Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics

Abstract

Abstract. The ability to model surface processes and to couple them to both subsurface and atmospheric regimes has proven invaluable to research in the Earth and planetary sciences. However, creating a new model typically demands a very large investment of time, and modifying an existing model to address a new problem typically means the new work is constrained to its detriment by model adaptations for a different problem.Landlab is an open-source software framework explicitly designed to accelerate the development of new process models by providing (1) a set of tools and existing grid structures -including both regular and irregular gridsto make it faster and easier to develop new process components, or numerical implementations of physical processes; (2) a suite of stable, modular, and interoperable process components that can be combined to create an integrated model; and (3) a set of tools for data input, output, manipulation, and visualization. A set of example models built with these components is also provided. Landlab's structure makes it ideal not only for fully developed modelling applications but also for model prototyping and classroom use. Because of its modular nature, it can also act as a platform for model intercomparison and epistemic uncertainty and sensitivity analyses. Landlab exposes a standardized model interoperability interface, and is able to couple to third-party models and software. Landlab also offers tools to allow the creation of cellular automata, and allows native coupling of such models to more traditional continuous differential equation-based modules. We illustrate the principles of component coupling in Landlab using a model of landform evolution, a cellular ecohydrologic model, and a flood-wave routing model.

Landscape evolution models using the stream power incision model show unrealistic behavior when <i>m</i> ∕ <i>n</i> equals 0.5

“…This range is consistent with results inferred from field work and map studies (Flint, 1974;Howard and Kerby, 1983;Tarboton et al, 1989Tarboton et al, , 1991Willgoose et al, 1990;Willgoose, 1994;Moglen and Bras, 1995;Snyder et al, 2000). Furthermore, many researchers specifically suggest, or offer as a default, the ratio m/n ∼ 0.5 (Snyder et al, 2000;Banavar et al, 2001;Hobley et al, 2017). The choice of this ratio is paramount in numerical landscape evolution models (LEMs) that utilize SPIM, such as the channel-hillslope integrated landscape development model, CHILD (Tucker et al, 2001).…”

“…Our result calls into question the common usage of the ratio m/n = 0.5 in landscape evolution models (Gasparini et al, 2006). For example, the Python-based landscape modeling environment, Landlab (Hobley et al, 2017) offers a default m/n ratio of 0.5. Our result also motivates further investigation as to why analysis of field data commonly yields values of m/n ∼ 0.5 (e.g., Snyder et al, 2000).…”

The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution

“…An array of sediment depths at all grid nodes could be found by typing grid.at_node ["soil__depth"]. The treatment of boundary conditions in Landlab grids is described thoroughly by Hobley et al (2017) and Adams et al (2017). In short, nodes may be set as "boundary" nodes and then defined as open, fixed-gradient, or closed boundaries.…”

A hydroclimatological approach to predicting regional landslide probability using Landlab

“…It provides a grid architecture, a suite of pre-built components for modeling surface or nearsurface processes, and utilities that handle data creation, management, and interoperability among process components (Tucker et al, 2016;Hobley et al, 2017;. The LandslideProbability component is written in Python and implemented with a model driver (written as a Jupyter Notebook) using the workflow shown in Fig.…”