首页> 外文期刊>Acta Geotechnica: An International journal for Geoengineering >Assessment of the coupled effects of vegetation leaf and root characteristics on soil suction: an integrated numerical modeling and probabilistic approach
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Assessment of the coupled effects of vegetation leaf and root characteristics on soil suction: an integrated numerical modeling and probabilistic approach

机译:评估植被叶片的耦合效应和根本特征对土壤吸力的评价:综合数值模拟与概率方法

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摘要

Root depth and leaf area ratio are two important features of a plant and exhibit a coupled relation. Assessing their coupled effects on induced soil suction is essential for analyzing the performance of a green infrastructure, such as water storage/drainage in green roofs and stability of a vegetated slope. Previously soil moisture induced by vegetation was often presented deterministically without considering the overall effects of leaf and root characteristics in a probabilistic manner. The main objective of this study is to investigate the influence of coupled variations in root and leaf characteristics on vegetation-induced soil suction. In addition, the coupled effects were analyzed using statistical approach. Different combinations of the leaf area index and root depth of the same plant were assessed. Probabilistic analysis was then conducted by computing suction profiles in form of quantiles. It was found that the biggest variability in suction profiles occurs at around 0.6 times the root depth and the minimum occurred at near surface and at maximum root depth. This depth at 0.6 times root depth corresponds to the maximum root density. It implies that the probabilistic analysis becomes more and more important while assessing suction profiles near the maximum root density.
机译:根深和叶面积比是植物的两个重要特征,并且具有耦合关系。评估其对诱导土壤吸力的耦合效果对于分析绿色基础设施的性能,例如绿色屋顶的储水/排水以及植被坡度的稳定性是必不可少的。以前的植被诱导的土壤水分通常在不考虑叶片和根特征以概率的方式的整体影响。本研究的主要目的是研究植被诱导的土壤吸力的根和叶特征耦合变化的影响。此外,使用统计方法分析耦合效果。评估叶面积指数和同一植物的根深的不同组合。然后通过以量子的形式计算抽吸分布进行概率分析。发现抽吸剖面的最大可变性发生在根深度约为0.6倍,最小在近表面和最大根深。该深度为0.6倍的根深度,对应于最大根密度。它意味着概率分析变得越来越重要,同时评估最大根密度附近的吸力曲线。

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