土壤水分对冬小麦气孔导度及光合速率的影响与模拟*1

为了更精确掌握水分在作物模型中的贡献，通过田间设置5种不同程度的水分控制试验，分别选择冬小麦抽穗期（2011年4月18日）和开花后期（5月5日）两个典型日，利用Li-6400光合作用仪测定冬小麦叶片气孔导度和光合速率的日变化及其光响应过程，并利用SPSS软件进行分析；考虑土壤湿度因子，对气孔导度模型（Jarvis 模型）和光合模型（非直角双曲线模型）进行修订，利用实测资料拟合得到各项参数，并分析其模拟效果。结果表明,气孔导度、光合速率的日变化与土壤水分含量间呈正相关关系，土壤含水量越少，气孔导度、光合速率越小。加入土壤湿度因子的气孔导度和光合作用模型，两个指标均具有更好的模拟效果，实测值与模拟值之间的相关系数由修订前的0.907、0.769分别提高至0.967、0.987，实测值与模型回代值之间的相关系数也由修订前的0.572、0.316分别提高至0.768、0.874，且均方差均显著降低。因此，土壤湿度对调节冬小麦叶片气孔导度和光合作用非常重要，在气孔导度模拟和光合作用模拟中不能忽略土壤湿度的影响。

Simulation on and Impactof Soil Moisture on Stomatal Conductance and Photosynthesis Rate of Winter Wheat

In order to understand accurately the contribution of soil moisture in the crop model, five-moisture level controlled experiment in the field was designed to measure the diurnal variation and light response process of the stomatal conductance and photosynthetic rate of the winter wheat leaf by using Li-6400 photosynthetic apparatus in the heading stage on 4 April 2011, and the late phase of flowering on 5 May 2011. The experiment was divided into 5 degrees, by holding the soil volumetric water content accounted for 45% (T1), 55% (T2), 65% (T3), 70% (T4), 80% (T5) of the maximum field capacity. Three replicates for each treatment. Each parameter was calculated based on the observed data by the Jarvis model and the non-rectangular hyperbolic model which were improved by considering the soil moisture factor. The results showed that there was a significant positive correlation between the diurnal variation of the stomatal conductance and photosynthetic rate and the soil moisture. The less the water content of the soil was, the little stomatal conductance and photosynthetic rate would be. The simulated effect of these two revised models by considering the soil moisture was satisfactory compared with the measured values. The correlation coefficients of the measured values and simulated values were 0.907 and 0.769 before the revision. However, their coefficients increased to 0.967 and 0.987 after the revision. In addition, the correlation coefficients of the measured values and the model returned values from 0.572 and 0.316 before the revision to 0.768 and 0.874 after the revision. The mean square error decreased significantly. Therefore, the soil moisture was a very important factor to adjust the stomatal conductance and photosynthetic rate. The impact of the soil moisture could not be ignored in the simulation of the stomatal conductance and photosynthetic rate.