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Remote sensing of evapotranspiration over cotton using the TSEB and METRIC energy balance models

French, Andrew N., Hunsaker, Douglas J., Thorp, Kelly R.
Remote sensing of environment 2015 v.158 pp. 281-294
algorithms, biophysics, canopy, climate, cotton, data collection, drought, energy balance, evapotranspiration, heat transfer, infrared radiation, irrigated farming, irrigation scheduling, models, plant stress, remote sensing, soil water, surface temperature, surveys, thermal radiation, vegetation index, Arizona
Remote sensing of evapotranspiration (ET) can help detect, map and provide guidance for crop water needs in irrigated lands that cannot be done in other ways. Remote sensing with thermal infrared (TIR) provides the potential to rapidly detect water-related plant stress that would otherwise be missed when using maps of vegetation indices. Two remote sensing ET models based on TIR, TSEB and METRIC, have been widely tested, reported and are strongly influencing remote sensing satellite development and on ways ET data can be used in climate and drought models. However questions continually arise about their relative accuracies, biases, complexity and ease of implementation. This study investigated these questions using airborne data collected at Maricopa, Arizona in 2009 and 2011. The site was a 4.9 ha irrigated cotton study focused on use of remote sensing for irrigation scheduling. TSEB and METRIC models both estimate ET, but do so in very different ways. TSEB is strongly tied to biophysics on the ground, while METRIC links the entire processing chain from satellite to ground. Here, aspects not directly related to turbulent flux estimation on the ground were set aside. Thus models were compared with respect to core algorithms that convert land surface temperatures (LST) into ET. Using image and ground data from seven airborne surveys, net radiation and soil heat fluxes were computed with the more physically based TSEB approach. These fluxes were then used as input layers for both models. Based on soil moisture profile observations at 112 locations, METRIC was found accurate to 2 mm/day in a majority of cases, while TSEB was similarly accurate at a 1.5 mm/day threshold. These accuracies were representative for emergent, full canopy, and late season cotton growth phases. TSEB and METRIC were similarly biased, ~ -0.7 mm/day, an outcome likely indicative of error in net radiation estimation and not to ET estimation. Extrapolation of instantaneous ET estimates to daily time steps was tested with the constant evaporative fraction (EF) approach and with an approach incorporating ground-based LST data; although the ground-based approach has potential to improve ET estimates on cloudy days, this study found the EF approach more consistent. Based on soil moisture depletion observations, ET results from both TSEB and METRIC were physically reasonable, though variability in ET on a plot-by-plot basis was 1/2 of the observed typical variation of +/-5 C. Considering model complexity, input data requirements, and ease of implementation, the recommended model choice for irrigated ET mapping is contingent upon the quality and extent of ancillary meteorological and agronomic observations. This study had rich data sets and hence TSEB is recommended. However, if such data were lacking, METRIC would also be strongly recommended.