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Volume 22, issue 4 | Copyright
Hydrol. Earth Syst. Sci., 22, 2311-2341, 2018
https://doi.org/10.5194/hess-22-2311-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 18 Apr 2018

Research article | 18 Apr 2018

Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

Nishan Bhattarai1, Kaniska Mallick2, Nathaniel A. Brunsell3, Ge Sun4, and Meha Jain1 Nishan Bhattarai et al.
  • 1School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, USA
  • 2Remote Sensing and Ecohydrological Modeling, Water Security and Safety Research Unit, Dept. ERIN, Luxembourg Institute of Science and Technology (LIST), 4422 Belvaux, Luxembourg
  • 3Geography and Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA
  • 4Eastern Forest Environmental Threat Assessment Center, Southern Research Station, US Department of Agriculture Forest Service, Raleigh, NC 27606, USA

Abstract. Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (gA and T0) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1km × 1km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66% of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4mm/8-day, mean absolute error (MAE) of 5mm/8-day, and percent bias (PBIAS) of −4%. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (zOM), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28%) and MOD16 was found to underestimate ET (PBIAS = −26%). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20% underestimation) and woody savanna (40% overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with gA and associated roughness length estimation uncertainties which are intrinsically connected to TR uncertainties, vapor pressure deficit (DA), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

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We report the first ever regional-scale implementation of the Surface Temperature Initiated Closure (STIC1.2) model for mapping evapotranspiration (ET) using MODIS land surface and gridded climate datasets to overcome the existing uncertainties in aerodynamic temperature and conductance estimation in global ET models. Validation and intercomparison with SEBS and MOD16 products across an aridity gradient in the US manifested better ET mapping potential of STIC1.2 in different climates and biomes.
We report the first ever regional-scale implementation of the Surface Temperature Initiated...
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