Based on the crop water stress index (CWSI) concept, a new model was proposed to account for advection to estimate evapotranspiration. Both local scale evaluation with sites observations and regional scale evaluation with a remote dataset from Landsat 7 ETM+ were carried out to assess the performance of this model. Local scale evaluation indicates that this newly developed model can effectively characterize the daily variations of evapotranspiration and the predicted results show good agreement with the site observations. For all the 6 corn sites, the coefficient of determination ( ) is 0.90 and the root mean square difference (RMSD) is 58.52W/m2. For all the 6 soybean sites, the and RMSD are 0.85 and 49.46W/m2, respectively. Regional scale evaluation shows that the model can capture the spatial variations of evapotranspiration at the Landsat-based scale. Clear spatial patterns were observed at the Landsat-based scale and are closely related to the dominant land covers, corn and soybean. Furthermore, the surface resistance derived from instantaneous CWSI was applied to the Penman-Monteith equation to estimate daily evapotranspiration. Overall, results indicate that this newly developed model is capable of estimating reliable surface heat fluxes using remotely sensed data. 1. Introduction Evapotranspiration ( ) is a very important process which relates to energy and water exchange between the hydrosphere, atmosphere, and biosphere [1, 2]. The research on evapotranspiration is very crucial to further our understanding of global climate change, land-atmosphere interaction, water cycle, and ecological studies [3–5]. Recently, the “evaporation paradox,” which is referred to as the decreasing pan observations and the increasing surface air temperature over the past 50 years, has been reported in many regions around the world [6–8]. Pan evaporation provides a measurement of the integrated effect of radiation, wind, temperature, and humidity on the evaporation from an open water surface. Actual evaporation is the quantity of water that is actually removed from natural surfaces. There is a need to understand the change of actual evapotranspiration at regional and global scales behind evaporation paradox. Actual evapotranspiration is a key factor to understand the regional water cycle and energy balance. An in-depth understanding of regional evapotranspiration will benefit the water resource planning and management in arid and semiarid areas [9]. As a promising means of land surface observation, remote sensing has some salient characteristics, such as large scale
References
[1]
W. Brutsaert, Hydrology: An Introduction, Cambridge University Press, New York, NY, USA, 2005.
[2]
C. Priestley and R. Taylor, “On the assessment of surface heat flux and evaporation using large-scale parameters,” Monthly Weather Review, vol. 100, no. 2, pp. 81–92, 1972.
[3]
R. A. Betts, P. M. Cox, M. Collins, P. P. Harris, C. Huntingford, and C. D. Jones, “The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming,” Theoretical and Applied Climatology, vol. 78, no. 1–3, pp. 157–175, 2004.
[4]
J. P. Goutorbe, T. Lebel, A. Tinga, P. Bessemoulin, and J. Brouwer, “A large-scale study of land-atmosphere interactions in the semi-arid tropics (HAPEX-Sahel),” in Exchange Processes at the Land Surface for a range of space and Time scales, H. J. Bolle, R. A. Feddes, and J. D. Kalma, Eds., vol. 212, pp. 357–364, AHS Press.
[5]
D. M. Lawrence, P. E. Thornton, K. W. Oleson, and G. B. Bonan, “The partitioning of evapotranspiration into transpiration, soil evaporation, and canopy evaporation in a GCM: impacts on land-atmosphere interaction,” Journal of Hydrometeorology, vol. 8, no. 4, pp. 862–880, 2007.
[6]
W. Brutsaert and M. B. Parlange, “Hydrologic cycle explains the evaporation paradox,” Nature, vol. 396, no. 6706, article 30, 1998.
[7]
G. Fu, S. P. Charles, and J. Yu, “A critical overview of pan evaporation trends over the last 50 years,” Climatic Change, vol. 97, no. 1, pp. 193–214, 2009.
[8]
M. L. Roderick and G. D. Farquhar, “The cause of decreased pan evaporation over the past 50 years,” Science, vol. 298, no. 5597, pp. 1410–1411, 2002.
[9]
R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, “Crop evapotranspiration guidelines for computing crop water requirements,” FAO Irrigation and Drainage Paper 56, FAO, Rome, 1998.
[10]
S. Liang, Advances in Land Remote Sensing: System, Modelling, Inversion and Application, Springer, New York, NY, USA, 2008.
[11]
R. Jackson, R. Reginato, and S. Idso, “Wheat canopy temperature: a practical tool for evaluating water requirements,” Water Resources Research, vol. 13, no. 3, pp. 651–656, 1977.
[12]
R. D. Jackson, M. S. Moran, L. W. Gay, and L. H. Raymond, “Evaluating evaporation from field crops using airborne radiometry and ground-based meteorological data,” Irrigation Science, vol. 8, no. 2, pp. 81–90, 1987.
[13]
M. Williams, A. D. Richardson, M. Reichstein et al., “Improving land surface models with FLUXNET data,” Biogeosciences, vol. 6, no. 7, pp. 1341–1359, 2009.
[14]
K. Zhang, J. S. Kimball, Q. Mu, L. A. Jones, S. J. Goetz, and S. W. Running, “Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005,” Journal of Hydrology, vol. 379, no. 1-2, pp. 92–110, 2009.
[15]
M. Jung, M. Reichstein, P. Ciais et al., “Recent decline in the global land evapotranspiration trend due to limited moisture supply,” Nature, vol. 467, no. 7318, pp. 951–954, 2010.
[16]
M. C. Anderson, J. M. Norman, W. P. Kustas, R. Houborg, P. J. Starks, and N. Agam, “A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales,” Remote Sensing of Environment, vol. 112, no. 12, pp. 4227–4241, 2008.
[17]
M. C. Anderson, J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas, “A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation,” Journal of Geophysical Research D, vol. 112, no. 10, Article ID D10117, 2007.
[18]
W. G. M. Bastiaanssen, M. Menenti, R. A. Feddes, and A. A. M. Holtslag, “A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation,” Journal of Hydrology, vol. 212-213, no. 1–4, pp. 198–212, 1998.
[19]
J. M. Norman, W. P. Kustas, and K. S. Humes, “Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature,” Agricultural and Forest Meteorology, vol. 77, no. 3-4, pp. 263–293, 1995.
[20]
Z. Su, “The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes,” Hydrology and Earth System Sciences, vol. 6, no. 1, pp. 85–99, 2002.
[21]
M. C. Anderson, J. M. Norman, G. R. Diak, W. P. Kustas, and J. R. Mecikalski, “A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing,” Remote Sensing of Environment, vol. 60, no. 2, pp. 195–216, 1997.
[22]
M. S. Moran, T. R. Clarke, Y. Inoue, and A. Vidal, “Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index,” Remote Sensing of Environment, vol. 49, no. 3, pp. 246–263, 1994.
[23]
G. J. Roerink, Z. Su, and M. Menenti, “S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance,” Physics and Chemistry of the Earth B, vol. 25, no. 2, pp. 147–157, 2000.
[24]
L. Jiang and S. Islam, “Estimation of surface evaporation map over southern Great Plains using remote sensing data,” Water Resources Research, vol. 37, no. 2, pp. 329–340, 2001.
[25]
R. Zhang, X. Sun, W. Wang, J. Xu, Z. Zhu, and J. Tian, “An operational two-layer remote sensing model to estimate surface flux in regional scale: physical background,” Science in China D, vol. 48, no. 1, pp. 225–244, 2005.
[26]
R. Zhang, J. Tian, H. Su, X. Sun, S. Chen, and J. Xia, “Two improvements of an operational two-layer model for terrestrial surface heat flux retrieval,” Sensors, vol. 8, no. 10, pp. 6165–6187, 2008.
[27]
K. Wang, Z. Li, and M. Cribb, “Estimation of evaporative fraction from a combination of day and night land surface temperatures and NDVI: a new method to determine the Priestley-Taylor parameter,” Remote Sensing of Environment, vol. 102, no. 3-4, pp. 293–305, 2006.
[28]
S. Stisen, I. Sandholt, A. N？rgaard, R. Fensholt, and K. H. Jensen, “Combining the triangle method with thermal inertia to estimate regional evapotranspiration: applied to MSG-SEVIRI data in the Senegal River basin,” Remote Sensing of Environment, vol. 112, no. 3, pp. 1242–1255, 2008.
[29]
Y. Shu, S. Stisen, K. H. Jensen, and I. Sandholt, “Estimation of regional evapotranspiration over the North China Plain using geostationary satellite data,” International Journal of Applied Earth Observation and Geoinformation, vol. 13, no. 2, pp. 192–206, 2011.
[30]
T. Carlson, “An overview of the “triangle method” for estimating surface evapotranspiration and soil moisture from satellite imagery,” Sensors, vol. 7, no. 8, pp. 1612–1629, 2007.
[31]
G. Petropoulos, T. N. Carlson, M. J. Wooster, and S. Islam, “A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture,” Progress in Physical Geography, vol. 33, no. 2, pp. 224–250, 2009.
[32]
H. A. Cleugh, R. Leuning, Q. Mu, and S. W. Running, “Regional evaporation estimates from flux tower and MODIS satellite data,” Remote Sensing of Environment, vol. 106, no. 3, pp. 285–304, 2007.
[33]
Q. Mu, F. A. Heinsch, M. Zhao, and S. W. Running, “Development of a global evapotranspiration algorithm based on MODIS and global meteorology data,” Remote Sensing of Environment, vol. 111, no. 4, pp. 519–536, 2007.
[34]
Q. Mu, M. Zhao, and S. W. Running, “Improvements to a MODIS global terrestrial evapotranspiration algorithm,” Remote Sensing of Environment, vol. 115, no. 8, pp. 1781–1800, 2011.
[35]
J. D. Kalma, T. R. McVicar, and M. F. McCabe, “Estimating land surface evaporation: a review of methods using remotely sensed surface temperature data,” Surveys in Geophysics, vol. 29, no. 4-5, pp. 421–469, 2008.
[36]
Z.-L. Li, R. Tang, Z. Wan et al., “A review of current methodologies for regional evapotranspiration estimation from remotely sensed data,” Sensors, vol. 9, no. 5, pp. 3801–3853, 2009.
[37]
R. Allen, “Initial report on closure error from Eddy-Covariance Systems used in the regional advection perturbations in an irrigated desert (RAPID)—impacts on evapotranspiration,” Technical Report, 1999, http://www.kimberly.uidaho.edu/~rallen/equip/rapidrp1.pdf.
[38]
J. Wang, G. Y. Gao, Y. Hu, Z. Shen, Y. Mitsuta, and K. Sahasi, “An overview of the Heife experiment in the Peoples-Republic-of-China,” in Exchange Processes at the Land Surface for a Range of Space and Time Scales, H. J. Bolle, R. A. Feddes, and J. D. Kalma, Eds., vol. 212, pp. 397–403, IAHS Press.
[39]
J. A. Tolk, S. R. Evett, and T. A. Howell, “Advection influences on evapotranspiration of alfalfa in a semiarid climate,” Agronomy Journal, vol. 98, no. 6, pp. 1646–1654, 2006.
[40]
J. A. Tolk, T. A. Howell, and S. R. Evett, “Nighttime evapotranspiration from alfalfa and cotton in a semiarid climate,” Agronomy Journal, vol. 98, no. 3, pp. 730–736, 2006.
[41]
R. Allen, A. Irmak, R. Trezza, J. M. H. Hendrickx, W. Bastiaanssen, and J. Kjaersgaard, “Satellite-based ET estimation in agriculture using SEBAL and METRIC,” Hydrological Processes, vol. 25, no. 26, pp. 4011–4027, 2011.
[42]
T. R. Oke, “Advectively-assisted evapotranspiration from irrigated urban vegetation,” Boundary-Layer Meteorology, vol. 17, no. 2, pp. 167–173, 1979.
[43]
D. A. Rijks, “Water use by irrigated cotton in Sudan .3. Bowen ratios and advective energy,” Journal of Applied Ecology, vol. 8, no. 3, pp. 643–663, 1971.
[44]
J. L. Chávez, C. M. U. Neale, J. H. Prueger, and W. P. Kustas, “Daily evapotranspiration estimates from extrapolating instantaneous airborne remote sensing et values,” Irrigation Science, vol. 27, no. 1, pp. 67–81, 2008.
[45]
H. O. Farah, W. G. M. Bastiaanssen, and R. A. Feddes, “Evaluation of the temporal variability of the evaporative fraction in a tropical watershed,” International Journal of Applied Earth Observation and Geoinformation, vol. 5, no. 2, pp. 129–140, 2004.
[46]
R. D. Crago, “Conservation and variability of the evaporative fraction during the daytime,” Journal of Hydrology, vol. 180, no. 1–4, pp. 173–194, 1996.
[47]
J. C. B. Hoedjes, A. Chehbouni, F. Jacob, J. Ezzahar, and G. Boulet, “Deriving daily evapotranspiration from remotely sensed instantaneous evaporative fraction over olive orchard in semi-arid Morocco,” Journal of Hydrology, vol. 354, no. 1–4, pp. 53–64, 2008.
[48]
R. G. Allen, M. Tasumi, and R. Trezza, “Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model,” Journal of Irrigation and Drainage Engineering, vol. 133, no. 4, pp. 380–394, 2007.
[49]
J. L. Monteith, “Evaporation and environment,” in The State and Movementof Water in Living Organisms, G. E. Fog, Ed., vol. 19, pp. 205–234, Cambridge University Press, Cambridge, UK, 1965.
[50]
R. J. Granger and D. M. Gray, “Evaporation from natural nonsaturated surfaces,” Journal of Hydrology, vol. 111, no. 1-4, pp. 21–29, 1989.
[51]
W. Brutsaert and H. Stricker, “An advection-aridity approach to estimate actual regional evapotranspiration,” Water Resources Research, vol. 15, no. 2, pp. 443–450, 1979.
[52]
R. D. Jackson, S. B. Idso, R. J. Reginato, and P. J. Pinter Jr., “Canopy temperature as a crop water stress indicator,” Water Resources Research, vol. 17, no. 4, pp. 1133–1138, 1981.
[53]
R. D. Jackson, W. P. Kustas, and B. J. Choudhury, “A reexamination of the crop water stress index,” Irrigation Science, vol. 9, no. 4, pp. 309–317, 1988.
[54]
W. L. Ehrler, “Cotton leaf temperatures as related to soil-water depletion and meteorological factors,” Agronomy Journal, vol. 65, no. 3, pp. 404–409, 1973.
[55]
H. A. R. De Bruin, O. K. Hartogensis, R. G. Allen, and J. W. J. L. Kramer, “Regional advection perturbations in an irrigated desert (RAPID) experiment,” Theoretical and Applied Climatology, vol. 80, no. 2-4, pp. 143–152, 2005.
[56]
M. Menenti and B. Choudhury, “Parameterization of land surface evaporation by means of location dependent potential evaporation and surface temperature range,” in Exchange Processes at the Land Surface for a Range of Space and Time Scales, H. J. Bolle, R. A. Feddes, and J. D. Kalma, Eds., vol. 212, pp. 561–568, IAHS Press, 1993.
[57]
H. Liu, Y. Zhang, S. Liu, H. Jiang, L. Sheng, and Q. L. Williams, “Eddy-Covariance measurements of surface energy budget and evaporation in a cool season over southern open water in Mississippi,” Journal of Geophysical Research D, vol. 114, no. D4, 2009.
[58]
H. Liu, P. D. Blanken, T. Weidinger, A. Nordbo, and T. Vesala, “Variability in cold front activities modulating cool-season evaporation from a southern inland water in the USA,” Environmental Research Letters, vol. 6, no. 2, Article ID 024022, 2011.
[59]
B. J. Choudhury, R. J. Reginato, and S. B. Idso, “An analysis of infrared temperature observations over wheat and calculation of latent heat flux,” Agricultural and Forest Meteorology, vol. 37, no. 1, pp. 75–88, 1986.
[60]
L. Mahrt and M. Ek, “The influence of atmospheric stability on potential evaporation,” Journal of Climate & Applied Meteorology, vol. 23, no. 2, pp. 222–234, 1984.
[61]
K. Yang, T. Koike, and D. Yang, “Surface flux parameterization in the Tibetan Plateau,” Boundary-Layer Meteorology, vol. 106, no. 2, pp. 245–262, 2003.
[62]
S. Liu, L. Lu, D. Mao, and L. Jia, “Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements,” Hydrology and Earth System Sciences, vol. 11, no. 2, pp. 769–783, 2007.
[63]
W. Brutsaert, Evaporation into the Atmosphere: Theory, History, and Applications, Springer, New York, NY, USA, 1982.
[64]
C. A. Paulson, “Mathematical representation of wind speed nd temperature profiles in the unstable atmospheric surface layer,” Journal of Applied Meteorology, vol. 9, no. 6, pp. 857–861, 1970.
[65]
J. A. Businger, J. C. Wyngaard, Y. Izumi, and E. F. Bradley, “Flux- profile relationships in the atmospheric surface layer,” Journal of the Atmospheric Sciences, vol. 28, no. 2, pp. 181–189, 1971.
[66]
E. K. Webb, G. I. Pearman, and R. Leuning, “Correction of flux measurements for density effects due to heat and water vapour transfer,” Quarterly Journal Royal Meteorological Society, vol. 106, no. 447, pp. 85–100, 1980.
[67]
G. G. Katul and M. B. Parlange, “A Penman-Brutsaert model for wet surface evaporation,” Water Resources Research, vol. 28, no. 1, pp. 121–126, 1992.
[68]
S. Liu, J. Bai, Z. Jia, L. Jia, H. Zhou, and L. Lu, “Estimation of evapotranspiration in the Mu Us Sandland of China,” Hydrology and Earth System Sciences, vol. 14, no. 3, pp. 573–584, 2010.
[69]
J. L. Monteith, Principles of Environmental Physics, Edward Arnold, London, UK, 1973.
[70]
W. P. Kustas, B. J. Choudhury, M. S. Moran et al., “Determination of sensible heat flux over sparse canopy using thermal infrared data,” Agricultural and Forest Meteorology, vol. 44, no. 3-4, pp. 197–216, 1989.
[71]
W. P. Kustas, J. L. Hatfield, and J. H. Prueger, “The soil moisture-atmosphere coupling experiment (SMACEX): background, hydrometeorological conditions, and preliminary findings,” Journal of Hydrometeorology, vol. 6, no. 6, pp. 791–804, 2005.
[72]
H. Su, M. F. McCabe, E. F. Wood, Z. Su, and J. H. Prueger, “Modeling evapotranspiration during SMACEX: comparing two approaches for local- and regional-scale prediction,” Journal of Hydrometeorology, vol. 6, no. 6, pp. 910–922, 2005.
[73]
M. F. McCabe and E. F. Wood, “Scale influences on the remote estimation of evapotranspiration using multiple satellite sensors,” Remote Sensing of Environment, vol. 105, no. 4, pp. 271–285, 2006.
[74]
T. E. Twine, W. P. Kustas, J. M. Norman et al., “Correcting Eddy-Covariance flux underestimates over a grassland,” Agricultural and Forest Meteorology, vol. 103, no. 3, pp. 279–300, 2000.
[75]
J. A. Sobrino, N. Raissouni, and Z.-L. Li, “A comparative study of land surface emissivity retrieval from NOAA data,” Remote Sensing of Environment, vol. 75, no. 2, pp. 256–266, 2001.
[76]
F. Li, T. J. Jackson, W. P. Kustas et al., “Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX,” Remote Sensing of Environment, vol. 92, no. 4, pp. 521–534, 2004.
[77]
S. Liang, “Narrowband to broadband conversions of land surface albedo I algorithms,” Remote Sensing of Environment, vol. 76, no. 2, pp. 213–238, 2001.
[78]
S. Liang, C. J. Shuey, A. L. Russ et al., “Narrowband to broadband conversions of land surface albedo: II. Validation,” Remote Sensing of Environment, vol. 84, no. 1, pp. 25–41, 2003.
[79]
B. J. Choudhury, S. B. Idso, and R. J. Reginato, “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,” Agricultural and Forest Meteorology, vol. 39, no. 4, pp. 283–297, 1987.
[80]
F. Baret, J. G. Clevers, and M. D. Steven, “The robustness of canopy gap fraction estimates from red and near-infrared reflectances: a comparison of approaches,” Remote Sensing of Environment, vol. 54, no. 2, pp. 141–151, 1995.
[81]
J. L. Chávez, C. M. U. Neale, L. E. Hipps, J. H. Prueger, and W. P. Kustas, “Comparing aircraft-based remotely sensed energy balance fluxes with Eddy-Covariance tower data using heat flux source area functions,” Journal of Hydrometeorology, vol. 6, no. 6, pp. 923–940, 2005.
[82]
J. L. Chávez, T. A. Howell, and K. S. Copeland, “Evaluating Eddy-Covariance cotton ET measurements in an advective environment with large weighing lysimeters,” Irrigation Science, vol. 28, no. 1, pp. 35–50, 2009.
[83]
T. Foken, “The energy balance closure problem: an overview,” Ecological Applications, vol. 18, no. 6, pp. 1351–1367, 2008.
[84]
T. Foken, F. Wimmer, M. Mauder, C. Thomas, and C. Liebethal, “Some aspects of the energy balance closure problem,” Atmospheric Chemistry and Physics, vol. 6, no. 12, pp. 4395–4402, 2006.
