Simulating evapotranspiration and photosynthesis of winter wheat over the growing season

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• 作者：Mo ; Xingguo ; Liu ; Suxia
• 关键词：Simulation ; Model ; Winter wheat ; Evapotranspiration ; Photosynthesis
• 刊名：Agricultural and Forest Meteorology
• 出版年：2001
• 出版时间：September 3, 2001
• 年：2001
• 卷：109
• 期：3
• 页码：203-222
• 全文大小：346 K

文摘

A soil–vegetation–atmosphere process model is established to simulate water, energy and CO₂ fluxes. The model includes: (1) an improved multi-layer canopy radiative transfer submodel; (2) a new canopy conductance/photosynthesis submodel that distinguishes sunlit and shaded leaves; (3) a two-source soil–canopy energy balance submodel; (4) a multi-layer soil water and heat transfer submodel. The model is validated using two groups of data collected in a winter wheat field transitioning from recovering green through to maturity (in 1992) and from overwintering to maturity (in 1998) at Yucheng Experimental Station, Chinese Academy of Sciences in North China Plain. Satisfactory agreement is obtained between simulated and measured energy partitioning, surface temperature, root zone soil moisture, and canopy photosynthesis. Model-derived rates of daily crop transpiration and soil evaporation are in agreement with field measurements obtained via lysimeter and the Bowen ratio method. Sensitivity results show that the Leuning model of stomatal conductance/photosynthesis gives better evapotranspiration estimates than the Jarvis and Ball–Berry models. There are significant differences between the photosynthesis rates produced from our model and the corresponding rates calculated by the traditional “big leaf” model, which does not differentiate sunlit and shaded effects. However, both models generate fairly similar evapotranspiration rates. The successful simulation in 1998 was achieved using meteorological station data alone as driving force of the model instead of using micrometeorological data as in 1992 case, suggesting that the new model could have general applicability without the need for detailed micrometeorological data.