Global estimation of evapotranspiration using a leaf area index-based surface energy and water balance model

REMOTE SENSING OF ENVIRONMENT

卷:124

Article

Yan, H.¹  Wang, S. Q.²  Billesbach, D.³  Oechel, W.⁴  Zhang, J. H.⁵  Meyers, T.⁶  Martin, T. A.⁷  Matamala, R.⁸  Baldocchi, D.⁹  Bohrer, G.¹⁰  Dragoni, D.¹¹  Scott, R.¹² 

[1] China Meteorol Adm, Natl Meteorol Ctr, Beijing 100081, Peoples R China

[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China

[3] Univ Nebraska, Dept Biol Syst Engn, Lincoln, NE 68583 USA

[4] San Diego State Univ, Dept Biol, San Diego, CA 92182 USA

[5] Chinese Acad Meteorol Sci, Inst Agr Meteorol, Beijing 100081, Peoples R China

[6] NOAA, Atmospher Turbulence & Diffus Div, ARL, Oak Ridge, TN 37831 USA

[7] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 USA

[8] Argonne Natl Lab, Biosci Div, Argonne, IL 60439 USA

[9] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA

[10] Ohio State Univ, Dept Civil Environm & Geodet Engn, Columbus, OH 43210 USA

[11] Indiana Univ, Dept Geog, Bloomington, IN 47405 USA

[12] ARS, USDA, SW Watershed Res Ctr, Tucson, AZ 85719 USA

关键词: Evapotranspiration;    Air relative humidity;    Stomatal conductance;    Canopy transpiration;    Soil evaporation;    Soil water balance model;    Eddy covariance;   

DOI  :  10.1016/j.rse.2012.06.004

来源: Elsevier

【 摘 要 】

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when. global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and environmental constraints on E. It uses remotely sensed leaf area index (L-ai) and surface meteorological data to estimate E by: 1) introducing a simple biophysical model for canopy conductance (G(c)), defined as a constant maximum stomatal conductance g(smax) of 12.2 mm s(-1) multiplied by air relative humidity (R-h) and L-ai (G(c) = g(srnax) x R-h X L-ai); 2) calculating canopy transpiration with the G(c)-based Penman-Monteith (PM) E model; 3) calculating soil evaporation from an air-relative-humidity-based model of evapotranspiration (Yan & Shugart, 2010); 4) calculating total E (E-0) as the sum of the canopy transpiration and soil evaporation, assuming the absence of soil water stress; and 5) correcting E-0 for soil water stress using a soil water balance model. This physiological ARTS E model requires no calibration. Evaluation against eddy covariance measurements at 19 flux sites, representing a wide variety of climate and vegetation types, indicates that daily estimated E had a root mean square error = 0.77 mm d(-1). bias = -0.14 mm d(-1), and coefficient of determination, R-2 = 0.69. Global, monthly, 0.5 degrees-gridded ARTS E simulations from 1984 to 1998, which were forced using Advanced Very High Resolution Radiometer Lai data, Climate Research Unit climate data, and surface radiation budget data, predicted a mean annual land E of 58.4 x 10(3) km(3). This falls within the range (58 x 10(3)-85 x 10(3) km(3)) estimated by the Second Global Soil Wetness Project (GSWP-2: Dirmeyer et al., 2006). The ARTS E spatial pattern agrees well with that of the global E estimated by GSWP-2. The global annual ARTS E increased by 15.5 mm per decade from 1984 to 1998, comparable to an increase of 9.9 mm per decade from the model tree ensemble approach (Jung et al., 2010). These comparisons confirm the effectivity of the ARTS E model to simulate the spatial. pattern and climate response of global E. This model is the first of its kind among remote-sensing-based PM E models to provide global land E estimation with consideration of the soil water balance. (C) 2012 Elsevier Inc. All rights reserved.

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