.1016/j.rse.2008.05.011
89. The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat G. Boulet et al. https://doi.org/10.5194/hess-19-4653-2015
90. Application of an energy balance method for estimating evapotranspiration in cropping systems S. Anapalli et al. https://doi.org/10.1016/j.agwat.2018.04.005
91. Evaluating European ECOSTRESS Hub Evapotranspiration Products Across a Range of Soil‐Atmospheric Aridity and Biomes Over Europe T. Hu et al. https://doi.org/10.1029/2022WR034132
92. Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China J. Colin & R. Faivre https://doi.org/10.5194/hess-14-2661-2010
93. An automated multi-model evapotranspiration mapping framework using remotely sensed and reanalysis data N. Bhattarai et al. https://doi.org/10.1016/j.rse.2019.04.026
94. Estimation of the crop evapotranspiration for Udham Singh Nagar district using modified Priestley-Taylor model and Landsat imagery A. Satpathi et al. https://doi.org/10.1038/s41598-024-72299-x
95. Two-source energy balance schemes exploiting land surface temperature and soil moisture for continuous vineyard water use estimation N. Paciolla et al. https://doi.org/10.1007/s00271-024-00991-x
96. The role of remote sensing in process-scaling studies of managed forest ecosystems J. Masek et al. https://doi.org/10.1016/j.foreco.2015.05.032
97. Estimation of Surface Heat Fluxes Over the Central Tibetan Plateau using the Maximum Entropy Production Model N. Li et al. https://doi.org/10.1029/2018JD029959
98. Comparison of blue and green water fluxes for different land use classes in a semi-arid cultivated catchment using remote sensing A. Msigwa et al. https://doi.org/10.1016/j.ejrh.2021.100860
99. Modelling daily reference evapotranspiration based on stacking hybridization of ANN with meta-heuristic algorithms under diverse agro-climatic conditions A. Elbeltagi et al. https://doi.org/10.1007/s00477-022-02196-0
100. Evapotranspiration estimation considering anthropogenic heat based on remote sensing in urban area Z. Cong et al. https://doi.org/10.1007/s11430-016-0216-3
101. Estimation of evapotranspiration for the blown-sand region in the Ordos basin based on the SEBAL model J. Kong et al. https://doi.org/10.1080/01431161.2018.1508919
102. Multidecadal Trend of Basin‐Scale Evapotranspiration Estimated Using AVHRR Data in the Krishna River Basin, India P. Teluguntla et al. https://doi.org/10.2136/vzj2012.0118
103. Quantifying lake evaporation from the largest saline lake on the Tibetan Plateau based on three surface energy balance models Y. Lei et al. https://doi.org/10.1016/j.jglr.2026.102945
104. Ecological Water Requirement of Vegetation and Water Stress Assessment in the Middle Reaches of the Keriya River Basin R. Wang et al. https://doi.org/10.3390/rs15184638
105. Estimation of evapotranspiration using a remote sensing model over agricultural land in the North China Plain D. Yang et al. https://doi.org/10.1080/01431161.2010.483492
106. Earth Observations and Integrative Models in Support of Food and Water Security S. Schollaert Uz et al. https://doi.org/10.1007/s41976-019-0008-6
107. Trends analysis of Evapotranspiration and responses to soil moisture and wind speed over the Taklimakan Desert, China J. Lang et al. https://doi.org/10.1080/15324982.2024.2393337
108. An improved remote sensing based approach for predicting actual Evapotranspiration by integrating LiDAR M. Khan et al. https://doi.org/10.1016/j.asr.2021.04.017
109. Basin-wide water accounting based on remote sensing data: an application for the Indus Basin P. Karimi et al. https://doi.org/10.5194/hess-17-2473-2013
110. Developing a New ANN Model to Estimate Daily Actual Evapotranspiration Using Limited Climatic Data and Remote Sensing Techniques for Sustainable Water Management H. Karahan et al. https://doi.org/10.3390/su16062481
111. Seasonal trends of satellite-based evapotranspiration algorithms over a complex ecosystem in East Asia K. Hwang & M. Choi https://doi.org/10.1016/j.rse.2013.06.006
112. Using remote sensing models to determine evapotranspiration of a pomegranate orchard in a Mediterranean-type climate R. Kgaphola et al. https://doi.org/10.17660/ActaHortic.2024.1395.7
113. Estimating Turbulent Heat Fluxes With a Weak-Constraint Data Assimilation Scheme: A Case Study (HiWATER-MUSOEXE) T. Xu et al. https://doi.org/10.1109/LGRS.2014.2326180
114. Estimating Monthly Energy Fluxes Using Observations of Near-Surface Air Temperature, Humidity and Radiosonde Profiles D. Brondani et al. https://doi.org/10.1007/s10546-019-00429-4
115. Crop RS-Met: A biophysical evapotranspiration and root-zone soil water content model for crops based on proximal sensing and meteorological data D. Helman et al. https://doi.org/10.1016/j.agwat.2018.09.043
116. A novel classifier-guided ensemble framework for global terrestrial evapotranspiration estimates L. Ni et al. https://doi.org/10.5194/hess-30-3283-2026
117. Combining scintillometer measurements and an aggregation scheme to estimate area-averaged latent heat flux during the AMMA experiment J. Ezzahar et al. https://doi.org/10.1016/j.jhydrol.2009.01.010
118. Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation Y. Kang et al. https://doi.org/10.1007/s00271-022-00798-8
119. A new parameterization scheme for estimating surface energy fluxes with continuous surface temperature, air temperature, and surface net radiation measurements J. Lu et al. https://doi.org/10.1002/2013WR014468
120. Improving the Operational Simplified Surface Energy Balance Evapotranspiration Model Using the Forcing and Normalizing Operation G. Senay et al. https://doi.org/10.3390/rs15010260
121. Sensitivity and Uncertainty Analysis of the GeeSEBAL Model Using High-Resolution Remote-Sensing Data and Global Flux Site Data S. Hu et al. https://doi.org/10.3390/w16202978
122. A hybrid deep learning framework with physical process description for simulation of evapotranspiration H. Chen et al. https://doi.org/10.1016/j.jhydrol.2021.127422
123. Spatio-Temporal Determination of Irrigated Paddy Rice Pixels Using Evapotranspiration and Vegetation Indices: A Case Study for Ca River Basin in Vietnam C. Luong et al. https://doi.org/10.4236/gep.2020.812006
124. Using GRACE to constrain precipitation amount over cold mountainous basins A. Behrangi et al. https://doi.org/10.1002/2016GL071832
125. Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements S. Saadi et al. https://doi.org/10.5194/hess-22-2187-2018
126. Integrated modeling to assess the impact of climate change on the groundwater and surface water in the South Aral Sea area X. Pan et al. https://doi.org/10.1016/j.jhydrol.2022.128641
127. Evaluation of SEBS for estimation of actual evapotranspiration using ASTER satellite data for irrigation areas of Australia W. Ma et al. https://doi.org/10.1007/s00704-012-0754-3
128. Estimation of Vegetation Latent Heat Flux over Three Forest Sites in ChinaFLUX using Satellite Microwave Vegetation Water Content Index Y. Wang et al. https://doi.org/10.3390/rs11111359
129. Determining water use of sorghum from two-source energy balance and radiometric temperatures J. Sánchez et al. https://doi.org/10.5194/hess-15-3061-2011
130. Up-scaling the latent heat flux from instantaneous to daily-scale: A comparison of three methods M. Cheng et al. https://doi.org/10.1016/j.ejrh.2022.101057
131. Progress in integrating remote sensing data and hydrologic modeling X. Xu et al. https://doi.org/10.1177/0309133314536583
132. A Method for Deriving All‐Sky Evapotranspiration From the Synergistic Use of Remotely Sensed Images and Meteorological Data P. Leng et al. https://doi.org/10.1002/2017JD027880
133. Aggregation of area-averaged evapotranspiration over the Ejina Oasis based on a flux matrix and footprint analysis F. Xu et al. https://doi.org/10.1016/j.jhydrol.2019.05.011
134. Satellite Retrieval of Surface Evapotranspiration with Nonparametric Approach: Accuracy Assessment over a Semiarid Region X. Pan et al. https://doi.org/10.1155/2016/1584316
135. Comparison of physical-based, data-driven and hybrid modeling approaches for evapotranspiration estimation X. Hu et al. https://doi.org/10.1016/j.jhydrol.2021.126592
136. Estimating surface evapotranspiration using combined MODIS and CBERS-02 data X. Xin et al. https://doi.org/10.1007/BF03039431
137. Impacts of climatology error on evapotranspiration data merging over the intensively irrigated Haihe river basin, China Y. Li et al. https://doi.org/10.1016/j.ejrh.2025.102568
138. Daily Evapotranspiration Estimation at the Field Scale: Using the Modified SEBS Model and HJ-1 Data in a Desert-Oasis Area, Northwestern China Z. Yi et al. https://doi.org/10.3390/w10050640
139. Spatio-temporal variation of evapotranspiration and its linkage with environmental factors in the largest freshwater lake wetland in China X. Pan et al. https://doi.org/10.1016/j.ejrh.2023.101424
140. Spatiotemporal Heterogeneity of Multiple In Situ Observational Sites and Its Site Deployment Optimization Strategy Y. Huang et al. https://doi.org/10.1109/TGRS.2023.3317482
141. Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle F. Tauro et al. https://doi.org/10.1080/02626667.2017.1420191
142. Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements L. Jia et al. https://doi.org/10.1016/S1474-7065(03)00009-3
143. Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites D. Long et al. https://doi.org/10.1002/2013WR014581
144. Evapotranspiration estimation using moderate resolution imaging spectroradiometer products through a surface energy balance algorithm for land model in Songnen Plain, China L. Zeng et al. https://doi.org/10.1117/1.3609840
145. 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 Y. Li et al. https://doi.org/10.1016/j.agrformet.2015.08.260
146. Using a Surface Energy Balance Model to Calculate Spatially Distributed Actual Evapotranspiration A. Elhaddad et al. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000276
147. Evaluating the Impact of Future Seasonal Climate Extremes on Crop Evapotranspiration of Maize in Western Kansas Using a Machine Learning Approach K. Igwe et al. https://doi.org/10.3390/land12081500
148. Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain) J. van der Kwast et al. https://doi.org/10.5194/hess-13-1337-2009
149. An investigation of sensible heat fluxes at a green roof in a laboratory setup T. Ayata et al. https://doi.org/10.1016/j.buildenv.2011.03.006
150. Assessing spatiotemporal variation in actual evapotranspiration for semi-arid watersheds in northwest China: Evaluation of two complementary-based methods M. Matin & C. Bourque https://doi.org/10.1016/j.jhydrol.2013.02.014
151. Estimating turbulent fluxes through assimilation of geostationary operational environmental satellites data using ensemble Kalman filter T. Xu et al. https://doi.org/10.1029/2010JD015150
152. Estimating evapotranspiration using remotely sensed solar-induced fluorescence measurements K. Zhou et al. https://doi.org/10.1016/j.agrformet.2021.108800
153. Incorporating Plant Access to Groundwater in Existing Global, Satellite‐Based Evaporation Estimates P. Hulsman et al. https://doi.org/10.1029/2022WR033731
154. Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin L. Ha et al. https://doi.org/10.3390/w10020212
155. Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey O. ORHAN et al. https://doi.org/10.26833/ijeg.417151
156. Advancements in Remote Sensing for Evapotranspiration Estimation: A Comprehensive Review of Temperature-Based Models B. Derardja et al. https://doi.org/10.3390/rs16111927
157. Further evaluation of the Sim-ReSET model for ET estimation driven by only satellite inputs Z. Sun et al. https://doi.org/10.1080/02626667.2013.791026
158. Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review Y. Liou & S. Kar https://doi.org/10.3390/en7052821
159. Complementary Relationship-Based Validation and Analysis of Evapotranspiration in the Permafrost Region of the Qinghai–Tibetan Plateau W. Yu et al. https://doi.org/10.3390/atmos16080932
160. A new empirical procedure for estimating intra-annual heat storage changes in lakes and reservoirs: Review and analysis of 22 lakes Z. Duan & W. Bastiaanssen https://doi.org/10.1016/j.rse.2014.09.009
161. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model M. Demirel et al. https://doi.org/10.5194/hess-22-1299-2018
162. Estimating the Water Deficit Index of a Mediterranean Holm Oak Forest From Landsat Optical/Thermal Data: A Phenomenological Correction for Trees Casting Shadow Effects V. Penot & O. Merlin https://doi.org/10.1109/JSTARS.2023.3288360
163. Strategies to increase wheat production in the water scarce Karkheh River Basin, Iran L. Muthuwatta et al. https://doi.org/10.1016/j.agwat.2013.03.013
164. Estimation of actual irrigation amount and its impact on groundwater depletion: A case study in the Hebei Plain, China X. Hu et al. https://doi.org/10.1016/j.jhydrol.2016.10.020
165. On the use of machine learning based ensemble approaches to improve evapotranspiration estimates from croplands across a wide environmental gradient Y. Bai et al. https://doi.org/10.1016/j.agrformet.2020.108308
166. Estimating Evapotranspiration of Mediterranean Oak Savanna at Multiple Temporal and Spatial Resolutions. Implications for Water Resources Management E. Carpintero et al. https://doi.org/10.3390/rs13183701
167. Developmentevaluation of an actual evapotranspiration estimation algorithm using satellite remote sensingmeteorological observational network in Oklahoma S. Ibrahim Khan et al. https://doi.org/10.1080/01431161.2010.483487
168. Climate-Induced Shifts in Global Soil Temperature Regimes M. Grillakis et al. https://doi.org/10.1097/SS.0000000000000156
169. Assessing the impacts of an ecological water diversion project on water consumption through high-resolution estimations of actual evapotranspiration in the downstream regions of the Heihe River Basin, China Y. Zhou et al. https://doi.org/10.1016/j.agrformet.2017.11.011
170. Spatial-scale effect on the SEBAL model for evapotranspiration estimation using remote sensing data R. Tang et al. https://doi.org/10.1016/j.agrformet.2013.01.008
171. Estimation of evapotranspiration and its partition based on an extended three-temperature model and MODIS products F. Tian et al. https://doi.org/10.1016/j.jhydrol.2013.06.038
172. Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities P. Stoy et al. https://doi.org/10.5194/bg-16-3747-2019
173. Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan F. Akhtar et al. https://doi.org/10.3390/rs10060972
174. Utility of an Automated Thermal-Based Approach for Monitoring Evapotranspiration W. Timmermans et al. https://doi.org/10.1515/acgeo-2015-0016
175. Effects of anthropogenic water regulation and groundwater lateral flow on land processes Y. Zeng et al. https://doi.org/10.1002/2016MS000646
176. Realization of Land Geophysical Products (Short-Wave Broad Band Albedo, Visible Albedo, Inland Water Bodies and Vegetation Indices) from EOS-06 Ocean Color Monitor3 Sensor V. Keerthi et al. https://doi.org/10.1007/s12524-025-02325-6
177. Improving Soil Moisture and Surface Turbulent Heat Flux Estimates by Assimilation of SMAP Brightness Temperatures or Soil Moisture Retrievals and GOES Land Surface Temperature Retrievals Y. Lu et al. https://doi.org/10.1175/JHM-D-19-0130.1
178. Retrieved actual ET using SEBS model from Landsat-5 TM data for irrigation area of Australia W. Ma et al. https://doi.org/10.1016/j.atmosenv.2012.05.040
179. A three-source satellite algorithm for retrieving all-sky evapotranspiration rate using combined optical and microwave vegetation index at twenty AsiaFlux sites Y. Wang et al. https://doi.org/10.1016/j.rse.2019.111463
180. Distribution of Actual Evapotranspiration over Qaidam Basin, an Arid Area in China X. Jin et al. https://doi.org/10.3390/rs5126976
181. DNN-MET: A deep neural networks method to integrate satellite-derived evapotranspiration products, eddy covariance observations and ancillary information K. Shang et al. https://doi.org/10.1016/j.agrformet.2021.108582
182. Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data P. Guillevic et al. https://doi.org/10.3390/rs11050573
183. A Temperature-Domain SEBAL Model Based on a Wind Speed-Independent Theoretical Trapezoidal Space Between Fractional Vegetation Coverage and Land Surface Temperature X. Wang et al. https://doi.org/10.1109/LGRS.2020.2987485
184. Spatial-temporal estimation of evapotranspiration over Black Volta of West Africa T. Amos et al. https://doi.org/10.5897/IJWREE2014.0530
185. Impact of High Concentrations of Saharan Dust Aerosols on Infrared-Based Land Surface Temperature Products F. Stante et al. https://doi.org/10.1109/JSTARS.2023.3263374
186. Estimating evapotranspiration by coupling Bayesian model averaging methods with machine learning algorithms Y. Yang et al. https://doi.org/10.1007/s10661-021-08934-1
187. Coupling physical constraints with machine learning for satellite-derived evapotranspiration of the Tibetan Plateau K. Shang et al. https://doi.org/10.1016/j.rse.2023.113519
188. Spatiotemporal analysis of crop water requirements in Lower Chenab Canal (LCC) Irrigation System for the better management of water resources M. Usman et al. https://doi.org/10.1007/s12517-021-06758-4
189. Inconsistencies of SEBS Model Output Based on the Model Inputs: Global Sensitivity Contemplations M. Elhag https://doi.org/10.1007/s12524-015-0502-0
190. Accuracy of the Temperature–Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions M. Garcia et al. https://doi.org/10.1016/j.rse.2014.04.002
191. Soft robotic grippers: a review Y. Zhang et al. https://doi.org/10.3389/fmats.2025.1692206
192. Estimates of land surface heat fluxes of the Mt. Everest region over the Tibetan Plateau utilizing ASTER data C. Han et al. https://doi.org/10.1016/j.atmosres.2015.09.012
193. Daily actual evapotranspiration estimation of different land use types based on SEBAL model in the agro-pastoral ecotone of northwest China L. Yang et al. https://doi.org/10.1371/journal.pone.0265138
194. Varying performance of eight evapotranspiration products with aridity and vegetation greenness across the globe H. Wang et al. https://doi.org/10.3389/fenvs.2023.1079520
195. Estimating cropland evapotranspiration based on remote sensing models: A global meta-analysis J. Ding et al. https://doi.org/10.1016/j.eja.2025.127758
196. Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind M. Liu et al. https://doi.org/10.5194/hess-16-357-2012
197. Evaluation of Algorithms to estimate Daily Evapotranspiration from Instantaneous Measurements under All-sky Conditions Z. Ruan et al. https://doi.org/10.1088/1755-1315/17/1/012133
198. Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau N. Ge et al. https://doi.org/10.3390/rs11242899
199. An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. I. Description of Method P. Nagler et al. https://doi.org/10.3390/rs1041273
200. A fully coupled crop-water-energy balance model based on satellite data for maize and tomato crops yield estimates: The FEST-EWB-SAFY model C. Corbari et al. https://doi.org/10.1016/j.agwat.2022.107850
201. Estimating ecosystem evaporation and transpiration using a soil moisture coupled two-source energy balance model across FLUXNET sites K. Xue et al. https://doi.org/10.1016/j.agrformet.2023.109513
202. Impacts of juniper woody plant encroachment into grasslands on local climate J. Wang et al. https://doi.org/10.1016/j.agrformet.2021.108508
203. The Surface Energy Budget and Its Impact on the Freeze-thaw Processes of Active Layer in Permafrost Regions of the Qinghai-Tibetan Plateau J. Ma et al. https://doi.org/10.1007/s00376-021-1066-2
204. Variational estimation of soil and vegetation turbulent transfer and heat flux parameters from sequences of multisensor imagery F. Caparrini et al. https://doi.org/10.1029/2004WR003358
205. Evapotranspiration estimated by using datasets from the Chinese FengYun-2D geostationary meteorological satellite over the Yellow River source area R. Liu et al. https://doi.org/10.1016/j.asr.2014.09.018
206. Surface energy exchanges and stability conditions associated with convective intense rainfall events on the central Andes of Peru J. Flores-Rojas et al. https://doi.org/10.1016/j.agrformet.2025.110570
207. Physics-constrained machine learning for satellite-derived evapotranspiration in China C. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.133512
208. Estimating Effective Soil Hydraulic Properties Using Spatially Distributed Soil Moisture and Evapotranspiration Y. Shin et al. https://doi.org/10.2136/vzj2012.0094
209. Evaluating the ability of deep learning on actual daily evapotranspiration estimation over the heterogeneous surfaces J. Feng et al. https://doi.org/10.1016/j.agwat.2023.108627
210. Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau R. Liu et al. https://doi.org/10.5194/hess-14-47-2010
211. More realistic land‐use and vegetation parameters in a regional climate model reduce model biases over China J. Gou et al. https://doi.org/10.1002/joc.6110
212. Global long term daily 1 km surface soil moisture dataset with physics informed machine learning Q. Han et al. https://doi.org/10.1038/s41597-023-02011-7
213. Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation C. Qin et al. https://doi.org/10.3390/s8074441
214. Multi-scale spatial analysis of satellite-retrieved surface evapotranspiration in Beijing, a rapidly urbanizing region under continental monsoon climate R. Liu et al. https://doi.org/10.1007/s11356-022-23580-x
215. Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges M. Taheri et al. https://doi.org/10.3390/en15041264
216. Higher temporal evapotranspiration estimation with improved SEBS model from geostationary meteorological satellite data J. Zhao et al. https://doi.org/10.1038/s41598-019-50724-w
217. Assessment of non-parametric method for evapotranspiration estimation across extreme conditions X. Wu et al. https://doi.org/10.1016/j.atmosres.2025.108279
218. Volume Removed - Publisher's Disclaimer https://doi.org/10.1016/S1876-6102(14)00453-6
219. An optimized two source energy balance model based on complementary concept and canopy conductance G. Gan et al. https://doi.org/10.1016/j.rse.2019.01.020
220. Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality S. Li et al. https://doi.org/10.1016/j.agrformet.2023.109702
221. Validation and Comparison of Seven Land Surface Evapotranspiration Products in the Haihe River Basin, China X. Guo et al. https://doi.org/10.3390/rs14174308
222. Irrigation Scheduling Using Remote Sensing Data Assimilation Approach B. Kamble et al. https://doi.org/10.4236/ars.2013.23028
223. Effects of spatial aggregation on the multi-scale estimation of evapotranspiration A. Ershadi et al. https://doi.org/10.1016/j.rse.2012.12.007
224. Pixel‐oriented land use classification in energy balance modelling G. Scavone et al. https://doi.org/10.1002/hyp.9507
225. Assessment of the Energy Balance Closure under Advective Conditions and Its Impact Using Remote Sensing Data Z. Xu et al. https://doi.org/10.1175/JAMC-D-16-0096.1
226. Estimation of net radiation flux distribution on the southern slopes of the central Himalayas using MODIS data P. Amatya et al. https://doi.org/10.1016/j.atmosres.2014.11.015
227. Spaceborne Imaging Spectroscopy for Sustainable Agriculture: Contributions and Challenges T. Hank et al. https://doi.org/10.1007/s10712-018-9492-0
228. Uncertain effect of component differences on land evapotranspiration P. Jiao et al. https://doi.org/10.1016/j.ejrh.2024.101904
229. Accuracy Assessment of Remote Sensing-Derived Evapotranspiration Products Against Eddy Covariance Measurements in Tensift Al-Haouz Semi-Arid Region, Morocco Y. Manyari et al. https://doi.org/10.3390/atmos16121407
230. A Review of Advances in Groundwater Evapotranspiration Research X. Hou et al. https://doi.org/10.3390/w15050969
231. Calculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2 A. Mokhtari et al. https://doi.org/10.1016/j.isprsjprs.2019.06.011
232. Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes . Jie Bai et al. https://doi.org/10.1109/LGRS.2014.2368580
233. Estimation of Grassland Latent Heat Flux in Inner Mongolia from a ConvTransformer Deep Learning Model and MODIS Data N. Yang et al. https://doi.org/10.3390/atmos17080800
234. Quantifying the heat flux regulation of metropolitan land use/land cover components by coupling remote sensing modeling with in situ measurement W. Kuang et al. https://doi.org/10.1002/2014JD022249
235. Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards K. Knipper et al. https://doi.org/10.1007/s00271-018-0591-y
236. Comparison of SEBAL, METRIC, and ALARM algorithms for estimating actual evapotranspiration of wheat crop M. Asadi & K. Kamran https://doi.org/10.1007/s00704-022-04026-3
237. Near-surface heat transfer at two gentle slope sites with differing aspects, Qinghai-Tibet Plateau X. Fan et al. https://doi.org/10.3389/fenvs.2022.1037331
238. Intercomparison of Three Two-Source Energy Balance Models for Partitioning Evaporation and Transpiration in Semiarid Climates Y. Yang et al. https://doi.org/10.3390/rs10071149
239. Biophysical drivers of short-term change in evapotranspiration after fire as estimated through the SSEBop Landsat-based model J. Fernández-Guisuraga et al. https://doi.org/10.1016/j.foreco.2025.122945
240. Robust historical evapotranspiration trends across climate regimes S. Hobeichi et al. https://doi.org/10.5194/hess-25-3855-2021
241. Evaluation of seven satellite-based and two reanalysis global terrestrial evapotranspiration products Z. Xie et al. https://doi.org/10.1016/j.jhydrol.2024.130649
242. Estimation of evapotranspiration based on METRIC and SEBAL model using remote sensing, near Al-Jouf, Saudi Arabia E. Adem et al. https://doi.org/10.5004/dwt.2023.29478
243. Estimation of Crop Water Requirement Based on Planting Structure Extraction from Multi-Temporal MODIS EVI C. Xu et al. https://doi.org/10.1007/s11269-021-02838-y
244. A GEE TSEB workflow for daily high-resolution fully remote sensing evapotranspiration: Validation over four crops in semi-arid conditions and comparison with the SSEBop experimental product I. El Hazdour et al. https://doi.org/10.1016/j.envsoft.2025.106365
245. Uncertainty and Sensitivity Analysis of a Remote-Sensing-Based Penman–Monteith Model to Meteorological and Land Surface Input Variables N. Majozi et al. https://doi.org/10.3390/rs13050882
246. Vegetation dynamics and their response to groundwater and climate variables in Qaidam Basin, China X. Jin et al. https://doi.org/10.1080/01431161.2015.1137648
247. Simulation of soil water in space and time using an agro-hydrological model and remote sensing techniques U. Singh et al. https://doi.org/10.1016/j.agwat.2010.03.002
248. High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product Y. Yang et al. https://doi.org/10.1016/j.jhydrol.2020.125730
249. Detecting and Attributing Evapotranspiration Deviations Using Dynamical Downscaling and Convection-Permitting Modeling over the Tibetan Plateau J. Dan et al. https://doi.org/10.3390/w13152096
250. Modeling soil evaporation efficiency in a range of soil and atmospheric conditions using a meta‐analysis approach O. Merlin et al. https://doi.org/10.1002/2015WR018233
251. Estimation of evapotranspiration over the terrestrial ecosystems in China X. Li et al. https://doi.org/10.1002/eco.1341
252. Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework T. Xu et al. https://doi.org/10.1002/2017JD027732
253. Coupled retrieval of turbulent heat fluxes and gross primary productivity via the assimilation of land surface temperature data from geostationary satellites Z. Xu et al. https://doi.org/10.1016/j.rse.2025.114862
254. Automated Directional Measurement System for the Acquisition of Thermal Radiative Measurements of Vegetative Canopies J. Timmermans et al. https://doi.org/10.3390/s90301409
255. Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches Y. Ke et al. https://doi.org/10.3390/rs8030215
256. Improving Meteorological Input for Surface Energy Balance System Utilizing Mesoscale Weather Research and Forecasting Model for Estimating Daily Actual Evapotranspiration D. Wang et al. https://doi.org/10.3390/w12010009
257. Assessment of automated evapotranspiration estimates obtained using the GP-SEBAL algorithm for dry forest vegetation (Caatinga) and agricultural areas in the Brazilian semiarid region C. Lima et al. https://doi.org/10.1016/j.agwat.2021.106863
258. Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review W. Maes & K. Steppe https://doi.org/10.1093/jxb/ers165
259. Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data E. Sutanudjaja et al. https://doi.org/10.1002/2013WR013807
260. Changes in the Land Surface Energy Budget in Eastern China over the Past Three Decades: Contributions of Land-Cover Change and Climate Change J. Yan et al. https://doi.org/10.1175/JCLI-D-13-00492.1
261. Estimation of Sensible and Latent Heat Flux Over Mountainous Areas Using the SEBAL Model W. Fu et al. https://doi.org/10.1109/TGRS.2025.3577180
262. Integrating RS data with fuzzy decision systems for innovative crop water needs assessment F. Sadat Hashemi et al. https://doi.org/10.1016/j.jag.2024.104338
263. Moving from model calibration towards process understanding F. Fenicia et al. https://doi.org/10.1016/j.pce.2008.06.008
264. Evaluation of Land Surface Temperature Retrieval from FY-3B/VIRR Data in an Arid Area of Northwestern China J. Jiang et al. https://doi.org/10.3390/rs70607080
265. A Scheme to Estimate Diurnal Cycle of Evapotranspiration from Geostationary Meteorological Satellite Observations J. Lu et al. https://doi.org/10.3390/w12092369
266. Numerical Modeling of Land Surface Temperature over Complex Geologic Terrains: A Remote Sensing Approach S. Asadzadeh & C. Souza Filho https://doi.org/10.3390/rs15194877
267. Actual evapotranspiration estimation and applicability assessment based on the Y-SEBAL model in China Y. Ma et al. https://doi.org/10.1016/j.jhydrol.2025.133476
268. Developing a Gap-Filling Algorithm Using DNN for the Ts-VI Triangle Model to Obtain Temporally Continuous Daily Actual Evapotranspiration in an Arid Area of China Y. Cui et al. https://doi.org/10.3390/rs12071121
269. Optimized algorithm for evapotranspiration retrieval via remote sensing . Wagner Wolff et al. https://doi.org/10.1016/j.agwat.2021.107390
270. Increased Bias in Evapotranspiration Modeling Due to Weather and Vegetation Indices Data Sources R. Dhungel et al. https://doi.org/10.2134/agronj2018.10.0636
271. Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method Y. Yao et al. https://doi.org/10.1016/j.jhydrol.2017.08.013
272. Estimation of Spatio-Temporal Variability of Actual Evapotranspiration Using the Sebs Model in the Semiarid Barotse Basin, South-Western Zambia W. Phiri et al. https://doi.org/10.53974/unza.jonas.1.2.352
273. Autumn daily characteristics of land surface heat and water exchange over the Loess Plateau mesa in China J. Wen et al. https://doi.org/10.1007/s00376-007-0301-9
274. Utility of Radiometric–aerodynamic Temperature Relations for Heat Flux Estimation W. Kustas et al. https://doi.org/10.1007/s10546-006-9093-1
275. Combining Remotely Sensed Data and Ground-Based Radiometers to Estimate Crop Cover and Surface Temperatures at Daily Time Steps A. French et al. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000169
276. Variability of urban surface temperatures and implications for aerodynamic energy exchange in unstable conditions B. Crawford et al. https://doi.org/10.1002/qj.3325
277. Using Satellite Thermal-Based Evapotranspiration Time Series for Defining Management Zones and Spatial Association to Local Attributes in a Vineyard N. Ohana-Levi et al. https://doi.org/10.3390/rs12152436
278. Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach G. Senay et al. https://doi.org/10.1111/jawr.12057
279. From Standard Weather Stations to Virtual Micro-Meteorological Towers in Ungauged Sites: Modeling Tool for Surface Energy Fluxes, Evapotranspiration, Soil Temperature, and Soil Moisture Estimations J. Celis et al. https://doi.org/10.3390/rs13071271
280. Intercomparison across scales between remotely-sensed land surface temperature and representative equilibrium temperature from a distributed energy water balance model C. Corbari & M. Mancini https://doi.org/10.1080/02626667.2014.946418
281. Estimation of transpiration and canopy cover of winter wheat under different fertilization levels using thermal infrared and visible imagery T. Zhang et al. https://doi.org/10.1016/j.compag.2019.104936
282. Impact of the Spatial Domain Size on the Performance of the Ts-VI Triangle Method in Terrestrial Evapotranspiration Estimation J. Tian et al. https://doi.org/10.3390/rs5041998
283. Potential Rainwater Harvesting Improvement Using Advanced Remote Sensing Applications M. Elhag & J. Bahrawi https://doi.org/10.1155/2014/806959
284. Modelagem Simplificada Para Estimativa do Balanço de Energia à Superfície em Escala Regional (R-SSEB) A. Araújo et al. https://doi.org/10.1590/0102-77863230010
285. Validation of Global Evapotranspiration Product (MOD16) Using Flux Tower Data from Panjin Coastal Wetland, Northeast China J. Du & K. Song https://doi.org/10.1007/s11769-018-0960-8
286. Potential of water balance and remote sensing-based evapotranspiration models to predict yields of spring barley and winter wheat in the Czech Republic F. Jurečka et al. https://doi.org/10.1016/j.agwat.2021.107064
287. Estimation of Landsat-like daily evapotranspiration for crop water consumption monitoring using TSEB model and data fusion D. Chen et al. https://doi.org/10.1371/journal.pone.0267811
288. BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt C. Jiang et al. https://doi.org/10.5194/hess-24-1251-2020
289. Impacts of Summer Extreme Precipitation Events on the Hydrothermal Dynamics of the Active Layer in the Tanggula Permafrost Region on the Qinghai‐Tibetan Plateau X. Zhu et al. https://doi.org/10.1002/2017JD026736
290. Multi-scale evaluation of global evapotranspiration products derived from remote sensing images: Accuracy and uncertainty W. Zhu et al. https://doi.org/10.1016/j.jhydrol.2022.127982
291. Basin-wide evapotranspiration management: Concept and practical application in Hai Basin, China B. Wu et al. https://doi.org/10.1016/j.agwat.2013.09.021
292. Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users A. Calera et al. https://doi.org/10.3390/s17051104
293. Characteristics of surface evapotranspiration and its response to climate and land use and land cover in the Huai River Basin of eastern China M. Li et al. https://doi.org/10.1007/s11356-020-10432-9
294. Estimating evapotranspiration in mountainous water-limited regions from thermal infrared data: Comparison of two approaches based on energy balance and evaporative fraction B. Sebbar et al. https://doi.org/10.1016/j.rse.2024.114481
295. Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System K. Jang et al. https://doi.org/10.1002/2013JD020639
296. Exploring evapotranspiration changes in a typical endorheic basin through the integrated observatory network Z. Xu et al. https://doi.org/10.1016/j.agrformet.2020.108010
297. Satellite-Based PT-SinRH Evapotranspiration Model: Development and Validation from AmeriFlux Data Z. Xie et al. https://doi.org/10.3390/rs16152783
298. Bridging satellite and UAS scales for surface soil moisture mapping: A two-step random forest downscaling framework R. Zhuang et al. https://doi.org/10.1016/j.rsase.2026.102178
299. Estimation of Daily Evapotranspiration Using Instantaneous Decoupling Coefficient From the MODIS and Field Data Y. Jiang et al. https://doi.org/10.1109/JSTARS.2018.2834469
300. Is scale really a challenge in evapotranspiration estimation? A multi-scale study in the Heihe oasis using thermal remote sensing and the three-temperature model Y. Wang et al. https://doi.org/10.1016/j.agrformet.2016.03.012
301. Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems C. Brenner et al. https://doi.org/10.1080/01431161.2018.1471550
302. High uncertainty of evapotranspiration products under extreme climatic conditions L. Qian et al. https://doi.org/10.1016/j.jhydrol.2023.130332
303. An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing Y. Xiong et al. https://doi.org/10.1016/j.jhydrol.2015.09.050
304. Mapping Evapotranspiration from ASTER Data through GIS Spatial Integration of Vegetation and Terrain Features I. Mariotto et al. https://doi.org/10.14358/PERS.77.5.483
305. Impact of reservoir evaporation on future water availability in north-eastern Brazil: a multi-scenario assessment G. Rodrigues et al. https://doi.org/10.5194/hess-28-3243-2024
306. Evapotranspiration in the Tono Reservoir Catchment in Upper East Region of Ghana Estimated by a Novel TSEB Approach from ASTER Imagery A. Alhassan & M. Jin https://doi.org/10.3390/rs12030569
307. Satellite-based estimation of daily average net radiation under clear-sky conditions J. Hou et al. https://doi.org/10.1007/s00376-013-3047-6
308. Modelling bulk surface resistance by MODIS data and assessment of MOD16A2 evapotranspiration product in an irrigation district of Southern Italy D. Autovino et al. https://doi.org/10.1016/j.agwat.2016.01.006
309. Estimating Actual Evapotranspiration in Orchard Systems Using the ALARM Energy Balance Model and MODIS Data H. Darouich et al. https://doi.org/10.3390/rs18142351
310. Crop Water Productivity Mapping and Benchmarking Using Remote Sensing and Google Earth Engine Cloud Computing A. Ghorbanpour et al. https://doi.org/10.3390/rs14194934
311. Influence of December snow cover over North America on January surface air temperature over the midlatitude Asia J. Li et al. https://doi.org/10.1002/joc.6235
312. Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms Y. Yao et al. https://doi.org/10.1016/j.agrformet.2017.04.011
313. Multi‐model, multi‐sensor estimates of global evapotranspiration: climatology, uncertainties and trends R. Vinukollu et al. https://doi.org/10.1002/hyp.8393
314. Different Vegetation Covers Leading to the Uncertainty and Consistency of ET Estimation: A Case Study Assessment with Extended Triple Collocation X. Li et al. https://doi.org/10.3390/rs16132484
315. Improving surface roughness lengths estimation using machine learning algorithms X. Hu et al. https://doi.org/10.1016/j.agrformet.2020.107956
316. Modeling urban evapotranspiration using remote sensing, flux footprints, and artificial intelligence S. Vulova et al. https://doi.org/10.1016/j.scitotenv.2021.147293
317. Satellite-based analysis of recent trends in the ecohydrology of a semi-arid region M. Gokmen et al. https://doi.org/10.5194/hess-17-3779-2013
318. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data Q. Mu et al. https://doi.org/10.1016/j.rse.2007.04.015
319. Estimates of Daily Evapotranspiration in the Source Region of the Yellow River Combining Visible/Near-Infrared and Microwave Remote Sensing R. Liu et al. https://doi.org/10.3390/rs13010053
320. Assessment of the Correction of the Reference Evapotranspiration at Nonirrigated Weather Stations Affected by Aridity and Delimitation of the Meteorological Conditions that Limit its Implementation I. de la Antonia Gonzalez https://doi.org/10.1007/s40710-023-00653-8
321. Calibrating an evapotranspiration model using radiometric surface temperature, vegetation cover fraction and near-surface soil moisture data B. Hssaine et al. https://doi.org/10.1016/j.agrformet.2018.02.033
322. Sensitivity and uncertainty quantification for the ECOSTRESS evapotranspiration algorithm – DisALEXI K. Cawse-Nicholson et al. https://doi.org/10.1016/j.jag.2020.102088
323. Deriving Aerodynamic Roughness Length at Ultra-High Resolution in Agricultural Areas Using UAV-Borne LiDAR K. Trepekli & T. Friborg https://doi.org/10.3390/rs13173538
324. Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges D. Miralles et al. https://doi.org/10.1111/nyas.13912
325. Estimation of Surface Soil Moisture Based on Improved Multi-index Models and Surface Energy Balance System M. Jahangir & M. Arast https://doi.org/10.1007/s11053-020-09728-x
326. Simulated Trends in Land Surface Sensible Heat Flux on the Tibetan Plateau in Recent Decades S. Wang et al. https://doi.org/10.3390/rs15030714
327. Comparison of three remote sensing based models for the estimation of latent heat flux over India R. Eswar et al. https://doi.org/10.1080/02626667.2017.1404067
328. Modified Penman–Monteith equation for monitoring evapotranspiration of wheat crop: Relationship between the surface resistance and remotely sensed stress index A. Amazirh et al. https://doi.org/10.1016/j.biosystemseng.2017.09.015
329. A universal triangle method for evapotranspiration estimation with MODIS products and routine meteorological observations: Algorithm development and global validation W. Zhu et al. https://doi.org/10.1016/j.agwat.2024.109017
330. Applying the Surface Energy Balance System (SEBS) remote sensing model to estimate spatial variations in evapotranspiration in Southern Zimbabwe C. Shoko et al. https://doi.org/10.1080/0035919X.2014.989933
331. Estimating Land Surface Temperature from Satellite Passive Microwave Observations with the Traditional Neural Network, Deep Belief Network, and Convolutional Neural Network S. Wang et al. https://doi.org/10.3390/rs12172691
332. Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin N. Yan et al. https://doi.org/10.3390/rs10020332
333. An integrated evaluation of land surface energy fluxes over China in seven reanalysis/modeling products H. Li et al. https://doi.org/10.1002/2016JD026166
334. Combining UAV remote sensing data to estimate seasonal actual evapotranspiration and surface conductance in rice paddies J. Wang et al. https://doi.org/10.1016/j.agwat.2026.110546
335. Evaluation of two end-member-based models for regional land surface evapotranspiration estimation from MODIS data R. Tang & Z. Li https://doi.org/10.1016/j.agrformet.2014.12.005
336. Actual Evapotranspiration in the Al-Khazir Gomal Basin (Northern Iraq) Using the Surface Energy Balance Algorithm for Land (SEBAL) and Water Balance H. Jassas et al. https://doi.org/10.3390/geosciences5020141
337. A remote sensing and modeling integrated approach for constructing continuous time series of daily actual evapotranspiration H. Awada et al. https://doi.org/10.1016/j.agwat.2021.107320
338. Estimation of daily average net radiation from MODIS data and DEM over the Baiyangdian watershed in North China for clear sky days D. Long et al. https://doi.org/10.1016/j.jhydrol.2010.04.042
339. Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches D. Courault et al. https://doi.org/10.1007/s10795-005-5186-0
340. Estimation of land surface temperature from AMSR2 microwave brightness temperature using machine learning methods W. Han et al. https://doi.org/10.1080/01431161.2023.2208714
341. Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework X. He et al. https://doi.org/10.1029/2019EA000705
342. How to Measure Evapotranspiration in Landscape-Ecological Studies? Overview of Concepts and Methods T. Pohanková et al. https://doi.org/10.2478/jlecol-2024-0017
343. Combining ATC and 3D-CNN for reconstructing spatially and temporally continuous land surface temperature H. Fu et al. https://doi.org/10.1016/j.jag.2022.102733
344. Tracking Evapotranspiration Patterns on the Yinchuan Plain with Multispectral Remote Sensing J. Meng et al. https://doi.org/10.3390/su16188025
345. Use of optical-microwave scintillometry to validate a thermal energy balance model for an olive orchard in Morocco J. Ezzahar et al. https://doi.org/10.1016/j.agwat.2026.110382
346. Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time: Towards an operational processing chain for integrated optical and thermal sensor data products W. Verstraeten et al. https://doi.org/10.1016/j.rse.2005.03.004
347. Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin N. Li et al. https://doi.org/10.1117/1.JRS.11.016028
348. Assessment of Roughness Length Schemes Implemented within the Noah Land Surface Model for High-Altitude Regions D. Zheng et al. https://doi.org/10.1175/JHM-D-13-0102.1
349. A method to estimate diurnal surface soil heat flux from MODIS data for a sparse vegetation and bare soil W. Zhu et al. https://doi.org/10.1016/j.jhydrol.2014.01.019
350. An improved empirical method for large spatial scale surface soil heat flux estimations W. Zhu et al. https://doi.org/10.1088/1755-1315/17/1/012124
351. Assessment on surface energy imbalance and energy partitioning using ground and satellite data over a semi-arid agricultural region in north China M. Rahman et al. https://doi.org/10.1016/j.agwat.2018.10.032
352. TS-PINN: a dual-branch physics-informed neural network based on two-source theory for evapotranspiration estimation X. Rong et al. https://doi.org/10.1016/j.jhydrol.2026.136292
353. Estimating Completely Remote Sensing-Based Evapotranspiration for Salt Cedar (Tamarix ramosissima), in the Southwestern United States, Using Machine Learning Algorithms S. Chatterjee et al. https://doi.org/10.3390/rs15205021
354. Impact of Soil Moisture Data Resolution on Soil Moisture and Surface Heat Flux Estimates through Data Assimilation: A Case Study in the Southern Great Plains Y. Lu et al. https://doi.org/10.1175/JHM-D-18-0234.1
355. On the usefulness of remote sensing input data for spatially distributed hydrological modelling: case of the Tarim River basin in China T. Liu et al. https://doi.org/10.1002/hyp.8129
356. Analysis of energy fluxes and vegetation-atmosphere parameters in irrigated and natural ecosystems of semi-arid Brazil A. Teixeira et al. https://doi.org/10.1016/j.jhydrol.2008.08.011
357. SEBS validation in a Spanish rotating crop N. Pardo et al. https://doi.org/10.1016/j.agrformet.2014.05.007
358. Developments and Future Strategies of Earth Science from Space in China J. SHI et al. https://doi.org/10.11728/cjss2021.01.095
359. Comparison of two methods to derive time series of actual evapotranspiration using eddy covariance measurements in the southeastern Australia G. Liu et al. https://doi.org/10.1016/j.jhydrol.2012.05.011
360. Improved global evapotranspiration estimates using proportionality hypothesis-based water balance constraints J. Fu et al. https://doi.org/10.1016/j.rse.2022.113140
361. Evapotranspiration‐based irrigation management technology and its application in China* X. Lei et al. https://doi.org/10.1002/ird.2517
362. Fusion of Five Satellite-Derived Products Using Extremely Randomized Trees to Estimate Terrestrial Latent Heat Flux over Europe K. Shang et al. https://doi.org/10.3390/rs12040687
363. Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach O. López Valencia et al. https://doi.org/10.5194/hess-24-5251-2020
364. Land Surface Temperature Retrieval for Agricultural Areas Using a Novel UAV Platform Equipped with a Thermal Infrared and Multispectral Sensor S. Heinemann et al. https://doi.org/10.3390/rs12071075
365. Evaluation of evapotranspiration models over semi‐arid and semi‐humid areas of China Z. Yang et al. https://doi.org/10.1002/hyp.10824
366. The use of dynamic global vegetation models for simulating hydrology and the potential integration of satellite observations S. Murray et al. https://doi.org/10.1177/0309133312460072
367. Influence of vineyard row orientation on evapotranspiration estimates from a satellite-based two-source energy balance model D. Salazar-Martínez et al. https://doi.org/10.1016/j.agwat.2025.109976
368. Urban surface heat fluxes infrared remote sensing inversion and their relationship with land use types Y. Liu et al. https://doi.org/10.1007/s11442-012-0957-7
369. Validation of evapotranspiration and its long-term trends in the Yellow River source region R. Liu et al. https://doi.org/10.2166/wcc.2017.134
370. Enhancing regional-scale simulation accuracy of paddy runoff by coupling water balance models with remote sensing H. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.132798
371. Temporal Upscaling and Reconstruction of Thermal Remotely Sensed Instantaneous Evapotranspiration T. Xu et al. https://doi.org/10.3390/rs70303400
372. A distributed thermodynamic model for energy and mass balance computation: FEST–EWB C. Corbari et al. https://doi.org/10.1002/hyp.7910
373. Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures L. Song et al. https://doi.org/10.1016/j.agrformet.2016.01.005
374. Spatiotemporal dynamics of evapotranspiration and implications for agricultural water management in the Lake Tana Basin, Ethiopia: a cloud-computing approach A. Worku et al. https://doi.org/10.1007/s00704-026-06473-8
375. Data fusion approach for predicting high resolution estimates of crop evapotranspiration F. Shimim et al. https://doi.org/10.1007/s11119-025-10273-x
376. Development of a Simple Remote Sensing EvapoTranspiration model (Sim-ReSET): Algorithm and model test Z. Sun et al. https://doi.org/10.1016/j.jhydrol.2009.07.054
377. Comparison of Actual Evapotranspiration assessment by satellite-based model SEBS and hydrological model BBH in northern Tunisia N. Abid et al. https://doi.org/10.5194/piahs-385-471-2024
378. Angular effect of MODIS emissivity products and its application to the split-window algorithm H. Ren et al. https://doi.org/10.1016/j.isprsjprs.2011.02.008
379. Impact of the spatial resolution on the energy balance components on an open-canopy olive orchard J. Ramírez-Cuesta et al. https://doi.org/10.1016/j.jag.2018.09.001
380. Effects of land cover change on evapotranspiration in the Yellow River Delta analyzed with the SEBAL model J. Ning et al. https://doi.org/10.1117/1.JRS.11.016009
381. A global assessment of PT-JPL soil evaporation in agroecosystems with optical, thermal, and microwave satellite data L. Zhang et al. https://doi.org/10.1016/j.agrformet.2021.108455
382. Estimating actual evapotranspiration of soil-vegetation system by combining a physics-based model and machine learning Y. Zhang et al. https://doi.org/10.1080/17538947.2026.2624207
383. Comparison of Satellite Based Models for Estimating Evapotranspiration of Soybean Crop S. Kadam et al. https://doi.org/10.52151/jae2025624.1967
384. Validating MODIS-derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region R. Tang et al. https://doi.org/10.1029/2010JD014543
385. Estimating surface energy fluxes using a dual‐source data assimilation approach adjoined to the heat diffusion equation S. Bateni & S. Liang https://doi.org/10.1029/2012JD017618
386. Evaluating the SSEBop and RSPMPT Models for Irrigated Fields Daily Evapotranspiration Mapping with MODIS and CMADS Data Q. Zhuang et al. https://doi.org/10.3390/agriculture11050424
387. Application of machine learning techniques to simulate the evaporative fraction and its relationship with environmental variables in corn crops T. Zenone et al. https://doi.org/10.1186/s13717-022-00400-1
388. Real-Time Estimation of Near-Surface Air Temperature over Greece Using Machine Learning Methods and LSA SAF Satellite Products A. Karagiannidis et al. https://doi.org/10.3390/rs17071112
389. Potential of Using Remote Sensing Techniques for Global Assessment of Water Footprint of Crops M. Romaguera et al. https://doi.org/10.3390/rs2041177
390. Reconciling the global terrestrial water budget using satellite remote sensing A. Sahoo et al. https://doi.org/10.1016/j.rse.2011.03.009
391. Using precipitation, vertical root distribution, and satellite‐retrieved vegetation information to parameterize water stress in a Penman‐Monteith approach to evapotranspiration modeling under Mediterranean climate Y. Bai et al. https://doi.org/10.1002/2016MS000702
392. Assessing the performance of a large-scale irrigation system by estimations of actual evapotranspiration obtained by Landsat satellite images resampled with cubic convolution H. Awada et al. https://doi.org/10.1016/j.jag.2018.10.016
393. Evapotranspiration Estimation with Small UAVs in Precision Agriculture H. Niu et al. https://doi.org/10.3390/s20226427
394. Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes T. Xia et al. https://doi.org/10.5194/hess-20-1523-2016
395. Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data‐Poor Regions J. Sheffield et al. https://doi.org/10.1029/2017WR022437
396. Surface Energy Exchanges during Pre-monsoon Thunderstorm Activity over a Tropical Station Kharagpur B. Tyagi et al. https://doi.org/10.1007/s00024-013-0682-x
397. Spatio-temporal estimation of consumptive water use for assessment of irrigation system performance and management of water resources in irrigated Indus Basin, Pakistan M. Usman et al. https://doi.org/10.1016/j.jhydrol.2015.03.031
398. Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data C. Corbari et al. https://doi.org/10.5194/hess-14-2141-2010
399. Surface energy and radiation budget over a tropical station: An observational study B. Tyagi et al. https://doi.org/10.1007/s13143-012-0037-z
400. Quantifying the Responses of Evapotranspiration and Its Components to Vegetation Restoration and Climate Change on the Loess Plateau of China L. Qiu et al. https://doi.org/10.3390/rs13122358
401. The Influence of Land Surface Temperature in Evapotranspiration Estimated by the S-SEBI Model N. Rocha et al. https://doi.org/10.3390/atmos11101059
402. High-Resolution Daily Evapotranspiration Estimation in Arid Agricultural Regions Based on Remote Sensing via an Improved PT-JPL and CUWFM Fusion Framework H. Liu et al. https://doi.org/10.3390/rs18020291
403. Regional evapotranspiration estimates using the relative soil moisture ratio derived from SMAP products E. Walker et al. https://doi.org/10.1016/j.agwat.2019.02.009
404. Estimation of Evapotranspiration in South Eastern Afghanistan Using the GCOM-C Algorithm on the Basis of Landsat Satellite Imagery E. Wali et al. https://doi.org/10.3390/hydrology11070095
405. Satellite-based estimation of actual evapotranspiration in the Buyuk Menderes Basin, Turkey H. Aksu & A. Arikan https://doi.org/10.2166/nh.2016.226
406. Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data Y. Ma et al. https://doi.org/10.1016/j.rse.2018.07.019
407. Remote Sensing for Vadose Zone Hydrology—A Synthesis from the Vantage Point B. Mohanty et al. https://doi.org/10.2136/vzj2013.07.0128
408. Inroads of remote sensing into hydrologic science during the WRR era D. Lettenmaier et al. https://doi.org/10.1002/2015WR017616
409. Analysis of variations and controls of evapotranspiration over major Indian River Basins (1982–2014) A. Soni & T. Syed https://doi.org/10.1016/j.scitotenv.2020.141892
410. Evaluation of four remote sensing algorithms in estimating actual evapotranspiration in agricultural environments P. Ratshiedana et al. https://doi.org/10.5194/hess-30-4383-2026
411. RETRACTED: A review and modelling results of the simulated response of deforestation on climate extremes in eastern Australia R. Deo https://doi.org/10.1016/j.atmosres.2012.01.007
412. Estimating Evapotranspiration from an Improved Two-Source Energy Balance Model Using ASTER Satellite Imagery Q. Zhuang & B. Wu https://doi.org/10.3390/w7126653
413. Two improved shuttleworth-wallace models for estimating consecutive daily evapotranspiration J. Zhao et al. https://doi.org/10.1016/j.agrformet.2025.110498
414. Urbanization Effect on Regional Thermal Environment and Its Mechanisms in Arid Zone Cities: A Case Study of Urumqi A. Abulimiti et al. https://doi.org/10.3390/rs16162939
415. Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin, India P. Teluguntla et al. https://doi.org/10.1002/hyp.13748
416. Quantification of Spatiotemporal Variability of Evapotranspiration (ET) and the Contribution of Influencing Factors for Different Land Cover Types in the Yunnan Province W. Su et al. https://doi.org/10.3390/w15183309
417. Satellite-based ET mapping to assess variation in ET with timing of crop development M. Tasumi & R. Allen https://doi.org/10.1016/j.agwat.2006.08.010
418. Estimating Surface Soil Heat Flux in Permafrost Regions Using Remote Sensing-Based Models on the Northern Qinghai-Tibetan Plateau under Clear-Sky Conditions C. Yang et al. https://doi.org/10.3390/rs11040416
419. Improving the Representation of Long‐Term Storage Variations With Conceptual Hydrological Models in Data‐Scarce Regions P. Hulsman et al. https://doi.org/10.1029/2020WR028837
420. A Spatial and Temporal Correlation between Remotely Sensing Evapotranspiration with Land Use and Land Cover S. Khoshnood et al. https://doi.org/10.3390/w15061068
421. Quantifying uncertainty in a remote sensing-based estimate of evapotranspiration over continental USA C. Ferguson et al. https://doi.org/10.1080/01431161.2010.483490
422. Coupling index of water consumption and soil fertility correlated with winter wheat production in North China Region E. Xu et al. https://doi.org/10.1016/j.ecolind.2019.02.045
423. A computational study of particulate emissions from Old Moor Quarry, UK G. Joseph et al. https://doi.org/10.1016/j.jweia.2017.10.018
424. A comparison of ASCAT and modelled soil moisture over South Africa, using TOPKAPI in land surface mode S. Sinclair & G. Pegram https://doi.org/10.5194/hess-14-613-2010
425. The application of satellite sensors, current state of utilization, and sources of remote sensing dataset in hydrology for water resource management D. Abegeja https://doi.org/10.2166/wh.2024.102
426. Impacts of land-use changes and landholding fragmentation on crop water demand and drought in Wadi El-Farigh, New Delta project, Egypt M. Elsharkawy et al. https://doi.org/10.1016/j.ejrs.2022.08.002
427. Regional actual evapotranspiration estimation and spatiotemporal evolution pattern in Northwest China X. Zhu et al. https://doi.org/10.1016/j.ecolind.2026.115238
428. Triple collocation-based multi-source evaporation and transpiration merging J. Park et al. https://doi.org/10.1016/j.agrformet.2023.109353
429. Extending the SCOPE model to combine optical reflectance and soil moisture observations for remote sensing of ecosystem functioning under water stress conditions B. Bayat et al. https://doi.org/10.1016/j.rse.2018.11.021
430. Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques M. Elhag & J. Bahrawi https://doi.org/10.5194/gi-6-141-2017
431. Partitioning Global Surface Energy and Their Controlling Factors Based on Machine Learning X. Yuan et al. https://doi.org/10.3390/rs12223712
432. Generating Hourly Continuous Evapotranspiration Using Fengyun‐2F Geostationary Satellite Data X. Geng et al. https://doi.org/10.1029/2021EA002090
433. Intercomparison of Spatially Distributed Models for Predicting Surface Energy Flux Patterns during SMACEX W. Crow et al. https://doi.org/10.1175/JHM468.1
434. Multiscale Assessment of Agricultural Consumptive Water Use in California's Central Valley A. Wong et al. https://doi.org/10.1029/2020WR028876
435. Continuous Daily Evapotranspiration Estimation at the Field-Scale over Heterogeneous Agricultural Areas by Fusing ASTER and MODIS Data Z. Yi et al. https://doi.org/10.3390/rs10111694
436. The intercomparison of six 0.1°×0.1° spatial resolution evapotranspiration products across mainland China X. Shi et al. https://doi.org/10.1016/j.jhydrol.2024.130949
437. A novel approach for estimating evapotranspiration by considering topographic effects in radiation over mountainous terrain Y. Zhang et al. https://doi.org/10.1016/j.agrformet.2025.110468
438. A worldwide evaluation of basin-scale evapotranspiration estimates against the water balance method W. Liu et al. https://doi.org/10.1016/j.jhydrol.2016.04.006
439. Evapotranspiration estimation using Landsat-8 data with a two-layer framework J. Yin et al. https://doi.org/10.1117/1.JRS.11.016034
440. The effect of pixel heterogeneity for remote sensing based retrievals of evapotranspiration in a semi-arid tree-grass ecosystem V. Burchard-Levine et al. https://doi.org/10.1016/j.rse.2021.112440
441. Refining surface net radiation estimates in arid and semi-arid climates of Iran F. Golkar et al. https://doi.org/10.1016/j.asr.2018.03.026
442. Estimating the spatial distribution of evapotranspiration within the Pra River Basin of Ghana J. Nsiah et al. https://doi.org/10.1016/j.heliyon.2021.e06828
443. Surface Energy Balance of Fresh and Saline Waters: AquaSEBS A. Abdelrady et al. https://doi.org/10.3390/rs8070583
444. Assimilation of Earth Observation Variables and In Situ Measurements in a Surface Energy Balance Model: A Case Study of a Desert City Area M. Lazzarini & H. Ghedira https://doi.org/10.1109/LGRS.2013.2258655
445. 100 Years of Progress in Hydrology C. Peters-Lidard et al. https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0019.1
446. Estimation of Hourly Actual Evapotranspiration Over the Tibetan Plateau from Multi-Source Data X. Wang et al. https://doi.org/10.2139/ssrn.4173880
447. Estimation of Soybean Evapotranspiration Using SSEBop Model with High-Resolution Imagery from an Unmanned Aerial Vehicle R. Casari et al. https://doi.org/10.1590/0102-77863910007
448. High-resolution satellite imagery reveals a recent accelerating rate of increase in land evapotranspiration H. Jaafar & L. Sujud https://doi.org/10.1016/j.rse.2024.114489
449. Large-Scale Spatial Modeling of Crop Coefficient and Biomass Production in Agroecosystems in Southeast Brazil C. De Oliveira Ferreira Silva et al. https://doi.org/10.3390/horticulturae4040044
450. An effective approach to estimate ground soil heat flux using half-order derivative method in permafrost regions of the Qinghai-Tibet Plateau C. Shang et al. https://doi.org/10.1016/j.ejrh.2025.102994
451. Evapotranspiration Estimation Using Surface Energy Balance System Model: A Case Study in the Nagqu River Basin L. Zhong et al. https://doi.org/10.3390/atmos10050268
452. Estimation of land surface evapotranspiration over complex terrain based on multi‐spectral remote sensing data X. Liu et al. https://doi.org/10.1002/hyp.11042
453. Estimation of global land surface evapotranspiration and its trend using a surface energy balance constrained deep learning model H. Chen et al. https://doi.org/10.1016/j.jhydrol.2023.130224
454. Modeling of sea surface temperature using a modified energy balance model: a regional climate change investigative approach T. Ayua et al. https://doi.org/10.1007/s00704-026-06287-8
455. Temporal Upscaling of Agricultural Evapotranspiration with an Improved Evaporative Fraction Method J. Wei et al. https://doi.org/10.3390/rs17061016
456. Determination of regional land surface heat fluxes over a heterogeneous landscape of the Jiddah area of Saudi Arabia by using Landsat‐7 ETM data Y. Ma et al. https://doi.org/10.1002/hyp.6389
457. Performance of the improved two-source energy balance model for estimating evapotranspiration over the heterogeneous surface J. Feng et al. https://doi.org/10.1016/j.agwat.2023.108159
458. Remote sensing and GIS-based WetSpass-S model for estimating actual evapotranspiration in Grombalia region, Northeast Tunisia: comparison with ETLook WaPOR model H. Sejine & M. Anane https://doi.org/10.1007/s41207-024-00628-7
459. Multi-site evaluation of terrestrial evaporation models using FLUXNET data A. Ershadi et al. https://doi.org/10.1016/j.agrformet.2013.11.008
460. Assessing Groundwater Storage Changes Using Remote Sensing–Based Evapotranspiration and Precipitation at a Large Semiarid Basin Scale M. Gokmen et al. https://doi.org/10.1175/JHM-D-12-0156.1
461. Estimation of ET and Crop Water Productivity in a Semi-Arid Region Using a Large Aperture Scintillometer and Remote Sensing-Based SETMI Model P. Singh et al. https://doi.org/10.3390/w16030422
462. Synthesizing a Regional Territorial Evapotranspiration Dataset for Northern China L. Wang et al. https://doi.org/10.3390/rs13061076
463. Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions B. Liu et al. https://doi.org/10.1016/j.agwat.2025.109634
464. An overview of the LOess Plateau mesa region land surface process field EXperiment series (LOPEXs) J. Wen et al. https://doi.org/10.5194/hess-13-945-2009
465. Evaluation of Remotely Sensed Evapotranspiration Over the CEOP EOP-1 Reference Sites H. SU et al. https://doi.org/10.2151/jmsj.85A.439
466. Energy partitioning dynamics of drying terrestrial surfaces M. Aminzadeh & D. Or https://doi.org/10.1016/j.jhydrol.2014.08.037
467. Quantifying riparian total evaporation along the Groot Letaba River: A comparison between infilled and spatially downscaled satellite derived total evaporation estimates S. Gokool et al. https://doi.org/10.1016/j.jaridenv.2017.07.014
468. An idealized sensitivity study of fine particles' impact on the urban vertical temperature structure H. Wu et al. https://doi.org/10.1016/j.uclim.2023.101492
469. Seasonal and interannual variation of radiation and energy fluxes over a rain-fed cropland in the semi-arid area of Loess Plateau, northwestern China X. Chen et al. https://doi.org/10.1016/j.atmosres.2016.03.003
470. Water consumption of agriculture and natural ecosystems at the Amu Darya in Lebap Province, Turkmenistan N. Thevs et al. https://doi.org/10.1007/s12665-014-3084-1
471. Integrating super resolution mapping and SEBS modeling for evapotranspiration mapping at the field scale M. Mahour et al. https://doi.org/10.1007/s11119-015-9395-8
472. Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications Z. Li et al. https://doi.org/10.1029/2022RG000777
473. Parameter Analysis and Estimates for the MODIS Evapotranspiration Algorithm and Multiscale Verification K. Zhang et al. https://doi.org/10.1029/2018WR023485
474. Evaluation of alternative two-source remote sensing models in partitioning of land evapotranspiration H. Chen et al. https://doi.org/10.1016/j.jhydrol.2021.126029
475. At-Surface Reflectance and Albedo from Satellite for Operational Calculation of Land Surface Energy Balance M. Tasumi et al. https://doi.org/10.1061/(ASCE)1084-0699(2008)13:2(51)
476. Assessing multi‐sensor hourly maize evapotranspiration estimation using a one‐source surface energy balance approach E. Costa‐Filho et al. https://doi.org/10.1002/ird.2923
477. Modeling and Spatiotemporal Analysis of Actual Evapotranspiration in a Desert Steppe Based on SEBS Y. Feng et al. https://doi.org/10.3390/hydrology12080205
478. OPTRAM-ET: A novel approach to remote sensing of actual evapotranspiration applied to Sentinel-2 and Landsat-8 observations A. Mokhtari et al. https://doi.org/10.1016/j.rse.2022.113443
479. Improvement approaches and performance of temperature-based remote sensing evapotranspiration models in agricultural fields: A meta analysis J. Ding et al. https://doi.org/10.1016/j.agrformet.2026.111166
480. Status of accuracy in remotely sensed and in-situ agricultural water productivity estimates: A review M. Blatchford et al. https://doi.org/10.1016/j.rse.2019.111413
481. Comparative Analysis of Satellite Remotely-Sensed Surface Energy Flux and Ground-Based Observation in the Sichuan Basin W. MIN et al. https://doi.org/10.2151/jmsj.2012-C15
482. Modelling of Basin Wide Daily Evapotranspiration with a Partial Integration of Remote Sensing Data V. Ivezic et al. https://doi.org/10.3390/atmos9040120
483. Evapotranspiration and Surface Energy Fluxes Estimation Using the Landsat-7 Enhanced Thematic Mapper Plus Image over a Semiarid Agrosystem in the North-West of Algeria N. Laounia et al. https://doi.org/10.1590/0102-7786324016
484. Evaluating evapotranspiration and water-use efficiency of terrestrial ecosystems in the conterminous United States using MODIS and AmeriFlux data X. Lu & Q. Zhuang https://doi.org/10.1016/j.rse.2010.04.001
485. Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests J. Gomis-Cebolla et al. https://doi.org/10.1016/j.jag.2019.04.009
486. Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels F. Li et al. https://doi.org/10.5194/hess-23-949-2019
487. Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa J. Kiptala et al. https://doi.org/10.5194/hess-18-2287-2014
488. Precision mapping of evapotranspiration in arid basins: Spatiotemporal optimization and sensitivity to extreme climate conditions based on multi-mechanism model fusion X. Li et al. https://doi.org/10.1016/j.jhydrol.2026.135795
489. The Two-layer Surface Energy Balance Parameterization Scheme (TSEBPS) for estimation of land surface heat fluxes X. Xin & Q. Liu https://doi.org/10.5194/hess-14-491-2010
490. Application of SEBAL Model for Mapping Evapotranspiration and Estimating Surface Energy Fluxes in South-Central Nebraska R. Singh et al. https://doi.org/10.1061/(ASCE)0733-9437(2008)134:3(273)
491. Regionalization of land surface heat fluxes over the heterogeneous landscape: from the Tibetan Plateau to the Third Pole region Y. Ma et al. https://doi.org/10.1080/01431161.2018.1508923
492. Surface energy balance-based surface urban heat island decomposition at high resolution F. Guo et al. https://doi.org/10.1016/j.rse.2024.114447
493. Accessible remote sensing data based reference evapotranspiration estimation modelling Z. Zhang et al. https://doi.org/10.1016/j.agwat.2018.07.039
494. A Full Satellite‐Driven Method for the Retrieval of Clear‐Sky Evapotranspiration P. Leng et al. https://doi.org/10.1029/2019EA000869
495. Evaluation of irrigation water use efficiency using remote sensing in the middle reach of the Heihe river, in the semi‐arid Northwestern China X. Wu et al. https://doi.org/10.1002/hyp.10365
496. Using uncertainty of Penman and Penman–Monteith methods in combined satellite and ground-based evapotranspiration estimates R. Westerhoff https://doi.org/10.1016/j.rse.2015.07.021
497. Assessing Satellite and Ground‐Based Potential Evapotranspiration for Hydrologic Applications in the Colorado River Basin M. Barik et al. https://doi.org/10.1111/1752-1688.12370
498. Determining Evapotranspiration by Using Combination Equation Models with Sentinel-2 Data and Comparison with Thermal-Based Energy Balance in a California Irrigated Vineyard G. D’Urso et al. https://doi.org/10.3390/rs13183720
499. A new roughness parameterization scheme based on vegetation dynamics and its applicability on the Tibetan Plateau Y. Yuan et al. https://doi.org/10.1016/j.jhydrol.2025.132822
500. Bias Analysis and Correction of Ground Surface Temperature Observations across China Y. Cui et al. https://doi.org/10.1007/s13351-020-0031-9
501. Evapotranspiration partitioning by integrating eddy covariance, micro-lysimeter and unmanned aerial vehicle observations: A case study in the North China Plain J. Bian et al. https://doi.org/10.1016/j.agwat.2024.108735
502. Analysis of various surface energy balance models for evapotranspiration estimation using satellite data B. Aryalekshmi et al. https://doi.org/10.1016/j.ejrs.2021.11.007
503. Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment R. Guzinski et al. https://doi.org/10.5194/hess-19-2017-2015
504. Estimation of Daily Actual Evapotranspiration Using Vegetation Coefficient Method for Clear and Cloudy Sky Conditions H. Shwetha & D. Kumar https://doi.org/10.1109/JSTARS.2020.2989422
505. A Novel Framework Based on Data Fusion and Machine Learning for Upscaling Evapotranspiration from Flux Towers to the Regional Scale P. Zhu et al. https://doi.org/10.3390/rs17233813
506. Practical analysis of remote sensing estimations of water use for major crops throughout the Urmia Lake basin M. Parsinejad et al. https://doi.org/10.1016/j.agwat.2021.107232
507. Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model K. Khand et al. https://doi.org/10.3390/hydrology4040049
508. Construction of a spatially gridded heat flux map based on airborne flux Measurements using remote sensing and machine learning methods Y. Sun et al. https://doi.org/10.1016/j.agrformet.2023.109424
509. A Modified Multi-Source Parallel Model for Estimating Urban Surface Evapotranspiration Based on ASTER Thermal Infrared Data Y. Zhang et al. https://doi.org/10.3390/rs9101029
510. Evapotranspiration Acquired with Remote Sensing Thermal-Based Algorithms: A State-of-the-Art Review V. García-Santos et al. https://doi.org/10.3390/rs14143440
511. Development of the GCOM-C global ET_index estimation algorithm M. TASUMI et al. https://doi.org/10.2480/agrmet.D-15-00022
512. High resolution evapotranspiration from UAV multispectral thermal imagery: Validation and comparison with EC, Landsat, and fused S2-MODIS HSEB ET H. H. Jaafar & L. H. Sujud https://doi.org/10.1016/j.jag.2025.104359
513. Insight into runoff characteristics using hydrological modeling in the data-scarce southern Tibetan Plateau: Past, present, and future M. Cai et al. https://doi.org/10.1371/journal.pone.0176813
514. Applying Multi-source Remote Sensing Data on Estimating Ecological Water Requirement of Grassland in Ungauged Region Y. Zhang et al. https://doi.org/10.1016/j.proenv.2010.10.107
515. Improvement of the Irrigation Scheme in the ORCHIDEE Land Surface Model and Impacts of Irrigation on Regional Water Budgets Over China Z. Yin et al. https://doi.org/10.1029/2019MS001770
516. geeSSEBI: Evaluating Actual Evapotranspiration Estimated with a Google Earth Engine Implementation of S-SEBI J. Kabala et al. https://doi.org/10.3390/rs17030395
517. A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation M. Anderson et al. https://doi.org/10.1029/2006JD007506
518. Intercomparison of methods for estimating land surface temperature from a Landsat-5 TM image in an arid region with low water vapour in the atmosphere J. Zhou et al. https://doi.org/10.1080/01431161.2011.617396
519. COMS-Based Retrieval of Daily Actual Evapotranspiration over Korea N. Park et al. https://doi.org/10.1155/2017/2151809
520. Actual Evapotranspiration from UAV Images: A Multi-Sensor Data Fusion Approach A. Mokhtari et al. https://doi.org/10.3390/rs13122315
521. A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas A. Ruhoff et al. https://doi.org/10.3390/rs4030703
522. Daily Evaporative Fraction Parameterization Scheme Driven by Day–Night Differences in Surface Parameters: Improvement and Validation J. Lu et al. https://doi.org/10.3390/rs6054369
523. Upscaling analysis of aerodynamic roughness length based on in situ data at different spatial scales and remote sensing in north Tibetan Plateau G. Sun et al. https://doi.org/10.1016/j.atmosres.2016.02.025
524. Performance Assessment of a New Stationarity-Based Parameter Estimation Method with a Simplified Land Surface Model Using In Situ and Remotely Sensed Surface States J. Sun & G. Salvucci https://doi.org/10.1175/JHM-D-12-0118.1
525. Estimation of Spatial Evapotranspiration Using Terra MODIS Satellite Image and SEBAL Model Y. LEE https://doi.org/10.11108/kagis.2015.18.1.090
526. A practical method for deriving all-weather ET from remote sensing and meteorological data P. Hao et al. https://doi.org/10.1016/j.jag.2025.104948
527. Assessing regional evapotranspiration and water balance across a Mediterranean montane climate gradient R. Anderson et al. https://doi.org/10.1016/j.agrformet.2012.07.004
528. Comparing Remotely-Sensed Surface Energy Balance Evapotranspiration Estimates in Heterogeneous and Data-Limited Regions: A Case Study of Tanzania’s Kilombero Valley W. Senkondo et al. https://doi.org/10.3390/rs11111289
529. Earth Observations-Based Evapotranspiration in Northeastern Thailand C. Zheng et al. https://doi.org/10.3390/rs11020138
530. Optimizing the Runoff Estimation with HEC-HMS Model Using Spatial Evapotranspiration by the SEBS Model M. Zare et al. https://doi.org/10.1007/s11269-021-02855-x
531. Remote detection of water management impacts on evapotranspiration in the Colorado River Basin S. Castle et al. https://doi.org/10.1002/2016GL068675
532. Crop stress detection from UAVs: best practices and lessons learned for exploiting sensor synergies E. Chakhvashvili et al. https://doi.org/10.1007/s11119-024-10168-3
533. Application of SEBAL and Ts/VI Trapezoid Models for Estimating Actual Evapotranspiration in the Algerian Semi-Arid Environment to Improve Agricultural Water Management F. Sahnoun et al. https://doi.org/10.1590/0102-77863610020
534. Assessing the Complementary Role of Surface Flux Equilibrium (SFE) Theory and Maximum Entropy Production (MEP) Principle in the Estimation of Actual Evapotranspiration Y. Kim et al. https://doi.org/10.1029/2022MS003224
535. An Improvement of Roughness Height Parameterization of the Surface Energy Balance System (SEBS) over the Tibetan Plateau X. Chen et al. https://doi.org/10.1175/JAMC-D-12-056.1
536. Assimilation of multiple data types for improved heat flux prediction: A one-dimensional field study R. Pipunic et al. https://doi.org/10.1016/j.rse.2013.05.015
537. Reintroducing radiometric surface temperature into the Penman‐Monteith formulation K. Mallick et al. https://doi.org/10.1002/2014WR016106
538. Land Surface Temperature Retrieval Using Airborne Hyperspectral Scanner Daytime Mid-Infrared Data E. Zhao et al. https://doi.org/10.3390/rs61212667
539. Modeling of Indian monsoon extremes during 850-2000AD using the proxy-data from speleothems P. Kumar et al. https://doi.org/10.1016/j.quaint.2021.02.009
540. Evaluation of Methods for Aerodynamic Roughness Length Retrieval from Very High-Resolution Imaging LIDAR Observations over the Heihe Basin in China R. Faivre et al. https://doi.org/10.3390/rs9010063
541. Temporal upscaling of instantaneous evapotranspiration on clear‐sky days using the constant reference evaporative fraction method with fixed or variable surface resistances at two cropland sites R. Tang et al. https://doi.org/10.1002/2016JD025975
542. Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: key scientific strides and challenges T. Govender et al. https://doi.org/10.1080/10106049.2022.2043451
543. Assessment of Blaney-Criddle Equation for Calculating Reference Evapotranspiration with NOAA/AVHRR Data A. Rahimikhoob & M. Hosseinzadeh https://doi.org/10.1007/s11269-014-0670-7
544. Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system C. Brenner et al. https://doi.org/10.1080/01431161.2017.1280202
545. Artificial intelligence and remote sensing for spatial prediction of daily air temperature: case study of Souss watershed of Morocco M. Meliho et al. https://doi.org/10.1080/10095020.2021.2014765
546. Impact of regional characteristics on the estimation of root-zone soil moisture from the evaporative index or evaporative fraction S. Sahaar & J. Niemann https://doi.org/10.1016/j.agwat.2020.106225
547. Remote Sensing—Based Assessment of the Water-Use Efficiency of Maize over a Large, Arid, Regional Irrigation District L. Jiang et al. https://doi.org/10.3390/rs14092035
548. Estimation of actual evapotranspiration and its components in an irrigated area by integrating the Shuttleworth-Wallace and surface temperature-vegetation index schemes using the particle swarm optimization algorithm Y. Cui et al. https://doi.org/10.1016/j.agrformet.2021.108488
549. Spatiotemporal patterns and driving factors of evapotranspiration (natural and artificial) in the Ziya River Basin, China W. Yan et al. https://doi.org/10.1016/j.ecohyd.2023.04.012
550. Estimation and Validation of Land Surface Evaporation Using Remote Sensing and Meteorological Data in North China J. Xiong et al. https://doi.org/10.1109/JSTARS.2010.2040806
551. Evaluation of the LI-710 evapotranspiration sensor in comparison to full eddy covariance for monitoring energy fluxes in perennial and annual crops S. Peddinti & I. Kisekka https://doi.org/10.1016/j.agwat.2025.109501
552. The Improvement of Land Cover Classification by Thermal Remote Sensing L. Sun & K. Schulz https://doi.org/10.3390/rs70708368
553. RETDNet: A Hierarchical Physical-Factor-Driven Network for Robust LST Interpolation and Prediction M. Xuan et al. https://doi.org/10.1109/TGRS.2026.3704809
554. A high performance GPU implementation of Surface Energy Balance System (SEBS) based on CUDA-C M. Abouali et al. https://doi.org/10.1016/j.envsoft.2012.12.005
555. Evaluating the Temperature Difference Parameter in the SSEBop Model with Satellite-Observed Land Surface Temperature Data L. Ji et al. https://doi.org/10.3390/rs11161947
556. Use of Remote Sensing to Assess the Water-Saving Effect of Winter Wheat Fallow L. Zhai et al. https://doi.org/10.3390/su131810192
557. Exploring scale‐dependent ecohydrological responses in a large endorheic river basin through integrated surface water‐groundwater modeling Y. Tian et al. https://doi.org/10.1002/2015WR016881
558. Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass E. Delogu et al. https://doi.org/10.5194/hess-16-2995-2012
559. Review of approaches for the estimation of sensible heat flux in remote sensing-based evapotranspiration models M. Mohan et al. https://doi.org/10.1117/1.JRS.14.041501
560. An improved constant evaporative fraction method for estimating daily evapotranspiration from remotely sensed instantaneous observations R. Tang & Z. Li https://doi.org/10.1002/2017GL072621
561. Reconciling the water balance of large lake systems A. Gronewold et al. https://doi.org/10.1016/j.advwatres.2020.103505
562. Interannual Variations of Evapotranspiration and Water Use Efficiency over an Oasis Cropland in Arid Regions of North-Western China H. Wang et al. https://doi.org/10.3390/w12051239
563. Prospects of Improving Agricultural and Water Productivity through Unmanned Aerial Vehicles L. Nhamo et al. https://doi.org/10.3390/agriculture10070256
564. estimation of ecosystem water consumption and the suitable scale of cultivated land in the Karamay region and Muzat River basin based on the optimized SEBAL energy balance model and water resource constraint model J. Ping et al. https://doi.org/10.1016/j.heliyon.2024.e28190
565. Downscaling and Forecasting of Evapotranspiration Using a Synthetic Model of Wavelets and Support Vector Machines Y. Kaheil et al. https://doi.org/10.1109/TGRS.2008.919819
566. Land-surface controls on afternoon precipitation diagnosed from observational data: uncertainties and confounding factors B. Guillod et al. https://doi.org/10.5194/acp-14-8343-2014
567. The accuracy of temporal upscaling of instantaneous evapotranspiration to daily values with seven upscaling methods Z. Liu https://doi.org/10.5194/hess-25-4417-2021
568. Increasing evapotranspiration trend and the dominant driving factors in the oasis areas of the Tarim Basin, China J. Lang et al. https://doi.org/10.1080/15324982.2025.2491452
569. Estimating Sensible and Latent Heat Fluxes over an Inland Water Body Using Optical and Microwave Scintillometers A. Pierre et al. https://doi.org/10.1007/s10546-022-00732-7
570. Mapping basin-level water productivity using remote sensing and secondary data in the Karkheh River Basin, Iran M. Ahmad et al. https://doi.org/10.1080/02508060802663903
571. A double two-sources energy-water balance model for improving evapotranspiration estimates and irrigation management in fruit trees fields C. Corbari et al. https://doi.org/10.1016/j.agwat.2023.108522
572. Estimation of actual evapotranspiration of Mediterranean perennial crops by means of remote-sensing based surface energy balance models M. Minacapilli et al. https://doi.org/10.5194/hess-13-1061-2009
573. Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach L. Sun et al. https://doi.org/10.1002/2017WR020700
574. Using regional characteristics to improve uncalibrated estimation of rootzone soil moisture from optical/thermal remote-sensing S. Sahaar et al. https://doi.org/10.1016/j.rse.2022.112982
575. Evaluation of satellite-retrieved evapotranspiration based on a nonparametric approach over an arid region X. Pan et al. https://doi.org/10.1080/01431161.2020.1763505
576. Extracting phreatic evaporation from remotely sensed maps of evapotranspiration P. Brunner et al. https://doi.org/10.1029/2007WR006063
577. How climate variations are reflected in root zone storage capacities T. de Boer-Euser et al. https://doi.org/10.1016/j.pce.2019.04.006
578. Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin N. Paciolla et al. https://doi.org/10.1016/j.jaridenv.2021.104466
579. Remote sensing estimation of urban surface evapotranspiration based on a modified Penman–Monteith model Y. Zhang et al. https://doi.org/10.1117/1.JRS.12.046006
580. Evaluating a new algorithm for satellite-based evapotranspiration for North American ecosystems: Model development and validation B. El Masri et al. https://doi.org/10.1016/j.agrformet.2019.01.025
581. Diagnostic analysis of interannual variation of global land evapotranspiration over 1982–2011: Assessing the impact of ENSO H. Yan et al. https://doi.org/10.1002/jgrd.50693
582. A Universal Ts‐VI Triangle Method for the Continuous Retrieval of Evaporative Fraction From MODIS Products W. Zhu et al. https://doi.org/10.1002/2017JD026964
583. Estimation of hourly actual evapotranspiration over the Tibetan Plateau from multi-source data X. Wang et al. https://doi.org/10.1016/j.atmosres.2022.106475
584. Comparison and application of remote sensing evapotranspiration retrieval models for the Inner Mongolian grassland region K. Qiao et al. https://doi.org/10.1016/j.agwat.2026.110833
585. Regional evaporation estimates from flux tower and MODIS satellite data H. Cleugh et al. https://doi.org/10.1016/j.rse.2006.07.007
586. A framework of crop water productivity estimation from UAV observations: A case study of summer maize M. Cheng et al. https://doi.org/10.1016/j.agwat.2025.109621
587. On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT‐JPL M. Marshall et al. https://doi.org/10.1029/2019WR026290
588. Spatially explicit estimation of soil denitrification rates and land use effects in the riparian buffer zone of the large Guanting reservoir X. Wang et al. https://doi.org/10.1016/j.geoderma.2009.01.026
589. ET mapping for agricultural water management: present status and challenges P. Gowda et al. https://doi.org/10.1007/s00271-007-0088-6
590. Improvements to a MODIS global terrestrial evapotranspiration algorithm Q. Mu et al. https://doi.org/10.1016/j.rse.2011.02.019
591. A revised surface resistance parameterisation for estimating latent heat flux from remotely sensed data Y. Song et al. https://doi.org/10.1016/j.jag.2011.10.011
592. Assessment of the best management practices under a semi-arid basin using SWAT model (case of M’dez watershed, Morocco) M. Boufala et al. https://doi.org/10.1007/s40808-021-01123-6
593. Developing a dynamic semi-distributed hydrological model considering interactions between soil moisture and evapotranspiration: application of bulk transfer method M. Taheri et al. https://doi.org/10.1080/02626667.2022.2155522
594. Testing the performance of a thermal-based crop coefficient technique in Idaho as a fundamental study for global ET estimation A. FUJII & M. TASUMI https://doi.org/10.2480/agrmet.69.3.5
595. Quantifying a Reliable Framework to Estimate Hydro-Climatic Conditions via a Three-Way Interaction between Land Surface Temperature, Evapotranspiration, Soil Moisture M. Taheri et al. https://doi.org/10.3390/atmos13111916
596. Development and validation of physically constrained machine learning for improving remote sensing-based evapotranspiration estimation J. Wei et al. https://doi.org/10.1016/j.rse.2026.115460
597. Improved methods for estimating monthly and growing season ET using METRIC applied to moderate resolution satellite imagery J. Kjaersgaard et al. https://doi.org/10.1002/hyp.8394
598. Impact of water stress on Mediterranean oak savanna grasslands productivity: Implications for on-farm grazing management M. Muñoz-Gómez et al. https://doi.org/10.1016/j.agwat.2024.109025
599. Estimation of soil moisture in the root-zone from remote sensing data B. Bezerra et al. https://doi.org/10.1590/S0100-06832013000300005
600. Satellite-based evapotranspiration over Gezira Irrigation Scheme, Sudan: A comparative study I. Al Zayed et al. https://doi.org/10.1016/j.agwat.2016.06.027
601. Utility of remote sensing-based surface energy balance models to track water stress in rain-fed switchgrass under dry and wet conditions N. Bhattarai et al. https://doi.org/10.1016/j.isprsjprs.2017.10.010
602. Analysis of the land surface heterogeneity and its impact on atmospheric variables and the aerodynamic and thermodynamic roughness lengths Y. Ma et al. https://doi.org/10.1029/2007JD009124
603. Groundwater use of a small Eucalyptus patch during the dry monsoon phase T. Enku et al. https://doi.org/10.2478/s11756-020-00430-0
604. Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations E. Tajfar et al. https://doi.org/10.3390/rs12071065
605. Estimating selected cultivated crop water requirement-based surface energy balance algorithm M. Asadi & K. Kamran https://doi.org/10.1007/s12517-023-11386-1
606. Global evapotranspiration estimation based on nonparametric methods: validation and comparison S. Liu et al. https://doi.org/10.1080/01431161.2026.2732268
607. Advances in water resources research in the Upper Blue Nile basin and the way forward: A review Y. Dile et al. https://doi.org/10.1016/j.jhydrol.2018.03.042
608. Linking observation, modelling and satellite-based estimation of global land evapotranspiration J. Zhang et al. https://doi.org/10.1080/20964471.2020.1743612
609. Approaches to assessing the daily average ground surface soil heat flux on a regional scale over the Qinghai-Tibet Plateau C. Yang et al. https://doi.org/10.1016/j.agrformet.2023.109494
610. Assessment of the Relationship Between NDVI-Based Actual Evapotranspiration by SEBS M. Arast et al. https://doi.org/10.1007/s40995-020-00895-3
611. Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces H. Nouri et al. https://doi.org/10.1002/hyp.13790
612. Characteristic Decrease in the Value of Rapeseed Evapotranspiration after Its Ripening J. Leśny et al. https://doi.org/10.3390/agronomy11122523
613. Mapping super high resolution evapotranspiration in oasis-desert areas using UAV multi-sensor data J. Wei et al. https://doi.org/10.1016/j.agwat.2023.108466
614. The comparison between single-point method and footprint-integrated validation method of the remote-sensing retrieval of evapotranspiration: a case study at Daman site Y. Zhou et al. https://doi.org/10.1080/01431161.2024.2412803
615. Validation of Satellite-Derived Sensible Heat Flux for TERRA/MODIS Images Over Three Different Landscapes Using Large Aperture Scintillometer and Eddy Covariance Measurements M. Rahman & W. Zhang https://doi.org/10.1109/JSTARS.2019.2928880
616. Comprehensive accuracy assessment of long-term geostationary SEVIRI-MSG evapotranspiration estimates across Europe B. Bayat et al. https://doi.org/10.1016/j.rse.2023.113875
617. Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review G. Balsamo et al. https://doi.org/10.3390/rs10122038
618. Evapotranspiration Estimation with the S-SEBI Method from Landsat 8 Data against Lysimeter Measurements at the Barrax Site, Spain J. Sobrino et al. https://doi.org/10.3390/rs13183686
619. Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation P. Gowda et al. https://doi.org/10.2136/vzj2012.0110
620. Exploring the interannual and spatial variations of ET and GPP with climate by a physical model and remote sensing data in a large basin of Northeast China X. Mo et al. https://doi.org/10.1002/joc.3813
621. A review of remote sensing estimation of crop water productivity: definition, methodology, scale, and evaluation M. Cheng et al. https://doi.org/10.1080/01431161.2023.2240523
622. Application of a simple algorithm to estimate daily evapotranspiration from NOAA–AVHRR images for the Iberian Peninsula J. Sobrino et al. https://doi.org/10.1016/j.rse.2007.02.017
623. Using remotely sensed data to estimate area-averaged daily surface fluxes over a semi-arid mixed agricultural land C. Abdelghani et al. https://doi.org/10.1016/j.agrformet.2007.09.014
624. Particular uncertainties encountered in using a pre-packaged SEBS model to derive evapotranspiration in a heterogeneous study area in South Africa L. Gibson et al. https://doi.org/10.5194/hess-15-295-2011
625. Techniques for ground-based soil moisture measurement: a detailed overview M. Mukhlisin et al. https://doi.org/10.1007/s12517-021-08263-0
626. A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data Z. Li et al. https://doi.org/10.3390/s90503801
627. Evaluation of Evapotranspiration Models Using Different LAI and Meteorological Forcing Data from 1982 to 2017 H. Chen et al. https://doi.org/10.3390/rs12152473
628. Estimation of regional evapotranspiration over the Hebei Plain using geostationary satellite data Y. SHU et al. https://doi.org/10.3724/SP.J.1011.2011.01151
629. Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets R. Wartenburger et al. https://doi.org/10.1088/1748-9326/aac4bb
630. Early prediction of wheat grain yield production from root-zone soil water content at heading using Crop RS-Met D. Helman et al. https://doi.org/10.1016/j.fcr.2018.12.003
631. Auto-correcting for atmospheric effects in thermal hyperspectral measurements J. Timmermans et al. https://doi.org/10.1016/j.jag.2018.04.007
632. First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry Z. Peng et al. https://doi.org/10.1016/j.rse.2023.113970
633. ECOSTRESS: NASA's Next Generation Mission to Measure Evapotranspiration From the International Space Station J. Fisher et al. https://doi.org/10.1029/2019WR026058
634. Assessment of an extended SPARSE model for estimating evapotranspiration from directional thermal infrared data S. Mwangi et al. https://doi.org/10.1016/j.agrformet.2022.108882
635. Estimation of actual evapotranspiration using TDTM model and MODIS derived variables M. Ruiz-Álvarez et al. https://doi.org/10.1080/10106049.2021.2017011
636. SURFACE ENERGY BALANCE SYSTEM (SEBS) AND SATELLITE DATA FOR MONITORING WATER CONSUMPTION OF IRRIGATED SUGARCANE E. Ferreira et al. https://doi.org/10.1590/1809-4430-eng.agric.v36n6p1176-1185/2016
637. Quantifying the uncertainty in estimates of surface–atmosphere fluxes through joint evaluation of the SEBS and SCOPE models J. Timmermans et al. https://doi.org/10.5194/hess-17-1561-2013
638. Monthly evapotranspiration estimation using optimal climatic parameters: efficacy of hybrid support vector regression integrated with whale optimization algorithm Y. Tikhamarine et al. https://doi.org/10.1007/s10661-020-08659-7
639. Contact and directional radiative temperature measurements of sunlit and shaded land surface components during the SEN2FLEX 2005 campaign J. Timmermans et al. https://doi.org/10.1080/01431160802036599
640. A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes K. Mallick et al. https://doi.org/10.1016/j.rse.2013.10.022
641. Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains X. Tian et al. https://doi.org/10.3390/rs71215806
642. Estimation of Bowen ratio in complex urban area by remotely sensed data H. Gan et al. https://doi.org/10.1016/j.scs.2026.107288
643. A Modeling Framework for Deriving Daily Time Series of Evapotranspiration Maps Using a Surface Energy Balance Model K. Khand et al. https://doi.org/10.3390/rs11050508
644. An Intercomparison of Satellite-Based Daily Evapotranspiration Estimates under Different Eco-Climatic Regions in South Africa N. Majozi et al. https://doi.org/10.3390/rs9040307
645. Trends of evaporation in Brazilian tropical reservoirs using remote sensing I. Rodrigues et al. https://doi.org/10.1016/j.jhydrol.2021.126473
646. Connectivity of evapotranspiration processes in a Brazilian dryland reservoir using remote sensing I. Rodrigues et al. https://doi.org/10.1016/j.agrformet.2024.110017
647. Using satellite remote sensing to assess evapotranspiration: Case study of the upper Ewaso Ng’iro North Basin, Kenya J. Mutiga et al. https://doi.org/10.1016/j.jag.2009.09.012
648. Energy balance and irrigation performance assessments in lemon orchards by applying the SAFER algorithm to Landsat 8 images A. Teixeira et al. https://doi.org/10.1016/j.agwat.2020.106725
649. Estimating crop coefficients for pistachios and grapes using SEBAL and simple reference evapotranspiration methods in the Central basin of Iran H. Malakinezhad et al. https://doi.org/10.1007/s12517-022-10853-5
650. How can urban water bodies be designed for climate adaptation? R. Sun & L. Chen https://doi.org/10.1016/j.landurbplan.2011.11.018
651. Actual Evapotranspiration (Water Use) Assessment of the Colorado River Basin at the Landsat Resolution Using the Operational Simplified Surface Energy Balance Model R. Singh et al. https://doi.org/10.3390/rs6010233
652. Improving the Xin'anjiang hydrological model based on mass–energy balance Y. Fang et al. https://doi.org/10.5194/hess-21-3359-2017
653. Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index X. He et al. https://doi.org/10.1029/2020WR028224
654. Necessity and feasibility for an ET-based modern water resources management strategy: A case study of soil water resources in the Yellow River Basin H. Wang et al. https://doi.org/10.1007/s11431-009-0102-8
655. Using solar-induced chlorophyll fluorescence to estimate forest evapotranspiration X. Liu et al. https://doi.org/10.1016/j.jhydrol.2025.133595
656. Improving iterative surface energy balance convergence for remote sensing based flux calculation R. Dhungel et al. https://doi.org/10.1117/1.JRS.10.026033
657. Incorporating an iterative energy restraint for the Surface Energy Balance System (SEBS) E. Webster et al. https://doi.org/10.1016/j.rse.2017.06.012
658. Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration E. Glenn et al. https://doi.org/10.1080/07352680701402503
659. A Global Intercomparison of Modeled and Observed Land–Atmosphere Coupling* C. Ferguson et al. https://doi.org/10.1175/JHM-D-11-0119.1
660. A Simple Model for Determining Reference Evapotranspiration Using NOAA Satellite Data: a Case Study S. Alavi & A. Rahimikhoob https://doi.org/10.1007/s40710-016-0141-7
661. Evaluation of a moderate resolution imaging spectroradiometer triangle-based algorithm for evapotranspiration estimates in subalpine regions K. Knipper et al. https://doi.org/10.1117/1.JRS.10.016002
662. Seasonal effects of irrigation on land–atmosphere latent heat, sensible heat, and carbon fluxes in semiarid basin Y. Zeng et al. https://doi.org/10.5194/esd-8-113-2017
663. Assessing Variations in Water Use Efficiency and Linkages with Land-Use Changes Using Three Different Data Sources: A Case Study of the Yellow River, China H. Sun et al. https://doi.org/10.3390/rs14051065
664. Estimating evapotranspiration using earth observation data: A comparison between hydrological and energy balance modelling approaches T. Peerbhai et al. https://doi.org/10.1016/j.jhydrol.2022.128347
665. Impact of scale/resolution on evapotranspiration from Landsat and MODIS images V. Sharma et al. https://doi.org/10.1002/2015WR017772
666. Spatio‐temporal distribution of actual evapotranspiration in the Indus Basin Irrigation System U. Liaqat et al. https://doi.org/10.1002/hyp.10401
667. A coupled remote sensing and the Surface Energy Balance with Topography Algorithm (SEBTA) to estimate actual evapotranspiration over heterogeneous terrain Z. Gao et al. https://doi.org/10.5194/hess-15-119-2011
668. A Review of Evapotranspiration Estimation Models: Advances and Future Development Y. Xue et al. https://doi.org/10.1007/s11269-025-04191-w
669. Analysis of the effect of seasonal changes on sensitive parameters of LAI-based Penman–Monteith evapotranspiration model based on particle swarm algorithm H. Duan et al. https://doi.org/10.1007/s11600-022-00959-5
670. A dual-source energy balance model-assisted ensemble learning approach for estimating latent heat flux L. Wang et al. https://doi.org/10.1007/s00704-025-05634-5
671. An unmixing-based spatial downscaling fusion approach for the MODIS evapotranspiration product H. Lu et al. https://doi.org/10.1080/10106049.2022.2068674
672. High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region J. Yan et al. https://doi.org/10.3390/land10040396
673. Estimating soil moisture storage change using quasi-terrestrial water balance method J. Moiwo et al. https://doi.org/10.1016/j.agwat.2011.10.003
674. A physical-based two-source evapotranspiration model with Monin–Obukhov similarity theory M. Khan et al. https://doi.org/10.1080/15481603.2020.1857625
675. Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin T. Lian et al. https://doi.org/10.3390/rs14061349
676. Synergistic estimates of global 4-day 500 m gross primary production, evapotranspiration, and ecosystem water use efficiency from satellite data Y. Sun et al. https://doi.org/10.1016/j.jhydrol.2025.133506
677. Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China X. Li et al. https://doi.org/10.3390/rs13081524
678. An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data B. Ait Hssaine et al. https://doi.org/10.5194/hess-24-1781-2020
679. Spatial and Temporal Characteristics of Evapotranspiration in the Upper Minjiang River Basin Based on the SiB2 Model B. Kong et al. https://doi.org/10.3390/land11081141
680. Actual Evapotranspiration Estimation Using Sentinel-1 SAR and Sentinel-3 SLSTR Data Combined with a Gradient Boosting Machine Model in Busia County, Western Kenya P. Musyimi et al. https://doi.org/10.3390/atmos13111927
681. The MISTIGRI thermal infrared project: scientific objectives and mission specifications J. Lagouarde et al. https://doi.org/10.1080/01431161.2012.716921
682. Detection of hydrological variations and their impacts on vegetation from multiple satellite observations in the Three-River Source Region of the Tibetan Plateau M. Xu et al. https://doi.org/10.1016/j.scitotenv.2018.05.226
683. The vertical turbulent structure within the surface boundary layer above a Vineyard in California’s Central Valley during GRAPEX J. Alfieri et al. https://doi.org/10.1007/s00271-022-00779-x
684. Continental-scale net radiation and evapotranspiration estimated using MODIS satellite observations Y. Jin et al. https://doi.org/10.1016/j.rse.2011.04.031
685. High-resolution crop yield and water productivity dataset generated using random forest and remote sensing M. Cheng et al. https://doi.org/10.1038/s41597-022-01761-0
686. Dynamic Mapping of Evapotranspiration Using an Energy Balance-Based Model over an Andean Páramo Catchment of Southern Ecuador G. Carrillo-Rojas et al. https://doi.org/10.3390/rs8020160
687. Obtenção dos fluxos de energia à superfície utilizando o algoritmo S-SEBI C. Santos & B. Silva https://doi.org/10.1590/S0102-77862010000300008
688. Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate J. Chirouze et al. https://doi.org/10.5194/hess-18-1165-2014
689. Influence of data spatial resolution in water resources management for oak-savanna distinctive vegetation patches A. Andreu et al. https://doi.org/10.5194/piahs-385-339-2024
690. Water Balance Approach for Evapotranspiration Dynamics: A Comprehensive Review M. Maskey et al. https://doi.org/10.3390/hydrometeorology1010007
691. Impacts of the broadband albedo on actual evapotranspiration estimated by S-SEBI model over an agricultural area C. Mattar et al. https://doi.org/10.1016/j.rse.2014.02.011
692. Groundwater-recharge estimation in the Ordos Plateau, China: comparison of methods L. Yin et al. https://doi.org/10.1007/s10040-011-0777-3
693. A Linear Relationship Between Temporal Multiband MODIS BRDF and Aerodynamic Roughness in HiWATER Wind Gradient Data . Bingfang Wu et al. https://doi.org/10.1109/LGRS.2014.2348074
694. Remote Sensing Data Fusion to Evaluate Patterns of Regional Evapotranspiration: A Case Study for Dynamics of Film-Mulched Drip-Irrigated Cotton in China’s Manas River Basin over 20 Years X. Qiao et al. https://doi.org/10.3390/rs14143438
695. Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling C. Corbari et al. https://doi.org/10.1016/j.agwat.2018.09.005
696. Evaluating satellite-derived evapotranspiration estimates against ground-based measurements in arid Upper Orange catchment, South Africa T. Dube et al. https://doi.org/10.1080/10106049.2026.2630432
697. Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model G. Senay et al. https://doi.org/10.1016/j.agwat.2010.10.014
698. Improving a Penman–Monteith evapotranspiration model by incorporating soil moisture control on soil evaporation in semiarid areas L. Sun et al. https://doi.org/10.1080/17538947.2013.783635
699. Paddy Field Scale Evapotranspiration Estimation Based on Two-Source Energy Balance Model with Energy Flux Constraints and UAV Multimodal Data T. Wu et al. https://doi.org/10.3390/rs17101662
700. Evapotranspiration management based on the application of SWAT for balancing water consumption: A case study in Guantao, China B. Liu & H. Gan https://doi.org/10.1007/s12040-018-0958-8
701. Validation of seven global remotely sensed ET products across Thailand using water balance measurements and land use classifications N. Sriwongsitanon et al. https://doi.org/10.1016/j.ejrh.2020.100709
702. Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model S. Liu et al. https://doi.org/10.1155/2016/4294219
703. Improving crop evapotranspiration estimation in the Yellow River Basin: A modified SEBAL model approach and spatiotemporal trend analysis X. Chen et al. https://doi.org/10.1016/j.agwat.2025.109771
704. Estimating surface fluxes over the north Tibetan Plateau area with ASTER imagery W. Ma et al. https://doi.org/10.5194/hess-13-57-2009
705. Comparative assessment of WRF’s parameterization scheme combinations in assessing land-surface feedback flux and its drivers: a case study of Phailin tropical cyclone S. Mandal et al. https://doi.org/10.1007/s00704-024-05032-3
706. Estimating actual evapotranspiration across China by improving the PML algorithm with a shortwave infrared-based surface water stress constraint Y. Yang https://doi.org/10.1016/j.rse.2024.114544
707. Improving Soil Water Content and Surface Flux Estimation Based on Data Assimilation Technique H. Chen et al. https://doi.org/10.3390/rs14133183
708. Stable isotopes contain substantial additive information about terrestrial carbon and water cycling B. Li et al. https://doi.org/10.1088/1748-9326/acf4ab
709. Estimation of surface heat fluxes using multi-angular observations of radiative surface temperature L. Song et al. https://doi.org/10.1016/j.rse.2020.111674
710. The Modified Soil Moisture Constraint Scheme Significantly Enhances the Evapotranspiration Simulation Accuracy of the MOD16 Model M. Guo et al. https://doi.org/10.3390/su151612460
711. Early season irrigation detection and evapotranspiration modeling of winter vegetables based on Planet satellite using water and energy balance algorithm in lower Colorado basin R. Dhungel et al. https://doi.org/10.1007/s00271-023-00874-7
712. Improving terrestrial evapotranspiration estimation using physics-guided machine learning model driven by solar-induced chlorophyll fluorescence R. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133468
713. Evaluation of Empirical Remote Sensing-Based Equations for Estimating Soil Heat Flux Z. SUN et al. https://doi.org/10.2151/jmsj.2013-505
714. Remote sensing products for predicting actual evapotranspiration and water stress footprints under different land cover M. Jahangir & M. Arast https://doi.org/10.1016/j.jclepro.2020.121818
715. Input/output inconsistencies of daily evapotranspiration conducted empirically using remote sensing data in arid environments M. Elhag et al. https://doi.org/10.1515/geo-2020-0141
716. A New Evapotranspiration Model Accounting for Advection and Its Validation during SMEX02 Y. Yang et al. https://doi.org/10.1155/2013/389568
717. Application of Remotely-Sensed Data to Estimate a Water Budget for Data-Scarce Endorheic Basins: A Case Study of Lake Urmia basin, Iran M. Bagheri et al. https://doi.org/10.1007/s12524-015-0522-9
718. Detection of trend changes in surface energy budget caused by urbanization and land cover/use changes in Dezful plain, Iran A. Parbaleh & H. Kaboli https://doi.org/10.1007/s12665-023-10990-4
719. Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau J. Peng et al. https://doi.org/10.5194/hess-20-3167-2016
720. Water Consumption of Agriculture and Natural Ecosystems along the Ili River in China and Kazakhstan N. Thevs et al. https://doi.org/10.3390/w9030207
721. Multiscale analysis of existing actual evapotranspiration products over agropastoral Sahel J. Etchanchu et al. https://doi.org/10.1016/j.jhydrol.2024.132585
722. Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels Z. Peng et al. https://doi.org/10.5194/hess-20-4409-2016
723. Coupled and continuous estimation of soil moisture and evaporative fraction within the remotely sensed surface temperature-vegetation index framework W. Zhu et al. https://doi.org/10.1016/j.jhydrol.2020.125827
724. Impacts of climate and vegetation on actual evapotranspiration in typical arid mountainous regions using a Budyko-based framework Y. Yu et al. https://doi.org/10.2166/nh.2020.051
725. A theoretical framework for critical canopy temperature and its application to improve remote-sensing-based estimation of evapotranspiration Z. Shi et al. https://doi.org/10.1088/1748-9326/ae33d3
726. An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance C. van der Tol et al. https://doi.org/10.5194/bg-6-3109-2009
727. Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods G. Senay et al. https://doi.org/10.1002/hyp.8379
728. Determination of regional distributions and seasonal variations of land surface heat fluxes from Landsat‐7 Enhanced Thematic Mapper data over the central Tibetan Plateau area Y. Ma et al. https://doi.org/10.1029/2005JD006742
729. Validation of ETWatch using field measurements at diverse landscapes: A case study in Hai Basin of China B. Wu et al. https://doi.org/10.1016/j.jhydrol.2012.02.043
730. Solar-induced chlorophyll fluorescence sheds light on global evapotranspiration Q. Zhang et al. https://doi.org/10.1016/j.rse.2024.114061
731. A dual-pass data assimilation scheme for estimating surface fluxes with FY3A-VIRR land surface temperature T. Xu et al. https://doi.org/10.1007/s11430-014-4964-7
732. An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources Z. Su et al. https://doi.org/10.3390/w12051495
733. Based on the Gaussian Fitting Method to Derive Daily Evapotranspiration from Remotely Sensed Instantaneous Evapotranspiration S. Liu et al. https://doi.org/10.1155/2019/6253832
734. A new technique to map groundwater recharge in irrigated areas using a SWAT model under changing climate U. Awan & A. Ismaeel https://doi.org/10.1016/j.jhydrol.2014.08.049
735. An independent framework-based evapotranspiration model (IFEM) for dual-source: From field to regional scale S. Wang et al. https://doi.org/10.1016/j.rse.2023.113792
736. A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery D. Long & V. Singh https://doi.org/10.1016/j.rse.2012.02.015
737. Evaporative water use of different land uses in the upper-Thukela river basin assessed from satellite imagery M. Kongo et al. https://doi.org/10.1016/j.agwat.2010.06.005
738. Quantification and Mapping of Satellite Driven Surface Energy Balance Fluxes in Semi-Arid to Arid Inter-Mountain Region B. Acharya et al. https://doi.org/10.3390/rs12244019
739. Natural forest regeneration is projected to reduce local temperatures S. Alibakhshi et al. https://doi.org/10.1038/s43247-024-01737-5
740. An improved algorithm to estimate the surface soil heat flux over a heterogeneous surface: A case study in the Heihe River Basin N. Li et al. https://doi.org/10.1007/s11430-014-5041-y
741. Estimates of evapotranspiration from MODIS and AMSR-E land surface temperature and moisture over the Southern Great Plains J. Sun et al. https://doi.org/10.1016/j.rse.2012.08.020
742. Open-source Google Earth Engine 30-m evapotranspiration rates retrieval: The SEBALIGEE system M. Mhawej & G. Faour https://doi.org/10.1016/j.envsoft.2020.104845
743. Assessing variability of evapotranspiration over the Ganga river basin using water balance computations T. Syed et al. https://doi.org/10.1002/2013WR013518
744. Spatial Patterns in Actual Evapotranspiration Climatologies for Europe S. Stisen et al. https://doi.org/10.3390/rs13122410
745. Improving Estimation of Evapotranspiration under Water-Limited Conditions Based on SEBS and MODIS Data in Arid Regions C. Huang et al. https://doi.org/10.3390/rs71215854
746. Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011 G. Hu et al. https://doi.org/10.1016/j.rse.2014.10.017
747. Accounting for Turbulence-Induced Canopy Heat Transfer in the Simulation of Sensible Heat Flux in SEBS Model S. Njuki et al. https://doi.org/10.3390/rs15061578
748. Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa A. Ramoelo et al. https://doi.org/10.3390/rs6087406
749. Spatial Representativeness of Eddy Covariance Measurements in a Coniferous Plantation Mixed with Cropland in Southeastern China W. Xiang et al. https://doi.org/10.3390/rs14195022
750. Estimating catchment evaporation and runoff using MODIS leaf area index and the Penman‐Monteith equation Y. Zhang et al. https://doi.org/10.1029/2007WR006563
751. Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the Penman–Monteith Method with Satellite-Based Surface Energy Balance R. Dhungel et al. https://doi.org/10.3390/rs6098844
752. A Critical Evaluation on the Role of Aerodynamic and Canopy–Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland K. Mallick et al. https://doi.org/10.3390/w10121753
753. A comparative study of LULC classifiers for analysing the cover management factor and support practice factor in RUSLE model V. Sampath & N. Radhakrishnan https://doi.org/10.1007/s12145-022-00911-7
754. The combined impact of shallow groundwater and soil salinity on evapotranspiration using remote sensing in an agricultural alluvial setting H. Aboelsoud et al. https://doi.org/10.1016/j.ejrh.2023.101372
755. A Column Canopy‐Air Turbulent Diffusion Method for Different Canopy Structures X. Chen et al. https://doi.org/10.1029/2018JD028883
756. Evapotranspiration estimation based on the SEBAL model in the Nansi Lake Wetland of China Z. Sun et al. https://doi.org/10.1016/j.mcm.2010.11.039
757. Estimating water consumption based on meta-analysis and MODIS data for an oasis region in northwestern China W. Zhao et al. https://doi.org/10.1016/j.agwat.2018.06.035
758. Satellite-based energy balance model to estimate seasonal evapotranspiration for irrigated sorghum: a case study from the Gezira scheme, Sudan M. Bashir et al. https://doi.org/10.5194/hess-12-1129-2008
759. The data-driven solution of energy imbalance-induced structural error in evapotranspiration models X. Hu et al. https://doi.org/10.1016/j.jhydrol.2021.126205
760. Estimation of water consumption and productivity for rice through integrating remote sensing and census data in the Songnen Plain, China J. Du et al. https://doi.org/10.1007/s10333-013-0411-1
761. Evaluation of surface heat fluxes in Chiayi plain of Taiwan by remotely sensed data T. Chang et al. https://doi.org/10.1080/01431161.2010.483481
762. Surface Energy Balance-Based Model for Estimating Evapotranspiration Taking into Account Spatial Variability in Weather A. Elhaddad & L. Garcia https://doi.org/10.1061/(ASCE)0733-9437(2008)134:6(681)
763. Simplifying the revised three-temperature model for remotely estimating regional evapotranspiration and its application to a semi-arid steppe Y. Xiong & G. Qiu https://doi.org/10.1080/01431161.2014.885149
764. Parameter sensitivity analysis and optimization for a satellite‐based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data K. Zhang et al. https://doi.org/10.1002/2016JD025768
765. Accuracy of five ground heat flux empirical simulation methods in the surface-energy-balance-based remote-sensing evapotranspiration models Z. Liu https://doi.org/10.5194/hess-26-6207-2022
766. Estimation of crop water stress index and leaf area index based on remote sensing data M. Cetin et al. https://doi.org/10.2166/ws.2023.051
767. Intercomparison and evaluation of ten global ET products at site and basin scales H. Liu et al. https://doi.org/10.1016/j.jhydrol.2022.128887
768. Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River B. van Osnabrugge et al. https://doi.org/10.5194/hess-23-1453-2019
769. Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land‐surface temperature observations F. Castellví et al. https://doi.org/10.1002/2015WR017587
770. The influence of Urmia Lake desiccation on an extreme snowfall event: A case study using the WRF-Lake model M. Rahimian et al. https://doi.org/10.1016/j.atmosres.2024.107327
771. Evapotranspiration Estimation and Irrigation Performance Assessment Using Remote Sensing: A Case Study of the Ergani Dam Irrigation System (Turkey) K. Doganay & B. Karatas https://doi.org/10.1002/ird.70181
772. Parameterization of the Surface Energy Balance of a Shallow Water Table Grassland Q. Tu et al. https://doi.org/10.3390/w12020523
773. A physics-informed spatiotemporal downscaling model for kilometer-scale hourly humid heat stress indices X. Wu et al. https://doi.org/10.1080/17538947.2026.2731676
774. Remote sensing techniques for predicting evapotranspiration from mixed vegetated surfaces H. Nouri et al. https://doi.org/10.1080/1573062X.2014.900092
775. Inter-comparison of evapotranspiration datasets over heterogeneous landscapes across Australia M. Khan et al. https://doi.org/10.1016/j.asr.2020.04.037
776. Improving Evapotranspiration Estimation in SWAT-Based Hydrologic Simulation through Data Assimilation in the SEBAL Algorithm O. Mikaeili & M. Shourian https://doi.org/10.1007/s11269-024-03854-4
777. Observation of the winter regional evaporative fraction using a UAV-based eddy covariance system over wetland area Y. Sun et al. https://doi.org/10.1016/j.agrformet.2021.108619
778. Estimation of large‐scale evaporation fields based on assimilation of remotely sensed land temperature F. Sini et al. https://doi.org/10.1029/2006WR005574
779. Comparison of Satellite Driven Surface Energy Balance Models in Estimating Crop Evapotranspiration in Semi-Arid to Arid Inter-Mountain Region B. Acharya & V. Sharma https://doi.org/10.3390/rs13091822
780. Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration T. Rientjes et al. https://doi.org/10.1016/j.jhydrol.2013.10.006
781. A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman‐Monteith equation R. Leuning et al. https://doi.org/10.1029/2007WR006562
782. Land Surface Temperature and Emissivity Retrieval from Nighttime Middle and Thermal Infrared Images of Chinese Fengyun-3D MERSI-II H. Zeng et al. https://doi.org/10.1109/JSTARS.2021.3098579
783. Integration of the GG model with SEBAL to produce time series of evapotranspiration of high spatial resolution at watershed scales D. Long & V. Singh https://doi.org/10.1029/2010JD014092
784. Evapotranspiration and land surface temperature of typical urban green spaces in a semi-humid region: Implications for green management X. Li et al. https://doi.org/10.3389/fenvs.2022.977084
785. Satellite-Based energy balance for estimating actual sugarcane evapotranspiration in the Ethiopian Rift Valley G. Woldemariam et al. https://doi.org/10.1016/j.isprsjprs.2025.03.003
786. Enhanced daily retrieval of Evapotranspiration from a Transformer-based deep learning model combined with satellite passive microwave and optical observations F. Bu et al. https://doi.org/10.1016/j.isprsjprs.2026.05.027
787. Analysis of Land Surface Temperature and NDVI Using Geo-Spatial Technique: A Case Study of Keti Bunder, Sindh, Pakistan . Zia Ur Rehman et al. https://doi.org/10.6000/1927-5129.2015.11.69
788. Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe D. Rwasoka et al. https://doi.org/10.1016/j.pce.2011.07.035
789. Analyzing the impact of area of interest (AOI) size and endmember selection on evapotranspiration (ET) estimation through a contextual model (SEBAL) H. Barguache et al. https://doi.org/10.1016/j.jag.2025.104514
790. Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India A. Danodia et al. https://doi.org/10.1080/10106049.2017.1374473
791. Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation W. Verstraeten et al. https://doi.org/10.3390/s8010070
792. A Method of Using WRF-Simulated Surface Temperature to Estimate Daily Evapotranspiration D. Wang et al. https://doi.org/10.1175/JAMC-D-19-0287.1
793. Modelling Actual Evapotranspiration Seasonal Variability by Meteorological Data-Based Models M. Mobilia et al. https://doi.org/10.3390/hydrology7030050
794. Calibration and Validation of the SEBS Model for Actual Evapotranspiration Assessment of Medicinal Herbs in Arid and Semi‐Arid Iran: Implications for Irrigation Management A. Eslami et al. https://doi.org/10.1002/ird.70115
795. An image-based four-source surface energy balance model to estimate crop evapotranspiration from solar reflectance/thermal emission data (SEB-4S) O. Merlin et al. https://doi.org/10.1016/j.agrformet.2013.10.002
796. Region- and pixel-based image fusion for disaggregation of actual evapotranspiration F. Alidoost et al. https://doi.org/10.1080/19479832.2015.1055834
797. Energy and Mass Exchange Over Incomplete Vegetation Cover M. Abraha & M. Savage https://doi.org/10.1080/07352689.2012.656497
798. The use of scintillometry for validating aggregation schemes over heterogeneous grids J. Ezzahar & A. Chehbouni https://doi.org/10.1016/j.agrformet.2009.09.004
799. Mapping daily evapotranspiration based on spatiotemporal fusion of ASTER and MODIS images over irrigated agricultural areas in the Heihe River Basin, Northwest China Y. Li et al. https://doi.org/10.1016/j.agrformet.2017.05.023
800. Large-scale radiation and energy balances with Landsat 8 images and agrometeorological data in the Brazilian semiarid region A. de Castro Teixeira et al. https://doi.org/10.1117/1.JRS.11.016030
801. Performance of Solar-Induced Chlorophyll Fluorescence in Estimating Water-Use Efficiency in a Temperate Forest X. Lu et al. https://doi.org/10.3390/rs10050796
802. High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania D. Nyolei et al. https://doi.org/10.1016/j.pce.2019.03.009
803. The study on the actual estimation of evapotranspiration in the Kuye River based on the SEBS model and its driving mechanisms H. Fan et al. https://doi.org/10.3389/fenvs.2026.1836222
804. Parameter estimation for a simple two-source evapotranspiration model using Bayesian inference and its application to remotely sensed estimations of latent heat flux at the regional scale Y. Song et al. https://doi.org/10.1016/j.agrformet.2016.03.019
805. Regional Estimation of Remotely Sensed Evapotranspiration Using the Surface Energy Balance-Advection (SEB-A) Method S. Liu et al. https://doi.org/10.3390/rs8080644
806. A Hybrid Model Coupling Physical Constraints and Machine Learning to Estimate Daily Evapotranspiration in the Heihe River Basin X. Li et al. https://doi.org/10.3390/rs16122143
807. Hyperspectral indices based on first derivative spectra closely trace canopy transpiration in a desert plant J. Jin & Q. Wang https://doi.org/10.1016/j.ecoinf.2016.06.004
808. A Review of Remote Sensing for Environmental Monitoring in China J. Li et al. https://doi.org/10.3390/rs12071130
809. A Global Implementation of Single‐ and Dual‐Source Surface Energy Balance Models for Estimating Actual Evapotranspiration at 30‐m Resolution Using Google Earth Engine H. Jaafar et al. https://doi.org/10.1029/2022WR032800
810. Incorporation of Net Radiation Model Considering Complex Terrain in Evapotranspiration Determination with Sentinel-2 Data L. Wang et al. https://doi.org/10.3390/rs14051191
811. Improving Estimation of Cropland Evapotranspiration by the Bayesian Model Averaging Method with Surface Energy Balance Models H. Sun et al. https://doi.org/10.3390/atmos10040188
812. Mapping soil moisture across the Tibetan Plateau plains using Aquarius active and passive L-band microwave observations Q. Wang et al. https://doi.org/10.1016/j.jag.2019.01.005
813. Hydrologic responses to land cover change: the case of Jedeb mesoscale catchment, Abay/Upper Blue Nile basin, Ethiopia S. Tekleab et al. https://doi.org/10.1002/hyp.9998
814. Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE) Z. Su et al. https://doi.org/10.3390/rs13183661
815. Rice growth period detection and paddy field evapotranspiration estimation based on an improved SEBAL model: Considering the applicable conditions of the advection equation J. Wei et al. https://doi.org/10.1016/j.agwat.2023.108141
816. Estimation and Validation of Actual Evapotranspiration (ETa) of Maize Wheat Cropping System Using SSEBop Model Over IARI Research Farm, New Delhi, India J. Mukherjee et al. https://doi.org/10.1007/s12524-021-01350-5
817. Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture K. Ribeiro-Gomes et al. https://doi.org/10.3390/s17102173
818. Characterization of spatial and temporal distribution of evapotranspiration in the Dawen River Basin and analysis of driving factors Z. Wang et al. https://doi.org/10.1007/s12665-024-12078-z
819. Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework J. Peng et al. https://doi.org/10.1016/j.jhydrol.2019.124245
820. Validation and consistency assessment of land surface temperature from geostationary and polar orbit platforms: SEVIRI/MSG and AVHRR/Metop I. Trigo et al. https://doi.org/10.1016/j.isprsjprs.2021.03.013
821. Integration of Remote Sensing Evapotranspiration into Multi-Objective Calibration of Distributed Hydrology–Soil–Vegetation Model (DHSVM) in a Humid Region of China S. Pan et al. https://doi.org/10.3390/w10121841
822. Improving LST Downscaling Quality on Regional and Field-Scale by Parameterizing the DisTrad Method T. Ibrahim et al. https://doi.org/10.3390/ijgi11060327
823. Vegetation restoration dominated the variation of water use efficiency in China Y. Xue et al. https://doi.org/10.1016/j.jhydrol.2022.128257
824. Angular Modeling of the Components of Net Radiation in Agricultural Crops and Its Implications on Energy Balance Closure F. Paz et al. https://doi.org/10.3390/w13213028
825. Seasonal and inter-annual variation in surface energy fluxes and forcing parameters in agro-climatic regions of India I. Choudhury https://doi.org/10.1080/01431161.2015.1035406
826. Land use/cover change and regional climate change in an arid grassland ecosystem of Inner Mongolia, China Z. Li et al. https://doi.org/10.1016/j.ecolmodel.2016.07.019
827. Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland R. Jana et al. https://doi.org/10.5194/hess-20-3987-2016
828. Simulation of water productivity of wheat in northwestern Bangladesh using multi-satellite data A. Islam et al. https://doi.org/10.1016/j.agwat.2023.108242
829. Modelling High-Resolution Actual Evapotranspiration through Sentinel-2 and Sentinel-3 Data Fusion R. Guzinski et al. https://doi.org/10.3390/rs12091433
830. Integration of soil moisture in SEBS for improving evapotranspiration estimation under water stress conditions M. Gokmen et al. https://doi.org/10.1016/j.rse.2012.02.003
831. Development of a new UAV-thermal imaging based model for estimating pecan evapotranspiration E. Mokari et al. https://doi.org/10.1016/j.compag.2022.106752
832. Comparison of Crop Evapotranspiration and Water Productivity of Typical Delta Irrigation Areas in Aral Sea Basin Z. Liu et al. https://doi.org/10.3390/rs14020249
833. Estimation of surface latent heat fluxes in an oasis utilizing a two-source energy balance model based on land surface temperature decomposition R. Wang et al. https://doi.org/10.1117/1.JRS.13.034504
834. Systematic review of thermal remote sensing for water status and evapotranspiration assessment in vineyard F. Mammarella et al. https://doi.org/10.1007/s00271-026-01185-3
835. Components of near-surface energy balance derived from satellite soundings – Part 2: Noontime latent heat flux K. Mallick et al. https://doi.org/10.5194/bg-11-7369-2014
836. Land surface temperature retrieval from AMSR-E passive microwave data E. Zhao et al. https://doi.org/10.1364/OE.25.00A940
837. Improving the evapotranspiration estimation by considering the effect of flux footprint climatology J. Bian et al. https://doi.org/10.1016/j.jhydrol.2024.130769
838. Spatially Disaggregating Satellite Land Surface Temperature With a Nonlinear Model Across Agricultural Areas K. Liu et al. https://doi.org/10.1029/2019JG005227
839. Evapotranspiration Estimation for Tibetan Plateau Headwaters Using Conjoint Terrestrial and Atmospheric Water Balances and Multisource Remote Sensing X. Li et al. https://doi.org/10.1029/2019WR025196
840. Estimating zero-plane displacement height and aerodynamic roughness length using synthesis of LiDAR and SPOT-5 data X. Tian et al. https://doi.org/10.1016/j.rse.2011.04.033
841. Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution P. Huang et al. https://doi.org/10.5194/hess-28-4455-2024
842. Forecasting of Remotely Sensed Daily Evapotranspiration Data Over Nile Delta Region, Egypt A. Psilovikos & M. Elhag https://doi.org/10.1007/s11269-013-0368-2
843. Parameterization of heat fluxes at heterogeneous surfaces by integrating satellite measurements with surface layer and atmospheric boundary layer observations Y. Ma et al. https://doi.org/10.1007/s00376-009-9024-4
844. Water balance‐based actual evapotranspiration reconstruction from ground and satellite observations over the conterminous United States Z. Wan et al. https://doi.org/10.1002/2015WR017311
845. Modeling soil heat flux from MODIS products for arid regions F. Aliabad & E. Ghaderpour https://doi.org/10.1016/j.ecoinf.2025.103005
846. Remotely sensed latent heat fluxes for model error diagnosis: a case study J. Schuurmans et al. https://doi.org/10.5194/hess-15-759-2011
847. A review of satellite-derived terrestrial evapotranspiration: theories, methods and products Y. Yao et al. https://doi.org/10.1186/s13717-026-00688-3
848. Determining Regional Actual Evapotranspiration of Irrigated Crops and Natural Vegetation in the São Francisco River Basin (Brazil) Using Remote Sensing and Penman-Monteith Equation A. Teixeira https://doi.org/10.3390/rs0251287
849. Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate S. Hobeichi et al. https://doi.org/10.5194/hess-22-1317-2018
850. Long-Term (1986–2015) Crop Water Use Characterization over the Upper Rio Grande Basin of United States and Mexico Using Landsat-Based Evapotranspiration G. Senay et al. https://doi.org/10.3390/rs11131587
851. Near-Surface Air Temperature Estimation Based on an Improved Conditional Generative Adversarial Network J. Zheng et al. https://doi.org/10.3390/s24185972
852. Generation of spatio-temporally continuous evapotranspiration and its components by coupling a two-source energy balance model and a deep neural network over the Heihe River Basin Y. Cui et al. https://doi.org/10.1016/j.jhydrol.2021.126176
853. Daily Actual Evapotranspiration Estimation in a Mediterranean Ecosystem from Landsat Observations Using SEBAL Approach H. Awada et al. https://doi.org/10.3390/f12020189
854. A modified MOD16 algorithm to estimate evapotranspiration over alpine meadow on the Tibetan Plateau, China Y. Chang et al. https://doi.org/10.1016/j.jhydrol.2018.03.054
855. Estimating surface heat and water vapor fluxes by combining two-source energy balance model and back-propagation neural network J. Feng et al. https://doi.org/10.1016/j.scitotenv.2020.138724
856. Long time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validation M. Cheng et al. https://doi.org/10.5194/essd-13-3995-2021
857. Landscape-scale hydrologic response of plant invasion relative to native vegetation in urban forests K. Singh et al. https://doi.org/10.1016/j.scitotenv.2021.149903
858. Estimación de la evapotranspiración real en zonas de llanura mediante productos de humedad de suelo de la misión SMAP E. Walker et al. https://doi.org/10.4995/raet.2018.10566
859. Influence of agricultural practices on micrometerological spatial variations at local and regional scales D. Courault et al. https://doi.org/10.1080/01431160802459551
860. Daily Evapotranspiration Estimation Using HJ-1 Data for Irrigation Water Management in a Desert-Oasis Irrigation District, Northwest China Z. Yi et al. https://doi.org/10.1051/matecconf/201824602006
861. Estimating evapotranspiration using METRIC model and Landsat data for better understandings of regional hydrology in the western Urmia Lake Basin M. Tasumi https://doi.org/10.1016/j.agwat.2019.105805
862. Evaluation of land surface radiation balance derived from moderate resolution imaging spectroradiometer (MODIS) over complex terrain and heterogeneous landscape on clear sky days Y. Ryu et al. https://doi.org/10.1016/j.agrformet.2008.05.008
863. An Enhanced MOD16 Evapotranspiration Model for the Tibetan Plateau During the Unfrozen Season L. Yuan et al. https://doi.org/10.1029/2020JD032787
864. Derivation of Daily Evaporative Fraction Based on Temporal Variations in Surface Temperature, Air Temperature, and Net Radiation J. Lu et al. https://doi.org/10.3390/rs5105369
865. Long-term changes in evapotranspiration over China and attribution to climatic drivers during 1980–2010 S. Li et al. https://doi.org/10.1016/j.jhydrol.2021.126037
866. Shifting from homogeneous to heterogeneous surfaces in estimating terrestrial evapotranspiration: Review and perspectives Y. Liu et al. https://doi.org/10.1007/s11430-020-9834-y
867. Integration of two semi-physical models of terrestrial evapotranspiration using the China Meteorological Forcing Dataset M. Liu et al. https://doi.org/10.1080/01431161.2018.1482026
868. Evaluation of satellite-based evapotranspiration estimates in China L. Huang et al. https://doi.org/10.1117/1.JRS.11.026019
869. Simulation of ecosystem fluxes with the SCOPE model: Sensitivity to parametrization and evaluation with flux tower observations E. Prikaziuk et al. https://doi.org/10.1016/j.rse.2022.113324
870. Assessment of Multi-Source Evapotranspiration Products over China Using Eddy Covariance Observations S. Li et al. https://doi.org/10.3390/rs10111692
871. Automatically selecting hot and cold pixels for satellite actual evapotranspiration estimation under different topographic and climatic conditions M. Saboori et al. https://doi.org/10.1016/j.agwat.2021.106763
872. Evaluating catchment‐scale hydrological modeling by means of terrestrial gravity observations S. Hasan et al. https://doi.org/10.1029/2007WR006321
873. Crop Water Requirements and Suitability Assessment in Arid Environments: A New Approach A. Elnashar et al. https://doi.org/10.3390/agronomy11020260
874. A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils A. Grachev et al. https://doi.org/10.1175/JAMC-D-20-0232.1
875. Remote estimation of terrestrial evapotranspiration without using meteorological data Y. Yang et al. https://doi.org/10.1002/grl.50450
876. Quantifying latent heat flux in plateau and plain lakes considering water heat storage changes W. Fu et al. https://doi.org/10.1016/j.agrformet.2026.111479
877. Evaporation rates in a vital lake: a 34-year assessment for the Karaoun Lake M. Mhawej et al. https://doi.org/10.1080/01431161.2020.1739354
878. Estimation of evapotranspiration in an arid region by remote sensing—A case study in the middle reaches of the Heihe River Basin X. Li et al. https://doi.org/10.1016/j.jag.2011.09.008
879. Evaluation of two strategies from the SEBS model for estimating the daily terrestrial evapotranspiration values of the Tibetan Plateau Y. Kan et al. https://doi.org/10.1016/j.jhydrol.2025.132921
880. Ecohydrological impacts of photovoltaic construction across aridity gradients in China: Divergent responses of vegetation and evapotranspiration S. Zhu et al. https://doi.org/10.1016/j.ejrh.2026.103766
881. Evaluating evaporation rate from high Aswan Dam Reservoir using RS and GIS techniques A. Hassan et al. https://doi.org/10.1016/j.ejrs.2017.10.001
882. Regional Distribution of Net Radiation over Different Ecohydrological Land Surfaces M. Rahman et al. https://doi.org/10.3390/atmos11111229
883. Energy balance quantification using Landsat 8 images and SAFER algorithm in Mashhad, Razavi Khorasan, Iran S. Dehziari & S. Sanaienejad https://doi.org/10.1117/1.JRS.13.014528
884. A calibration free radiation driven model for estimating actual evapotranspiration of mountain grasslands (CLIME-MG) D. Gisolo et al. https://doi.org/10.1016/j.jhydrol.2022.127948
885. Evapotranspiration estimation over agricultural plains using MODIS data for all sky conditions T. Luo et al. https://doi.org/10.1080/01431161.2015.1009648
886. Mapping regional evapotranspiration in cloudy skies via variational assimilation of all-weather land surface temperature observations X. He et al. https://doi.org/10.1016/j.jhydrol.2020.124790
887. Comparison of Differences in Actual Cropland Evapotranspiration under Two Irrigation Methods Using Satellite-Based Model Y. Liu et al. https://doi.org/10.3390/rs16010175
888. Regional estimates of evapotranspiration over Northern China using a remote-sensing-based triangle interpolation method H. Wang & G. Jia https://doi.org/10.1007/s00376-013-2294-x
889. Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration V. Stefan et al. https://doi.org/10.3390/rs70810444
890. Improving remotely sensed actual evapotranspiration estimation with raster meteorological data I. Cherif et al. https://doi.org/10.1080/01431161.2015.1084439
891. An improved framework for anchor pixel selection in the Surface Energy Balance Model (SEBAL) for consistent estimation of evapotranspiration M. Noufia et al. https://doi.org/10.1080/01431161.2026.2689172
892. A Quantitative Inspection on Spatio-Temporal Variation of Remote Sensing-Based Estimates of Land Surface Evapotranspiration in South Asia A. Li et al. https://doi.org/10.3390/rs70404726
893. Comprehensive study of energy and water exchange over the Tibetan Plateau: A review and perspective: From GAME/Tibet and CAMP/Tibet to TORP, TPEORP, and TPEITORP Y. Ma et al. https://doi.org/10.1016/j.earscirev.2023.104312
894. Comparison of three dual‐source remote sensing evapotranspiration models during the MUSOEXE‐12 campaign: Revisit of model physics Y. Yang et al. https://doi.org/10.1002/2014WR015619
895. Evapotranspiration data assimilation with genetic algorithms and SWAP model for on-demand irrigation A. Irmak & B. Kamble https://doi.org/10.1007/s00271-009-0193-9
896. Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements J. Timmermans et al. https://doi.org/10.5194/hess-13-1249-2009
897. A Method for Deriving the Boundary Layer Mixing Height from MODIS Atmospheric Profile Data X. Feng et al. https://doi.org/10.3390/atmos6091346
898. Evapotranspiration and water yield over China's landmass from 2000 to 2010 Y. Liu et al. https://doi.org/10.5194/hess-17-4957-2013
899. Monitoring and Modeling the Tibetan Plateau’s climate system and its impact on East Asia Y. Ma et al. https://doi.org/10.1038/srep44574
900. Estimates of spatial variation in evaporation using satellite‐derived surface temperature and a water balance model L. Bouwer et al. https://doi.org/10.1002/hyp.6636
901. Spatiotemporal assessment of actual evapotranspiration using satellite remote sensing technique in the Nile Delta, Egypt H. Fawzy et al. https://doi.org/10.1016/j.aej.2020.11.001
902. Dual-model approaches for evapotranspiration analyses over homo- and heterogeneous land surface conditions K. Byun et al. https://doi.org/10.1016/j.agrformet.2014.07.001
903. Drone-Based Hyperspectral and Thermal Imagery for Quantifying Upland Rice Productivity and Water Use Efficiency after Biochar Application H. Jin et al. https://doi.org/10.3390/rs13101866
904. Coupled estimation of surface heat fluxes and vegetation dynamics from remotely sensed land surface temperature and fraction of photosynthetically active radiation S. Bateni et al. https://doi.org/10.1002/2013WR014573
905. Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas T. Alexandridis et al. https://doi.org/10.3390/rs1030445
906. Quantifying soybean evapotranspiration using an eddy covariance approach S. Anapalli et al. https://doi.org/10.1016/j.agwat.2018.07.023
907. Estimating the Actual Evapotranspiration Using Remote Sensing and SEBAL Model in an Arid Environment of Northwest China X. Chen et al. https://doi.org/10.3390/w15081555
908. Optimizing variable rate irrigation using model and satellite-based dynamic prescription maps C. Corbari et al. https://doi.org/10.1016/j.agwat.2024.108896
909. Estimation of surface energy fluxes from remotely sensed data over Akure, Nigeria K. Ogunjobi et al. https://doi.org/10.1007/s41324-017-0149-8
910. Remote Sensing of Global Daily Evapotranspiration based on a Surface Energy Balance Method and Reanalysis Data X. Chen et al. https://doi.org/10.1029/2020JD032873
911. Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: a systematic review of methods and gaps B. Tran et al. https://doi.org/10.5194/hess-27-4505-2023
912. Multi-pixel Calibration of a Distributed Energy Water Balance Model Using Satellite Data of Land Surface Temperature and Eddy Covariance Data C. Corbari et al. https://doi.org/10.1016/j.proenv.2013.06.033
913. Remote sensing-based estimation of actual evapotranspiration using the SEBAL model: application to the Dashte Abbas Plain, Iran P. Mirkhorli et al. https://doi.org/10.1007/s10333-026-01072-9
914. Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin G. Senay et al. https://doi.org/10.1016/j.rse.2015.12.043
915. Feasibility of Retrieving Land Surface Heat Fluxes from ASTER Data Using SEBS: a Case Study from the NamCo Area of the Tibetan Plateau W. Ma et al. https://doi.org/10.1657/1938-4246-43.2.239
916. Resolve the Clear‐Sky Continuous Diurnal Cycle of High‐Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature J. Wen et al. https://doi.org/10.1029/2022WR032227
917. Spatial extrapolation of lysimeter results using thermal infrared imaging B. Voortman et al. https://doi.org/10.1016/j.jhydrol.2016.09.064
918. Effects of topography on the spatial distribution of evapotranspiration over a complex terrain using two‐source energy balance model with ASTER data H. Kafle & Y. Yamaguchi https://doi.org/10.1002/hyp.7336
919. Complementary relationship estimation of actual evapotranspiration in extreme cold and arid areas: a case study of the Hotan River Basin, northwest China X. Zhang et al. https://doi.org/10.2166/nh.2017.104
920. Quantifying the contribution of riparian total evaporation to streamflow transmission losses: Preliminary investigations along the Groot Letaba river S. Gokool et al. https://doi.org/10.1016/j.pce.2019.11.002
921. Calculating net radiation of freshwater reservoir to estimate spatial distribution of evaporation using satellite images R. Ghahreman & M. Rahimzadegan https://doi.org/10.1016/j.jhydrol.2021.127392
922. A Thermal Disaggregation Model Based on Trapezoid Interpolation K. Liu et al. https://doi.org/10.1109/JSTARS.2018.2790002
923. Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies M. McCabe et al. https://doi.org/10.1016/j.rse.2007.03.027
924. Land-surface evapotranspiration derived from a first-principles primary production model S. Tan et al. https://doi.org/10.1088/1748-9326/ac29eb
925. Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations G. Hu & L. Jia https://doi.org/10.3390/rs70303056
926. Groundwater Resource Assessment Using Modelling and Remote Sensing: A Case Study of Sesheke, Zambia J. Kabika et al. https://doi.org/10.53974/unza.jonas.1.1.477
927. Using high-spatiotemporal thermal satellite ET retrievals to monitor water use over California vineyards of different climate, vine variety and trellis design K. Knipper et al. https://doi.org/10.1016/j.agwat.2020.106361
928. Estimation of water requirements for a drip-irrigated apple orchard using Landsat 7 satellite images D. de la Fuente-Sáiz et al. https://doi.org/10.17660/ActaHortic.2017.1150.26
929. Remote Sensing, Geophysics, and Modeling to Support Precision Agriculture—Part 2: Irrigation Management A. Pradipta et al. https://doi.org/10.3390/w14071157
930. A Satellite-Based Tool for Mapping Evaporation in Inland Water Bodies: Formulation, Application, and Operational Aspects E. Matta et al. https://doi.org/10.3390/rs14112636
931. A method for estimating soil moisture storage in regions under water stress and storage depletion: a case study of Hai River Basin, North China J. Moiwo et al. https://doi.org/10.1002/hyp.7991
932. Methodological comparison of alpine meadow evapotranspiration on the Tibetan Plateau, China Y. Chang et al. https://doi.org/10.1371/journal.pone.0189059
933. Improving a land surface scheme for estimating sensible and latent heat fluxes above grasslands with contrasting soil moisture zones K. Ishola et al. https://doi.org/10.1016/j.agrformet.2020.108151
934. Hydrometeorological application of a microwave link: 1. Evaporation H. Leijnse et al. https://doi.org/10.1029/2006WR004988
935. Imbalanced supply and demand of temperature regulation service provided by urban forests: A case study in Shenzhen, China H. Li et al. https://doi.org/10.1016/j.ecolind.2022.109666
936. Seasonal variation in canopy reflectance and its application to determine the water status and water use by citrus trees in the Western Cape, South Africa S. Dzikiti et al. https://doi.org/10.1016/j.agrformet.2011.03.007
937. Evapotranspiration Retrieval Under Different Aridity Conditions Over North American Grasslands Q. Liao et al. https://doi.org/10.1109/TGRS.2020.2980453
938. Modeling the influence of land surface flux on the regional climate of the Tibetan Plateau W. Ma & Y. Ma https://doi.org/10.1007/s00704-015-1495-x
939. Surface energy fluxes in the Northeast Asia ecosystem: SEBS and METRIC models using Landsat satellite images U. Liaqat & M. Choi https://doi.org/10.1016/j.agrformet.2015.08.245
940. A method for downscaling daily evapotranspiration based on 30-m surface resistance S. Tan et al. https://doi.org/10.1016/j.jhydrol.2019.06.054
941. Modeling the Near-Surface Energies and Water Vapor Fluxes Behavior in Response to Summer Canopy Density across Yanqi Endorheic Basin, Northwestern China P. Kayumba et al. https://doi.org/10.3390/rs13183764
942. Combining a Two Source Energy Balance Model Driven by MODIS and MSG-SEVIRI Products with an Aggregation Approach to Estimate Turbulent Fluxes over Sparse and Heterogeneous Vegetation in Sahel Region (Niger) B. Hssaine et al. https://doi.org/10.3390/rs10060974
943. Trend analysis of reference evapotranspiration: Case study of Ogun-Osun River Basin, Nigeria H. Alabi et al. https://doi.org/10.1016/j.nexres.2026.101796
944. Land surface emissivity change in China from 2001 to 2010 X. Wang et al. https://doi.org/10.1007/s11442-012-0935-0
945. A Hybrid Dual-Source Model of Estimating Evapotranspiration over Different Ecosystems and Implications for Satellite-Based Approaches H. Lu et al. https://doi.org/10.3390/rs6098359
946. Estimation of surface energy fluxes in the permafrost region of the Tibetan Plateau based on in situ measurements and the surface energy balance system model J. Yao et al. https://doi.org/10.1002/joc.6551
947. Evaluation of the SEBS for upscaling the evapotranspiration based on in-situ observations over the Tibetan Plateau W. Ma et al. https://doi.org/10.1016/j.atmosres.2013.10.020
948. Satellite-based crop coefficient and regional water use estimates for Hawaiian sugarcane H. Zhang et al. https://doi.org/10.1016/j.fcr.2015.05.023
949. Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America B. de Andrade et al. https://doi.org/10.3390/rs13122337
950. Single-Source Energy Balance Model Inversion of Actual Evapotranspiration from Irrigated Pasture and Analysis of Its Spatio-Temporal Characteristics 佳. 牛 https://doi.org/10.12677/GSER.2024.131021
951. Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China J. Sun & S. Ongsomwang https://doi.org/10.3390/ijgi10120809
952. Evaluation of a surface energy balance method based on optical and thermal satellite imagery to estimate root‐zone soil moisture N. Alburn et al. https://doi.org/10.1002/hyp.10562
953. The impact of coastal development on land surface temperature in the mangrove ecosystem of the Chattogram coast in Bangladesh H. Alam et al. https://doi.org/10.1007/s11852-022-00869-0
954. Assessment of consumption and availability of water in the upper Omo-Gibe basin, Ethiopia M. Nesru et al. https://doi.org/10.1007/s12517-019-4897-8
955. Comparative analysis of the pysebal model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey A. SAWADOGO et al. https://doi.org/10.26833/ijeg.573503
956. Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications E. Koksal et al. https://doi.org/10.1002/met.1644
957. Comparison of Three Operative Models for Estimating the Surface Water Deficit Using ASTER Reflective and Thermal Data M. García et al. https://doi.org/10.3390/s7060860
958. Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data N. Ge et al. https://doi.org/10.1007/s00376-020-0169-5
959. Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites T. Xu et al. https://doi.org/10.1016/j.rse.2018.11.023
960. Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites X. He et al. https://doi.org/10.3390/rs10121994
961. Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands L. Tang et al. https://doi.org/10.1080/15481603.2021.1947622
962. Verification of land surface evapotranspiration estimation from remote sensing spatial contextual information R. Tang et al. https://doi.org/10.1002/hyp.8341
963. Evaluating the SEBS‐estimated evaporative fraction from MODIS data for a complex underlying surface J. Lu et al. https://doi.org/10.1002/hyp.9440
964. Multi-variable calibration of hydrological model in the upper Omo-Gibe basin, Ethiopia M. Nesru et al. https://doi.org/10.1007/s11600-020-00417-0
965. Evapotranspiration of Winter Wheat in the Semi-Arid Southeastern Loess Plateau Based on Multi-Source Satellite Data P. He et al. https://doi.org/10.3390/rs15082095
966. ETWatch cloud: APIs for regional actual evapotranspiration data generation F. Wu et al. https://doi.org/10.1016/j.envsoft.2021.105174
967. Recent trends (2003–2013) of land surface heat fluxes on the southern side of the central Himalayas, Nepal P. Amatya et al. https://doi.org/10.1002/2015JD023510
968. Satellite-based observations of hydrological processes Q. Tang et al. https://doi.org/10.1080/01431161.2010.483496
969. Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications Y. Shin & B. Mohanty https://doi.org/10.1002/wrcr.20495
970. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin A. Ruhoff et al. https://doi.org/10.1080/02626667.2013.837578
971. Socio‐ecohydrology and the urban water challenge D. Pataki et al. https://doi.org/10.1002/eco.209
972. Long-term water stress and drought assessment of Mediterranean oak savanna vegetation using thermal remote sensing M. González-Dugo et al. https://doi.org/10.5194/hess-25-755-2021
973. Developing an Automated Python Surface Energy Balance System (PySEBS) Software for Calculating Actual Evapotranspiration-Software Development and Application Case in Jilin Province, China H. Liu et al. https://doi.org/10.3390/rs14215629
974. A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses L. Karthikeyan et al. https://doi.org/10.1016/j.jhydrol.2020.124905
975. A novel approach for next generation water-use mapping using Landsat and Sentinel-2 satellite data R. Singh et al. https://doi.org/10.1080/02626667.2020.1817461
976. Numerical study of the impacts of urban expansion on Meiyu precipitation over Eastern China X. Ma & Y. Zhang https://doi.org/10.1007/s13351-015-4063-5
977. Influence of modeling domain and meteorological forcing data on daily evapotranspiration estimates from a Shuttleworth–Wallace model using Sentinel-2 surface reflectance data N. Bhattarai et al. https://doi.org/10.1007/s00271-022-00768-0
978. The effect of embedding actual evapotranspiration uncertainty in water balance model: coupling of interval-based hydrologic model and METRIC method M. Khodadadi et al. https://doi.org/10.1007/s11600-023-01112-6
979. Estimation of High-Resolution Land Surface Shortwave Albedo From AVIRIS Data T. He et al. https://doi.org/10.1109/JSTARS.2014.2302234
980. The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets C. Linés et al. https://doi.org/10.5194/hess-21-4747-2017
981. Evapotranspiration estimation using SMAP soil moisture products and bouchet complementary evapotranspiration over Southern Great Plains E. Walker et al. https://doi.org/10.1016/j.jaridenv.2019.01.002
982. Understanding of Coupled Terrestrial Carbon, Nitrogen and Water Dynamics—An Overview B. Chen & N. Coops https://doi.org/10.3390/s91108624
983. Multiscale remote-sensing retrieval in the evapotranspiration of Haloxylon ammodendron in the Gurbantunggut desert, China X. Cao et al. https://doi.org/10.1007/s12665-012-1989-0
984. Estimation of high spatiotemporal resolution actual evapotranspiration by combining the SWH model with the METRIC model J. Zhao et al. https://doi.org/10.1016/j.jhydrol.2020.124883
985. Global assessment of partitioning transpiration from evapotranspiration based on satellite solar-induced chlorophyll fluorescence data Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2022.128044
986. Impact of sensor footprint on measurement of directional brightness temperature of row crop canopies H. Ren et al. https://doi.org/10.1016/j.rse.2013.02.025
987. Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms Y. Yao et al. https://doi.org/10.1016/j.jag.2016.10.009
988. Advancements in earth observation for water resources monitoring and management in Africa: A comprehensive review T. Dube et al. https://doi.org/10.1016/j.jhydrol.2023.129738
989. Combing both simulated and field-measured data to develop robust hyperspectral indices for tracing canopy transpiration in drought-tolerant plant J. Jin et al. https://doi.org/10.1007/s10661-018-7140-2
990. Multi-scale partitioning of evapotranspiration using the three-temperature model in an oasis–desert landscape of northwest China C. Yan et al. https://doi.org/10.1016/j.ejrh.2025.102831
991. Regional crop water use assessment using Landsat‐derived evapotranspiration A. Bawa et al. https://doi.org/10.1002/hyp.14015
992. Surface roughness length dynamic over several different surfaces and its effects on modeling fluxes Y. Zhou et al. https://doi.org/10.1007/s11430-006-8262-x
993. Global canopy rainfall interception loss derived from satellite earth observations C. Zheng & L. Jia https://doi.org/10.1002/eco.2186
994. Synthesis of global actual evapotranspiration from 1982 to 2019 A. Elnashar et al. https://doi.org/10.5194/essd-13-447-2021
995. A VI-based phenology adaptation approach for rice crop monitoring using UAV multispectral images Q. Yang et al. https://doi.org/10.1016/j.fcr.2021.108419
996. Assessment of the agricultural water budget in southern Iran using Sentinel-2 to Landsat-8 datasets A. Caiserman et al. https://doi.org/10.1016/j.jaridenv.2021.104461
997. Intercomparison of remote sensing‐based models for estimation of evapotranspiration and accuracy assessment based on SWAT Y. Gao & D. Long https://doi.org/10.1002/hyp.7104
998. The role of vadose zone physics in the ecohydrological response of a Tibetan meadow to freeze–thaw cycles L. Yu et al. https://doi.org/10.5194/tc-14-4653-2020
999. Estimation of aerodynamic roughness of a harvested Douglas-fir forest using airborne LiDAR E. Paul-Limoges et al. https://doi.org/10.1016/j.rse.2013.05.007
1000. Multi-scales and multi-satellites estimates of evapotranspiration with a residual energy balance model in the Muzza agricultural district in Northern Italy C. Corbari et al. https://doi.org/10.1016/j.jhydrol.2015.02.041
1001. Automated actual evapotranspiration estimation: Hybrid model of a novel attention based U-Net and metaheuristic optimization algorithms A. Bafti et al. https://doi.org/10.1016/j.atmosres.2023.107107
1002. Water and Energy Dynamics in a Disturbed Ecosystem S. Alibakhshi et al. https://doi.org/10.1007/s41748-024-00498-7
1003. Comparative Assessment of Two Vegetation Fractional Cover Estimating Methods and Their Impacts on Modeling Urban Latent Heat Flux Using Landsat Imagery K. Liu et al. https://doi.org/10.3390/rs9050455
1004. Performance of Satellite-Based Evapotranspiration Models in Temperate Pastures of Southern Chile I. Moletto-Lobos et al. https://doi.org/10.3390/w12123587
1005. Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in situ air temperature observations C. Cammalleri et al. https://doi.org/10.1016/j.rse.2012.06.009
1006. Cloud-Based Fusion of Sentinel-1 Radar, MODIS and Soil Moisture Data for Resolution-Refined Evapotranspiration Mapping in Mountain Coffee Systems G. Klinke Neto et al. https://doi.org/10.3390/su18136473
1007. Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery W. Ma et al. https://doi.org/10.5194/hess-15-1403-2011
1008. An original interpretation of the wet edge of the surface temperature–albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico O. Merlin https://doi.org/10.5194/hess-17-3623-2013
1009. Characterizing the Effect of Vegetation Dynamics on the Bulk Heat Transfer Coefficient to Improve Variational Estimation of Surface Turbulent Fluxes A. Abdolghafoorian et al. https://doi.org/10.1175/JHM-D-16-0097.1
1010. Deriving daily evapotranspiration from remotely sensed instantaneous evaporative fraction over olive orchard in semi-arid Morocco J. Hoedjes et al. https://doi.org/10.1016/j.jhydrol.2008.02.016
1011. Bridging Thermal Infrared Sensing and Physically‐Based Evapotranspiration Modeling: From Theoretical Implementation to Validation Across an Aridity Gradient in Australian Ecosystems K. Mallick et al. https://doi.org/10.1029/2017WR021357
1012. Basin scale rainfall-evapotranspiration dynamics in a tropical semiarid environment during dry and wet years P. Mutti et al. https://doi.org/10.1016/j.jag.2018.10.007
1013. Evaluating satellite-based evapotranspiration estimates for hydrological applications in data-scarce regions: A case in Ethiopia Y. Dile et al. https://doi.org/10.1016/j.scitotenv.2020.140702
1014. A one – source model to estimate sensible heat flux in agricultural landscapes F. Castellví & M. González Dugo https://doi.org/10.1016/j.agrformet.2021.108628
1015. Multimodel ensemble estimation of Landsat-like global terrestrial latent heat flux using a generalized deep CNN-LSTM integration algorithm X. Guo et al. https://doi.org/10.1016/j.agrformet.2024.109962
1016. Estimation of evapotranspiration fluxes from Sal (Shorea robusta Gaertn.f) forest using METRIC model: case study of Doon Valley, India S. Purohit et al. https://doi.org/10.1080/10106049.2021.1920630
1017. Actual evapotranspiration estimation using METRIC model and Landsat satellite images over an irrigated field in the Eastern Mediterranean Region of Turkey O. Alsenjar et al. https://doi.org/10.1007/s42990-023-00099-y
1018. How does film mulching modify available energy, evapotranspiration, and crop coefficient during the seed–maize growing season in northwest China? Y. Zhao et al. https://doi.org/10.1016/j.agwat.2020.106666
1019. Relationship between Evapotranspiration and Land Surface Temperature under Energy- and Water-Limited Conditions in Dry and Cold Climates Z. Sun et al. https://doi.org/10.1155/2016/1835487
1020. Impact of land use change on actual evapotranspiration in the Songnen Plain, China Z. Lu et al. https://doi.org/10.1016/j.ejrh.2024.101854
1021. Estimating Turbulent Fluxes in the Tropical Andes M. Córdova et al. https://doi.org/10.3390/atmos11020213
1022. Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion S. Wang et al. https://doi.org/10.3390/rs10121978
1023. Estimation of evapotranspiration for ungauged areas using MODIS measurements and GLDAS data J. Du & R. Sun https://doi.org/10.1016/j.proenv.2012.01.165
1024. Daily global transpiration estimation (2001–2018) by integrating satellite solar-induced fluorescence and spatially heterogeneous slope parameter in a conductance-photosynthesis model J. Jin et al. https://doi.org/10.1016/j.agrformet.2025.110993
1025. Optical-based and thermal-based surface conductance and actual evapotranspiration estimation, an evaluation study in the North China Plain X. Hu et al. https://doi.org/10.1016/j.agrformet.2018.09.015
1026. Coordinated estimates of 4-day 500 m global land surface energy balance components J. Wang et al. https://doi.org/10.1016/j.rse.2025.114795
1027. Determining spatio-temporal variations of ecological water consumption by natural oases for sustainable water resources allocation in a hyper-arid endorheic basin G. Gao et al. https://doi.org/10.1016/j.jclepro.2018.03.025
1028. Estimating Actual Evapotranspiration from Satellite and Meteorological Data in Central Bolivia C. Seiler & A. Moene https://doi.org/10.1175/2010EI332.1
1029. Improving Predictions of Water and Heat Fluxes by Assimilating MODIS Land Surface Temperature Products into the Common Land Model T. Xu et al. https://doi.org/10.1175/2010JHM1300.1
1030. Evaluation of evapotranspiration data and gridded products using robust linear estimators in Colombia G. Araujo-Carrillo et al. https://doi.org/10.1007/s00704-025-05406-1
1031. The spatial variability of actual evapotranspiration across the Amazon River Basin based on remote sensing products validated with flux towers V. Paca et al. https://doi.org/10.1186/s13717-019-0158-8
1032. Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data P. Karimi & W. Bastiaanssen https://doi.org/10.5194/hess-19-507-2015
1033. Spatio-temporal variability of evapotranspiration and crop water requirement from space A. Samuel et al. https://doi.org/10.1016/j.jhydrol.2018.01.058
1034. Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa J. Kiptala et al. https://doi.org/10.1002/2013WR014240
1035. Hydrological Parameters Estimation Using Remote Sensing and GIS for Indian Region: A Review P. Thakur et al. https://doi.org/10.1007/s40010-017-0440-z
1036. Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations C. Zheng et al. https://doi.org/10.1016/j.jhydrol.2022.128444
1037. Improving terrestrial evapotranspiration estimation of the Tibetan Plateau by coupling SEBS with machine learning-derived aerodynamic resistance Y. Kan et al. https://doi.org/10.1016/j.jhydrol.2025.133711
1038. Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach K. Semmens et al. https://doi.org/10.1016/j.rse.2015.10.025
1039. Evaporation mapping at two scales using optical imagery in the White Volta Basin, Upper East Ghana H. Compaoré et al. https://doi.org/10.1016/j.pce.2007.04.021
1040. Estimating spatial variations of total evaporation using multispectral sensors within the uMngeni catchment, South Africa C. Shoko et al. https://doi.org/10.1080/10106049.2015.1047414
1041. Estimating evaporative fraction from readily obtainable variables in mangrove forests of the Everglades, U.S.A. A. Yagci et al. https://doi.org/10.1080/01431161.2017.1312033
1042. Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA) A. French et al. https://doi.org/10.1016/j.rse.2005.05.015
1043. Dominant Modes of Tibetan Plateau Summer Surface Sensible Heating and Associated Atmospheric Circulation Anomalies W. Fan et al. https://doi.org/10.3390/rs14040956
1044. Irrigation and Precipitation Hydrological Consistency with SMOS, SMAP, ESA-CCI, Copernicus SSM1km, and AMSR-2 Remotely Sensed Soil Moisture Products N. Paciolla et al. https://doi.org/10.3390/rs12223737
1045. A Robust Framework for Improving Fine-Scale Evapotranspiration Estimation From UAV-Based Multispectral and Thermal Images J. Wei et al. https://doi.org/10.1109/TGRS.2025.3601120
1046. Estimation of hourly land surface heat fluxes over the Tibetan Plateau by the combined use of geostationary and polar-orbiting satellites L. Zhong et al. https://doi.org/10.5194/acp-19-5529-2019
1047. Utility of single-source surface energy balance models in estimation of daily actual evapotranspiration in arid regions N. Kumar & M. Hamouda https://doi.org/10.1080/02626667.2024.2446266
1048. A high-throughput shared service to estimate evapotranspiration using Landsat imagery J. Cunha et al. https://doi.org/10.1016/j.cageo.2019.104341
1049. Using Simplified Thermal Inertia to Determine the Theoretical Dry Line in Feature Space for Evapotranspiration Retrieval S. Mi et al. https://doi.org/10.3390/rs70810856
1050. Improving the Evapotranspiration Estimation under Cloudy Condition by Extending the Ts-VI Triangle Model B. Li et al. https://doi.org/10.3390/rs13081516
1051. Different Vegetation Information Inputs Significantly Affect the Evapotranspiration Simulations of the PT-JPL Model Z. Luo et al. https://doi.org/10.3390/rs14112573
1052. Intercomparison of Surface Energy Fluxes Estimates from the FEST-EWB and TSeB Models over the Heterogeneous REFLEX 2012 Site (Barrax, Spain) C. Corbari et al. https://doi.org/10.2478/s11600-014-0258-x
1053. MODIS Evapotranspiration Downscaling Using a Deep Neural Network Trained Using Landsat 8 Reflectance and Temperature Data X. Che et al. https://doi.org/10.3390/rs14225876
1054. Modelling soil moisture and daily actual evapotranspiration: Integrating remote sensing surface energy balance and 1D Richards equation H. Awada et al. https://doi.org/10.1016/j.jag.2024.103744
1055. A new approach to estimate daily evapotranspiration, based on Landsat data and FAO56 principles S. Veysi et al. https://doi.org/10.1080/01431161.2023.2237662
1056. Separating Vegetation Greening and Climate Change Controls on Evapotranspiration trend over the Loess Plateau Z. Jin et al. https://doi.org/10.1038/s41598-017-08477-x
1057. Medium-Resolution Mapping of Evapotranspiration at the Catchment Scale Based on Thermal Infrared MODIS Data and ERA-Interim Reanalysis over North Africa A. Diarra et al. https://doi.org/10.3390/rs14205071
1058. Crop coefficients and actual evapotranspiration of a drip-irrigated Merlot vineyard using multispectral satellite images M. Carrasco-Benavides et al. https://doi.org/10.1007/s00271-012-0379-4
1059. The use of remote sensing in soil and terrain mapping — A review V. Mulder et al. https://doi.org/10.1016/j.geoderma.2010.12.018
1060. Estimation and mechanism analysis of global evapotranspiration based on a physics-informed deep-learning model J. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.134351
1061. Determination of canopy‐shadow‐affected area in sparse steppes and its effects on evaporation and evapotranspiration Y. Feng et al. https://doi.org/10.1002/eco.1482
1062. Field-Scale Assessment of Land and Water Use Change over the California Delta Using Remote Sensing M. Anderson et al. https://doi.org/10.3390/rs10060889
1063. Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data L. Sun et al. https://doi.org/10.1016/j.cageo.2017.04.007
1064. Interpretable model responsibility for cropland evapotranspiration across environmental gradients H. Chen & Y. Bai https://doi.org/10.1016/j.agwat.2026.110801
1065. Multiple sources of uncertainties in satellite retrieval of terrestrial actual evapotranspiration M. Cao et al. https://doi.org/10.1016/j.jhydrol.2021.126642
1066. Integrating eco-evolutionary optimality principle and land processes for evapotranspiration estimation M. Zou et al. https://doi.org/10.1016/j.jhydrol.2022.128855
1067. A Simulation Study of Global Evapotranspiration Components Using the Community Land Model M. Yang et al. https://doi.org/10.3390/atmos9050178
1068. Triple collocation-based merging of multi-source gridded evapotranspiration data in the Nordic Region X. Li et al. https://doi.org/10.1016/j.agrformet.2023.109451
1069. The Radiation Energy Distribution over the Tibetan Plateau: A Review and Perspective Y. Ma et al. https://doi.org/10.1007/s00376-025-5065-6
1070. Assessment of surface energy balance algorithm for land and operational simplified surface energy balance algorithm over freshwater and saline water bodies in Urmia Lake Basin M. Rahimpour & M. Rahimzadegan https://doi.org/10.1007/s00704-020-03472-1
1071. Evaluation of three complementary relationship approaches for evapotranspiration over the Yellow River basin S. Liu et al. https://doi.org/10.1002/hyp.6048
1072. Validation and Comparison of ANEM-SBAC Method for Temperature and Emissivity Separation Using MODIS and VIIRS Data in the València Test Site O. Soriano-Masia et al. https://doi.org/10.1109/JSTARS.2026.3726996
1073. The Performance of Satellite-Based Actual Evapotranspiration Products and the Assessment of Irrigation Efficiency in Egypt S. Ayyad et al. https://doi.org/10.3390/w11091913
1074. The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models I. Trebs et al. https://doi.org/10.1016/j.rse.2021.112602
1075. Spatiotemporal Variabilities in Evapotranspiration of Alfalfa: A Case Study Using Remote Sensing METRIC and SSEBop Models and Eddy Covariance Z. Tawalbeh et al. https://doi.org/10.3390/rs16132290
1076. A New Material-Oriented TES for Land Surface Temperature and SUHI Retrieval in Urban Areas: Case Study over Madrid in the Framework of the Future TRISHNA Mission A. Michel et al. https://doi.org/10.3390/rs13245139
1077. Combination of Multiple Variables and Machine Learning for Regional Cropland Water and Carbon Fluxes Estimation: A Case Study in the Haihe River Basin M. Cheng et al. https://doi.org/10.3390/rs16173280
1078. Unveiling spatial and temporal characteristics of cooling effects of rice paddy expansion in Northeast China T. Yang et al. https://doi.org/10.1016/j.agrformet.2025.110967
1079. Crop Drought Identification Index for winter wheat based on evapotranspiration in the Huang-Huai-Hai Plain, China X. Wu et al. https://doi.org/10.1016/j.agee.2018.05.001
1080. NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms K. Cawse-Nicholson et al. https://doi.org/10.1016/j.rse.2021.112349
1081. Progress of evapotranspiration research based on VOSviewer: A review Z. Yang et al. https://doi.org/10.2166/wst.2024.036
1082. Warming-Wetting Climate Contributes to the Evapotranspiration Increasing Trend in the Heihe River Basin, China J. Wang et al. https://doi.org/10.1109/JSTARS.2026.3713958
1083. Estimating groundwater contribution to transpiration using satellite-derived evapotranspiration estimates coupled with stable isotope analysis S. Gokool et al. https://doi.org/10.1016/j.jaridenv.2018.02.002
1084. Towards Estimating Land Evaporation at Field Scales Using GLEAM B. Martens et al. https://doi.org/10.3390/rs10111720
1085. An estimation of the evapotranspiration of typical steppe areas using Landsat images and the METRIC model J. Wang et al. https://doi.org/10.2166/wcc.2021.432
1086. A remote sensing-based irrigation performance assessment: a case study of the Office du Niger in Mali S. Zwart & L. Leclert https://doi.org/10.1007/s00271-009-0199-3
1087. Analysis and estimation of tallgrass prairie evapotranspiration in the central United States P. Wagle et al. https://doi.org/10.1016/j.agrformet.2016.08.005
1088. A global 30-m ET model (HSEB) using harmonized Landsat and Sentinel-2, MODIS and VIIRS: Comparison to ECOSTRESS ET and LST H. Jaafar et al. https://doi.org/10.1016/j.rse.2022.112995
1089. Improving WISE Crop Evapotranspiration Estimates Using Crop Coefficients Derived from Remote-Sensing Algorithms E. Costa-Filho et al. https://doi.org/10.1061/JIDEDH.IRENG-10104
1090. Assessing Satellite-Derived OpenET Platform Evapotranspiration of Mature Pecan Orchard in the Mesilla Valley, New Mexico Z. Tawalbeh et al. https://doi.org/10.3390/rs16081429
1091. Inferring transpiration from evapotranspiration: A transpiration indicator using the Priestley-Taylor coefficient of wet environment G. Gan & Y. Liu https://doi.org/10.1016/j.ecolind.2019.105853
1092. Spatially remotely sensed evapotranspiration estimates in Sahel region using an ensemble contextual model with automated heterogeneity assessment N. Farhani et al. https://doi.org/10.1016/j.srs.2025.100229
1093. How sensitive is SEBAL to changes in input variables, domain size and satellite sensor? D. Long et al. https://doi.org/10.1029/2011JD016542
1094. Performance Assessment of MOD16 in Evapotranspiration Evaluation in Northwestern Mexico A. Aguilar et al. https://doi.org/10.3390/w10070901
1095. Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia E. Tegegne et al. https://doi.org/10.1007/s00704-020-03397-9
1096. Mapping daily and seasonal evapotranspiration from irrigated crops using global climate grids and satellite imagery: Automation and methods comparison T. Biggs et al. https://doi.org/10.1002/2016WR019107
1097. Can we trust remote sensing evapotranspiration products over Africa? I. Weerasinghe et al. https://doi.org/10.5194/hess-24-1565-2020
1098. A first assessment of airborne HyTES-based land surface temperature and evapotranspiration M. Pascolini-Campbell et al. https://doi.org/10.1016/j.rsase.2024.101344
1099. Effect of pixel scale on evapotranspiration estimation by remote sensing over oasis areas in north-western China H. Tian et al. https://doi.org/10.1007/s12665-012-1677-0
1100. The spatial heterogeneity of land surface conditions and its influence on surface fluxes over a typical underlying surface in the Tibetan Plateau G. Sun et al. https://doi.org/10.1007/s00704-018-2369-9
1101. Evaluation of remotely sensed actual evapotranspiration products from COMS and MODIS at two different flux tower sites in Korea J. Baik & M. Choi https://doi.org/10.1080/01431161.2014.998349
1102. Breaking the zero-flux paradigm: an iterative surface energy balance framework for enhanced cold pixel characterization J. Wei et al. https://doi.org/10.1016/j.jclepro.2025.147011
1103. Spatio-Temporal Characteristics of the Evapotranspiration in the Lower Mekong River Basin during 2008–2017 X. Pan et al. https://doi.org/10.3390/rs14112609
1104. Modelling of the Effects of Canopy Structure on Evapotranspiration in Root Zone of Lycium Barbarum B. Ma & J. He https://doi.org/10.2139/ssrn.4069592
1105. METRIC–random forest fusion framework for daily 30-m evapotranspiration mapping in Northern Thailand M. Shanmugam et al. https://doi.org/10.1016/j.rsase.2026.102257
1106. Parameter estimation of coupled water and energy balance models based on stationary constraints of surface states J. Sun et al. https://doi.org/10.1029/2010WR009293
1107. Comparison of ET estimations by the three-temperature model, SEBAL model and eddy covariance observations X. Zhou et al. https://doi.org/10.1016/j.jhydrol.2014.08.004
1108. Remote Sensing for Irrigation Water Management—The State of the Art and Prospects for Near‐Future Operations W. Bastiaanssen et al. https://doi.org/10.1002/ird.70202
1109. Observations of Turbulent Heat Fluxes Variability in a Semiarid Coastal Lagoon (Gulf of California) L. Benítez-Valenzuela & Z. Sanchez-Mejia https://doi.org/10.3390/atmos11060626
1110. Remote Sensing-Based Algorithms for Estimating Evapotranspiration in Agricultural Systems: A systematic literature review W. Oliveira et al. https://doi.org/10.1109/MGRS.2024.3469182
1111. Coupling water and carbon processes to estimate field-scale maize evapotranspiration with Sentinel-2 data Z. Ma et al. https://doi.org/10.1016/j.agrformet.2021.108421
1112. Remote sensing: hydrology Q. Tang et al. https://doi.org/10.1177/0309133309346650
1113. A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations B. Bhattacharya et al. https://doi.org/10.5194/bg-19-5521-2022
1114. From 2D Flat Maps to 4D Living Models: A review of UAV remote sensing in agriculture J. Zhou et al. https://doi.org/10.1109/MGRS.2026.3686306
1115. A method for sensible heat flux model parameterization based on radiometric surface temperature and environmental factors without involving the parameter KB−1 Q. Zhuang et al. https://doi.org/10.1016/j.jag.2015.11.015
1116. Accuracy comparison of remotely sensed evapotranspiration products and their associated water stress footprints under different land cover types in Korean peninsula U. Liaqat & M. Choi https://doi.org/10.1016/j.jclepro.2016.09.022
1117. Assessing wheat crop water productivity for sustainable agricultural water management in diverse agro-climatic regions of Uttarakhand, India P. Singh & K. Kothari https://doi.org/10.1016/j.indic.2025.100738
1118. Optimization of a remote sensing energy balance method over different canopy applied at global scale X. Chen et al. https://doi.org/10.1016/j.agrformet.2019.107633
1119. Application of A Simple Landsat-MODIS Fusion Model to Estimate Evapotranspiration over A Heterogeneous Sparse Vegetation Region S. Jamshidi et al. https://doi.org/10.3390/rs11070741
1120. Validation of a large scale hydrological model with data fields retrieved from reflective and thermal optical remote sensing data – A case study for the Upper Rhine Valley M. Casper & M. Vohland https://doi.org/10.1016/j.pce.2008.06.001
1121. High-Resolution Crop Evapotranspiration Estimation Using the Automated OPTRAM-ETc Method M. Alavi et al. https://doi.org/10.1007/s41748-025-00852-3
1122. Remote sensing for agricultural applications: A meta-review M. Weiss et al. https://doi.org/10.1016/j.rse.2019.111402
1123. Evapotranspiration Estimates over Non-Homogeneous Mediterranean Land Cover by a Calibrated “Critical Resistance” Approach P. Martano https://doi.org/10.3390/atmos6030255
1124. Ecosystem Evapotranspiration as a Response to Climate and Vegetation Coverage Changes in Northwest Yunnan, China H. Yang et al. https://doi.org/10.1371/journal.pone.0134795
1125. geeSEBAL-MODIS: Continental-scale evapotranspiration based on the surface energy balance for South America B. Comini de Andrade et al. https://doi.org/10.1016/j.isprsjprs.2023.12.001
1126. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature Y. Yang et al. https://doi.org/10.3390/rs9010043
1127. Evapotranspiration estimates in a traditional irrigated area in semi-arid Mediterranean. Comparison of four remote sensing-based models J. Elfarkh et al. https://doi.org/10.1016/j.agwat.2022.107728
1128. An intercomparison of three remote sensing-based energy balance models using Large Aperture Scintillometer measurements over a wheat–corn production region R. Tang et al. https://doi.org/10.1016/j.rse.2011.07.004
1129. Study on daily surface evapotranspiration with SEBS in Tibet Autonomous Region G. Zhuo et al. https://doi.org/10.1007/s11442-014-1076-4
1130. Implementation and evaluation of a global evapotranspiration index algorithm based on land surface temperature K. TANADA et al. https://doi.org/10.2480/agrmet.D-25-00022
1131. Remote-Sensing Estimation of Evapotranspiration for Multiple Land Cover Types Based on an Improved Canopy Conductance Model J. Wang et al. https://doi.org/10.3390/rs18030513
1132. A framework for automating the configuration of OpenCL R. de Souza Rosa Gomes et al. https://doi.org/10.1016/j.envsoft.2013.11.005
1133. Preliminary evaluation of remote sensing evapotranspiration models for field-scale agricultural water management in arid central Iran S. Sima et al. https://doi.org/10.1016/j.agwat.2025.110084
1134. Improving parameterization of an evapotranspiration estimation model with eddy covariance measurements for a regional irrigation scheduling program A. Talib et al. https://doi.org/10.1016/j.agrformet.2024.109967
1135. Comparative analysis of actual evapotranspiration values estimated by METRIC model using LOCAL data and EEFlux for an irrigated area in Northern Sinaloa, Mexico B. Vázquez-Rodríguez et al. https://doi.org/10.1016/j.heliyon.2024.e34767
1136. Estimation of the Terrestrial Water Budget over Northern Eurasia through the Use of Multiple Data Sources T. Troy et al. https://doi.org/10.1175/2011JCLI3936.1
1137. The Karkheh River basin: the food basket of Iran under pressure M. Ahmad & M. Giordano https://doi.org/10.1080/02508060.2010.510326
1138. The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms D. Michel et al. https://doi.org/10.5194/hess-20-803-2016
1139. Exploiting the modified surface energy balance system (mSEBS) model and monitoring actual land surface evapotranspiration in China L. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.133596
1140. Comprehensive Evaluation of the Variable Infiltration Capacity (VIC) Model in the North American Land Data Assimilation System Y. Xia et al. https://doi.org/10.1175/JHM-D-18-0139.1
1141. Estimating the regional evapotranspiration in Zhalong wetland with the Two-Source Energy Balance (TSEB) model and Landsat7/ETM+ images W. Yao et al. https://doi.org/10.1016/j.ecoinf.2010.06.002
1142. Assessment of Spatial Representativeness of Eddy Covariance Flux Data from Flux Tower to Regional Grid H. Wang et al. https://doi.org/10.3390/rs8090742
1143. Challenges and Future Perspectives of Multi-/Hyperspectral Thermal Infrared Remote Sensing for Crop Water-Stress Detection: A Review M. Gerhards et al. https://doi.org/10.3390/rs11101240
1144. Satellite-derived land surface temperature: Current status and perspectives Z. Li et al. https://doi.org/10.1016/j.rse.2012.12.008
1145. An artificial neural network approach to estimate evapotranspiration from remote sensing and AmeriFlux data Z. Chen et al. https://doi.org/10.1007/s11707-012-0346-7
1146. A practical method for reducing terrain effect on land surface temperature using random forest regression W. Zhao et al. https://doi.org/10.1016/j.rse.2018.12.008
1147. Automated evapotranspiration retrieval model with missing soil-related datasets: The proposal of SEBALI M. Mhawej et al. https://doi.org/10.1016/j.agwat.2019.105938
1148. ReSET-Raster: Surface Energy Balance Model for Calculating Evapotranspiration Using a Raster Approach A. Elhaddad & L. Garcia https://doi.org/10.1061/(ASCE)IR.1943-4774.0000282
1149. Modelling soil heat flux C. Núñez et al. https://doi.org/10.1007/s00704-009-0185-y
1150. Regional estimation of daily to annual regional evapotranspiration with MODIS data in the Yellow River Delta wetland L. Jia et al. https://doi.org/10.5194/hess-13-1775-2009
1151. Ground heat flux: An analytical review of 6 models evaluated at 88 sites and globally A. Purdy et al. https://doi.org/10.1002/2016JG003591
1152. Coupling a groundwater model with a land surface model to improve water and energy cycle simulation W. Tian et al. https://doi.org/10.5194/hess-16-4707-2012
1153. Conserving Land–Atmosphere Synthesis Suite (CLASS) S. Hobeichi et al. https://doi.org/10.1175/JCLI-D-19-0036.1
1154. Assessment of the performance of the drag and bulk transfer method in estimating sensible and latent heat fluxes in a tropical station M. Adeniyi & O. Ogunsola https://doi.org/10.1007/s00704-011-0496-7
1155. Variational assimilation of land surface temperature and the estimation of surface energy balance components S. Bateni et al. https://doi.org/10.1016/j.jhydrol.2012.12.039
1156. Climate Change Amplifies the Effects of Vegetation Restoration on Evapotranspiration and Water Availability in the Beijing–Tianjin Sand Source Region, Northern China X. Li et al. https://doi.org/10.3390/land14030527
1157. Monitoring surface soil moisture status based on remotely sensed surface temperature and vegetation index information L. Sun et al. https://doi.org/10.1016/j.agrformet.2012.07.015
1158. ECOSTRESS estimates gross primary production with fine spatial resolution for different times of day from the International Space Station X. Li et al. https://doi.org/10.1016/j.rse.2021.112360
1159. Development of a 10-year (2001–2010) 0.1° data set of land-surface energy balance for mainland China X. Chen et al. https://doi.org/10.5194/acp-14-13097-2014
1160. Impact and consequences of evapotranspiration changes on water resources availability in the arid Zhangye Basin, China X. Jin et al. https://doi.org/10.1080/01431160802559053
1161. Comparison of Four Different Energy Balance Models for Estimating Evapotranspiration in the Midwestern United States R. Singh & G. Senay https://doi.org/10.3390/w8010009
1162. Assessment of Irrigation Efficiency by Coupling Remote Sensing and Ground-Based Data: Case Study of Sprinkler Irrigation of Alfalfa in the Saratovskoye Zavolgie Region of Russia A. Zeyliger et al. https://doi.org/10.3390/s23052601
1163. An Automated and Improved Methodology to Retrieve Long-time Series of Evapotranspiration Based on Remote Sensing and Reanalysis Data M. Saboori et al. https://doi.org/10.3390/rs14246253
1164. Review on estimation methods of the Earth’s surface energy balance components from ground and satellite measurements M. Rahman & W. Zhang https://doi.org/10.1007/s12040-019-1098-5
1165. A Remote Sensing Method for Estimating Surface Air Temperature and Surface Vapor Pressure on a Regional Scale R. Zhang et al. https://doi.org/10.3390/rs70506005
1166. The spatio-temporal soil moisture variation along the major tributaries of Zambezi River in the Mbire District, Zimbabwe W. Gumindoga et al. https://doi.org/10.1016/j.ejrh.2020.100753
1167. Impact of model structure and parameterization on Penman–Monteith type evaporation models A. Ershadi et al. https://doi.org/10.1016/j.jhydrol.2015.04.008
1168. Remote sensing based yield monitoring: Application to winter wheat in United States and Ukraine B. Franch et al. https://doi.org/10.1016/j.jag.2018.11.012
1169. Mixtures of Gaussians for Uncertainty Description in Bivariate Latent Heat Flux Proxies R. Wójcik et al. https://doi.org/10.1175/JHM491.1
1170. Transport processes and ground temperature affected by solar irradiation through the troposphere layer P. Wei et al. https://doi.org/10.1016/j.rineng.2025.105736
1171. The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally gridded forcing data M. McCabe et al. https://doi.org/10.5194/gmd-9-283-2016
1172. Satellite assessment of land surface evapotranspiration for the pan‐Arctic domain Q. Mu et al. https://doi.org/10.1029/2008WR007189
1173. Estimation of evapotranspiration from a suite of geostationary satellites R. Nigam et al. https://doi.org/10.1080/01431161.2021.1910366
1174. Evaluation of evapotranspiration using energy-based and water balance hydrological models R. Fitria et al. https://doi.org/10.2166/wcc.2024.499
1175. Modeling canopy conductance and transpiration from solar-induced chlorophyll fluorescence N. Shan et al. https://doi.org/10.1016/j.agrformet.2019.01.031
1176. Flux Measurements in Cairo. Part 2: On the Determination of the Spatial Radiation and Energy Balance Using ASTER Satellite Data C. Frey & E. Parlow https://doi.org/10.3390/rs4092635
1177. Evaluating Four Remote Sensing Methods for Estimating Surface Air Temperature on a Regional Scale S. Liu et al. https://doi.org/10.1175/JAMC-D-16-0188.1
1178. Applying multiple land surface temperature products to derive heat fluxes over a grassland site C. Jiménez et al. https://doi.org/10.1016/j.rsase.2017.01.002
1179. Water balance change and its implications to vegetation in the Tarim River Basin, Central Asia M. Xu et al. https://doi.org/10.1016/j.quaint.2019.06.011
1180. Remote Sensing of Water: The Observation-to-Inference Arc Across Six Decades and Toward an AI-Native Future D. Ames https://doi.org/10.3390/rs18081127
1181. Analysis of the Diurnal Pattern of Evaporative Fraction and Its Controlling Factors over Croplands in the Northern China D. YANG et al. https://doi.org/10.1016/S2095-3119(13)60540-7
1182. Modelling landscape dynamics with Python D. Karssenberg et al. https://doi.org/10.1080/13658810601063936
1183. Remote sensing contributions to evapotranspiration modeling and assessment: models and methods S. Merzoug et al. https://doi.org/10.1007/s42990-026-00233-6
1184. Comparison of M5 Model Tree and Artificial Neural Network’s Methodologies in Modelling Daily Reference Evapotranspiration from NOAA Satellite Images A. Rahimikhoob https://doi.org/10.1007/s11269-016-1331-9
1185. Improving remote sensing based evapotranspiration modelling in a heterogeneous urban environment M. Faridatul et al. https://doi.org/10.1016/j.jhydrol.2019.124405
1186. A geo-informatics approach for estimating water resources management components and their interrelationships U. Liaqat et al. https://doi.org/10.1016/j.agwat.2016.09.010
1187. An observation-driven optimization method for continuous estimation of evaporative fraction over large heterogeneous areas W. Zhu et al. https://doi.org/10.1016/j.rse.2020.111887
1188. A novel index for ecological drought monitoring based on ecological water deficit T. Jiang et al. https://doi.org/10.1016/j.ecolind.2021.107804
1189. Urban green space classification and water consumption analysis with remote-sensing technology: a case study in Beijing, China S. Di et al. https://doi.org/10.1080/01431161.2018.1479798
1190. A physical method for downscaling land surface temperatures using surface energy balance theory Y. Hu et al. https://doi.org/10.1016/j.rse.2022.113421
1191. Evapotranspiration Estimates at High Spatial and Temporal Resolutions from an Energy–Water Balance Model and Satellite Data in the Capitanata Irrigation Consortium C. Corbari et al. https://doi.org/10.3390/rs12244083
1192. Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region J. Lian & M. Huang https://doi.org/10.1016/j.agwat.2015.12.001
1193. Estimation of surface energy fluxes under complex terrain of Mt. Qomolangma over the Tibetan Plateau X. Chen et al. https://doi.org/10.5194/hess-17-1607-2013
1194. Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data J. Kalma et al. https://doi.org/10.1007/s10712-008-9037-z
1195. Analytical framework based on thermodynamics to estimate spatially distributed surface energy fluxes from remotely sensed radiations M. Gupta et al. https://doi.org/10.1016/j.rse.2023.113659
1196. Global water cycle and remote sensing big data: overview, challenge, and opportunities Y. Cui et al. https://doi.org/10.1080/20964471.2018.1548052
1197. Spatiotemporal Variation of Evapotranspiration on Different Land Use/Cover in the Inner Mongolia Reach of the Yellow River Basin X. Zhang et al. https://doi.org/10.3390/rs14184499
1198. Validation of the SEBS-derived sensible heat for FY3A/VIRR and TERRA/MODIS over an alpine grass region using LAS measurements Y. Wang et al. https://doi.org/10.1016/j.jag.2012.09.005
1199. Modifying an Image Fusion Approach for High Spatiotemporal LST Retrieval in Surface Dryness and Evapotranspiration Estimations T. Januar et al. https://doi.org/10.3390/rs12030498
1200. Evapotranspiration estimation using a satellite-based surface energy balance: a case study of Upper Bari Doab, Pakistan M. Zahid et al. https://doi.org/10.1007/s12665-023-11284-5
1201. Critical soil moisture thresholds for evapotranspiration in rainfed semi-arid maize in Kenya M. Räsänen et al. https://doi.org/10.1016/j.agrformet.2026.111219
1202. Estimation of air temperature and reference evapotranspiration using MODIS land surface temperature over Greece G. Kitsara et al. https://doi.org/10.1080/01431161.2017.1395965
1203. Environmental factors affecting the accuracy of surface fluxes from a two-source model in Mediterranean drylands: Upscaling instantaneous to daytime estimates L. Morillas et al. https://doi.org/10.1016/j.agrformet.2014.01.018
1204. Proximal Remote Sensing-Based Vegetation Indices for Monitoring Mango Tree Stem Sap Flux Density J. Jin et al. https://doi.org/10.3390/rs14061483
1205. Upscaling of Latent Heat Flux in Heihe River Basin Based on Transfer Learning Model J. Lin et al. https://doi.org/10.3390/rs15071901
1206. Physics-guided temporal fusion for long-term daily urban land surface temperature: Accuracy, uncertainty, and interpretability in Geneva, Switzerland S. Hamze-Ziabari & M. Lehning https://doi.org/10.1016/j.uclim.2026.102987
1207. A comparative assessment of the accuracies of split-window algorithms for retrieving of land surface temperature using Landsat 8 data F. Arabi Aliabad et al. https://doi.org/10.1007/s40808-020-01007-1
1208. A comparative spectral assessment approach of SEBAL and SEBS for actual evaporation estimation in Ardabil Province K. Valizadeh Kamran et al. https://doi.org/10.26833/ijeg.1344679
1209. Remote sensing temporal and spatial patterns of evapotranspiration and the responses to water management in a large irrigation district of North China Y. Yang et al. https://doi.org/10.1016/j.agrformet.2012.05.011
1210. Multi-scale EO-based agricultural drought monitoring indicator for operative irrigation networks management in Italy C. Corbari et al. https://doi.org/10.1016/j.ejrh.2024.101732
1211. Evaluation of SEBAL and METRIC algorithms to estimate evaporation over fresh and saline water bodies (case study: Urmia Lake, Dez reservoir, and Karkhe reservoir) R. Ghahreman & M. Rahimzadegan https://doi.org/10.61186/jgit.11.4.1
1212. Utility of Assimilating Surface Radiometric Temperature Observations for Evaporative Fraction and Heat Transfer Coefficient Retrieval W. Crow & W. Kustas https://doi.org/10.1007/s10546-004-2121-0
1213. Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States V. Mishra et al. https://doi.org/10.5194/hess-22-4935-2018
1214. Monitoring water stress using time series of observed to unstressed surface temperature difference G. Boulet et al. https://doi.org/10.1016/j.agrformet.2007.05.012
1215. A satellite-based hybrid algorithm to determine the Priestley–Taylor parameter for global terrestrial latent heat flux estimation across multiple biomes Y. Yao et al. https://doi.org/10.1016/j.rse.2015.05.013
1216. Comparing actual evapotranspiration estimations by METRIC to in-situ water balance measurements over an irrigated field in Turkey M. Cetin et al. https://doi.org/10.1080/02626667.2023.2198649
1217. Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors M. McCabe & E. Wood https://doi.org/10.1016/j.rse.2006.07.006
1218. Influence of the biochar application on the thermal properties of soddy-podzolic soil and on the energy balance fluxes of spring wheat in the Leningrad region under various soil moisture conditions A. Dobrokhotov & L. Kozyreva https://doi.org/10.19047/0136-1694-2023-116-43-75
1219. Evaluation and comparison of multiple evapotranspiration data models over the contiguous United States: Implications for the next phase of NLDAS (NLDAS-Testbed) development B. Zhang et al. https://doi.org/10.1016/j.agrformet.2019.107810
1220. Spatio-temporal pattern of ecological droughts and their impacts on health of vegetation in Northwestern China T. Jiang et al. https://doi.org/10.1016/j.jenvman.2021.114356
1221. Comparison of the Remote Sensing Based-Energy Balance Models for Estimating Evaporation from Salin Lakes M. Khorsand Movaghar & S. Sima https://doi.org/10.29252/jgit.7.2.155
1222. Mass and energy flux estimates at different spatial resolutions in a heterogeneous area through a distributed energy–water balance model and remote-sensing data C. Corbari et al. https://doi.org/10.1080/01431161.2012.716924
1223. Spatiotemporal Variability in Water-Use Efficiency in Tianshan Mountains (Xinjiang, China) and the Influencing Factors J. Chen & L. Cao https://doi.org/10.3390/su14138191
1224. Water use efficiency and its drivers of two typical cash crops in an arid area of Northwest China H. Yu et al. https://doi.org/10.1016/j.agwat.2023.108433
1225. Regional estimation and validation of remotely sensed evapotranspiration in China C. Zhan et al. https://doi.org/10.1016/j.catena.2015.04.018
1226. Automated Geospatial Models of Varying Complexities for Pine Forest Evapotranspiration Estimation with Advanced Data Mining S. Panda et al. https://doi.org/10.3390/w10111687
1227. Improving irrigation and evapotranspiration simulation by incorporating seasonal irrigation map into a land surface model D. Li et al. https://doi.org/10.1186/s40562-026-00500-2
1228. Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time E. Sutanudjaja et al. https://doi.org/10.1016/j.rse.2013.07.022
1229. Surface temperature adjustment in METRIC model for monitoring crop water consumption in North China Plain H. Li et al. https://doi.org/10.1016/j.agwat.2023.108654
1230. A Two-Step Reconstruction Framework for Mapping Seamless All-Weather Daily Evapotranspiration Using Thermal Infrared Data G. Zhao et al. https://doi.org/10.1109/JSTARS.2024.3492033
1231. Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description F. Alkhaier et al. https://doi.org/10.5194/hess-16-1817-2012
1232. Optimizing Latent Heat Flux Calculation via Composited Thermal Infrared Temperatures Y. Jiang et al. https://doi.org/10.1109/TGRS.2025.3618869
1233. Influence of Chicken Manure Amendment on the Thermal Properties of Selected Benchmark Soils in Zambia M. Chishala et al. https://doi.org/10.4236/ojss.2019.92002
1234. Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US N. Bhattarai et al. https://doi.org/10.5194/hess-22-2311-2018
1235. Coupling Xinanjiang model and SWAT to simulate agricultural non-point source pollution in Songtao watershed of Hainan, China S. Yang et al. https://doi.org/10.1016/j.ecolmodel.2011.09.004
1236. Thermally derived evapotranspiration from the Surface Temperature Initiated Closure (STIC) model improves cropland GPP estimates under dry conditions Y. Bai et al. https://doi.org/10.1016/j.rse.2022.112901
1237. Significant Decrease of Uncertainties in Sensible Heat Flux Simulation Using Temporally Variable Aerodynamic Roughness in Two Typical Forest Ecosystems of China Y. Zhou et al. https://doi.org/10.1175/JAMC-D-11-0243.1
1238. Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum P. Wagle et al. https://doi.org/10.1016/j.isprsjprs.2017.03.022
1239. Estimation of Regional Evapotranspiration by TM/ETM+ Data over Heterogeneous Surfaces S. Liu et al. https://doi.org/10.14358/PERS.73.10.1169
1240. Projection of net irrigation requirement over India using a bias-corrected spatially downscaled dataset G. Nengzouzam et al. https://doi.org/10.2166/wcc.2023.406
1241. SMAP soil moisture improves global evapotranspiration A. Purdy et al. https://doi.org/10.1016/j.rse.2018.09.023
1242. Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS F. Alkhaier et al. https://doi.org/10.5194/hess-16-1833-2012
1243. Time continuous two-source energy-water balance modelling of heterogeneous crops: FEST-2-EWB N. Paciolla et al. https://doi.org/10.1016/j.jhydrol.2023.129265
1244. Long-term monthly 0.05° terrestrial evapotranspiration dataset (1982–2018) for the Tibetan Plateau L. Yuan et al. https://doi.org/10.5194/essd-16-775-2024
1245. A review of remote sensing based actual evapotranspiration estimation K. Zhang et al. https://doi.org/10.1002/wat2.1168
1246. Calibration and validation of a remote sensing algorithm to estimate energy balance components and daily actual evapotranspiration over a drip-irrigated Merlot vineyard C. Poblete-Echeverría & S. Ortega-Farias https://doi.org/10.1007/s00271-012-0381-x
1247. Evaluation and verification of two evapotranspiration models based on precision screening and partitioning of field temperature data C. Xiao et al. https://doi.org/10.1016/j.agwat.2023.108166
1248. Evapotranspiration over a camelina crop at Maricopa, Arizona A. French et al. https://doi.org/10.1016/j.indcrop.2008.06.001
1249. Spatio-temporal patterns of energy exchange and evapotranspiration during an intense drought for drylands in Brazil C. dos Santos et al. https://doi.org/10.1016/j.jag.2019.101982
1250. Survival of the Qaidam mega-lake system under mid-Pliocene climates and its restoration under future climates D. Scherer https://doi.org/10.5194/hess-24-3835-2020
1251. Rationale and Efficacy of Assimilating Remotely Sensed Potential Evapotranspiration for Reduced Uncertainty of Hydrologic Models A. Rajib et al. https://doi.org/10.1029/2017WR021147
1252. STEEP: A remotely-sensed energy balance model for evapotranspiration estimation in seasonally dry tropical forests U. Bezerra et al. https://doi.org/10.1016/j.agrformet.2023.109408
1253. Evaluation of Actual Evapotranspiration from Rice Fields of Odisha Using Remote Sensing Based Surface Energy Balance Approach K. Behura et al. https://doi.org/10.1007/s12524-025-02345-2
1254. Global intercomparison of 12 land surface heat flux estimates C. Jiménez et al. https://doi.org/10.1029/2010JD014545
1255. Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products M. Soltani et al. https://doi.org/10.3390/rs13050853
1256. Satellite-Based Water Consumption Dynamics Monitoring in an Extremely Arid Area S. Tan et al. https://doi.org/10.3390/rs10091399
1257. Effects of floating macrophytes on open-water evaporation in a Brazilian tropical reservoir I. Rodrigues et al. https://doi.org/10.1016/j.jsames.2025.105683
1258. Application of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture M. Romaguera et al. https://doi.org/10.3390/rs61010033
1259. Spatial-temporal patterns of land surface evapotranspiration from global products R. Tang et al. https://doi.org/10.1016/j.rse.2024.114066
1260. Evapotranspiration modelling at large scale using near-real time MSG SEVIRI derived data N. Ghilain et al. https://doi.org/10.5194/hess-15-771-2011
1261. Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges S. Liang et al. https://doi.org/10.1016/j.srs.2024.100152
1262. Evolution of evapotranspiration models using thermal and shortwave remote sensing data J. Chen & J. Liu https://doi.org/10.1016/j.rse.2019.111594
1263. Quantifying the contribution of biophysical and environmental factors in uncertainty of modeling canopy conductance J. Xu et al. https://doi.org/10.1016/j.jhydrol.2020.125612
1264. Spatiotemporal variation of heat fluxes in Beijing with land use change from 1997 to 2017 M. Guo et al. https://doi.org/10.1016/j.pce.2018.11.001
1265. Effects of thermal and hydrophysical properties of sandy Haplic Podzol on actual evapotranspiration of spring wheat E. Balashov et al. https://doi.org/10.2478/johh-2023-0013
1266. A new parameterisation scheme of ground heat flux for land surface flux retrieval from remote sensing information M. Tanguy et al. https://doi.org/10.1016/j.jhydrol.2012.06.002
1267. Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards J. Xue et al. https://doi.org/10.1016/j.agwat.2021.107132
1268. Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data X. Li et al. https://doi.org/10.3390/rs9080836
1269. Use of remote sensing and long-term in-situ time-series data in an integrated hydrological model of the Central Kalahari Basin, Southern Africa M. Lekula & M. Lubczynski https://doi.org/10.1007/s10040-019-01954-9
1270. A Novel NIR–Red Spectral Domain Evapotranspiration Model From the Chinese GF-1 Satellite: Application to the Huailai Agricultural Region of China Y. Yao et al. https://doi.org/10.1109/TGRS.2020.3020125
1271. On the surface energy balance closure at different temporal scales A. Grachev et al. https://doi.org/10.1016/j.agrformet.2019.107823
1272. Developing a soil water index-based Priestley–Taylor algorithm for estimating evapotranspiration over East Asia and Australia Y. Hao et al. https://doi.org/10.1016/j.agrformet.2019.107760
1273. Deep learning and regression modelling of cloudless downward longwave radiation N. Obot et al. https://doi.org/10.1186/s43088-019-0018-8
1274. A satellite-based energy balance algorithm with reference dry and wet limits J. Feng & Z. Wang https://doi.org/10.1080/01431161.2012.748990
1275. Combining Landsat optical/thermal and LiDAR High Definition data to estimate turbulent fluxes over Mediterranean forests V. Penot & O. Merlin https://doi.org/10.1016/j.srs.2025.100323
1276. Evapotranspiration over a processing cassava field: a comparative analysis of micrometeorological methods and remote sensing N. da Silva et al. https://doi.org/10.1007/s00704-024-05008-3
1277. Regional Daily ET Estimates Based on the Gap-Filling Method of Surface Conductance J. Xu et al. https://doi.org/10.3390/rs10040554
1278. Crop Water Consumption at Lake Sevan, Armenia N. Thevs et al. https://doi.org/10.3390/hydrometeorology1010004
1279. Viewpoint: Irrigation water management in a space age M. Hafeez & U. Awan https://doi.org/10.1002/ird.2705
1280. Evaluation of WaPOR V2 evapotranspiration products across Africa M. Blatchford et al. https://doi.org/10.1002/hyp.13791
1281. Remotely Sensed and Empirical Reference Evapotranspiration Models to Derive Crop Coefficients for Pistachios in the Central Basin of Iran F. Firoozi et al. https://doi.org/10.1007/s40996-023-01169-9
1282. Impacts of climate variability and landscape pattern change on evapotranspiration in a grassland landscape mosaic D. Yu et al. https://doi.org/10.1002/hyp.13642
1283. Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area J. Cheng & W. Kustas https://doi.org/10.3390/rs11060613
1284. Modeling Evapotranspiration during SMACEX: Comparing Two Approaches for Local- and Regional-Scale Prediction H. Su et al. https://doi.org/10.1175/JHM466.1
1285. Extension of the Generalized Split-Window Algorithm for Land Surface Temperature Retrieval to Atmospheres With Heavy Dust Aerosol Loading X. Fan et al. https://doi.org/10.1109/JSTARS.2014.2358584
1286. Global estimates of 500 m daily aerodynamic roughness length from MODIS data Z. Peng et al. https://doi.org/10.1016/j.isprsjprs.2021.11.015
1287. Tracing water and energy fluxes and reflectance in an arid ecosystem using the integrated model SCOPE J. Jin et al. https://doi.org/10.1016/j.jenvman.2018.10.090
1288. Critical comparison of actual evapotranspiration estimates using ground based, remotely sensed, and simulated data in the USA S. Kibria et al. https://doi.org/10.1016/j.agwat.2021.106753
1289. Estimating Regional Evapotranspiration Using a Satellite-Based Wind Speed Avoiding Priestley–Taylor Approach J. Sun et al. https://doi.org/10.3390/w13213144
1290. Estimation of Evapotranspiration Using a Nonparametric Approach Under All Sky: Accuracy Evaluation and Error Analysis X. Pan et al. https://doi.org/10.1109/JSTARS.2017.2707586
1291. Quantifying spatio-temporal variations of evapotranspiration over a heterogeneous terrain in the Arid regions of Northwestern China. D. Jiao et al. https://doi.org/10.1080/01431161.2020.1868604
1292. Does the Normalized Difference Vegetation Index explain spatial and temporal variability in sap velocity in temperate forest ecosystems? A. Hoek van Dijke et al. https://doi.org/10.5194/hess-23-2077-2019
1293. A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches Y. Zhang et al. https://doi.org/10.1016/j.agwat.2023.108499
1294. Two Improvements of an Operational Two-Layer Model for Terrestrial Surface Heat Flux Retrieval R. Zhang et al. https://doi.org/10.3390/s8106165
1295. From Global Goals to Local Gains—A Framework for Crop Water Productivity M. Blatchford et al. https://doi.org/10.3390/ijgi7110414
1296. A trade-off method between environment restoration and human water consumption: A case study in Ebinur Lake H. Zeng et al. https://doi.org/10.1016/j.jclepro.2018.12.284
1297. A conjugate application of MODIS/Terra data and empirical method to assess reference evapotranspiration for the southwest region of Bangladesh I. Newton et al. https://doi.org/10.1007/s12665-021-09482-0
1298. High-resolution land surface fluxes from satellite and reanalysis data (HOLAPS v1.0): evaluation and uncertainty assessment A. Loew et al. https://doi.org/10.5194/gmd-9-2499-2016
1299. A Dual-Source Energy Balance Model Coupled with Jarvis Canopy Resistance for Estimating Surface Evapotranspiration in Arid and Semi-Arid Regions Q. Zhang et al. https://doi.org/10.3390/agriculture14122362
1300. Evaluating one- and two-source energy balance models in estimating surface evapotranspiration from Landsat-derived surface temperature and field measurements R. Tang et al. https://doi.org/10.1080/01431161.2012.716529
1301. Multisource Estimation of Long-Term Terrestrial Water Budget for Major Global River Basins M. Pan et al. https://doi.org/10.1175/JCLI-D-11-00300.1
1302. Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements S. Liu et al. https://doi.org/10.5194/hess-11-769-2007
1303. Spatio-temporal dynamics of evapotranspiration on the Tibetan Plateau from 2000 to 2010 L. Song et al. https://doi.org/10.1088/1748-9326/aa527d
1304. Parameterization of Urban Sensible Heat Flux from Remotely Sensed Surface Temperature: Effects of Surface Structure J. Yang et al. https://doi.org/10.3390/rs11111347
1305. A novel TIR-derived three-source energy balance model for estimating daily latent heat flux in mainland China using an all-weather land surface temperature product J. Yang et al. https://doi.org/10.1016/j.agrformet.2022.109066
1306. Land-surface processes and summer-cloud-precipitation characteristics in the Tibetan Plateau and their effects on downstream weather: a review and perspective Y. Fu et al. https://doi.org/10.1093/nsr/nwz226
1307. Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data L. Ji et al. https://doi.org/10.1016/j.agwat.2021.107106
1308. A Comparative Analysis of Different Algorithms for Estimating Evapotranspiration with Limited Observation Variables: A Case Study in Beijing, China D. Sun et al. https://doi.org/10.3390/rs17040636
1309. Water Stress Regime of Irrigated Crops Based on Remote Sensing and Ground-Based Data A. Zeyliger & O. Ermolaeva https://doi.org/10.3390/agronomy11061117
1310. Modification of harmonic analysis model for diurnal surface soil heat flux estimate from multiple remote sensing data H. Hu et al. https://doi.org/10.1117/1.JRS.12.036009
1311. Assessment of an evapotranspiration algorithm accounting for land cover types and photosynthetic perspectives using remote sensing images C. Sur et al. https://doi.org/10.1080/15481603.2023.2279802
1312. A hybrid dual‐source scheme and trapezoid framework–based evapotranspiration model (HTEM) using satellite images: Algorithm and model test Y. Yang & S. Shang https://doi.org/10.1002/jgrd.50259
1313. Trends of land surface heat fluxes on the Tibetan Plateau from 2001 to 2012 C. Han et al. https://doi.org/10.1002/joc.5119
1314. Evapotranspiration Estimation Using Surface Energy Balance-Based Evaporative Fraction for Water Management in Canal Irrigation Command H. Parmar & N. Gontia https://doi.org/10.1007/s12524-021-01467-7
1315. Land cover change mitigated 20 % of the total increased evapotranspiration in tropical Lancang-Mekong River Basin during 2001–2019 H. Chen et al. https://doi.org/10.1016/j.ejrh.2024.102160
1316. Estimating surface turbulent heat fluxes from land surface temperature and soil moisture observations using the particle batch smoother Y. Lu et al. https://doi.org/10.1002/2016WR018943
1317. Satellite time series data reveal interannual and seasonal spatiotemporal evapotranspiration patterns in China in response to effect factors M. Cheng et al. https://doi.org/10.1016/j.agwat.2021.107046
1318. The regulation and management of water resources in groundwater over-extraction area based on ET F. Li et al. https://doi.org/10.1007/s00704-021-03713-x
1319. Extensive review of evapotranspiration estimation methodologies over a semi-arid region V. Gargi & S. Manickam https://doi.org/10.3389/frsen.2026.1770598
1320. Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumption A. Msigwa et al. https://doi.org/10.5194/hess-26-4447-2022
1321. Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model H. Yan et al. https://doi.org/10.1016/j.rse.2012.06.004
1322. Substantial uncertainties in gridded evapotranspiration products in high-latitude cold regions of the Northern Hemisphere K. Ma et al. https://doi.org/10.1007/s00704-026-06549-5
1323. Assessment of soil water deficit for the middle reaches of Yarlung-Zangbo River from optical and passive microwave images L. Zhong et al. https://doi.org/10.1016/j.rse.2013.11.008
1324. Estimation of Growing Season Daily ET in the Middle Stream and Downstream Areas of the Heihe River Basin Using HJ-1 Data . Zhansheng Li et al. https://doi.org/10.1109/LGRS.2014.2368694
1325. A Revised Temporal Scaling Method to Yield Better ET Estimates at a Regional Scale Y. Song et al. https://doi.org/10.3390/rs70506433
1326. Estimating hourly crop ET using a two-source energy balance model and multispectral airborne imagery J. Chávez et al. https://doi.org/10.1007/s00271-009-0177-9
1327. Mapping Evapotranspiration Patterns in the Desert-Oasis Ecotone Using UAV-Based Thermal Infrared Imagery with a Three-Temperature Model S. Li et al. https://doi.org/10.3390/rs18132242
1328. Evaluating the Impact of Assimilating Soil Moisture Variability Data on Latent Heat Flux Estimation in a Land Surface Model N. Alavi et al. https://doi.org/10.4296/cwrj3502157
1329. Estimating Crop Evapotranspiration in Data-Scare Regions: A Comparative Analysis of Eddy Covariance, Empirical and Remote-Sensing Approaches N. Cutting et al. https://doi.org/10.1007/s41101-024-00299-z
1330. Comparison of Remote Sensing based Multi-Source ET Models over Cropland in a Semi-Humid Region of China Q. Zhuang et al. https://doi.org/10.3390/atmos11040325
1331. Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI P. Wagle et al. https://doi.org/10.1016/j.agrformet.2016.03.009
1332. Physical connection of sensible and ground heat flux M. Sadeghi et al. https://doi.org/10.1016/j.jhydrol.2021.126687
1333. Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites D. Salazar-Martínez et al. https://doi.org/10.1016/j.jhydrol.2022.127786
1334. Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies M. Dembélé et al. https://doi.org/10.1016/j.advwatres.2020.103667
1335. Substitution of satellite-based land surface temperature defective data using GSP method M. Mokhtari et al. https://doi.org/10.1016/j.asr.2021.01.058
1336. Water and Energy Balance Model GOES-PRWEB: Development and Validation E. Harmsen et al. https://doi.org/10.3390/hydrology8030113
1337. Scale-aware triple collocation: optimizing spatiotemporal windows for enhanced multi-source fusion of meteorological data Z. Peng et al. https://doi.org/10.1016/j.jhydrol.2026.135662
1338. A Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty in meteorological forcing to improve model prediction A. Ershadi et al. https://doi.org/10.1002/wrcr.20231
1339. Estimation of actual evapotranspiration and water stress in the Lijiang River Basin, China using a modified Operational Simplified Surface Energy Balance (SSEBop) model Y. Yao & A. Mallik https://doi.org/10.1016/j.jher.2022.01.003
1340. Estimation of Regional Evapotranspiration Based on the Decouple Model and Remote Sensing Information ——a Case Study in Beijing City and Nearby Region S. Di et al. https://doi.org/10.1080/01431161.2024.2316674
1341. Estimation of Seasonal Evapotranspiration for Crops in Arid Regions Using Multisource Remote Sensing Images M. Cha et al. https://doi.org/10.3390/rs12152398
1342. Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area M. Bahir et al. https://doi.org/10.3390/rs9111178
1343. Long-term variations in actual evapotranspiration over the Tibetan Plateau C. Han et al. https://doi.org/10.5194/essd-13-3513-2021
1344. Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes S. Peddinti et al. https://doi.org/10.1007/s00271-024-00943-5
1345. Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate N. Bhattarai et al. https://doi.org/10.1016/j.jag.2016.01.010
1346. Enhancing Evapotranspiration Estimations through Multi-Source Product Fusion in the Yellow River Basin, China R. Wang et al. https://doi.org/10.3390/w16182603
1347. Evapotranspiration Variability and Its Association with Vegetation Dynamics in the Nile Basin, 2002–2011 H. Alemu et al. https://doi.org/10.3390/rs6075885
1348. Estimating Daily Actual Evapotranspiration at a Landsat-Like Scale Utilizing Simulated and Remote Sensing Surface Temperature D. Wang et al. https://doi.org/10.3390/rs13020225
1349. How does irrigation alter the water, carbon, and nitrogen budgets in a large endorheic river basin? S. Yang et al. https://doi.org/10.1016/j.jhydrol.2022.128317
1350. Estimation of Evapotranspiration from NDVI for Irrigated Agriculture in Arid Regions M. Tasumi https://doi.org/10.7132/jrcsa.17.1_17
1351. Changes in evapotranspiration and phenology as consequences of shrub removal in dry forests of central Argentina V. Marchesini et al. https://doi.org/10.1002/eco.1583
1352. Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data Y. Lu et al. https://doi.org/10.1002/2017WR021415
1353. Estimation of the Regional Evaporative Fraction over the Tibetan Plateau Area by Using Landsat-7 ETM Data and the Field Observations Y. MA et al. https://doi.org/10.2151/jmsj.85A.295
1354. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources M. Anderson et al. https://doi.org/10.1016/j.rse.2011.08.025
1355. High spatial resolution thermal infrared data from airborne acquisition reveal inconsistencies in evapotranspiration and crop water stress retrieval from different models C. Corbari et al. https://doi.org/10.1016/j.rsase.2025.101563
1356. Total evaporation estimation for accurate water accounting purposes: an appraisal of various available estimation methods C. Shoko et al. https://doi.org/10.1080/10106049.2016.1208682
1357. Spatial sensitivity of surface energy balance algorithms to meteorological data in a heterogeneous environment E. Webster et al. https://doi.org/10.1016/j.rse.2016.10.019
1358. The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets D. Miralles et al. https://doi.org/10.5194/hess-20-823-2016
1359. Comparison of ET models over different land cover L. Sun et al. https://doi.org/10.1088/1755-1315/17/1/012128
1360. The Modified SEBAL for Mapping Daily Spatial Evapotranspiration of South Korea Using Three Flux Towers and Terra MODIS Data Y. Lee & S. Kim https://doi.org/10.3390/rs8120983
1361. Analysis of urban water dissipation characteristics considering anthropogenic impacts: a case study in Beijing C. Liu et al. https://doi.org/10.2166/wcc.2023.195
1362. An intercomparison of the Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) modeling schemes W. Timmermans et al. https://doi.org/10.1016/j.rse.2006.11.028
1363. Modifying SEBAL Model Based on the Trapezoidal Relationship between Land Surface Temperature and Vegetation Index for Actual Evapotranspiration Estimation X. Wang et al. https://doi.org/10.3390/rs6075909
1364. Satellite retrieval of actual evapotranspiration in the Tibetan Plateau: Components partitioning, multidecadal trends and dominated factors identifying W. Wang et al. https://doi.org/10.1016/j.jhydrol.2018.02.065
1365. A simple temperature domain two‐source model for estimating agricultural field surface energy fluxes from Landsat images Y. Yao et al. https://doi.org/10.1002/2016JD026370
1366. Detecting the Response of Irrigation Water Management to Climate by Remote Sensing Monitoring of Evapotranspiration F. El Ghandour et al. https://doi.org/10.3390/w11102045
1367. Integrating two layers of soil moisture parameters into the MOD16 algorithm to improve evapotranspiration estimations S. Di et al. https://doi.org/10.1080/01431161.2015.1040136
1368. Evaluation of uncalibrated energy balance model (BAITSSS) for estimating evapotranspiration in a semiarid, advective climate R. Dhungel et al. https://doi.org/10.1002/hyp.13458
1369. Local-scale monitoring of evapotranspiration based on downscaled GRACE observations and remotely sensed data: An application of terrestrial water balance approach B. Khorrami et al. https://doi.org/10.1007/s12145-023-00964-2
1370. Estimation of Evapotranspiration from the People’s Victory Irrigation District Based on the Data Mining Sharpener Model J. Zhang et al. https://doi.org/10.3390/agronomy13123082
1371. Integration of soil moisture as an auxiliary parameter for the anchor pixel selection process in SEBAL using Landsat 8 and Sentinel - 1A images M. Prakash Mohan et al. https://doi.org/10.1080/01431161.2019.1658239
1372. Assessing the impact of end‐member selection on the accuracy of satellite‐based spatial variability models for actual evapotranspiration estimation D. Long & V. Singh https://doi.org/10.1002/wrcr.20208
1373. Utilizing the Google Earth Engine for an Efficient Spatial–Temporal Fusion Model of Grassland Evapotranspiration (OL-SS) H. Yu et al. https://doi.org/10.3390/w17071034
1374. Investigating the potential for cool roofs to mitigate urban heat in the Kansas City metropolitan area K. Reed & F. Sun https://doi.org/10.1007/s00382-022-06296-z
1375. Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests I. Numata et al. https://doi.org/10.3390/rs9010046
1376. Spatiotemporal patterns of water consumption and irrigation requirements of wheat-maize in the Huang-Huai-Hai Plain, China and options of their reduction P. Ren et al. https://doi.org/10.1016/j.agwat.2022.107468
1377. Calibration of aerodynamic roughness over the Tibetan Plateau with Ensemble Kalman Filter analysed heat flux J. Lee et al. https://doi.org/10.5194/hess-16-4291-2012
1378. A Bayesian approach to estimate sensible and latent heat over vegetated land surface C. van der Tol et al. https://doi.org/10.5194/hess-13-749-2009
1379. Multi-Scale Evaluation of the TSEB Model over a Complex Agricultural Landscape in Morocco J. Elfarkh et al. https://doi.org/10.3390/rs12071181
1380. Impact of land use and land cover transitions and climate on evapotranspiration in the Lake Naivasha Basin, Kenya V. Odongo et al. https://doi.org/10.1016/j.scitotenv.2019.04.062
1381. Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest–Savanna Transition in Brazil L. Laipelt et al. https://doi.org/10.3390/rs12071108
1382. Numerical simulations of the atmospheric and land conditions over the Jinta oasis in northwestern China with satellite‐derived land surface parameters X. Meng et al. https://doi.org/10.1029/2008JD010360
1383. Evapotranspiration Estimation Assessment Using Various Satellite-Based Surface Energy Balance Models in Arid Climates A. Elkatoury et al. https://doi.org/10.1007/s41748-024-00501-1
1384. Evaluation of dynamic linkages between evapotranspiration and land-use/land-cover changes with Landsat TM and ETM+ data Z. Gao et al. https://doi.org/10.1080/01431161.2011.636766
1385. Evaluation of SEBS Algorithm for Estimation of Daily Evapotranspiration Using Landsat-8 Dataset in a Semi-Arid Region of Central Iran M. Mohammadian et al. https://doi.org/10.4236/ojg.2017.73023
1386. Use of MODIS Images to Quantify the Radiation and Energy Balances in the Brazilian Pantanal A. Teixeira et al. https://doi.org/10.3390/rs71114597
1387. Evaluating water-saving efficiency of plastic mulching in Northwest China using remote sensing and SEBAL Y. Yang et al. https://doi.org/10.1016/j.agwat.2018.07.011
1388. Wind Speed-Independent Two-Source Energy Balance Model Based on a Theoretical Trapezoidal Relationship between Land Surface Temperature and Fractional Vegetation Cover for Evapotranspiration Estimation X. Wang et al. https://doi.org/10.1155/2020/6364531
1389. Investigating the changes in agricultural land use and actual evapotranspiration of the Urmia Lake basin based on FAO’s WaPOR database R. Barideh & F. Nasimi https://doi.org/10.1016/j.agwat.2022.107509
1390. Integrating thermal stress indexes within Shuttleworth–Wallace model for evapotranspiration mapping over a complex surface J. Elfarkh et al. https://doi.org/10.1007/s00271-020-00701-3
1391. Integrating sentinel-2 and sentinel-3 for actual evapotranspiration estimation across diverse climate zones using the sen-ET plugin and machine learning models S. Amani et al. https://doi.org/10.1007/s12145-025-01786-0
1392. Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem V. Burchard-Levine et al. https://doi.org/10.3390/rs12060904
1393. Estimation of land surface heat fluxes based on visible infrared imaging radiometer suite data: case study in northern China X. Li et al. https://doi.org/10.1117/1.JRS.11.046012
1394. Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions? D. Melo et al. https://doi.org/10.1029/2020WR028752
1395. Assessment of Water Availability and Consumption in the Karkheh River Basin, Iran—Using Remote Sensing and Geo-statistics L. Muthuwatta et al. https://doi.org/10.1007/s11269-009-9455-9
1396. Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing R. Vinukollu et al. https://doi.org/10.1175/2011JHM1372.1
1397. Delineation of irrigated croplands and spatial analysis of crop water use for water resource management in the Orange River valley, Northern Cape T. Dube & N. Sechemane https://doi.org/10.1016/j.pce.2026.104809
1398. A Weak-Constraint-Based Data Assimilation Scheme for Estimating Surface Turbulent Fluxes J. Qin et al. https://doi.org/10.1109/LGRS.2007.904004
1399. Multi‐model and multi‐sensor estimations of evapotranspiration over the Volta Basin, West Africa S. Andam‐Akorful et al. https://doi.org/10.1002/joc.4198
1400. Monitoring Evapotranspiration in an Agricultural Field and Determination of Irrigation Rates and Dates by Automated Mobile Field Agrometeorological Complex A. Efimov et al. https://doi.org/10.1134/S0097807818010086
1401. Crop Evapotranspiration Dynamics in Morocco’s Climate-Vulnerable Saiss Plain A. Oumou et al. https://doi.org/10.3390/rs17142412
1402. Uncertainties in long-term ensemble estimates of contextual evapotranspiration over southern France S. Mwangi et al. https://doi.org/10.5194/hess-30-1117-2026
1403. Temporal and Spatial Differences and Driving Factors of Evapotranspiration from Terrestrial Ecosystems of the Qinghai Province in the Past 20 Years Z. Song et al. https://doi.org/10.3390/w14040536
1404. Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed, Hoshangabad, Madhya Pradesh M. Malik & J. Shukla https://doi.org/10.1007/s12594-018-1010-y
1405. Water stress assessment in rainfed crops and pastures by using remotely sensed evapotranspiration M. Moqbeli et al. https://doi.org/10.1007/s10661-025-13984-w
1406. Ensemble Machine Learning Outperforms Empirical Equations for the Ground Heat Flux Estimation with Remote Sensing Data J. Bonsoms & G. Boulet https://doi.org/10.3390/rs14081788
1407. Regional Actual Evapotranspiration Estimation with Land and Meteorological Variables Derived from Multi-Source Satellite Data B. Wu et al. https://doi.org/10.3390/rs12020332
1408. An integrated hydrological and meteorological approach for the simulation of terrestrial evapotranspiration / Une approche hydrologique et météorologique intégrée pour la simulation de l'évapotranspiration terrestre C. ZHAN et al. https://doi.org/10.1623/hysj.53.6.1151
1409. Integration of microwave satellite soil moisture products in the contextual surface temperature-vegetation index models for spatially continuous evapotranspiration estimation W. Zhu et al. https://doi.org/10.1016/j.isprsjprs.2023.08.004
1410. Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China Q. Dai et al. https://doi.org/10.3390/rs16010008
1411. The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources J. Fisher et al. https://doi.org/10.1002/2016WR020175
1412. A machine learning residual correction framework for enhancing physical-based evapotranspiration estimates over croplands A. Dobrokhotov et al. https://doi.org/10.1080/22797254.2026.2695909
1413. Evaluation of Standardized MODIS-Terra Satellite-Derived Evapotranspiration Using Genetic Algorithm for Better Field Applicability in a Tropical River Basin U. Kumar et al. https://doi.org/10.1007/s12524-023-01675-3
1414. Surface Energy Fluxes Estimation Over the South Asia Subcontinent Through Assimilating MODIS/TERRA Satellite Data With In Situ Observations and GLDAS Product by SEBS Model W. Zhao et al. https://doi.org/10.1109/JSTARS.2014.2325966
1415. Exploring Long-Term Anomalies in the Vegetation Cover of Peri-Urban Parks Using the Fisher-Shannon Method L. Telesca et al. https://doi.org/10.3390/e24121784
1416. Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil V. Souza et al. https://doi.org/10.3390/w11091911
1417. Use of commercial microwave links as scintillometers: potential and limitations towards evaporation estimation L. van der Valk et al. https://doi.org/10.5194/amt-18-6143-2025
1418. Calibration and Validation of a Distributed Energy–Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements C. Corbari & M. Mancini https://doi.org/10.1175/JHM-D-12-0173.1
1419. Estimation of Evaporation and Drought Stress of Pistachio Plant Using UAV Multispectral Images and a Surface Energy Balance Approach H. Khormizi et al. https://doi.org/10.3390/horticulturae10050515
1420. Suitability of Earth Engine Evaporation Flux (EEFlux) Estimation of Evapotranspiration in Rainfed Crops S. Kadam et al. https://doi.org/10.3390/rs13193884
1421. A new method based on remote sensing observations and data assimilation for estimation of evapotranspiration over field crops J. Qin et al. https://doi.org/10.1080/00288230709510378
1422. Evaporation in Brazilian dryland reservoirs: Spatial variability and impact of riparian vegetation I. Rodrigues et al. https://doi.org/10.1016/j.scitotenv.2021.149059
1423. Evapotranspiration Estimation in the Sahel Using a New Ensemble-Contextual Method A. Allies et al. https://doi.org/10.3390/rs12030380
1424. Satellite characterization of terrestrial drought over Xinjiang Uygur Autonomous Region of China over past three decades Y. Zhang et al. https://doi.org/10.1007/s12665-016-5315-0
1425. Observation and Assessment of Model Retrievals of Surface Exchange Components Over a Row Canopy Using Directional Thermal Data S. Mwangi et al. https://doi.org/10.1109/JSTARS.2023.3297709
1426. Application of the Sebs Water Balance Model in Estimating Daily Evapotranspiration and Evaporative Fraction from Remote Sensing Data Over the Nile Delta M. Elhag et al. https://doi.org/10.1007/s11269-011-9835-9
1427. Assessing geeSEBAL automated calibration and meteorological reanalysis uncertainties to estimate evapotranspiration in subtropical humid climates R. Kayser et al. https://doi.org/10.1016/j.agrformet.2021.108775