63 citations as recorded by crossref.

1. 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
2. Assessing the effect of broadleaf woodland expansion on acidic dry deposition and streamwater acidification Z. Gagkas et al. https://doi.org/10.1016/j.foreco.2011.06.044
3. 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
4. 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
5. Single vs dual source surface energy balance model based actual evapotranspiration estimation R. Pandey et al. https://doi.org/10.36953/ECJ.27532611
6. Rethinking the Roughness Height: An Improved Description of Temperature Profiles over Short Vegetation J. Boekee et al. https://doi.org/10.1007/s10546-024-00871-z
7. Evaluating the Accuracy of RANS Wind Flow Modeling Over Forested Terrain—Part 1: Canopy Model Validation V. Morales Garza et al. https://doi.org/10.1115/1.4042242
8. A SVAT scheme describing energy and CO2 fluxes for multi-component vegetation: calibration and test for a Sahelian savannah A. Verhoef & S. Allen https://doi.org/10.1016/S0304-3800(99)00213-6
9. 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
10. OliveCan: A Process-Based Model of Development, Growth and Yield of Olive Orchards Á. López-Bernal et al. https://doi.org/10.3389/fpls.2018.00632
11. A comparison between various definitions of forest stand height and aerodynamic canopy height T. Nakai et al. https://doi.org/10.1016/j.agrformet.2010.05.005
12. A Column Canopy‐Air Turbulent Diffusion Method for Different Canopy Structures X. Chen et al. https://doi.org/10.1029/2018JD028883
13. Bulk Transfer Relations for the Roughness Sublayer K. De Ridder https://doi.org/10.1007/s10546-009-9450-y
14. An Application of the WAsP Program in Complex, Forested Terrain as Part of a Wind Farm Feasibility Study K. Reutter et al. https://doi.org/10.1260/030952405776234562
15. 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
16. Surface roughness analysis of a conifer forest canopy with airborne and terrestrial laser scanning techniques K. Weligepolage et al. https://doi.org/10.1016/j.jag.2011.08.014
17. Estimation of land surface water and energy balance parameters using conditional sampling of surface states L. Farhadi et al. https://doi.org/10.1002/2013WR014049
18. 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
19. Flux-profile relationships over a boreal forest — roughness sublayer corrections M. Mölder et al. https://doi.org/10.1016/S0168-1923(99)00131-8
20. On the performance of surface renewal analysis to estimate sensible heat flux over two growing rice fields under the influence of regional advection F. Castellví & R. Snyder https://doi.org/10.1016/j.jhydrol.2009.07.005
21. Scalar Concentration Profiles in the Canopy and Roughness Sublayer I. Harman & J. Finnigan https://doi.org/10.1007/s10546-008-9328-4
22. Surface boundary layer of cattle feedlots: Implications for air emissions measurement K. Baum et al. https://doi.org/10.1016/j.agrformet.2008.06.017
23. Examination of the Quantitative Relationship between Vegetation Canopy Height and LAI Y. Yuan et al. https://doi.org/10.1155/2013/964323
24. Relationship between aerodynamic roughness length and bulk sedge leaf area index in a mixed‐species boreal mire complex P. Alekseychik et al. https://doi.org/10.1002/2017GL073884
25. Estimating inputs for dispersion modeling in mobile platform applications R. Thiruvenkatachari et al. https://doi.org/10.1016/j.scitotenv.2023.163306
26. 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
27. Effect of sub-layer corrections on the roughness parameterization of a Douglas fir forest K. Weligepolage et al. https://doi.org/10.1016/j.agrformet.2012.04.017
28. Methane efflux from an American bison herd P. Stoy et al. https://doi.org/10.5194/bg-18-961-2021
29. Variations in bulk canopy conductance of an irrigated olive (Olea europaea L.) orchard L. Testi et al. https://doi.org/10.1016/j.envexpbot.2004.09.008
30. Combined analysis of energy and water balances to estimate latent heat flux of a sudanian small catchment A. Guyot et al. https://doi.org/10.1016/j.jhydrol.2008.12.027
31. Stability Dependence of Canopy Flows over a Flat Larch Forest N. Kobayashi & T. Hiyama https://doi.org/10.1007/s10546-010-9572-2
32. A wind tunnel study of flows over idealised urban surfaces with roughness sublayer corrections Y. Ho & C. Liu https://doi.org/10.1007/s00704-016-1877-8
33. Testing the hypothesis on estimating field maize height and above-ground biomass using tower-based gradient wind data Q. Xing et al. https://doi.org/10.1016/j.fcr.2021.108081
34. A New Procedure Based on Surface Renewal Analysis to Estimate Sensible Heat Flux: A Case Study over Grapevines F. Castellví & R. Snyder https://doi.org/10.1175/2009JHM1151.1
35. Water requirements of olive orchards: I simulation of daily evapotranspiration for scenario analysis L. Testi et al. https://doi.org/10.1007/s00271-005-0011-y
36. A simple parameterization of bulk canopy resistance from climatic variables for estimating hourly evapotranspiration P. Perez et al. https://doi.org/10.1002/hyp.5919
37. 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
38. Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard M. Jimenez-Bello et al. https://doi.org/10.1109/JSTARS.2015.2418817
39. Aerodynamic resistance of coppiced poplar R. Hall https://doi.org/10.1016/S0168-1923(02)00133-8
40. 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
41. 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
42. Turbulent Flow in Plant Canopies: Historical Perspective and Overview Y. Brunet https://doi.org/10.1007/s10546-020-00560-7
43. Simulation of Soil Heating in Ridges partly covered with Plastic Mulch, Part II: Model Calibration and Validation J. Graefe et al. https://doi.org/10.1016/j.biosystemseng.2005.08.001
44. Precision-Based Assessment of Environmental Water and Thermal Balance in Basin-Mulched Date Palm Orchards Under Arid Conditions A. Alharbi & M. Ghonimy https://doi.org/10.3390/agronomy16050539
45. Nighttime transpiration observed over a larch forest in Hokkaido, Japan N. Kobayashi et al. https://doi.org/10.1029/2006WR005556
46. Influence of wind direction on the surface roughness of vineyards J. Alfieri et al. https://doi.org/10.1007/s00271-018-0610-z
47. Dependence of kB−1 factor on roughness Reynolds number for barley and pasture M. Mölder & A. Lindroth https://doi.org/10.1016/S0168-1923(00)00200-8
48. Computer simulation of atmospheric flows over real forests for wind energy resource evaluation J. Lopes da Costa et al. https://doi.org/10.1016/j.jweia.2006.02.002
49. Roughness layer corrections with emphasis on SVAT model applications J. Graefe https://doi.org/10.1016/j.agrformet.2004.01.003
50. 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
51. Coupling processes and exchange of energy and reactive and non-reactive trace gases at a forest site – results of the EGER experiment T. Foken et al. https://doi.org/10.5194/acp-12-1923-2012
52. 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
53. Improving the Capability of the SCOPE Model for Simulating Solar-Induced Fluorescence and Gross Primary Production Using Data from OCO-2 and Flux Towers H. Wang & J. Xiao https://doi.org/10.3390/rs13040794
54. Canopy Temperature and Heat Flux Prediction by Leaf Area Index of Bell Pepper in a Greenhouse Environment: Experimental Verification and Application Y. Jeon et al. https://doi.org/10.3390/agronomy12081807
55. Merging flux-variance with surface renewal methods in the roughness sublayer and the atmospheric surface layer M. Fischer et al. https://doi.org/10.1016/j.agrformet.2023.109692
56. A New Approach to Estimating the Sensible Heat Flux in Bare Soils F. Castellví & N. Agam https://doi.org/10.3390/atmos16040458
57. WAsP in the Forest E. Dellwik et al. https://doi.org/10.1002/we.155
58. A simple model for estimating the Bowen ratio from climatic factors for determining latent and sensible heat flux P. Perez et al. https://doi.org/10.1016/j.agrformet.2007.08.015
59. Energy balance determination of crop evapotranspiration using a wireless sensor network J. Jimenez-Berni et al. https://doi.org/10.3389/fagro.2023.1244633
60. 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
61. Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08 G. Paul et al. https://doi.org/10.1016/j.advwatres.2013.06.003
62. Measuring H2O and CO2 fluxes at field scales with scintillometry: Part I – Introduction and validation of four methods B. Van Kesteren et al. https://doi.org/10.1016/j.agrformet.2012.09.013
63. Parameterisation of aerodynamic roughness over boreal, cool- and warm-temperate forests T. Nakai et al. https://doi.org/10.1016/j.agrformet.2008.03.009