Publications

Zhang, JH, Hu, YL, Xiao, XM, Chen, PS, Han, SJ, Song, GZ, Yu, GR (2009). Satellite-based estimation of evapotranspiration of an old-growth temperate mixed forest. AGRICULTURAL AND FOREST METEOROLOGY, 149(7-Jun), 976-984.

Abstract
Evapotranspiration (ET) is a key flux in the water cycle and has strong seasonal dynamics for forest ecosystems. Recently eddy flux covariance measurements are continuously taken at a temperate mixed forest in Northeastern China since 2002. In an effort to better understanding the factors that control the seasonal dynamics of ET, here we (1) calculate ecosystem-level water use efficiency (WUE) from observed water and CO2 flux data, and (2) relate the resultant WUE with satellite-derived vegetation indices, and (3) develop and evaluate a simple model that uses satellite images and climate data as input data to predict ET on the coupling of photosynthesis and transpiration processes. Ground WUE estimates obtained from eddy covariance tower were correlated with moderate resolution imaging spectroradiometer (MODIS) vegetation indexes (VIs) and ground micrometeorological data over 3 years (20032005). The enhanced vegetation index (EVI) was more closely correlated (r = 0.82) with WUE than the normalized difference vegetation index (NDVI; r = 0.64). Air temperature (T-A) measured over the canopy was the meteorological variable that was most closely correlated with WUE (r = 0.74) over years. For the significant correlation between EVI and T-A (r = 0.82, P < 0.05). EVI was selected as the single variable to predict WUE to simplify calculation. We calculated ET by ET = GPP/WUE, gross primary production (GPP) was predicted by vegetation photosynthesis model (VPM) that uses satellite images and meteorological variables. At a temporal resolution of 8 days, the annual curves showed good correspondence between measured and predicted values of WUE and ET in terms of phase and magnitude for each year. Seasonally integrated predicted ET was +4% (in 2003), +2% (in 2004), +0.4% (in 2005) higher than observed values. (C) 2008 Elsevier B.V. All rights reserved.

DOI:
10.1016/j.agrformet.2008.12.002

ISSN:
0168-1923