Articles | Volume 20, issue 4
Hydrol. Earth Syst. Sci., 20, 1523–1545, 2016
Hydrol. Earth Syst. Sci., 20, 1523–1545, 2016

Research article 20 Apr 2016

Research article | 20 Apr 2016

Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one- and two-source modeling schemes

Ting Xia1,2, William P. Kustas2, Martha C. Anderson2, Joseph G. Alfieri2, Feng Gao2, Lynn McKee2, John H. Prueger3, Hatim M. E. Geli4, Christopher M. U. Neale5, Luis Sanchez6, Maria Mar Alsina6, and Zhongjing Wang1,7 Ting Xia et al.
  • 1Department of Hydraulic Engineering, Tsinghua University, Beijing, 100084, China
  • 2USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA
  • 3USDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA, USA
  • 4Department of Civil and Environmental Engineering, Utah State University, Logan, UT, USA
  • 5Robert B. Daugherty Water for Food Institute, University of Nebraska-Lincoln, Lincoln, NE, USA
  • 6E. & J. Gallo Winery, Viticulture, Chemistry and Enology, Modesto, CA 95353, USA
  • 7State Key Laboratory of Hydro-Science and Engineering, Tsinghua University, Beijing, 100084, China

Abstract. Thermal and multispectral remote sensing data from low-altitude aircraft can provide high spatial resolution necessary for sub-field (≤  10 m) and plant canopy (≤  1 m) scale evapotranspiration (ET) monitoring. In this study, high-resolution (sub-meter-scale) thermal infrared and multispectral shortwave data from aircraft are used to map ET over vineyards in central California with the two-source energy balance (TSEB) model and with a simple model having operational immediate capabilities called DATTUTDUT (Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature). The latter uses contextual information within the image to scale between radiometric land surface temperature (TR) values representing hydrologic limits of potential ET and a non-evaporative surface. Imagery from 5 days throughout the growing season is used for mapping ET at the sub-field scale. The performance of the two models is evaluated using tower-based measurements of sensible (H) and latent heat (LE) flux or ET. The comparison indicates that TSEB was able to derive reasonable ET estimates under varying conditions, likely due to the physically based treatment of the energy and the surface temperature partitioning between the soil/cover crop inter-row and vine canopy elements. On the other hand, DATTUTDUT performance was somewhat degraded presumably because the simple scaling scheme does not consider differences in the two sources (vine and inter-row) of heat and temperature contributions or the effect of surface roughness on the efficiency of heat exchange. Maps of the evaporative fraction (EF  =  LE/(H + LE)) from the two models had similar spatial patterns but different magnitudes in some areas within the fields on certain days. Large EF discrepancies between the models were found on 2 of the 5 days (DOY 162 and 219) when there were significant differences with the tower-based ET measurements, particularly using the DATTUTDUT model. These differences in EF between the models translate to significant variations in daily water use estimates for these 2 days for the vineyards. Model sensitivity analysis demonstrated the high degree of sensitivity of the TSEB model to the accuracy of the TR data, while the DATTUTDUT model was insensitive to systematic errors in TR as is the case with contextual-based models. However, it is shown that the study domain and spatial resolution will significantly influence the ET estimation from the DATTUTDUT model. Future work is planned for developing a hybrid approach that leverages the strengths of both modeling schemes and is simple enough to be used operationally with high-resolution imagery.

Short summary
This paper describes a model inter-comparison and validation study conducted using sub-meter resolution thermal data from an aircraft. The model inter-comparison is between a physically based model and a very simple empirical model. The strengths and weaknesses of both modeling approaches for high-resolution mapping of water use in vineyards is described. The findings provide significant insight into the utility of complex versus simple models for precise water resources management.