Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/22/2011
Publication Date: 12/8/2011
Publication URL: http://handle.nal.usda.gov/10113/56517
Citation: Tang, R., Jia, Y., Li, C., Sun, X., Kustas, W.P., Anderson, M.C. 2011. An intercomparison of three remote sensing-based energy balance models using large aperture scintillometer measurements over a wheat-corn production region. Remote Sensing of Environment. 115:3187-3202. Interpretive Summary: There are several remote sensing-based models being applied routinely with satellite observations of land surface temperature for estimating evapotranspiration (ET). These remote sensing-based methods are considered one of the few viable means for monitoring crop water use and stress, and for water resource and irrigation management applications at field, watershed and regional scales. There have been few studies comparing the various modeling approaches with ground ET measurements and in evaluating the uncertainty in model predicted ET due to errors in the remote sensing inputs. This paper describes such a study with ground validation and satellite remote sensing data collected during wheat and corn growing seasons in a subhumid climate at a measurement station in Yucheng, China. The validation and intercomparison study was conducted using three remote sensing-based models having operational capabilities, namely the Surface Energy Balance System (SEBS), the Two-Source Energy Balance (TSEB) model, and the surface Temperature-Vegetation index Triangle (TVT) model. Each modeling approach has a different level of complexity in relating the remote sensing inputs of land surface temperature and fractional vegetation cover/leaf area to ET. The results indicate that the TSEB model provides the best overall agreement with the ET observations. Although performance of SEBS in estimating ET is comparable to TSEB, SEBS has significantly greater sensitivity to the uncertainty in satellite-derived land surface temperature and fractional vegetation cover/leaf area. On the other hand, the TVT model performs poorly, indicating that assumptions used in this modeling approach are not appropriate for this subhumid agricultural region in China. It is concluded that the TSEB modeling is the most robust scheme to be used operationally with satellite data. The TSEB modeling framework has been incorporated into a regionally-based ET modeling system using weather satellite data. This remote sensing-based ET modeling system has potential to provide ET/crop water use and stress estimates on a regional scale.
Technical Abstract: This paper compares three remote sensing-based models for estimating evapotranspiration (ET), namely the Surface Energy Balance System (SEBS), the Two-Source Energy Balance (TSEB) model, and the surface Temperature-Vegetation index Triangle (TVT). The models used as input MODIS/TERRA products and ground measurements collected during the wheat and corn growth period in a subhumid climate at a measurement station in Yucheng, China. MODIS land surface temperature (LST) and leaf area index (LAI) products, corrected using ground-truth observations, were used in the three models. The TSEB model output of sensible (H) and latent (LE) heat fluxes were in good agreement with Large Aperture Scintillometer (LAS)-measured H and LE derived by residual (RMSD < 45 W/m^2). Reasonable agreement was also obtained with the SEBS model output yielding RMSD for H of ~ 40 W/m^2 and LE ~ 55 W/m^2. However, the TVT model output resulted in poor agreement with the LAS-estimated H and LE with RMSD-values > 110 W/m^2. Using the uncorrected MODIS LST and LAI products resulted in a deterioration of the agreement in H and LE with LAS-estimated values for both the TSEB and SEBS models, whereas TVT performance improved marginally. These results indicate that the TSEB model yielded the closest agreement with the LAS-estimated fluxes using either the corrected or uncorrected MODIS inputs (LST and LAI). The SEBS model also computed reasonable H and LE values but was significantly more sensitive to errors in MODIS LST and LAI inputs than the TSEB model. In the TVT model, output of H and LE was unacceptable in either scenario of MODIS input which was attributable to errors in selection of the dry edge. With the TVT method, accurate determination of the dry edge end member is critical in regional ET estimation, but for humid and subhumid regions this end member may often be quite difficult to identify or encompass within a satellite scene.