Utility of an Automated Thermal-Based Approach for Monitoring Evapotranspiration

Timmermans, W. J.; Kustas, W. P.; Andreu, A.

doi:10.1515/acgeo-2015-0016

Artykuł - szczegóły

Tytuł artykułu

Utility of an Automated Thermal-Based Approach for Monitoring Evapotranspiration

Autorzy

Timmermans W. J. , Kustas W. P. , Andreu A.

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1515/acgeo-2015-0016

Warianty tytułu

Języki publikacji

Abstrakty

A very simple remote sensing-based model for water use monitoring is presented. The model acronym DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature) is a Dutch word which loosely translates as “it’s unbelievable that it works”. DATTUTDUT is fully automated and only requires a surface temperature map, making it simple to use and providing a rapid estimate of spatially- distributed fluxes. The algorithm is first tested over a range of environmental and land-cover conditions using data from four short-term field experiments and then evaluated over a growing season in an agricultural region. Flux model output is in satisfactory agreement with observations and established remote sensing-based models, except under dry and partial canopy cover conditions. This suggests that DATTUTDUT has utility in identifying relative water use and as an operational tool providing initial estimates of ET anomalies in data-poor regions that would be confirmed using more robust modeling techniques

Słowa kluczowe

remote sensing water use monitoring temperature index scheme automated operational

teledetekcja monitorowanie zużycia wody wskaźniki temperatury automatyzacja operacyjność

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2015

Tom

Vol. 63, no. 6

Strony

1571--1608

Opis fizyczny

Bibliogr. 80 poz., rys., tab., wykr.

Twórcy

autor

Timmermans W. J.

w.j.timmermans@utwente.nl

University of Twente, Faculty of Geo-information Science and Earth Observation, Department of Water Resources, Enschede, The Netherlands

autor

Kustas W. P.

Hydrology and Remote Sensing Laboratory, USDA/ARS, Beltsville, MD, USA

autor

Andreu A.

Instituto de Investigación y Formación Agraria y Pesquera (IFAPA), Cordoba, Spain

Bibliografia

1. Anderson, M.C., J.M. Norman, G.R. Diak, W.P. Kustas, and J.R. Mecikalski (1997), A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing, Remote Sens. Environ. 60, 2, 195-216, DOI: 10.1016/S0034-4257(96)00215-5.
2. Anderson, M.C., J.M. Norman, W.P. Kustas, F. Li, J.H. Prueger, and J.R. Mecikalski (2005), Effects of vegetation clumping on two-source model estimates of surface energy fluxes from an agricultural landscape during SMACEX, J. Hydrometeor. 6, 6, 892-909, DOI: 10.1175/JHM465.1.
3. Anderson, M.C., W.P. Kustas, and J.M. Norman (2007), Upscaling flux observations from local to continental scales using thermal remote sensing, Agron. J. 99, 1, 240-254, DOI: 10.2134/agronj2005.0096S.
4. Anderson, M.C., W.P. Kustas, J.M. Norman, C.R. Hain, J.R. Mecikalski, L. Schultz, M.P. González-Dugo, C. Cammalleri, G. d’Urso, A. Pimstein, and F. Gao (2011), Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery, Hydrol. Earth Syst. Sci. 15, 223-239, DOI: 10.5194/hess-15-223-2011.
5. Andreu, A., W.J. Timmermans, D. Skokovic, and M.P. Gonzalez-Dugo (2015), Influence of component temperature derivation from dual angle thermal infrared observations on TSEB flux estimates over an irrigated vineyard, Acta Geophys. 63, 6, 1540-1570, DOI: 10.1515/acgeo-2015-0037 (this issue).
6. Bastiaanssen, W.G.M. (1995), Regionalization of surface flux densities and moisture indicators in composite terrain: a remote sensing approach under clear skies in Mediterranean climates, Ph.D. Thesis, Wageningen Agricultural University, Wageningen, The Netherlands, 273 pp.
7. Bastiaanssen, W.G.M., M. Menenti, R.A.Feddes, and A.A.M. Holtslag (1998), A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, J. Hydrol. 212-213, 198-212, DOI: 10.1016/S0022-1694(98)00253-4.
8. Bateni, S.M., D. Entekhabi, S. Margulis, F. Castelli, and L. Kergoat (2014), Coupled estimation of surface heat fluxes and vegetation dynamics from remotely sensed land surface temperature and fraction of photosynthetically active radiation, Water Resour. Res. 50, 11, 8420-8440, DOI: 10.1002/2013WR014573.
9. Brutsaert, W. (1982), Evaporation into the Atmosphere. Theory, History, and Applications, Reidel, Dordrecht, 299 pp.
10. Brutsaert, W., and D. Chen(1996), Diurnal variation of surface fluxes during thorough drying (or severe drought) of natural prairie, Water Resour. Res. 32, 7, 2013-2019, DOI: 10.1029/96WR00995.
11. Burridge, D.M., and A.J. Gadd (1974), The Meteorological Office operational 10-level numerical weather prediction model (December 1974), Tech. Notes 12 and 48, British Meteorological Office, Bracknell, England, 57 pp.
12. Cammalleri, C., M.C. Anderson, and W.P. Kustas (2014), Upscaling of evapotranspiration fluxes from instantaneous to daytime scales for thermal remote sensing applications, Hydrol. Earth Syst. Sci. 18, 1885-1894, DOI: 10.5194/hess-18-1885-2014.
13. Campbell, G.S., and J.M. Norman (1998), An Introduction to Environmental Biophysics, 2nd ed., Springer, New York, 286 pp., DOI: 10.1007/978-1-4612-1626-1.
14. Carlson, T.N., and D.A. Ripley (1997), On the relation between NDVI, fractional vegetation cover, and leaf area index,Remote Sens. Environ. 62, 3, 241-252, DOI: 10.1016/S0034-4257(97)00104-1.
15. Chehbouni, A., J.C.B. Hoedjes, J.-C. Rodriguez, C.J. Watts, J. Garatuza, F. Jacob, and Y.H. Kerr (2008), Using remotely sensed data to estimate area-averaged daily surface fluxes over a semi-arid mixed agricultural land, Agr. Forest Meteorol. 148, 3, 330-342, DOI: 10.1016/j.agrformet.2007.09.014.
16. Choi, M., W.P. Kustas, M.C. Anderson, R.G. Allen, F. Li, and J.H. Kjaersgaard (2009), An intercomparison of three remote sensing-based surface energy balance algorithms over a corn and soybean production region (Iowa, U.S.) during SMACEX, Agr. Forest Meteorol. 149, 12, 2082-2097, DOI: 10.1016/j.agrformet.2009.07.002.
17. Choudhury, B.J. (1987), Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis, Remote Sens. Environ. 22, 2, 209-233, DOI: 10.1016/0034-4257(87)90059-9.
18. Choudhury, B.J., N.U. Ahmed, S.B. Idso, R.J. Reginato, and C.S.T. Daughtry (1994), Relations between evaporation coefficients and vegetation indices studied by model simulations, Remote. Sens. Environ. 50, 1, 1-17, DOI: 10.1016/0034-4257(94)90090-6.
19. Crago, R.D. (1996), Conservation and variability of the evaporative fraction during the daytime, J. Hydrol. 180, 1-4, 173-194, DOI: 10.1016/0022-1694(95)02903-6.
20. de Bruin, H.A.R. (1987), From Penman to Makkink. In: J.C. Hooghart (ed.), "Evaporation and Weather" Proceedings and Information, 25 March 1987, Hague, Netherlands, TNO Committee on Hydrological Research, Vol. 39, 5-31.
21. de Bruin, H.A.R. (1994), Analytic solutions of the equations governing the temperature fluctuation method, Bound.-Lay. Meteorol. 68, 4, 427-432, DOI: 10.1007/BF00706800.
22. de Miguel, E., M. Jiménez, I. Pérez, Ó.G. de la Cámara, F. Muñoz, and J.A. Gómez-Sánchez (2015), AHS and CASI processing for the REFLEX remote sensing campaign: methods and results, Acta Geophys. 63, 6, 1485-1498, DOI: 10.1515/ acgeo-2015-0031 (this issue).
23. Delogu, E.,G. Boulet, A. Olioso, B. Coudert, J. Chirouze, E. Ceschia, V. le Dantec, O. Marloie, G. Chehbouni, and J.-P. Lagouarde (2012), Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass, Hydrol. Earth Syst Sci. 16, 2995-3010, DOI: 10.5194/hess-16-2995-2012.
24. Droogers, P., and W. Bastiaanssen (2002), Irrigation performance using hydrological and remote sensing modeling, J. Irrig. Drain. Eng. ASCE 128, 1, 11-18, DOI: 10.1061/(ASCE)0733-9437(2002)128:1(11).
25. Duffie, J.A., and W.A. Beckman (1991), Solar Engineering of Thermal Processes, 2nd ed., John Wiley & Sons, New York, 944 pp.
26. Foken, T., and M.Y. Leclerc (2004), Methods and limitations in validation of footprint models, Agr. Forest Meteorol. 127, 3-4, 223-234, DOI: 10.1016/j.agrformet.2004.07.015.
27. French, A.N., T.J. Schmugge, W.P. Kustas, K.L. Brubaker, and J. Prueger (2003), Surface energy fluxes over El Reno, Oklahoma, using high-resolution remotely sensed data, Water Resour. Res. 39, 6, 1164, DOI: 10.1029/2002WR001734.
28. French, A.N., F. Jacob, M.C. Anderson, W.P. Kustas, W. Timmermans, A. Gieske, Z. Su, H. Su, M.F. McCabe, F. Li, J. Prueger, and N. Brunsell (2005a), Corrigendum to "Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA)" [Remote Sensing of Environment 2005 99/1-2; 55-65], Remote Sens. Environ. 99, 4, 471, DOI: 10.1016/j.rse.2005.10.001.
29. French, A.N., F. Jacob, M.C. Anderson, W.P. Kustas, W. Timmermans, A. Gieske, Z. Su, H. Su, M.F. McCabe, F. Li, J. Prueger, and N. Brunsell (2005b), Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA), Remote Sens. Environ. 99, 1-2, 55-65, DOI: 10.1016/j.rse.2005.05.015.
30. Garratt, J.R. (1992), The Atmospheric Boundary Layer, Cambridge University Press, Cambridge.
31. Gentine, P., D. Entekhabi, A. Chehbouni, G. Boulet, and B. Duchemin (2007), Analysis of evaporative fraction diurnal behaviour, Agr. Forest Meteorol. 143, 1-2, 13-29, DOI: 10.1016/j.agrformet.2006.11.002.
32. Gieske, A., and W. Meijninger (2005), High density NOAA time series of ET in the Gediz Basin, Turkey, Irrig. Drain. Syst. 19, 3-4, 285-299, DOI: 10.1007/s10795-005-5191-3.
33. Goetz, S.J., S.D. Prince, S.N. Goward, M.M. Thawley, and J. Small (1999), Satellite remote sensing of primary production: an improved production efficiency modeling approach, Ecol. Model. 122, 3, 239-255, DOI: 10.1016/S0304-3800(99)00140-4.
34. Hanna, S.R., and J.C. Chang (1992), Boundary-layer parameterizations for applied dispersion modeling over urban areas, Bound.-Lay. Meteorol. 58, 3, 229-259, DOI: 10.1007/BF02033826.
35. Hoedjes, J.C.B., A. Chehbouni, J. Ezzahar, R. Escadafal, and H.A.R. de Bruin (2007), Comparison of large aperture scintillometer and eddy covariance measurements: Can thermal infrared data be used to capture footprint-induced differences? J. Hydrometeorol. 8, 2, 144-159, DOI: 10.1175/JHM561.1.
36. Humes, K.S., W.P. Kustas, and M.S. Moran (1994), Use of remote sensing and reference site measurements to estimate instantaneous surface energy balance components over a semiarid rangeland watershed, Water Resour. Res. 30, 5, 1363-1373, DOI: 10.1029/93WR03082.
37. Jackson, R.D., S.B. Idso, R.J. Reginato, and P.J. Pinter Jr. (1981), Canopy temperature as a crop water stress indicator, Water Resour. Res. 17, 4, 1133-1138, DOI: 10.1029/WR017i004p01133.
38. Jackson, T.J., D.M. le Vine, A.Y. Hsu, A. Oldak, P.J. Starks, C.T. Swift, J.D. Isham, and M. Haken (1999), Soil moisture mapping at regional scales using microwave radiometry: the Southern Great Plains hydrology experiment, IEEE Trans. Geosci. Remote. Sens. 37, 5, 2136-2151, DOI: 10.1109/36.789610.
39. J acob, F., A. Olioso, X.F. Gu, Z. Su, and B. Seguin (2002), Mapping surface fluxes using airborne visible, near infrared, thermal infrared remote sensing data and a spatialized surface energy balance model, Agronomie 22, 6, 669-680, DOI: 10.1051/agro:2002053.
40. Jiang, L., and S. Islam (2001), Estimation of surface evaporation map over Southern Great Plains using remote sensing data, Water Resour. Res. 37, 2, 329-340, DOI: 10.1029/2000WR900255.
41. Kalma, J.D., T.R. McVicar, and M.F. McCabe (2008), Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data, Surv. Geophys. 29, 4-5, 421-469, DOI: 10.1007/s10712-008-9037-z.
42. Kite, G.W., and P. Droogers (2000), Comparing evapotranspiration estimates from satellites, hydrological models and field data, J. Hydrol. 229, 1-2, 3-18, DOI: 10.1016/S0022-1694(99)00195-X.
43. Kustas, W.P., and J.M. Norman (1997), A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations, Water Resour. Res. 33, 6, 1495-1508, DOI: 10.1029/97WR00704.
44. Kustas, W.P., and J.M. Norman (1999), Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover, Agr. Forest Meteorol. 94, 1, 13-29, DOI: 10.1016/S0168-1923(99)00005-2.
45. Kustas, W.P., and J.M. Norman (2000), Evaluating the effects of subpixel heterogeneity on pixel average fluxes, Remote Sens. Environ. 74, 3, 327-342, DOI: 10.1016/S0034-4257(99)00081-4.
46. Kustas, W.P., M.S. Moran, K.S. Humes, D.I. Stannard, P.J. Pinter Jr., L.E. Hipps, E. Swiatek, and D.C. Goodrich (1994a), Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands, Water Resour. Res. 30, 5, 1241-1259, DOI: 10.1029/93WR03038.
47. Kustas, W.P., E.M. Perry, P.C. Doraiswamy, and M.S. Moran (1994b), Using satellite remote sensing (to extrapolate evapotranspiration estimates in time and space over a semiarid Rangeland basin), Remote Sens. Environ. 49, 3, 275-286, DOI: 10.1016/0034-4257(94)90022-1.
48. Kustas, W.P., X. Zhan, and T.J. Schmugge (1998), Combining optical and microwave remote sensing for mapping energy fluxes in a semiarid watershed, Remote Sens. Environ. 64, 2, 116-131, DOI: 10.1016/S0034-4257(97)00176-4.
49. Kustas, W.P., J.L. Hatfield, and J.H. Prueger (2005), The Soil-Moisture-Atmosphere Couopling Experiment (SMACEX): background, hydrometeorological conditions, and preliminary findings, J. Hydrometeorol. 6, 6, 791-804, DOI: 10.1175/JHM456.1.
50. Mecikalski, J.R., G.R. Diak, M.C. Anderson, and J.M. Norman (1999), Estimating fluxes on continental scales using remotely sensed data in an atmospheric-land exchange model, J. Appl. Meteorol. 38, 9, 1352-1369, DOI: 10.1175/1520-0450(1999)038<1352:EFOCSU>2.0.CO;2.
51. Meijninger, W.M.L. (2003), Surface fluxes over natural landscapes using scintillometry, Ph.D. Thesis, Wageningen University, Wageningen, The Netherlands.
52. Meijninger, W.M.L., and H.A.R. de Bruin (2000), The sensible heat fluxes over irrigated areas in western Turkey determined with a large aperture scintillometer, J. Hydrol. 229, 1-2, 42-49, DOI: 10.1016/S0022-1694(99)00197-3.
53. Menenti, M., and B.J. Choudhury (1993), Parameterization of land surface evaporation by means of location dependant potential evaporation and surface temperature range. In: H.J. Bolle, R.A.Feddes, and J.D. Kalma (eds.), Proc. Int. Symp. "Exchange Processes at the Land surface for a range of space and time scales", 13-16 July 1993, Yokohama, Japan.
54. Menenti, M., W.G.M. Bastiaanssen, and D. van Eick (1989), Determination of surface hemispherical reflectance with Thematic Mapper data, Remote Sens. Environ. 28, 327-337, DOI: 10.1016/0034-4257(89)90124-7.
55. Monteith, J.L., and M.H. Unsworth (1990), Principles of Environmental Physics, Edward Arnold Publishers, London, 291 pp.
56. Nichols, W.E., and R.H. Cuenca (1993), Evaluation of the evaporative fraction for parameterization of the surface energy balance, Water Resour. Res. 29, 11, 3681-3690, DOI: 10.1029/93WR01958.
57. Norman, J.M., W.P. Kustas, and K.S. Humes (1995), Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature, Agr. Forest Meteorol. 77, 3-4, 263-293, DOI: 10.1016/0168-1923(95)02265-Y.
58. Norman, J.M., W.P. Kustas, J.H. Prueger, and G.R. Diak (2000), Surface flux estimation using radiometric temperature: A dual-temperature-difference method to minimize measurement errors, Water Resour. Res. 36, 8, 2263-2274, DOI: 10.1029/2000WR900033.
59. Norman, J.M., M.C. Anderson, and W.P. Kustas (2006), Are single-source, remote-sensing surface-flux models too simple?, AIP Conf. Proc. 852, 170, DOI: 10.1063/1.2349341.
60. Oncley, S.P., T. Foken, R. Vogt, C. Bernhofer, W. Kohsiek, H. Liu, A. Pitacco, D. Grantz, L. Ribeiro, and T. Weidinger (2002), The energy balance experiment EBEX-2000. In: Proc. 15th Conf. on Boundary Layers and Turbulence, American Meteorological Society (AMS), 15-19 July 2002, Wageningen University, Wageningen, The Netherlands.
61. Parlange, M.B., W.E. Eichinger, and J.D. Albertson (1995), Regional scale evaporation and the atmospheric boundary layer, Rev. Geophys. 33, 1, 99-124, DOI: 10.1029/94RG03112.
62. Pelgrum, H., and W.G.M. Bastiaanssen (1996), An intercomparison of techniques to determine the area-averaged latent heat flux from individual in situ observations: A remote sensing approach using the European Field Experiment in a Desertification-Threatened Area data, Water Resour. Res. 32, 9, 2775-2786, DOI: 10.1029/96WR01396.
63. Prihodko, L., and S.N. Goward (1997), Estimation of air temperature from remotely sensed surface observations, Remote Sens. Environ. 60, 3, 335-346, DOI: 10.1016/S0034-4257(96)00216-7.
64. Prince, S.D., S.J. Goetz, R.O. Dubayah, K.P. Czajkowski, and M. Thawley (1998), Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using Advanced Very High-Resolution Radiometer satellite observations: comparison with field observations, J. Hydrol. 212-213, 230-249, DOI: 10.1016/S0022-1694(98)00210-8.
65. Prueger, J.H., J.L. Hatfield, T.B. Parkin W.P. Kustas, L.E. Hipps, C.M.U. Neale, J.I. MacPherson, W.E. Eichinger, and D.I. Cooper (2005), Tower and aircraft eddy covariance measurementsof water vapor, energy, and carbon dioxide fluxes during SMACEX, J. Hydrometeorol. 6, 6, 954-960, DOI: 10.1175/JHM457.1.
66. Roerink, G.J., Z. Su, and M. Menenti (2000), S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance, Phys. Chem. Earth B 25, 2, 147-157, DOI: 10.1016/S1464-1909(99)00128-8.
67. Santanello, J.A., and M.A. Friedl (2003), Diurnal covariation in soil heat flux and net radiation, J. Appl. Meteorol. 42, 6, 851-862, DOI: 10.1175/1520-0450(2003)042<0851:DCISHF> 2.0.CO;2.
68. Schmid, H.P. (1994), Source areas for scalars and scalar fluxes, Bound.-Lay. Meteorol. 67, 3, 293-318, DOI: 10.1007/BF00713146.
69. Senay, G.B., S. Bohms, R.K. Singh, P.H. Gowda, N.M. Velpuri, H. Alemu, and J.P. Verdin (2013), Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach, J. Am. Water Resour. Assoc. 49, 3, 577-591, DOI: 10.1111/jawr.12057.
70. Shuttleworth, W.J., R.J. Gurney, A.Y. Hsu, and J.P. Ormsby (1989), FIFE: The variation in energy partition at surface flux sites, IAHS Publ. 186, 67-74.
71. Su, Z. (2002), The SurfaceEnergy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrol. Earth Syst. Sci. 6, 1, 85-100, DOI: 10.5194/hess-6-85-2002.
72. Tasumi, M., R.G. Allen, and W.G.M. Bastiaanssen (2000), The theoretical basis of SEBAL. In: A. Morse, T.Tasumi, G.A. Richard, and J.K. William (eds.), Application of the SEBAL Methodology for Estimating Consumptive Use of Water and Stream flow Depletion in the Bear River Basin of Idaho through Remote Sensing, Final report, Department of Biological and Agriculture Engineering, University of Idaho, Moscow, USA, 46-69.
73. Timmermans, W.J., W.P. Kustas, M.C. Anderson, and A.N. French (2007), An intercomparison of the Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) modeling schemes, Remote Sens. Environ. 108, 4, 369-384, DOI: 10.1016/j.rse.2006.11.028.
74. Timmermans, W.J., G. Bertoldi, J.D. Albertson, A. Olioso, Z. Su, and A.S.M. Gieske (2008), Accounting for atmospheric boundary layer variability on flux estimation from RS observations, Int. J. Remote Sens. 29, 17-18, 5275-5290, DOI: 10.1080/01431160802036383.
75. Timmermans, W.J., Z. Su, and A. Olioso (2009), Footprint issues in scintillometry over heterogeneous landscapes, Hydrol. Earth Syst. Sci. 13, 2179-2190, DOI: 10.5194/hess-13-2179-2009.
76. Timmermans, W.J., C. van der Tol, J. Timmermans, M. Ucer, X. Chen, L. Alonso, J. Moreno, A. Carrara, R. Lopez, F. de la Cruz Tercero, H.L. Corcoles, E. de Miguel, J.A.G. Sanchez, I. Pérez, B. Franch, J.-C.J. Munoz, D. Skokovic, J. Sobrino, G. Soria, A. MacArthur, L. Vescovo, I. Reusen, A. Andreu, A. Burkart, C. Cilia, S. Contreras, C. Corbari, J.F. Calleja, R. Guzinski, C. Hellmann, I. Herrmann, G. Kerr, A.-L. Lazar, B. Leutner, G. Mendiguren, S. Nasilowska, H. Nieto, J. Pachego-Labrador, S. Pulanekar, R. Raj, A. Schikling, B. Siegmann, S. von Bueren, and Z.B. Su (2015), An overview of the Regional Experiments For Land-atmosphere Exchanges 2012 (REFLEX 2012) campaign, Acta Geophys. 63, 6, 1465-1484, DOI: 10.2478/s11600-014-0254-1 (this issue).
77. Twine, T.E., W.P. Kustas, J.M. Norman, D.R. Cook, P.R. Houser, T.P. Meyers, J.H. Prueger, P.J. Starks, and M.L. Wesely (2000), Correcting eddy-covariance flux underestimates over a grassland, Agr. Forest Meteorol. 103, 3, 279-300, DOI: 10.1016/S0168-1923(00)00123-4.
78. van der Tol, C., W.J. Timmermans, C. Corbari, A. Carrara, J. Timmermans, and Z. Su (2014), An analysis of turbulent heat fluxes and the energy balance during the REFLEX campaign, Acta Geophys. 63, 6, 1516-1539, DOI: 10.1515/acgeo-2015-0061 (this issue).
79. Willmott, C.J. (1984), On the evaluation of model performance in physical geography. In: G.L. Gaile and C.J. Willmott (eds.), Spatial Statistics and Models, Theory and Decision Library, Vol. 40, Reidel Publ., Boston, 443-460.
80. Zhan, X., W.P. Kustas, and K.S. Humes (1996), An intercomparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperature, Remote Sens. Environ. 58, 3, 242-256, DOI: 10.1016/S0034-4257(96)00049-1.

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