Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances

Hydrology and Earth System Sciences

Volumn 17, Issue 7, 2013, Pages 2947-2966

  Conradt, T ^a   Wechsung, F ^a   Bronstert, A ^b  

^a POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH   (Germany)

^b UNIVERSITY OF POTSDAM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DISCHARGE CALCULATION; DISTRIBUTED HYDROLOGICAL MODEL; DISTRIBUTED HYDROLOGICAL MODELLING; ECO-HYDROLOGICAL MODELS; ERROR AMPLIFICATION; SOURCES OF UNCERTAINTY; SPATIAL CALIBRATION; SURFACE TEMPERATURES;

ATMOSPHERIC TEMPERATURE; CLIMATE MODELS; COMPUTER SIMULATION; EVAPOTRANSPIRATION; GAGES; REMOTE SENSING; RUNOFF; SURFACE PROPERTIES; WATER SUPPLY;

HYDROLOGY;

CALIBRATION; DATA SET; ECOHYDROLOGY; EVAPOTRANSPIRATION; GAUGE; HYDROLOGICAL MODELING; PERCEPTION; REMOTE SENSING; RUNOFF; SPATIAL ANALYSIS; SURFACE TEMPERATURE;

ELBE BASIN;

EID: 84881001045     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-17-2947-2013     Document Type: Article

References (123)

1. Ajami, N. K., Gupta, H., Wagener, T., and Sorooshian, S.: Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system, J. Hydrol., 298, 112-135, doi:10.1016/j.jhydrol.2004.03.033, 2004.
2. Albertz, J.: Grundlagen der Interpretation von Luft-und Satellitenbildern, Wissenschaftliche Buchgesellschaft, Darmstadt, 1991.
3. Andersen, J., Refsgaard, J. C., and Jensen, K. H.: Distributed hydrological modelling of the Senegal River Basin-model construction and validation, J. Hydrol., 247, 200-214, doi:10.1016/S0022-1694(01)00384-5, 2001.
4. Arnold, J. G., Allen, P. M., and Bernhardt, G.: A comprehensive surface-groundwater flow model, J. Hydrol., 142, 47-69, doi:10.1016/0022- 1694(93)90004-S, 1993.
5. Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large area hydrologic modeling and assessment Part I: Model development, J. Am. Water Resour. As., 34, 73-89, doi:10.1111/j.1752-1688.1998.tb05961.x, 1998.
6. ATV-DVWK: Verdunstung in Bezug zu Landnutzung, Bewuchs und Boden, DWA-Merkblatt atv-dvwk-m 504, DWA Deutsche Vereinigung f̈ur Wasserwirtschaft, Abwasser und Abfall e. V., Hennef, 2002.
7. Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A. A. M.: A remote sensing surface engergy balance algorithm for land (SEBAL). 1. Formulation, J. Hydrol., 212-213, 198-212, doi:10.1016/S0022-1694(98)00253-4, 1998a.
8. Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F., Roerink, G. J., and van der Wal, T.: A remote sensing surface engergy balance algorithm for land (SEBAL). 2. Validation, J. Hydrol., 212-213, 213-229, doi:10.1016/S0022-1694(98)00254-6, 1998b.
9. Becker, F. and Li, Z. L.: Towards a local split method over land surfaces, Int. J. Remote Sens., 11, 369-393, doi:10.1080/01431169008955028, 1990.
10. Bergstr̈om, S. and Graham, L. P.: On the scale problem in hydrological modelling, J. Hydrol., 211, 253-265, doi:10.1016/S0022-1694(98) 00248-0, 1998.
11. Beven, K.: The limits of splitting: hydrology, Sci. Total Environ., 183, 89-97, doi:10.1016/0048-9697(95)04964-9, 1996.
12. Beven, K.: How far can we go in distributed hydrological modelling?, Hydrol. Earth Syst. Sci., 5, 1-12, doi:10.5194/hess-5-1-2001, 2001; EGS Dalton Lecture, 2001.
13. Beven, K. J.: On environmental models of everywhere on the GRID, Hydrol. Process., 17, 171-174, doi:10.1002/hyp.5090, 2003.
14. Beven, K.: Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process, Hydrol. Earth Syst. Sci., 11, 460-467, doi:10.5194/hess-11-460-2007, 2007.
15. Bilbao, J. and Miguel, A. H. D.: Estimation of daylight downward longwave atmospheric irradiance under clear-sky and all-sky conditions, J. Appl. Meteorol. Clim., 46, 878-889, doi:10.1175/JAM2503.1, 2007.
16. Boegh, E., Thorsen, M., Butts, M. B., Hansen, S., Christiansen, J. S., Abrahamsen, P., Hasager, C. B., Jensen, N. O., van der Keur, P., Refsgaard, J. C., Schelde, K., Soegaard, H., and Thomsen, A.: Incorporating remote sensing data in physically based distributed agro-hydrological modelling, J. Hydrol., 287, 279-299, doi:10.1016/j.jhydrol.2003.10.018, 2004.
17. Bowen, I. S.: The ratio of heat losses by conduction and evaporation from any water surface, Ph. D. thesis, California Institute of Technology, Pasadena, CA, 12 pp., 1926a.
18. Bowen, I. S.: The ratio of heat losses by conduction and evaporation from any water surface, Phys. Rev., 27, 779-787, doi:10.1103/PhysRev.27.779, 1926b.
19. Brunsell, N. A., Ham, J. M., and Owensby, C. E.: Assessing the multi-resolution information content of remotely sensed variables and elevation for evapotranspiration in a tall-grass prairie environment, Remote Sens. Environ., 112, 2977-2987, doi:10.1016/j.rse.2008.02.002, 2008.
20. Brunt, D.: Notes on radiation in the atmosphere. I, Q. J. Roy. Meteor. Soc., 58, 389-418, doi:10.1002/qj.49705824704, 1932.
21. Brutsaert, W.: Evaporation into the Atmosphere-Theory, History, and Applications, Kluver Academic Publishers, Dordrecht, 1982.
22. Choi, M., Jacobs, J. M., and Kustas, W. P.: Assessment of clear and cloudy sky parameterizations for daily downwelling longwave radiation over different land surfaces in Florida, USA, Geophys. Res. Lett., 35, L20402, doi:10.1029/2008GL035731, 2008.
23. Conradt, T., Kundzewicz, Z. W., Hattermann, F., and Wechsung, F.: Measured effects of new lake surfaces on regional precipitation, Hydrolog. Sci. J., 52, 936-955, doi:10.1623/hysj.52.5.936, 2007.
24. Conradt, T., Hattermann, F. F., Koch, H., and Wechsung, F.: Precipitation or evapotranspiration? Bayesian analysis of potential error sources in the simulation of sub-basin discharges in the Czech Elbe River basin, Reg. Environ. Change, 12, 649-661, doi:10.1007/s10113-012-0280-y, 2012a.
25. Conradt, T., Koch, H., Hattermann, F. F., and Wechsung, F.: Spatially differentiated management-revised discharge scenarios for an integrated analysis of multi-realisation climate and land use scenarios for the Elbe River basin, Reg. Environ. Change, 12, 633-648, doi:10.1007/s10113-012-0279-4, 2012b.
26. Conradt, T., Koch, H., Hattermann, F. F., and Wechsung, F.: Szenariosimulationen des Wasserabflusses, in: Die Elbe und ihr Einzugsgebiet im globalenWandel, Chapt. 2.3, edited by:Wechsung, F., Hartje, V., Kaden, S., Venohr, M., Hansj̈urgens, B., and Gr̈afe, P., Weißensee Verlag, Berlin, in press, 2013a.
27. Conradt, T., Koch, H., Hattermann, F. F., and Wechsung, F.: Validierung von Lokalkorrekturen der Verdunstung bei den Szenariosimulationen des Wasserabflusses, in: Die Elbe und ihr Einzugsgebiet im globalenWandel, Chapt. 2.4, edited by:Wechsung, F., Hartje, V., Kaden, S., Venohr, M., Hansj̈urgens, B., and Gr̈afe, P., Weißensee Verlag, Berlin, in press, 2013b.
28. Das, T., B́ardossy, A., Zehe, E., and He, Y.: Comparison of conceptual model performance using different representations of spatial variability, J. Hydrol., 356, 106-118, doi:10.1016/j.jhydrol.2007.11.017, 2008.
29. de C. Teixeira, A. H., Bastiaanssen, W. G. M., Ahmad, M. D., and Bos, M. G.: Reviewing SEBAL input parameters for assessing evapotranspiration and water productivity for the Low-Middle S̃ao Francisco River basin, Brazil-Part A: Calibration and validation, Agr. Forest Meteorol., 149, 462-476, doi:10.1016/j.agrformet.2008.09.016, 2009.
30. Doorenbos, J. and Pruitt,W. O.: Guidelines for Predicting CropWater Requirements, no. 24 in FAO Irrigation And Drainage Papers, Food and Agriculture Organisation of the United Nations, Rome, revised Edn., 1977.
31. DVWK: Ermittlung der Verdunstung von Land-und Wasserfl̈achen, dwa-Merkblatt DVWK-M 238, DWA Deutsche Vereinigung f̈ur Wasserwirtschaft, Abwasser und Abfall e. V., Hennef, 1996.
32. Evensen, G.: Data Assimilation-The Ensemble Kalman Filter, Springer, Heidelberg, 2007.
33. Feyen, L., Kalas, M., and Vrugt, J. A.: Semi-distributed parameter optimization and uncertainty assessment for large-scale streamflow simulation using global optimization, Hydrolog. Sci. J., 53, 293-308, doi:10.1623/hysj.53. 2.293, 2008.
34. FGG Elbe: Zusammenfassender Bericht der Flussgebietsgemeinschaft Elbe ̈uber die Analysen nach Artikel 5 der Richtlinie 2000/60/EG (A-Bericht), Tech. rep., Flussgebietsgemeinschaft Elbe, Magdeburg, 2005.
35. Finger, D., Pellicciotti, F., Konz, M., Rimkus, S., and Burlando, P.: The value of glacier mass balance, satellite snow cover images, and hourly discharge for improving the performance of a physically based distributed hydrological model, Water Resour. Res., 47, W07519, doi:10.1029/2010WR009824, 2011.
36. Galleguillos, M., Jacob, F., Pŕevot, L., French, A., and Lagacherie, P.: Comparison of two temperature differencing methods to estimate daily evapotranspiration over a Mediterranean vineyard watershed from ASTER data, Remote Sens. Environ., 115, 1326-1340, doi:10.1016/j.rse.2011.01.013, 2011.
37. Gao, Y. and Long, D.: Intercomparison of remote sensing-based models for estimation of evapotranspiration and accuracy assessment based on SWAT, Hydrol. Process., 22, 4850-4869, doi:10.1002/hyp.7104, 2008.
38. Garatuza-Payan, J., Pinker, R. T., Shuttleworth, W. J., and Watts, C. J.: Solar radiation and evapotranspiration in northern Mexico estimated from remotely sensed measurements of cloudiness, Hydrolog. Sci. J., 46, 465-478, doi:10.1080/02626660109492839, 2001.
39. Gassman, P. W., Reyes, M. R., Green, C. H., and Arnold, J. G.: The soil and water assessment tool: historical development, applications, and future research directions, T. ASABE, 50, 1211-1250, 2007.
40. Githui, F., Selle, B., and Thayalakumaran, T.: Recharge estimation using remotely sensed evapotranspiration in an irrigated catchment in southeast Australia, Hydrol. Process., 26, 1379-1389, doi:10.1002/hyp.8274, 2012.
41. Glenn, E. P., Doody, T. M., Guerschman, J. P., Huete, A. R., King, E. A., McVicar, T. R., Van Dijk, A. I. J. M., Van Niel, T. G., Yebra, M., and Zhang, Y.: Actual evapotranspiration estimation by ground and remote sensing methods: the Australian experience, Hydrol. Process., 25, 4103-4116, doi:10.1002/hyp. 8391, 2011.
42. Grossmann, M., Koch, H., Lienhoop, N., V̈ogele, S., Mutafo?glu, K., M̈ohring, J., Dietrich, O., and Kaltofen, M.: Economic risks associated with low flows in the Elbe River Basin (Germany): an integrated economic-hydrologic approach to assess vulnerability to climate change, Reg. Environ. Change, submitted, 2013.
43. Gr̈unewald, U.: Water resources management in river catchments influenced by lignite mining, Ecol. Eng., 17, 143-152, doi:10.1016/S0925- 8574(00)00154-3, 2001.
44. Ǵomez, M., Olioso, A., Sobrino, J. A., and Jacob, F.: Retrieval of evapotranspiration over the Alpilles/ReSeDA experimental site using airborne POLDER sensor and a thermal camera, Remote Sens. Environ., 96, 399-408, doi:10.1016/j.rse.2005.03.006, 2005.
45. G̈untner, A. and Bronstert, A.: Representation of landscape variability and lateral redistribution processes for large-scale hydrological modelling in semi-arid areas, J. Hydrol., 297, 136-161, doi:10.1016/j.jhydrol. 2004.04.008, 2004.
46. Hoedjes, J. C. B., Chehbouni, A., Jacob, F., Ezzahar, J., and Boulet, G.: Delivering daily evapotranspiration from remotely sensed instantaneous evaporative fraction over olive orchard in semi-arid Morocco, J. Hydrol., 354, 53-64, doi:10.1016/j.jhydrol.2008.02.016, 2008.
47. Immerzeel, W. W. and Droogers, P.: Calibration of a distributed hydrological model based on satellite evapotranspiration, J. Hydrol., 349, 411-424, doi:10.1016/j.jhydrol.2007.11.017, 2008.
48. Ivanov, N. N.: Estimation of the amount of evaporation, P. All-Union Geogr. Soc., 86, 189-195, 1954 (in Russian)
49. Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Preserving high-resolution surface and rainfall data in operational-scale basin hydrology: a fully distributed physically-based approach, J. Hydrol., 298, 80-111, doi:10.1016/j.jhydrol.2004.03.041, 2004.
50. Jacobs, J. M., Anderson, M. C., Friess, L. C., and Diak, G. R.: Solar radiation, longwave radiation and emergent wetland evapotranspiration estimates from satellite data in Florida, USA/Estimations ̀a partir de donńees satellitales du rayonnement solaire, du rayonnement de grande longueur d'onde et de l'́evapotranspiration d'une zone humide de Floride (EUA), Hydrolog. Sci. J., 49, 461-476, doi:10.1623/hysj.49.3.461.54352, 2004.
51. Jhorar, R. K., Smit, A. A. M. F. R., Bastiaanssen, W. G. M., and Roest, C. W. J.: Calibration of a distributed irrigation water management model using remotely sensed evapotranspiration rates and groundwater heads, Irrig. Drain., 60, 57-69, doi:10.1002/ird.541, 2011.
52. Jiang, L. and Islam, S.: Estimation of surface evaporation map over Southern Great Plains using remote sensing data, Water Resour. Res., 37, 329-340, doi:10.1029/2000WR900255, 2001.
53. Kaltofen, M., Hentschel, M., Kaden, S., Dietrich, O., and Koch, H.: Wasserverf̈ugbarkeit im deutschen Elbegebiet, in: Die Elbe und ihr Einzugsgebiet im globalen Wandel, Chapt. 3.1, edited by: Wechsung, F., Hartje, V., Kaden, S., Venohr, M., Hansj̈urgens, B., and Gr̈afe, P., Weißensee Verlag, Berlin, in press, 2013a.
54. Kaltofen, M., Hentschel, M., Kaden, S., Dietrich, O., and Koch, H.: Modelling of water availability in the Elbe River basin and impacts of global change in the German part, Reg. Environ. Change, in preparation, 2013b.
55. Kite, G. W. and Droogers, P.: Comparing evapotranspiration estimates from satellites, hydrological models and field data, J. Hydrol., 229, 3-18, doi:10.1016/S0022-1694(99)00195-X, 2000.
56. Kite, G. W. and Pietroniro, A.: Remote sensing applications in hydrological modelling, Hydrolog. Sci. J., 41, 563-591, doi:10.1080/ 02626669609491526, 1996.
57. Kleme?s, V.: Conceptualization and scale in hydrology, J. Hydrol., 65, 1-23, doi:10.1016/0022-1694(83)90208-1, 1983.
58. Kleme?s, V.: A hydrological perspective, J. Hydrol., 100, 3-28, doi:10.1016/0022-1694(88)90179-5, 1988.
59. Koch, H., Kaltofen, M., Kaden, S., and Gr̈unewald, U.: Wasserverf̈ugbarkeit im tschechischen Elbegebiet, in: Die Elbe und ihr Einzugsgebiet im globalenWandel, Chapt. 3.2, edited by: Wechsung, F., Hartje, V., Kaden, S., Venohr, M., Hansj̈urgens, B., and Gr̈afe, P., Weißensee Verlag, Berlin, in press, 2013a.
60. Koch, H., Kaltofen, M., Kaden, S., and Gr̈unewald, U.: Effects of global change on water availability in the Czech Elbe region, Reg. Environ. Change, in preparation, 2013b.
61. Koloskov, G., Mukhamejanov, K., and Tanton, T. W.: Monin-Obukhov length as a cornerstone of the SEBAL calculations of evapotranspiration, J. Hydrol., 335, 170-179, doi:10.1016/j.jhydrol.2006.11.010, 2007.
62. Krause, S. and Bronstert, A.: The impact of groundwater-surface water interactions on the water balance of a mesoscale lowland river catchment in northeastern Germany, Hydrol. Process., 21, 169-184, doi:10.1002/hyp.6182, 2007.
63. Krause, S., Bronstert, A., and Zehe, E.: Groundwater-surface water interactions in a North German lowland floodplain-implications for the river discharge dynamics and riparian water balance, J. Hydrol., 347, 404-417, doi:10.1016/j.jhydrol.2007.09.028, 2007.
64. Krysanova, V., M̈uller-Wohlfeil, D.-I., and Becker, A.: Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds, Ecol. Model., 106, 261-289, doi:10.1016/S0304-3800(97) 00204-4, 1998.
65. Krysanova, V., Bronstert, A., and M̈uller-Wohlfeil, D.-I.: Modelling river discharge for large drainage basins: from lumped to distributed approach, Hydrolog. Sci. J., 44, 313-331, doi:10.1080/02626669909492224, 1999.
66. Krysanova, V., Wechsung, F., Arnold, J., Srinivasan, R., and Williams, J.: SWIM (Soil and Water Integrated Model) User Manual, PIK Report 69, Potsdam Institute for Climate Impact Research, Potsdam, Germany, http://www.pik-potsdam. de/research/publications/pikreports/.files/pr69.pdf, last access: October 2012, 2000.
67. Lewis, J. M.: The story behind the Bowen ratio, B. Am. Meteorol. Soc., 76, 2433-2443, doi:10.1175/1520-0477(1995)0762.0.CO;2, 1995.
68. Lindroth, A.: Aerodynamic and canopy resistance of short-rotation forest in relation to leaf area index and climate, Bound.-Lay. Meteorol., 66, 265-279, doi:10.1007/BF00705478, 1993.
69. Liu, Y. and Gupta, H. V.: Uncertainty in hydrologic modeling: toward an integrated data assimilation framework, Water Resour. Res., 43, W07401, doi:10.1029/2006WR005756, 2007.
70. Liu, Shaomin, Lu, L., Mao, D., and Jia, L.: Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements, Hydrol. Earth Syst. Sci., 11, 769-783, doi:10.5194/hess-11-769-2007, 2007.
71. Liu, T., Willems, P., Feng, X. W., Li, Q., Huang, Y., Bao, A. M., Chen, X., Veroustraete, F., and Dong, Q. H.: On the usefulness of remote sensing input data for spatially distributed hydrological modelling: case of the Tarim River basin in China, Hydrol. Process., 26, 335-344, doi:10.1002/hyp.8129, 2012.
72. Long, D. and Singh, V. P.: Integration of the GG model with SEBAL to produce time series of evapotranspiration of high spatial resolution at watershed scales, J. Geophys. Res., 115, D21128, doi:10.1029/2010JD014092, 2010.
73. Maniak, U.: Hydrologie und Wasserwirtschaft-Eine Einf̈uhrung f̈ur Ingenieure, Springer, Heidelberg, 5th Edn., 2005.
74. Mathieu, P.-P. and O'Neill, A.: Data assimilation: from photon counts to Earth System forecasts, Remote Sens. Environ., 112, 1258-1267, doi:10.1016/j.rse.2007.02.040, 2008.
75. McCabe, M. F. and Wood, E. F.: Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors, Remote Sens. Environ., 105, 271-285, doi:10.1016/j.rse.2006.07.006, 2006.
76. McCabe, M. F., Wood, E. F., Ẃojcik, R., Pan, M., Sheffield, J., Gao, H., and Su, H.: Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies, Remote Sens. Environ., 112, 430-444, doi:10.1016/j.rse.2007.03.027, 2008.
77. McMahon, T. A., Peel, M. C., Lowe, L., Srikanthan, R., and McVicar, T. R.: Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis, Hydrol. Earth Syst. Sci., 17, 1331-1363, doi:10.5194/hess-17-1331-2013, 2013.
78. Merz, R., Parajka, J., and Bl̈oschl, G.: Scale effects in conceptual hydrological modeling, Water Resour. Res., 45, W09405, doi:10.1029/2009WR007872, 2009.
79. Mo, X., Pappenberger, F., Beven, K., Liu, S., de Roo, A., and Lin, Z.: Parameter conditioning and prediction uncertainties of the LISFLOOD-WB distributed hydrological model/Conditionnement de paraḿetrage et incertitudes de pŕevision du mod̀ele hydrologique distribúe LISFLOOD-WB, Hydrolog. Sci. J., 51, 45-65, doi:10.1623/hysj.51.1.45, 2006.
80. Moran, M. S., Kustas, W. P., Vidal, A., Stannard, D. I., Blanford, J. H., and Nichols, W. D.: Use of ground-based remotely sensed data for surface energy balance evaluation of a semiarid rangeland, Water Resour. Res., 30, 1339-1349, doi:10.1029/93WR03064, 1994.
81. Moussa, R., Chahinian, N., and Bocquillon, C.: Distributed hydrological modelling of a Mediterranean mountainous catchment-model construction and multi-site validation, J. Hydrol., 337, 35-51, doi:10.1016/j.jhydrol.2007.01. 028, erratum: J. Hydrol., 345, 254, doi:10.1016/j.jhydrol.2007.08.012, 2007.
82. M̈uller-Westermeier, G. and Rieke, W.: Die Witterung in Deutschland, in: Klimastatusbericht 2002, Deutscher Wetterdienst, Offenbach, 79-87, 2003.
83. M̈uller-Westermeier, G. and Rieke, W.: Die Witterung in Deutschland, in: Klimastatusbericht 2003, Deutscher Wetterdienst, Offenbach, 71-78, 2004.
84. M̈uller-Westermeier, G., Czeplak, G., and Kreis, A.: Die Witterung in Deutschland, in: Klimastatusbericht 2001, Deutscher Wetterdienst, Offenbach, 125-130, 2002.
85. Nagler, P.: The role of remote sensing observations and models in hydrology: the science of evapotranspiration, Hydrol. Process., 25, 3977-3978, doi:10.1002/hyp.8436, preface to Special Issue, 2011.
86. Pan, M.,Wood, E. F.,Ẃojcik, R., and McCabe, M. F.: Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation, Remote Sens. Environ., 112, 1282-1294, doi:10.1016/j.rse.2007.02.039, 2008.
87. Patel, N. R., Rakhesh, D., and Mohammed, A. J.: Mapping of regional evapotranspiration in wheat using Terra/MODIS satellite data/Cartographie de l'́evapotranspiration ŕegionale du bĺe gr̂ace ́a des donńees satellitales Terra/MODIS, Hydrolog. Sci. J., 51, 325-335, doi:10.1623/hysj.51.2.325, 2006.
88. Pechlivanidis, I. G., McIntyre, N. R., and Wheater, H. S.: Calibration of the semi-distributed PDM rainfall-runoff model in the Upper Lee catchment, UK, J. Hydrol., 386, 198-209, doi:10.1016/j.jhydrol.2010.03.022, 2010.
89. Pokhrel, P. and Gupta, H. V.: On the use of spatial regularization strategies to improve calibration of distributed watershed models, Water Resour. Res., 46, W01505, doi:10.1029/2009WR008066, 2010.
90. Pokhrel, P. and Gupta, H. V.: On the ability to infer spatial catchment variability using streamflow hydrographs, Water Resour. Res., 47, W08534, doi:10.1029/2010WR009873, 2011.
91. Qin, C., Jia, Y., Su, Z. B., Zhou, Z., Qiu, Y., and Suhui, S.: Integrating remote sensing information into a distributed hydrological model for improving water budget predictions in largescale basins through data assimilation, Remote Sens. Environ., 8, 4441-4465, doi:10.3390/s8074441, 2008.
92. Ramakrishna, R. N. and Running, S. W.: Estimation of regional surface resistance to evapotranspiration from NDVI and Thermal-IR AVHRR data, J. Appl. Meteorol., 28, 276-284, doi:10.1175/1520-0450(1989)0282.0.CO;2, 1989.
93. Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., Seo, D.-J., and DMIP Participants: Overall distributed model intercomparison project results, J. Hydrol., 298, 27-60, doi:10.1016/j.jhydrol.2004.03.031, 2004.
94. Reichle, R. H.: Data assimilation methods in the Earth sciences, Adv. Water Resour., 31, 1411-1418, doi:10.1016/j.advwatres.2008.01.001, 2008.
95. Richter, D.: Verdunstung, in: Klimadaten der Deutschen Demokratischen Republik-Ein Handbuch f̈ur die Praxis, Vol. 6 of Reihe B, Meteorologischer Dienst der Deutschen Demokratischen Republik, Potsdam, 1984.
96. Ritchie, J. T.: A model for predicting evaporation from a row crop with incomplete cover, Water Resour. Res., 8, 1204-1213, doi:10.1029/WR008i005p01204, 1972.
97. Santhi, C., Kannan, N., Arnold, J. G., and Di Luzio, M.: Spatial calibration and temporal validation of flow for regional scale hydrologic modeling, J. Am. Water Resour. As., 44, 829-846, doi:10.1111/j.1752-1688.2008. 00207.x, 2008.
98. Sauer, V. B. and Meyer, R. W.: Determination of error in individual discharge measurements, Open-File Report 92-144, US Geological Survey, Norcross, Georgia, available at: http://pubs.usgs.gov/of/1992/ofr92-144/(last access date: 22 January 2013), 1992.
99. Schaller, M. F. and Fan, Y.: River basins as groundwater exporters and importers: Implications for water cycle and climate modeling, J. Geophys. Res.-Atmos., 114, D04103, doi:10.1029/2008JD010636, 2009.
100. Schultz, G. A.: Parameter determination and input estimation in rainfall-runoff modelling based on remote sensing techniques, in: Water for the Future: Hydrology in Perspective, Proceedings of the International Symposium on Water for the Future held in Rome, April 1987, edited by: Rodda, J. C. and Matalas, N. C., no. 164 in IAHS Publications ("Red Books" series), IAHS Press, Wallingford, UK, 425-438, 1987.
101. Schultz, G. A.: Remote sensing in hydrology, J. Hydrol., 100, 239-265, doi:10.1016/0022-1694(88)90187-4, 1988.
102. Schuurmans, J. M., van Geer, F. C., and Bierkens, M. F. P.: Remotely sensed latent heat fluxes for model error diagnosis: a case study, Hydrol. Earth Syst. Sci., 15, 759-769, doi:10.5194/hess-15-759-2011, 2011.
103. Singh, U. K., Ren, L., and Kang, S.: Simulation of soil water in space and time using an agro-hydrological model and remote sensing techniques, Agr. Water Manage., 97, 1210-1220, doi:10.1016/j.agwat.2010.03.002, 2010.
104. Smith, M. B., Koren, V., Reed, S., Zhang, Z., Zhang, Y., Moreda, F., Cui, Z., Mizukami, N., Anderson, E. A., and Cosgrove, B. A.: The distributed model intercomparison project-Phase 2: Motivation and design of the Oklahoma experiments, J. Hydrol., 418-419, 3-16, doi:10.1016/j.jhydrol.2011.08.055, 2012a.
105. Smith, M. B., Koren, V., Zhang, Z., Zhang, Y., Reed, S. M., Cui, Z., Moreda, F., Cosgrove, B. A., Mizukami, N., Anderson, E. A., and DMIP 2 Participants: Results of the DMIP 2 Oklahoma experiments, J. Hydrol., 418-419, 17-48, doi:10.1016/j.jhydrol.2011.08.056, 2012b.
106. Srinivasan, R., Ramanarayanan, T. S., Arnold, J. G., and Bednarz, S. T.: Large area hydrologic modeling and assessment Part II: Model application, J. Am. Water Resour. As., 34, 91-101, doi:10.1111/j.1752-1688.1998.tb05962.x, 1998.
107. Stisen, S., Sandholt, I., Norgaard, A., Fensholt, R., and Jensen, K. H.: Combining the triangle method with thermal inertia to estimate regional evapotranspiration-applied to MSGSEVIRI data in the Senegal River basin, Remote Sens. Environ., 112, 1242-1255, doi:10.1016/j.rse.2007.08.013, 2008.
108. Stisen, S., McCabe, M. F., Refsgaard, J. C., Lerer, S., and Butts, M. B.: Model parameter analysis using remotely sensed pattern information in a multi-constraint framework, J. Hydrol., 409, 337-349, doi:10.1016/j.jhydrol. 2011.08.030, 2011.
109. Śanchez, J. M., Scavone, G., Caselles, V., Valor, E., Copertino, V. A., and Telesca, V.: Monitoring daily evapotranspiration at a regional scale from Landsat-TM and ETM+ data: application to the Basilicata region, J. Hydrol., 351, 58-70, doi:10.1016/j.jhydrol.2007.11.041, 2008.
110. Thom, A. S. and Oliver, H. R.: On Penman's equation for estimating regional evaporation, Q. J. Roy. Meteor. Soc., 103, 345-357, doi:10.1002/qj.49710343610, 1977.
111. Tungalagsaikhan, P. and Guenther, K. P.: NOAA AVHRR Derived Land Surface Temperature Maps (LST)-Source, Image Characteristics, and Processing, online publication, available at: http://eoweb.dlr.de/short guide/D-LST.html, last access: September 2012, 2007.
112. Turc, L.: ́ Evaluation des besoins en eau d'irrigation, ́evaporation potentielle, Ann. Agron., 12, 13-49, 1961 (in French).
113. van de Griend, A. A. and Owe, M.: On the relationship between thermal emissivity and the normalised difference vegetation index for natural surfaces, Int. J. Remote Sens., 14, 1119-1131, doi:10.1080/01431169308904400, 1993.
114. van Dijk, A. I. J. M. and Renzullo, L. J.:Water resource monitoring systems and the role of satellite observations, Hydrol. Earth Syst. Sci., 15, 39-55, doi:10.5194/hess-15-39-2011, 2011.
115. Verstraeten W.W., Veroustraete F. Feyen J.: Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time: towards an operational processing chain for integrated optical and thermal sendor data products Remote Sens. Environ, 96, 256-276, doi:10.1016/j.rse.2005.03.004, 2005.
116. Vinukollu, R. K., Sheffield, J., Wood, E. F., Bosilovich, M. G., and Mocko, D.: Multimodel analysis of energy and water fluxes: intercomparison between operational analyses, a land surface model, and remote sensing, J. Hydrometeorol., 13, 3-26, doi:10.1175/2011JHM1372.1, 2012.
117. Wechsung, F., Hartje, V., Kaden, S., Venohr, M., Hansj̈urgens, B., and Gr̈afe, P. (Eds.): Die Elbe und ihr Einzugsgebiet im globalen Wandel, Weißensee Verlag, Berlin, in press, 2013.
118. Wendling, U. and Schellin, H.-G.: Neue Ergebnisse zur Berechnung der potentiellen Evapotranspiration, Z. Meteorol., 36, 214-217, 1986.
119. Wild, M.: Enlightening global dimming and brightening, B. Am. Meteorol. Soc., 93, 27-37, doi:10.1175/BAMS-D-11-00074.1, 2012.
120. Williams, J. R. and Hann, R. W.: Optimal operation of large agricultural watersheds with water quality constraints, Tech. Rep. 96, Texas Water Resources Institute, Texas A&M University, College Station, TX, 1978.
121. Wloczyk, C.: Entwicklung und Validierung einer Methodik zur Ermittlung der realen Evapotranspiration anhand von Fernerkundungsdaten in Mecklenburg-Vorpommern, Ph. D. thesis, Universit ̈at Rostock, Agrar-und Umweltwissenschaftliche Fakulẗat, 2007.
122. Wright, J. L. and Jensen, M. E.: Peak water requirements of crops in Southern Idaho, J. Irr. Drain. Div.-ASCE, 98, 193-201, 1972.
123. Zhang, X., Srinivasan, R., and Van Liew, M.: Multi-site calibration of the SWAT model for hydrologic modeling, T. ASABE, 51, 2039-2049, 2008.