PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

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

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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.
Czasopismo
Rocznik
Strony
1609--1638
Opis fizyczny
Bibliogr. 69 poz., rys., tab., wykr.
Twórcy
autor
  • Politecnico di Milano, Department of Civil and Environmental Engineering, Milano, Italy
  • University of Twente, Faculty of Geo-information Science and Earth Observation, Department of Water Resources, Enschede, The Netherlands
autor
  • Instituto de Investigación y Formación Agraria y Pesquera (IFAPA), Sevilla, Spain
Bibliografia
  • 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.
  • 2. Andreu, A., W.J. Timmermans, D. Skokovic, and M.P. Gonzalez-Dugo (2015), Influence of component temperature derivation from dual angle thermal infra-red observations on TSEB flux estimates over an irrigated vineyard, Acta Geophys. 63, 6, 1540-1570, DOI: 10.1515/acgeo-2015-0037 (this issue).
  • 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.
  • 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/j.jhydrol.2003.12.044.
  • 5. Brutsaert, W. (1982), Evaporation into the Atmosphere, Reidel, Dordrecht. Brutsaert, W. (2005), Hydrology: An Introduction, Cambridge University Press, Cambridge.
  • 6. 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.
  • 7. 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.
  • 8. 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.
  • 9. 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.
  • 10. Corbari, C., and M. Mancini (2013), Calibration and validation of a distributed energy - water balance model using satellitedata of land surface temperature and ground discharge measurements, J. Hydrometeorol. 15, 1, 376-392, DOI: 10.1175/JHM-D-12-0173.1.
  • 11. 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.
  • 12. 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.
  • 13. 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.
  • 14. Corbari, C., D. Masseroni, and M. Mancini (2012), Effetto delle correzioni dei dati misurati da stazioni eddy covariance sullastima dei flussi evapotraspirativi, Ital. J. Agrometeorol. 1, 35-51 (in Italian).
  • 15. 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.
  • 16. 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).
  • 17. Corbari, C., M. Mancini, J. 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.
  • 18. 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.
  • 19. 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.
  • 20. 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.
  • 21. 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.
  • 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. de Vries, D.A. (1963), Thermal properties of soils. In: W.R. van Wijk (ed.), Physics of Plant Environment, North Holland, Amsterdam, 210-233.
  • 24. Dooge, J.C.I. (1986), Looking for hydrologic laws, Water Resour. Res. 22, 9S, 46-58, DOI: 10.1029/WR022i09Sp0046S.
  • 25. 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.
  • 26. FAO/IIASA/ISRIC/ISSCAS/JRC (2009), Harmonized world soil database (version 1.1), FAO, Rome, Italy and IIASA, Laxenburg, Austria.
  • 27. Foken, T. (2008), Micrometeorology, Springer, Berlin.
  • 28. 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.
  • 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 (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.
  • 30. Gillespie, A., S. Rokugawa, T. Matsunaga, J.S. 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.
  • 31. Gonzalez-Dugo, M.P., C.M.U. Neale, L. Mateos, W.P. Kustas, J.H. 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.
  • 32. 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.
  • 33. 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.
  • 34. 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. B273, 593-610, DOI:10.1098/rstb.1976.0035.
  • 35. 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
  • 36. 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.
  • 37. 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.
  • 38. Kustas, W.P., J.H. Prueger, J.L. 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.
  • 39. 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. Water Resour. 29, 2, 355-368, DOI:10.1016/j.advwatres.2005.05.003.
  • 40. 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. Chávez, 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.
  • 41. 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.
  • 42. 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.
  • 43. 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.
  • 44. 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).
  • 45. 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.
  • 46. 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.
  • 47. 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.
  • 48. 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.
  • 49. 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.
  • 50. 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.
  • 51. 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 B25, 2, 147-157, DOI:10.1016/S1464-1909(99)00128-8.
  • 52. Sobrino, J.A., J.C. Jiménez-Muñoz, G. Sòria, M. Gómez, A. Barella Ortiz, M. Romaguera, M. Zaragoza, Y. Julien, J. Cuenca, M. Atitar, V. Hidalgo, B. Franch, C. Mattar, A.
  • 53. Ruescas, L. Morales, A. Gillespie, L. 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.
  • 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.
  • 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.
  • 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-atmosphere ex-changes 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.
  • 57. Sun, S.F. (1982), Moisture and heat transport in a soil layer forced by atmospheric conditions, M.Sc. Thesis, University of Connecticut, Storrs.
  • 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.
  • 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.
  • 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.
  • 61. Timmermans, W.J., J.C. Jiménez-Muñoz, 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.
  • 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).
  • 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.
  • 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.
  • 65. van der Tol, C., W.J. Timmermans, C. Corbari, A. 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).
  • 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.
  • 67. Wang, T., G.R. Ochs, and S.F. Clifford (1978), A saturation-resistant optical scintillometer to measure C2n, J. Opt. Soc. Am. 68, 3, 334-338, DOI: 10.1364/JOSA.68.000334.
  • 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.
  • 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 Intercomparison 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.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-999b94ba-266b-45dd-aabd-e3d5d3bcf5fe
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.