Interactions between water flow and patchy vegetation are governing the functioning of many ecosystems. Yet, numerical models that simulate those interactions explicitly at the submeter patch scale to predict geomorphological and ecological consequences at the landscape scale (order of km²) are still very computationally demanding. Here, we present a novel and efficient convolution technique to incorporate biogeomorphic feedbacks in numerical models across multiple spatial scales (from less than 1 m² to several km²). This new methodology allows for spatially refining coarse‐resolution hydrodynamic simulations of flow velocities (order of m) around fine‐resolution patchy vegetation patterns (order of 10 cm). Although flow perturbations around each vegetation grid cell are not simulated with the same level of accuracy as with more expensive finer‐resolution models, we show that our approach enables spatial refinement of coarse‐resolution hydrodynamic models by resolving efficiently subgrid‐scale flow velocity patterns within and around vegetation patches (mean error, spatial variability, and spatial correlation improved by, respectively, 13%, 66%, and 49% on average in our test cases). We also provide evidence that our approach can substantially improve the representation of important biogeomorphic processes, such as subgrid‐scale effects on net sedimentation rate and habitable surface area for vegetation (respectively 66% and 39% better on average). Finally, we estimate that replacing a fine‐resolution model by a coarser‐resolution model associated with the convolution method could reduce the computational time of real‐life fluctuating flow simulations by several orders of magnitude. This marks an important step forward toward more computationally efficient multiscale biogeomorphic modeling.

中文翻译：

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一种评估生物地貌模型中流与斑驳植被之间亚网格相互作用的卷积方法

水流与斑驳的植被之间的相互作用决定着许多生态系统的功能。然而，仍然需要非常高的计算量来模拟在亚米级面片尺度上的相互作用，以预测景观尺度（km ²量级）的地貌和生态后果的数值模型。在这里，我们提出了一种新颖有效的卷积技术，可将生物地貌反馈纳入多个空间尺度（从不到1 m ²到几km ^2的数值模型）中）。这种新的方法可以对精细分辨率的斑驳植被模式（10 cm量级）周围的流速（m量级）进行空间细化的粗分辨率水动力模拟。尽管模拟每个植被网格单元周围的流动扰动并没有达到与更昂贵的较细分辨率模型相同的精度水平，但是我们证明了我们的方法通过有效解决分辨率范围内的亚网格尺度流速模式，可以对粗分辨率流体动力学模型进行空间细化。和植被斑块周围（在我们的测试案例中，平均误差，空间变异性和空间相关性分别平均提高了13％，66％和49％）。我们还提供证据表明我们的方法可以大大改善重要生物地貌过程的代表性，例如亚网格规模对植被的净沉降速率和可居住表面积的影响（平均分别提高66％和39％）。最后，我们估计用与卷积方法相关联的粗分辨率模型替换精细分辨率模型可以将实际波动流模拟的计算时间减少几个数量级。这标志着朝着计算效率更高的多尺度生物地貌建模迈出的重要一步。