A Convolution Method to Assess Subgrid‐Scale Interactions Between Flow and Patchy Vegetation in Biogeomorphic Models.

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. Plain Language Summary: The functioning of many ecosystems, such as rivers, wetlands, and shallow seas, is governed by the interactions between water flow and small patches of vegetation. Powerful tools to investigate the formation and evolution of these ecosystems are computer programs that split the study area into different grid cells on which fundamental equations of water movement are solved. However, these programs (so‐called numerical models) necessitate a lot of computational power, as they require fine grid resolutions (a lot of small grid cells) to account for small patches of vegetation. In this paper, we present a new approach where the fundamental equations are solved at relatively coarse resolution (few large grid cells of tens of square meters). The water flow patterns are then recalculated at finer resolution (smaller grid cells of less than 1 m2) with a novel technique that requires only little computational power (so‐called convolution method). By comparing with laboratory measurements and the results from a numerical model at much finer resolution (grid cells of a few square centimeters), we provide evidence that this approach is a good compromise between accuracy and computational time, hence allowing to study the formation and evolution of large ecosystems with more extensive details. Key Points: Fine‐scale flow‐vegetation interactions can considerably impact large‐scale biogeomorphic feedbacksCurrent large‐scale biogeomorphic models are too coarse to include these fine‐scale interactionsOur computationally efficient method allows large‐scale models to account for fine‐scale interactions [ABSTRACT FROM AUTHOR]