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首页> 外文期刊>Journal of hydrometeorology >Modeling the response of canopy stomatal conductance to humidity
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Modeling the response of canopy stomatal conductance to humidity

机译:模拟冠层气孔导度对湿度的响应

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摘要

Humidity of air is a key environmental variable in controlling the stomatal conductance (g) of plant leaves. The stomatal conductance-humidity relationships employed in the Ball-Woodrow-Berry (BWB) model and the Leuning model have been widely used in the last decade. Results of independent evaluations of the two models vary greatly. In this study, the authors develop a new diagnostic parameter that is based on canopy water vapor and CO2 fluxes to assess the response of canopy g to humidity. Using eddy-covariance flux measurements at three boreal forest sites in Canada, they critically examine the performance of the BWB and the Leuning models. The results show that the BWB model, which employs a linear relationship between g and relative humidity (hs ), leads to large underestimates of g when the air is wet. The Leuning model, which employs a nonlinear function of water vapor pressure deficit (Ds ), reduced this bias, but it still could not adequately capture the significant increase of g under the wet conditions. New models are proposed to improve the prediction of canopy g to humidity. The best performance was obtained by the model that employs a power function of Ds , followed by the model that employs a power function of relative humidity deficit (1 - hs ). The results also indicate that models based on water vapor pressure deficit generally performed better than those based on relative humidity. This is consistent with the hypothesis that the stomatal aperture responds to leaf water loss because water vapor pressure deficit rather than relative humidity directly affects the transpiration rate of canopy leaves.
机译:空气湿度是控制植物叶片气孔导度(g)的关键环境变量。在Ball-Woodrow-Berry(BWB)模型和Leuning模型中采用的气孔电导-湿度关系在过去十年中得到了广泛应用。两种模型的独立评估结果差异很大。在这项研究中,作者开发了一种基于冠层水蒸气和CO2通量的新诊断参数,以评估冠层g对湿度的响应。他们使用加拿大三个寒带林场的涡度-协方差通量测量,严格审查了BWB和Leuning模型的性能。结果表明,BWB模型采用g与相对湿度(hs)之间的线性关系,导致当空气潮湿时g的低估很大。 Leuning模型采用了水蒸气压力亏缺(Ds)的非线性函数,虽然减小了这种偏差,但是在潮湿条件下仍无法充分捕捉到g的显着增加。提出了新的模型来改善对湿度的冠层g的预测。使用Ds的幂函数的模型获得最佳性能,然后使用相对湿度不足(1-hs)的幂函数的模型获得最佳性能。结果还表明,基于水蒸气压亏空的模型通常比基于相对湿度的模型表现更好。这与以下假设相符:气孔孔径对叶片失水有反应,因为水蒸气压力不足而不是相对湿度直接影响冠层叶片的蒸腾速率。

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