Download PDF

Intercomparison of Surface Energy Fluxes Estimates from the FEST-EWB and TSeB Models over the Heterogeneous REFLEX 2012 Site (Barrax, Spain)

Acta Geophysica volume 63, pages1609–1638(2015)Cite this article

ab]Abstract

An intercomparison between the Energy Water Balance model (FEST-EWB) and the Two-Source Energy Balance model (TSEB) is performed over a heterogeneous agricultural area. TSEB is a residual model which uses Land Surface Temperature (LST) from remote sensing as a main input parameter so that energy fluxes are computed instantaneously at the time of data acquisition. FEST-EWB is a hydrological model that predicts soil moisture and the surface energy fluxes on a continuous basis. LST is then a modelled variable. Ground and remote sensing data from the Regional Experiments For Land-atmosphere Exchanges (REFLEX) campaign in 2012 in Barrax gave the opportunity to validate and compare spatially distributed energy fluxes. The output of both models matches the ground observations quite well. However, a spatial analysis reveals significant differences between the two approaches for latent and sensible heat fluxes over relatively small fields characterized by high heterogeneity in vegetation cover.

References

  1. 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. Hydrometeorol. 6, 6, 892–909, DOI: 10.1175/JHM465.1.

    Article  Google Scholar 

  2. 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).

    Article  Google Scholar 

  3. 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.

    Article  Google Scholar 

  4. Brath, A., A. Montanari, and E. Toth (2004), Analysis of the effects of different scenarios of historical data availability on the calibration of a spatially-distributed hydrological model, J. Hydrol. 291, 3–4, 232–253, DOI: 10.1016/jjhydrol.2003.12.044.

    Article  Google Scholar 

  5. Brutsaert, W. (1982), Evaporation into the Atmosphere, Reidel, Dordrecht.

    Book  Google Scholar 

  6. Brutsaert, W. (2005), Hydrology: An Introduction, Cambridge University Press, Cambridge.

    Book  Google Scholar 

  7. Cammalleri, C., M.C. Anderson, G. Ciraolo, G. D’Urso, W.P. Kustas, G. La Loggia, and M. Minacapilli (2012), Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in situ air temperature observations, Remote Sens. Environ. 124, 502–515, DOI: 10.1016/j.rse.2012.06.009.

    Article  Google Scholar 

  8. Chehbouni, A., C. Watts, J.-P. Lagouarde, Y.H. Kerr, J.-C. Rodriguez, J.-M. Bonnefond, F. Santiago, G. Dedieu, D.C. Goodrich, and C. Unkrich (2000), Estimation of heat and momentum fluxes over complex terrain using a large aperture scintillometer, Agr. Forest Meteorol. 105, 1–3, 215–226, DOI: 10.1016/S0168-1923(00)00187-8.

    Article  Google Scholar 

  9. 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, 330–342, DOI: 10.1016/j.agrformet.2007.09.014.

    Article  Google Scholar 

  10. Choudhury, B.J., S.B. Idso, and R.J. Reginato (1987), Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infrared-temperature based energy balance equation, Agr. Forest Meteorol. 39, 4, 283–297, DOI: 10.1016/0168-1923(87)90021-9.

    Article  Google Scholar 

  11. Corbari, C., and M. Mancini (2013), Calibration and validation of a distributed energy–water balance model using satellite data of land surface temperature and ground discharge measurements, J. Hydrometeorol. 15, 1, 376-392, DOI: 10.1175/JHM-D-12-0173.1.

    Google Scholar 

  12. Corbari, C., G. Ravazzani, J. Martinelli, and M. Mancini (2009), Elevation based correction of snow coverage retrieved from satellite images to improve model calibration, Hydrol. Earth Syst. Sci. 13, 639–649, DOI: 10.5194/hess-13-639-2009.

    Article  Google Scholar 

  13. Corbari, C., J.A. Sobrino, M. Mancini, and V. Hidalgo (2010), Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data, Hydrol. Earth Syst. Sci. 14, 2141–2151, DOI: 10.5194/hessd-7-5335-2010.

    Article  Google Scholar 

  14. Corbari, C., G. Ravazzani, and M. Mancini (2011), A distributed thermodynamic model for energy and mass balance computation: FEST-EWB, Hydrol. Process. 25, 9, 1443–1452, DOI: 10.1002/hyp.7910.

    Article  Google Scholar 

  15. Corbari, C., D. Masseroni, and M. Mancini (2012), Effetto delle correzioni dei dati misurati da stazioni eddy covariance sulla stima dei flussi evapotraspirativi, Ital. J. Agrometeorol. 1, 35–51 (in Italian).

    Google Scholar 

  16. Corbari, C., J.A. Sobrino, M. Mancini, and V. Hidalgo (2013), Mass and energy flux estimates at different spatial resolutions in a heterogeneous area through a distributed energy-water balance model and remote-sensing data, Int. J. Remote Sens. 34, 9–10, 3208–3230, DOI: 10.1080/01431161. 2012.716924.

    Article  Google Scholar 

  17. Corbari C., D. Masseroni, A. Ceppi, A. Facchi, C. Gandolfi, and M. Mancini (2014), Comparison between high frequency and thirty minutes averaged data from eddy covariance measurements for operative water management, J. Irrig. Drainage Eng. (in review).

    Google Scholar 

  18. Corbari, C., M. Mancini, Li, and Z. Su (2015), Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration?, Hydrol. Sci. J. 60, 2, 202–217, DOI: 10.1080/02626667.2013.866709.

    Article  Google Scholar 

  19. Crow, W.T., E.F. Wood, and M. Pan (2003), Multiobjective calibration of land surface model evapotranspiration predictions using streamflow observations and spaceborne surface radiometric temperature retrievals, J. Geophys. Res. 108, D23, 4725, DOI: 10.1029/2002JD003292.

    Article  Google Scholar 

  20. Crow, W.T., F. Li, and W.P. Kustas (2005), Intercomparison of spatially distributed models for predicting surface energy flux patterns during SMACEX, J. Hydrometeorol. 6, 6, 941–953, DOI: 10.1175/JHM468.1.

    Article  Google Scholar 

  21. Crow, W.T., W.P. Kustas, and J.H. Prueger (2008), Monitoring root zone soil moisture though the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model, Remote Sens. Environ. 112, 4, 1268–1281, DOI: 10.1016/j.rse.2006.11.033.

    Article  Google Scholar 

  22. Dai, Y., X. Zeng, R.E. Dickinson, I. Baker, G.B. Bonan, M.G. Bosilovich, A. Scott Denning, P.A. Dirmeyer, P.R. Houser, G. Niu, K.W. Oleson, C. Adam Schlosser, and Z.-L. Yang (2003), The Common Land Model, Bull. Amer. Meteor. Soc. 84, 8, 1013–1023, DOI: 10.1175/BAMS-84-8-1013.

    Article  Google Scholar 

  23. 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).

    Article  Google Scholar 

  24. de Vries, D.A. (1963), Thermal properties of soils. In: W.R. van Wijk (ed.), Physics of Plant Environment, North Holland, Amsterdam, 210–233.

    Google Scholar 

  25. Dooge, J.C.I. (1986), Looking for hydrologic laws, Water Resour. Res. 22, 9S, 46-58, DOI: 10.1029/WR022i09Sp0046S.

    Google Scholar 

  26. Famiglietti, J.S., and E.F. Wood (1994), Multiscale modeling of spatially variable water and energy balance processes, Water Resour. Res. 30, 11, 3061–3078, DOI: 10.1029/94WR01498.

    Article  Google Scholar 

  27. FAO/IIASA/ISRIC/ISSCAS/JRC (2009), Harmonized world soil database (version 1.1), FAO, Rome, Italy and IIASA, Laxenburg, Austria.

    Google Scholar 

  28. Foken, T. (2008), Micrometeorology, Springer, Berlin.

    Google Scholar 

  29. Franks, S.W., and K.J. Beven (1999), Conditioning a multiple-patch SVAT Model using uncertain time-space estimates of latent heat fluxes as inferred from remotely sensed data, Water Resour. Res. 35, 9, 2751–2761, DOI: 10.1029/1999WR900108.

    Article  Google Scholar 

  30. French, A.N., F. Jacob, M.C. Anderson, W.P. Kustas, W. Timmermans, A. Gieske, Z. Su, Su, M.F. McCabe, F. Li, J. Prueger, and N. Brunsell (2005), 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.

    Article  Google Scholar 

  31. Gillespie, A., S. Rokugawa, T. Matsunaga, Cothern, S. Hook, and A.B. Kahle (1998), A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, IEEE Geosci. Remote S. 36, 4, 1113–1126, DOI: 10.1109/36.700995.

    Article  Google Scholar 

  32. Gonzalez-Dugo, M.P., C.M.U. Neale, L. Mateos, W.P. Kustas, Prueger, M.C. Anderson, and F. Li (2009), A comparison of operational remote sensing-based models for estimating crop evapotranspiration, Agr. Forest Meteorol. 149, 11, 1843–1853, DOI: 10.1016/j.agrformet.2009.06.012.

    Article  Google Scholar 

  33. Gutmann, E.D., and E.E. Small (2010), A method for the determination of the hydraulic properties of soil from MODIS surface temperature for use in land-surface models, Water Resour. Res. 46, 6, W06520, DOI: 10.1029/2009WR008203.

    Article  Google Scholar 

  34. Huntingford, C., S.J. Allen, and R.J. Harding (1995), An intercomparison of single and dual-source vegetation-atmosphere transfer models applied to transpiration from sahelian savannah, Bound.-Lay. Meteorol. 74, 4, 397–418, DOI: 10.1007/BF00712380.

    Article  Google Scholar 

  35. Jarvis, P.G (1976), The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field, Phil. Trans. R. Soc. Lond. B 273, 593–610, DOI: 10.1098/rstb.1976.0035.

    Article  Google Scholar 

  36. Kustas, W.P., and J.M. Norman (1999), Evaluation of soil and vegetation heat flux predictions using a simple two-sourcemodel with radiometric temperatures for partial canopy cover, Agr. Forest Meteorol. 94, 1, 13–29, DOI: 10.1016/S0168-1923(99)00005-2

    Article  Google Scholar 

  37. Kustas, W.P., K.S. Humes, J.M. Norman, and M.S. Moran (1996), Single- and dual-source modeling of surface energy fluxes with radiometric surface temperature, J. Appl. Meteor. 35, 1, 110–121, DOI: 10.1175/1520-0450(1996) 035<0110:SADSMO>2.0.CO;2.

    Article  Google Scholar 

  38. Kustas, W.P., X. Zhan, and T.J. Schmugge (1998), Combining optical and micro-wave 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.

    Article  Google Scholar 

  39. Kustas, W.P., J.H. Prueger, Hatfield, K. Ramalingam, and L. Hipps (2000), Variability in soil heat flux from a mesquite dune site, Agr. Forest Meteorol. 103, 3, 249–264, DOI: 10.1016/S0168-1923(00)00131-3.

    Article  Google Scholar 

  40. Kustas, W.P., M.C. Anderson, A.N. French, and D. Vickers (2006), Using a remote sensing field experiment to investigate flux-footprint relations and flux sampling distributions for tower and aircraft-based observations, Adv. WaterResour. 29, 2, 355–368, DOI: 10.1016/j.advwatres.2005.05.003.

    Article  Google Scholar 

  41. Kustas, W.P., J.G. Alfieri, M.C. Anderson, P.D. Colaizzi, J.H. Prueger, S.R. Evett, C.M.U. Neale, A.N. French, L.E. Hipps, J.L. Chavez, K.S. Copeland, and T.A. Howell (2012), Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area, Adv. Water Resour. 50, 120–133, DOI: 10.1016/j.advwatres.2012.07.005.

    Article  Google Scholar 

  42. Lagouarde, J.-P., F. Jacob, X.F. Gu, A. Olioso, J.-M. Bonnefond, Y. Kerr, K.J. McAneney, and M. Irvine (2002), Spatialization of sensible heat flux over a heterogeneous landscape, Agronomie 22, 6, 627–633, DOI: 10.1051/agro:2002032.

    Article  Google Scholar 

  43. Lhomme, J.-P., and A. Chehbouni (1999), Comments on dual-source vegetation-atmosphere transfer models, Agr. Forest Meteorol. 94, 3–4, 269–273, DOI: 10.1016/S0168-1923(98)00109-9.

    Article  Google Scholar 

  44. Liang, X., D.P. Lettenmaier, E.F. Wood, and S.J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for GCMs, J. Geophys. Res. 99, D7, 14415–14428, DOI: 10.1029/94JD00483.

    Article  Google Scholar 

  45. Mancini, M (1990), La modellazione distribuita della risposta idrologica: effetti della variabilità spaziale e della scala di rappresentazione del fenomeno dell’assorbimento, Ph.D. Thesis, Politecnico di Milano, Milan (in Italian).

    Google Scholar 

  46. McCumber, M.C., and R.A. Pielke (1981) Simulation of the effects of surface fluxes of heat and moisture in a mesoscale numerical model: 1. Soil layer, J. Geophys. Res. 86, C10, 9929–9938, DOI: 10.1029/JC086iC10p09929.

    Article  Google Scholar 

  47. 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.

    Article  Google Scholar 

  48. Rabuffetti, D., G. Ravazzani, C. Corbari, and M. Mancini (2008), Verification of operational Quantitative Discharge Forecast (QDF) for a regional warning system–the AMPHORE case studies in the upper Po River, Nat. Hazards Earth Syst. Sci. 8, 161–173, DOI: 10.5194/nhess-8-161-2008.

    Article  Google Scholar 

  49. Ravazzani, G., D. Rametta, and M. Mancini (2011), Macroscopic Cellular Automata for groundwater modelling: A first approach, Environ. Modell. Softw. 26, 5, 634-643, DOI: 10.1016/j.envsoft.2010.11.011.

    Google Scholar 

  50. Rawls, W.J., and D.L. Brakensiek (1985), Prediction of soil water properties for hydrologic modeling. In: E.B. Jones and T.J. Ward (eds.), Watershed Management in the Eighties, A Symposium of ASCE Convention; April 30–May 1, 1985, Denver, Colorado, United States, ASCE, New York, NY, 293–299.

    Google Scholar 

  51. Richter, K., and W.J. Timmermans (2009), Physically based retrieval of crop characteristics for improved water use estimates, Hydrol. Earth Syst. Sci. 13, 5, 663–674, DOI: 10.5194/hess-13-663-2009.

    Article  Google Scholar 

  52. 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.

    Article  Google Scholar 

  53. Sobrino, J.A., J.C. Jiménez-Munoz, G. Sòria, M. Gómez, A. Barella Ortiz, M. Romaguera, M. Zaragoza, Y. Julien, J. Cuenca, M. Atitar, V. Hidalgo, B. Franch, C. Mattar, A. Ruescas, L. Morales, A. Gillespie, Balick, Z. Su, F. Nerry, L. Peres, and R. Libonati (2008), Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications, Int. J. Remote Sens. 29, 17–18, 4961–4991, DOI: 10.1080/01431160802036516.

    Article  Google Scholar 

  54. Su, Z. (2002), The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrol. Earth Syst. Sci. 6, 1, 85–100, DOI: 10.5194/hess-6-85-2002.

    Article  Google Scholar 

  55. Su, Z., T. Schmugge, W.P. Kustas, and W.J. Massman (2001), An evaluation of two models for estimation of the roughness height for heat transfer between the land surface and the atmosphere, J. Appl. Meteor. 40, 1933–1951, DOI: 10.1175/1520-0450(2001)040<1933:AEOTMF>2.0.CO;2.

    Article  Google Scholar 

  56. Su, Z., W. Timmermans, A. Gieske, L. Jia, J.A. Elbers, A. Olioso, J. Timmermans, R. van der Velde, X. Jin, H. van der Kwast, D. Sabol, J.A. Sobrino, J. Moreno, and R. Bianchi (2008), Quantification of land-atmo sphere exchanges of water, energy and carbon dioxide in space and time over the heterogeneous Barrax site, Int. J. Remote Sens. 29, 17–18, 5215–5235, DOI: 10.1080/01431160802326099.

    Article  Google Scholar 

  57. Sun, S.F. (1982), Moisture and heat transport in a soil layer forced by atmospheric conditions, M.Sc. Thesis, University of Connecticut, Storrs.

    Google Scholar 

  58. Thom, A.S. (1975), Momentum, mass and heat exchange of plant communities. In: J.L. Monteith (ed.), Vegetation and Atmosphere, Academic Press, London, 57–110.

    Google Scholar 

  59. 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.

    Article  Google Scholar 

  60. Timmermans, W.J., Z. Su, and A. Olioso (2009), Footprint issues in scintillometry over heterogeneous landscapes, Hydrol. Earth Syst. Sci. 13, 11, 2179–2190, DOI: 10.5194/hess-13-2179-2009.

    Article  Google Scholar 

  61. Timmermans, W.J., J.C. Jiménez-Munoz, V. Hidalgo, K. Richter, J.A. Sobrino, G. D’Urso, F. Mattia, G. Satalino, E. De Lathauwer, and V.R.N. Pauwels (2011), Estimation of the spatially distributed surface energy budget for AgriSAR 2006, Part I: Remote sensing model intercomparison, JSTARS-IEEE 4, 2, 465–481, DOI: 10.1109/JSTARS.2010.2098019.

    Google Scholar 

  62. Timmermans, W., 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).

    Google Scholar 

  63. 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.

    Article  Google Scholar 

  64. van der Tol, C. (2012), Validation of remote sensing of bare soil ground heat flux, Remot. Sens. Environ. 121, 275–286, DOI: 10.1016/j.rse.2012.02.009.

    Article  Google Scholar 

  65. van der Tol, C., W.J. Timmermans, C. Corbari, Carrara, J. Timmermans, and Z. Su (2015), 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).

    Article  Google Scholar 

  66. Verhoef, A., B.J.J.M. van den Hurk, A.F.G. Jacobs, and B.G. Heusinkveld (1996), Thermal soil properties for vineyard (EFEDA-I) and savanna (HAPEX-Sahel) sites, Agr. Forest Meteorol. 78, 1–2, 1–18, DOI: 10.1016/0168-1923(95)02254-6.

    Article  Google Scholar 

  67. Wang, T., G.R. Ochs, and S.F. Clifford (1978), A saturation-resistant optical scintillometer to measure Cn2, J. Opt. Soc. Am. 68, 3, 334–338, DOI: 10.1364/JOSA.68.000334.

    Article  Google Scholar 

  68. Wilson, K., A. Goldstein, E. Falge, M. Aubinet, D. Baldocchi, P. Berbigier, C. Bernhofer, R. Ceulemans, H. Dolman, C. Field, A. Grelle, A. Ibrom, B.E. Law, A. Kowalski, T. Meyers, J. Moncrieff, R. Monson, W. Oechel, J. Tenhunen, S. Verma, and R. Valentini (2002), Energy balance closure at FLUXNET sites, Agr. Forest Meteorol. 113, 1–4, 223–243, DOI: 10.1016/S0168-1923(02)00109-0.

    Article  Google Scholar 

  69. Wood, E.F., D.P. Lettenmaier, X. Liang, D. Lohmann, A. Boone, S. Chang, F. Chen, Y. Dai, R.E. Dickinson, Q. Duan, M. Ek, Y.M. Gusev, F. Habets, P. Irannejad, R. Koster, K.E. Mitchel, O.N. Nasonova, J. Noilhan, J. Schaake, A. Schlosser, Y. Shao, A.B. Shmakin, D. Verseghy, K. Warrach, P. Wetzel, Y. Xue, Z.-L. Yang, and Q. Zeng (1998), The Project for Inter-comparison of Land-surface Parameterization Schemes (PILPS) Phase 2(c) Red-Arkansas river basin experiment: 1. Experiment description and summary intercomparisons, Global Planet. Change 19, 1–4, 115–135, DOI: 10.1016/S0921-8181(98)00044-7.

    Article  Google Scholar 

Download references

Author information

Affiliations

  1. Department of Civil and Environmental Engineering, Politecnico di Milano, Milano, Italy

    Chiara Corbari

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

    Wim Timmermans

  3. Instituto de Investigación y Formación Agraria y Pesquera (IFAPA), Sevilla, Spain

    Ana Andreu

Authors
  1. Chiara Corbari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wim Timmermans
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ana Andreu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chiara Corbari.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Corbari, C., Timmermans, W. & Andreu, A. Intercomparison of Surface Energy Fluxes Estimates from the FEST-EWB and TSeB Models over the Heterogeneous REFLEX 2012 Site (Barrax, Spain). Acta Geophys. 63, 1609–1638 (2015). https://doi.org/10.2478/s11600-014-0258-x

Download citation

Key words

  • energy balance model
  • water and energy balance model
  • remote sensing