The Landlab v1.0 OverlandFlow component: a Python tool for computing shallow-water flow across watersheds

Abstract

Abstract. Representation of flowing water in landscape evolution models (LEMs) is often simplified compared to hydrodynamic models, as LEMs make assumptions reducing physical complexity in favor of computational efficiency. The Landlab modeling framework can be used to bridge the divide between complex runoff models and more traditional LEMs, creating a new type of framework not commonly used in the geomorphology or hydrology communities. Landlab is a Python-language library that includes tools and process components that can be used to create models of Earth-surface dynamics over a range of temporal and spatial scales. The Landlab OverlandFlow component is based on a simplified inertial approximation of the shallow water equations, following the solution of de Almeida et al.(2012). This explicit two-dimensional hydrodynamic algorithm simulates a flood wave across a model domain, where water discharge and flow depth are calculated at all locations within a structured (raster) grid. Here, we illustrate how the OverlandFlow component contained within Landlab can be applied as a simplified event-based runoff model and how to couple the runoff model with an incision model operating on decadal timescales. Examples of flow routing on both real and synthetic landscapes are shown. Hydrographs from a single storm at multiple locations in the Spring Creek watershed, Colorado, USA, are illustrated, along with a map of shear stress applied on the land surface by flowing water. The OverlandFlow component can also be coupled with the Landlab DetachmentLtdErosion component to illustrate how the non-steady flow routing regime impacts incision across a watershed. The hydrograph and incision results are compared to simulations driven by steady-state runoff. Results from the coupled runoff and incision model indicate that runoff dynamics can impact landscape relief and channel concavity, suggesting that, on landscape evolution timescales, the OverlandFlow model may lead to differences in simulated topography in comparison with traditional methods. The exploratory test cases described within demonstrate how the OverlandFlow component can be used in both hydrologic and geomorphic applications.

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.…”

“…Landlab is a plug-and-play environment in which users can easily build two-dimensional numerical models consisting of any number of well-vetted components (e.g., Tucker et al, 2016;Adams et al, 2017) along with user-specific equations and functionality. The greatest advantages of using Landlab are (1) its built-in gridding engine, which creates model grids, efficiently stores spatially distributed variables, and handles boundary conditions, and (2) the ability to easily couple different components into a single model sharing a single grid.…”

Developing and exploring a theory for the lateral erosion of bedrock channels for use in landscape evolution models

“…In some of these models, channel segments are assumed to exist as sub-grid-scale features that are free to switch direction arbitrarily as the topography around them changes. Other LEMs represent water movement as a two-dimensional flow field, whether through multiple-direction routing algorithms (e.g., Coulthard et al, 2002;Pelletier, 2004;Perron et al, 2008) or with a simplified form of the shallow-water equations (Adams et al, 2017;Simpson and Castelltort, 2006). Regardless of the approach to flow routing, LEMs differ from meander models in treating a self-forming, two-dimensional flow network rather than a single channel reach and in explicitly modeling the evolution of topography.…”

Multicore Parallel Tempering Bayeslands for Basin and Landscape Evolution

“…Over the last decades, many numerical models have been proposed to simulate how the Earth surface has evolved over geological timescales in response to different driving forces such as tectonics or climatic variability (Adams et al., ; Campforts et al., ; Salles & Duclaux, ; Tucker & Hancock, ; Whipple & Tucker, ). These models combine empirical data and conceptual methods into a set of mathematical equations that can be used to reconstruct landscape evolution and associated sediment fluxes (Hobley et al., ; Howard et al., ).…”