Landlab: A numerical modeling framework for evolving Earth surfaces from mountains to the coast

Landlab is an open-source, user-friendly, component-based modeling framework for exploring the evolution of Earth's surface. Landlab itself is not a model. Instead, it is a computational framework that facilitates the development of numerical models of coupled earth surface processes. The Landlab Python library includes a gridding engine and process components, along with support functions for tasks such as reading in DEM data and input variables, setting boundary conditions, and plotting and outputting data. Each user of Landlab builds his or her own unique model. The first step in building a Landlab model is generally initializing a grid, either regular (raster) or irregular (e.g. delaunay or radial), and process components. This initialization process involves reading in relevant parameter values and data. The process components act on the grid to alter grid properties over time. For example, a component exists that can track the growth, death, and succession of vegetation over time. There are also several components that evolve surface elevation, through processes such as fluvial sediment transport and linear diffusion, among others. Users can also build their own process components, taking advantage of existing functions in Landlab such as those that identify grid connectivity and calculate gradients and flux divergence. The general nature of the framework makes it applicable to diverse environments - from bedrock rivers to a pile of sand - and processes acting over a range of spatial and temporal scales. In this poster we illustrate how a user builds a model using Landlab and propose a number of ways in which Landlab can be applied in coastal environments - from dune migration to channelization of barrier islands. We seek input from the coastal community as to how the process component library can be expanded to explore the diverse phenomena that act to shape coastal environments.