Application of SEBAL Model for Mapping Evapotranspiration and Estimating Surface Energy Fluxes in South-Central Nebraska

Knowledge of spatiotemporal distribution of evapotranspiration ET on large scales, as quantified by satellite remote sensing techniques, can provide important information on a variety of water resources issues such as evaluating water distributions, water use by different land surfaces, water allocations, water rights, consumptive water use and planning, and better management of ground and surface water resources. The objective of this study was to assess the operational characteristics and performance of the surface energy balance algorithm for land SEBAL model for estimating crop ET ETc and other energy balance components, and mapping spatial distribution and seasonal variation of ETc on a large scale in south-central Nebraska climatic conditions. A total of seven cloud free Landsat Thematic Mapper TM/Enhanced Thematic Mapper ETM satellite images May 19, June 20, July 22, August 7, September 8, September 16, and October 18, 2005 were processed to generate ETc maps and estimate surface energy fluxes. Predictions from the SEBAL model were compared with the Bowen ratio energy balance system BREBS-measured fluxes on an instantaneous and daily basis. The ETc maps generated by the model for seven Landsat overpass days showed a very good progression of ETc with time during the growing season in 2005 as the surface conditions continuously changed. The predictions for some surface energy fluxes were very good. Overall, a very good correlation was found between the BREBS-measured and SEBAL-estimated ETc with a good r 2 of 0.73 and a root-mean-square difference RMSD of 1.04 mm day 1 . The estimated ETc was within 5% of the measured ETc. The model was able to predict growing season from emergence to physiological maturity cumulative daily corn ET reasonable well within 5% of the BREBS-measured values. The model overestimated the surface albedo by about 26% with a RMSD of 0.05. The difference between the measured and predicted albedo was the greatest on May 19, early in the growing season before the full canopy cover. The second largest difference between the two albedo values was on October 18, a day after harvest. The model significantly under predicted soil heat flux with a large RMSD of 80 W m 2 and most of the underestimation occurred in the late growing season. Local calibration of soil heat flux significantly improved the agreement between the measured and predicted values. Furthermore, the sensible heat flux was underestimated between September 20 after physiological maturity and October 18 a day after harvest. While our results showed that SEBAL can be a viable tool for generating ETc maps to assess and quantify spatiotemporal distribution of ET on large scales as well as estimating surface energy fluxes, its operational assessment for estimating sensible heat flux and ETc, especially during the drier periods for different surfaces, needs further development.

[1]  Assefa M. Melesse,et al.  Estimation of spatially distributed surface energy fluxes using remotely‐sensed data for agricultural fields , 2005 .

[2]  Yann Kerr,et al.  Seasonal estimates of riparian evapotranspiration using remote and in situ measurements. , 2000 .

[3]  A. Holtslag,et al.  A remote sensing surface energy balance algorithm for land (SEBAL)-1. Formulation , 1998 .

[4]  Albert Olioso,et al.  Mapping surface fluxes using airborne visible, near infrared, thermal infrared remote sensing data and a spatialized surface energy balance model , 2002 .

[5]  James L. Wright,et al.  Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Applications , 2007 .

[6]  Manfred Owe,et al.  On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces , 1993 .

[7]  Wim G.M. Bastiaanssen,et al.  A New Simple Method to Determine Crop Coefficients for Water Allocation Planning from Satellites: Results from Kenya , 2000 .

[8]  Lalith Chandrapala,et al.  Evapotranspiration fluxes over mixed vegetation areas measured from large aperture scintillometer , 2003 .

[9]  Thomas J. Schmugge,et al.  Parameterization of surface heat fluxes above forest with satellite thermal sensing and boundary-layer soundings , 1993 .

[10]  M. S. Moran,et al.  Using satellite remote sensing to extrapolate evapotranspiration estimates in time and space over a semiarid Rangeland basin , 1994 .

[11]  E. Noordman,et al.  SEBAL model with remotely sensed data to improve water-resources management under actual field conditions , 2005 .

[12]  Robert Clement,et al.  Momentum, water vapor, and carbon dioxide exchange at a centrally located prairie site during FIFE , 1992 .

[13]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[14]  B. Markham,et al.  Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges , 2003, IEEE Trans. Geosci. Remote. Sens..

[15]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature [Agric. For. Meteorol., 77 (1995) 263–293]☆ , 1996 .

[16]  Massimo Menenti,et al.  S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance , 2000 .

[17]  Yann Kerr,et al.  Use of meteorological satellites for water balance monitoring in Sahelian regions , 1989 .

[18]  Wilfried Brutsaert,et al.  Application of self‐preservation in the diurnal evolution of the surface energy budget to determine daily evaporation , 1992 .

[19]  Ayse Irmak,et al.  Sensitivity Analyses and Sensitivity Coefficients of Standardized Daily ASCE-Penman-Monteith Equation , 2006 .

[20]  A. Gieske,et al.  High density NOAA time series of ET in the Gediz Basin, Turkey , 2005 .

[21]  Craig S. T. Daughtry,et al.  Estimation of the soil heat flux/net radiation ratio from spectral data , 1990 .

[22]  Ayse Irmak,et al.  Reference and Crop Evapotranspiration in South Central Nebraska. I: Comparison and Analysis of Grass and Alfalfa-Reference Evapotranspiration , 2008 .

[23]  Jing M. Chen,et al.  Mapping evapotranspiration based on remote sensing: An application to Canada's landmass , 2003 .

[24]  Z. Su The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes , 2002 .

[25]  Anthony Morse,et al.  A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning , 2005 .

[26]  Martha C. Anderson,et al.  Satellite-based estimates of longwave radiation for agricultural applications. , 2000 .

[27]  Tammo S. Steenhuis,et al.  Investigating ponding depth and soil detachability for a mechanistic erosion model using a simple experiment , 2003 .

[28]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[29]  Raffaele Casa,et al.  Radiation measurement for plant ecophysiology. , 2003, Journal of experimental botany.

[30]  Wim G.M. Bastiaanssen,et al.  Water balance variability across Sri Lanka for assessing agricultural and environmental water use , 2003 .

[31]  Anthony Morse,et al.  SATELLITE-BASED EVAPOTRANSPIRATION BY METRIC AND LANDSAT FOR WESTERN STATES WATER MANAGEMENT , 2005 .

[32]  Martha C. Anderson,et al.  A Two-Source Time-Integrated Model for Estimating Surface Fluxes Using Thermal Infrared Remote Sensing , 1997 .

[33]  R. Qualls,et al.  Effect of Vegetation Density on the Parameterization of Scalar Roughness to Estimate Spatially Distributed Sensible Heat Fluxes , 1996 .

[34]  I. A. Walter,et al.  The ASCE standardized reference evapotranspiration equation , 2005 .

[35]  Craig S. T. Daughtry,et al.  Spectral estimates of net radiation and soil heat flux , 1990 .

[36]  T. J. Lyons,et al.  Estimation of Regional Evapotranspiration through Remote Sensing , 1999 .

[37]  Wilfried Brutsaert,et al.  Regional Surface Fluxes From Remotely Sensed Skin Temperature and Lower Boundary Layer Measurements , 1990 .

[38]  James L. Wright,et al.  Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid U.S. , 2005 .

[39]  W. Bastiaanssen SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey , 2000 .

[40]  William P. Kustas,et al.  Use of remote sensing for evapotranspiration monitoring over land surfaces , 1996 .

[41]  Ayse Irmak,et al.  Reference and Crop Evapotranspiration in South Central Nebraska. II: Measurement and Estimation of Actual Evapotranspiration for Corn , 2008 .

[42]  W. Bastiaanssen,et al.  Evaporative depletion assessments for irrigated watersheds in Sri Lanka , 2001, Irrigation Science.

[43]  Keith Beven,et al.  Estimation of evapotranspiration at the landscape scale: A fuzzy disaggregation approach , 1997 .

[44]  Richard G. Allen,et al.  Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model , 2007 .

[45]  M. S. Moran,et al.  Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands , 1994 .

[46]  S. Goetz,et al.  Satellite remote sensing of surface energy balance : success, failures, and unresolved issues in FIFE , 1992 .

[47]  Steven P. Loheide,et al.  A local-scale, high-resolution evapotranspiration mapping algorithm (ETMA) with hydroecological applications at riparian meadow restoration sites , 2005 .

[48]  William P. Kustas,et al.  Evaluating the effects of subpixel heterogeneity on pixel average fluxes. , 2000 .

[49]  Weimin Ju,et al.  Distributed hydrological model for mapping evapotranspiration using remote sensing inputs , 2005 .

[50]  T. M. Crawford,et al.  An Improved Parameterization for Estimating Effective Atmospheric Emissivity for Use in Calculating Daytime Downwelling Longwave Radiation , 1999 .

[51]  Wenbin Min,et al.  A scheme for pixel-scale aerodynamic surface temperature over hilly land , 2004 .

[52]  Martha C. Anderson,et al.  Solar radiation, longwave radiation and emergent wetland evapotranspiration estimates from satellite data in Florida, USA / Estimations à partir de données satellitales du rayonnement solaire, du rayonnement de grande longueur d’onde et de l’évapotranspiration d’une zone humide de Floride (EUA) , 2004 .

[53]  Hubert H. G. Savenije,et al.  Spatial variability of evaporation and moisture storage in the swamps of the upper Nile studied by remote sensing techniques , 2004 .

[54]  Wim G.M. Bastiaanssen,et al.  Irrigation Performance Indicators Based on Remotely Sensed Data: a Review of Literature , 1999 .

[55]  Richard G. Allen,et al.  U.S. Validation Tests on the SEBAL Model for Evapotranspiration via Satellite , 2003 .

[56]  Wim G.M. Bastiaanssen,et al.  Satellite surveillance of evaporative depletion across the Indus Basin , 2002 .

[57]  Eric Elguero,et al.  Examination of evaporative fraction diurnal behaviour using a soil-vegetation model coupled with a mixed-layer model , 1999 .