Although the fidelity of computational-fluid-dynamics (CFD) models for the study of flow in plant canopies has significantly increased over the past decades, the inability to exactly measure the canopy structure and its material and physiological properties introduces a degree of uncertainty in model results that is often difficult to quantify. The present work addresses this problem by proposing a Bayesian uncertainty quantification (UQ) framework for evaluating the impact of uncertain canopy geometry on selected microscale flow statistics (the quantities of interest, QoIs, of the problem). The framework links available in-situ measurements of flow statistics to the uncertainty stemming from foliage spatial distribution and orientation, as well as from the aerodynamic plant response. The uncertainty is first characterized via a Markov chain Monte Carlo procedure, and then propagated to the QoIs through the Monte Carlo sampling method, which returns mean profiles and two-standard-deviation-(2SD-)intervals for the QoIs. The UQ framework relies on a one-dimensional CFD solver to simulate the flow over the Duke Forest, located near Durham, North Carolina, USA. Model results are compared against a standard deterministic solution in terms of mean velocity, Reynolds stress and turbulence-kinetic-energy profiles, as well as canopy aerodynamic parameters. For the considered QoIs, it is found that the 2SD-intervals obtained with the UQ procedure cover \(80\%\) of the experimental intervals, whereas the deterministic solution overlaps with only \(47 \%\) of them. Overall, this study highlights the potential of UQ to advance CFD capabilities for predicting exchange processes between realistic plant canopies and the surrounding atmosphere.

尽管在过去几十年中，用于研究植物冠层流动的计算流体动力学 (CFD) 模型的保真度显着提高，但无法准确测量冠层结构及其材料和生理特性会在模型中引入一定程度的不确定性往往难以量化的结果。目前的工作通过提出贝叶斯不确定性量化 (UQ) 框架来解决这个问题，该框架用于评估不确定冠层几何形状对选定的微尺度流量统计（问题的感兴趣量，QoI）的影响。该框架将可用的流量统计现场测量与来自树叶空间分布和方向以及空气动力学植物响应的不确定性联系起来。不确定性首先通过马尔可夫链蒙特卡洛程序进行表征，然后通过蒙特卡洛采样方法传播到 QoI，该方法返回 QoI 的平均分布和两个标准偏差 (2SD-) 间隔。UQ 框架依靠一维 CFD 求解器来模拟位于美国北卡罗来纳州达勒姆附近的杜克森林上空的流动。模型结果在平均速度、雷诺应力和湍流动能分布以及冠层空气动力学参数方面与标准确定性解决方案进行了比较。对于考虑的 QoI，发现使用 UQ 程序获得的 2SD 间隔覆盖 UQ 框架依靠一维 CFD 求解器来模拟位于美国北卡罗来纳州达勒姆附近的杜克森林上空的流动。模型结果在平均速度、雷诺应力和湍流动能分布以及冠层空气动力学参数方面与标准确定性解决方案进行了比较。对于考虑的 QoI，发现使用 UQ 程序获得的 2SD 间隔覆盖 UQ 框架依靠一维 CFD 求解器来模拟位于美国北卡罗来纳州达勒姆附近的杜克森林上空的流动。模型结果在平均速度、雷诺应力和湍流动能分布以及冠层空气动力学参数方面与标准确定性解决方案进行了比较。对于考虑的 QoI，发现使用 UQ 程序获得的 2SD 间隔覆盖\(80\%\)的实验区间，而确定性解决方案仅与其中的\(47\%\)重叠。总体而言，这项研究强调了 UQ 提高 CFD 能力以预测现实植物冠层与周围大气之间交换过程的潜力。