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Abstract

Landscape evolution models (LEMs) are prime tools for simulating the evolution of source-to-sink systems through ranges of spatial and temporal scales. A plethora of various empirical laws have been successfully applied to describe the different parts of these systems: fluvial erosion, sediment transport and deposition, hillslope diffusion, or hydrology. Numerical frameworks exist to facilitate the combination of different subsets of laws, mostly by superposing grids of fluxes calculated independently. However, the exercise becomes increasingly challenging when the different laws are inter-connected: for example when a lake breaks the upstream–downstream continuum in the amount of sediment and water it receives and transmits; or when erosional efficiency depends on the lithological composition of the sediment flux. In this contribution, we present a method mixing the advantages of cellular automata and graph theory to address such cases. We demonstrate how the former ensure interoperability of the different fluxes (e.g. water, fluvial sediments, hillslope sediments) independently of the process law implemented in the model, while the latter offers a wide range of tools to process numerical landscapes, including landscapes with closed basins. We provide three scenarios largely benefiting from our method: (i) one where lake systems are primary controls on landscape evolution, (ii) one where sediment provenance is closely monitored through the stratigraphy and (iii) one where heterogeneous provenance influences fluvial incision dynamically. We finally outline the way forward to make this method more generic and flexible.