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A convolution method to assess subgrid‐scale interactions between flow and patchy vegetation in biogeomorphic models
Gourgue, O.; van Belzen, J.; Schwarz, C.; Bouma, T.J.; van de Koppel, J.; Temmerman, S. (2021). A convolution method to assess subgrid‐scale interactions between flow and patchy vegetation in biogeomorphic models. J. Adv. Model. Earth Syst. 13(2): e2020MS002116.

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Peer reviewed article  

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  • Bouma, T.J., meer
  • van de Koppel, J., meer
  • Temmerman, S., meer

    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.

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