气候变化领域集成服务门户(CCPortal): 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

CCPortal

DOI	10.5194/hess-22-2311-2018
	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
	Bhattarai N.; Mallick K.; Brunsell N.A.; Sun G.; Jain M.
发表日期	2018
ISSN	1027-5606
起始页码	2311
结束页码	2341
卷号	22 期号:4
英文摘要	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 1 km × 1 km 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 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/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. © Author(s) 2018.
语种	英语
scopus关键词	Atmospheric structure; Atmospheric temperature; Bond (masonry); Ecosystems; Energy balance; Error statistics; Errors; Evapotranspiration; Interfacial energy; Mapping; Mean square error; Radiometers; Remote sensing; Satellite imagery; Surface properties; Surface roughness; Aerodynamic conductances; Model inter comparisons; Moderate resolution imaging spectroradiometer; North american land data assimilation systems; Penman-Monteith equations; Radiometric surface temperatures; Regional evapotranspiration; Surface energy balance systems; Analytical models; agricultural land; biome; evapotranspiration; forest ecosystem; grassland; image analysis; land surface; model validation; MODIS; numerical model; precipitation (climatology); remote sensing; savanna; spatial resolution; surface energy; surface roughness; surface temperature; vapor pressure; vegetation cover; United States
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160055
作者单位	Bhattarai, N., School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, United States; Mallick, K., Remote Sensing and Ecohydrological Modeling, Water Security and Safety Research Unit, Dept. ERIN, Luxembourg Institute of Science and Technology (LIST), Belvaux, 4422, Luxembourg; Brunsell, N.A., Geography and Atmospheric Science, University of Kansas, Lawrence, KS 66045, United States; Sun, G., Eastern Forest Environmental Threat Assessment Center, Southern Research Station, US Department of Agriculture Forest Service, Raleigh, NC 27606, United States; Jain, M., School for Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109, United States
推荐引用方式 GB/T 7714	Bhattarai N.,Mallick K.,Brunsell N.A.,et al. 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[J],2018,22(4).
APA	Bhattarai N.,Mallick K.,Brunsell N.A.,Sun G.,&Jain M..(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.Hydrology and Earth System Sciences,22(4).
MLA	Bhattarai N.,et al."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".Hydrology and Earth System Sciences 22.4(2018).