李璐, 李俊, 同小娟, 杨永民, 于强. 不同冠层阻力公式在玉米田蒸散模拟中的应用[J]. 中国生态农业学报(中英文), 2015, 23(8): 1026-1034. DOI:10.13930/j.cnki.cjea.150094
引用本文: 李璐, 李俊, 同小娟, 杨永民, 于强. 不同冠层阻力公式在玉米田蒸散模拟中的应用[J]. 中国生态农业学报(中英文), 2015, 23(8): 1026-1034.DOI:10.13930/j.cnki.cjea.150094
LI Lu, LI Jun, TONG Xiaojuan, YANG Yongmin, YU Qiang. Application of different canopy resistance models in summer maize evapotranspiration simulation[J]. Chinese Journal of Eco-Agriculture, 2015, 23(8): 1026-1034. DOI:10.13930/j.cnki.cjea.150094
Citation: LI Lu, LI Jun, TONG Xiaojuan, YANG Yongmin, YU Qiang. Application of different canopy resistance models in summer maize evapotranspiration simulation[J].Chinese Journal of Eco-Agriculture, 2015, 23(8): 1026-1034.DOI:10.13930/j.cnki.cjea.150094

不同冠层阻力公式在玉米田蒸散模拟中的应用

Application of different canopy resistance models in summer maize evapotranspiration simulation

  • 摘要:在我国北方地区, 水分供给一直是影响粮食产量的主要因素。玉米作为我国三大粮食作物之一, 关乎其水分蒸散的观测和模拟一直是气象、水文、生态等相关学科的重要研究内容。研究玉米蒸散对于粮食安全、节水灌溉、提高作物水分利用效率具有重要意义。作为经典的双源模型, Shuttleworth-Wallace(SW)模型分别考虑土壤蒸发和植被蒸腾, 非常适合于稀疏植被的蒸散估算。本文在SW模型中采用不同冠层阻力公式对玉米地蒸散进行模拟, 并用涡度相关实测通量数据对模型的模拟效果进行验证。结果表明, 采用Jarvis冠层阻力公式的SW1模型与采用Kelliher-Leuning冠层阻力公式的SW2模型模拟的蒸散量都与实测值吻合较好, 相关系数均在0.85以上( P<0.01), 一致性指数都达到0.92以上。敏感性分析表明, SW模型估算蒸散对冠层阻力最敏感。在计算冠层阻力的各个参数中, SW1模型估算蒸散对田间持水量最敏感, 其次是最小气孔阻力和有效叶面积指数; SW2模型估算蒸散对最大气孔导度最敏感。传统SW模型中, 冠层阻力计算采用Jarvis公式, 计算复杂。改用Kelliher-Leuning公式后, 在一定程度上简化了模型的计算, 更方便模型应用。

    Abstract:In the northern area of China, water supply is a major factor limiting crop yield. Maize is one of three major crops in China. The observation and simulation of evapotranspiration (ET) in maize fields are important processes in meteorology, hydrology, ecology and the other related fields. Thus studies on maize ET are critical for ensuring food security, saving irrigation water and increasing crop water use efficiency. A classical two-layer ET model, the Shuttleworth-Wallace (SW) model is appropriate for estimating ET in sparse vegetation conditions where soil evaporation and vegetation transpiration are significant. In this study, we adopted the Jarvis and Kelliher-Leuning canopy resistance models in relation to SW model to construct SW1 model and SW2 model, respectively. The SW1 and SW2 models were used to simulate ET in a summer maize field in Yucheng Agricultural Experimental Station of Chinese Academy of Sciences. Also experiments were conducted to measure daily ET in summer maize field via eddy covariance system during the main growing period of 20032004. ET simulated by the two models was validated using measured flux data. The results suggested that ET obtained by the two models were consistent with observed data. Correlation coefficients of the measured and simulated ET were above 0.85 ( P< 0.01) and the index of agreement of the measured and simulated data was over 0.92. The ratio of soil evaporation to ET decreased rapidly with increased leaf area index and that ratio for July was higher than those for August and September. At blossom and milk stage, both ET and soil evaporation reached maximum values. During this period, maize leaf growth was vegetative and with the largest canopy transpiration. Then ET and soil evaporation slowly decreased thereafter with gradual reduction in leaf area index, and with the ratio of soil evaporation to ET of 0.2. Sensitivity analysis showed that estimated ET by the SW model was most sensitive to the canopy resistance and the model sensitivity to canopy resistance increased with increasing leaf area index. At early growth stage of maize, the impact of soil surface resistance on ET was not negligible, especially with less vegetation cover. Among the parameters for canopy resistance calculation, estimated ET by SW1 model was most sensitive to change in field capacity. This was followed by minimum stomatal resistance and then effective leaf area index. SW2 model was most sensitive to maximum stomata conductance. Traditional SW model based on Jarvis’s equation for canopy resistance calculation had a complex calculation with several parameters. Then SW2 model based on Kelliher-Leuning equation only had half of SW parameters and therefore considerably simplified the ET model calculation. Compared with SW1 model, SW2 model was much more convenient in terms of application in ET calculation.

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