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Key Points Modeled ecosystem response to climate follows the “geo‐ecological law of distribution,” highlights the importance of ecohdyrologic refugia Woody Plant Encroachment is predicted as a three‐phase phenomenon: early establishment, rapid expansion, and woody plant equilibrium Regime shifts from grassland to shrubland are marked by vegetation cover thresholds 

Steep landscapes evolve largely by debris flows, in addition to fluvial and hillslope processes. Abundant field observations document that debris flows incise valley bottoms and transport substantial sediment volumes, yet their contributions to steepland morphology remain uncertain. This has, in turn, limited the development of debris‐flow incision rate formulations that produce morphology consistent with natural landscapes. In many landscapes, including the San Gabriel Mountains (SGM), California, steady‐state fluvial channel longitudinal profiles are concave‐up and exhibit a power‐law relationship between channel slope and drainage area. At low drainage areas, however, valley slopes become nearly constant. These topographic forms result in a characteristically curved slope‐area signature in log‐log space. Here, we use a one‐dimensional landform evolution model that incorporates debris‐flow erosion to reproduce the relationship between this curved slope‐area signature and erosion rate in the SGM. Topographic analysis indicates that the drainage area at which steepland valleys transition to fluvial channels correlates with measured erosion rates in the SGM, and our model results reproduce these relationships. Further, the model only produces realistic valley profiles when parameters that dictate the relationship between debris‐flow erosion, valley‐bottom slope, and debris‐flow depth are within a narrow range. This result helps place constraints on the mathematical form of a debris‐flow incision law. Finally, modeled fluvial incision outpaces debris‐flow erosion at drainage areas less than those at which valleys morphologically transition from near‐invariant slopes to concave profiles. This result emphasizes the critical role of debris‐flow incision for setting steepland form, even as fluvial incision becomes the dominant incisional process.

 

Abstract. Computational modeling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature – models as both infrastructure and hypotheses – means that modeling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These include a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language-bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed. 

Abstract. Models of landscape evolution provide insight into the geomorphic history of specific field areas, create testable predictions of landform development, demonstrate the consequences of current geomorphic process theory, and spark imagination through hypothetical scenarios. While the last 4 decades have brought the proliferation of many alternative formulations for the redistribution of mass by Earth surface processes, relatively few studies have systematically compared and tested these alternative equations. We present a new Python package, terrainbento 1.0, that enables multi-model comparison, sensitivity analysis, and calibration of Earth surface process models. Terrainbento provides a set of 28 model programs that implement alternative transport laws related to four process elements: hillslope processes, surface-water hydrology, erosion by flowing water, and material properties. The 28 model programs are a systematic subset of the 2048 possible numerical models associated with 11 binary choices. Each binary choice is related to one of these four elements – for example, the use of linear or nonlinear hillslope diffusion. Terrainbento is an extensible framework: base classes that treat the elements common to all numerical models (such as input/output and boundary conditions) make it possible to create a new numerical model without reinventing these common methods. Terrainbento is built on top of the Landlab framework such that new Landlab components directly support the creation of new terrainbento model programs. Terrainbento is fully documented, has 100 % unit test coverage including numerical comparison with analytical solutions for process models, and continuous integration testing. We support future users and developers with introductory Jupyter notebooks and a template for creating new terrainbento model programs. In this paper, we describe the package structure, process theory, and software implementation of terrainbento. Finally, we illustrate the utility of terrainbento with a benchmark example highlighting the differences in steady-state topography between five different numerical models.

 

Abstract. Numerical simulation of the form and characteristics of Earth's surface provides insight into its evolution. Landlab is an open-source Python package that contains modularized elements of numerical models for Earth's surface, thus reducing time required for researchers to create new or reimplement existing models. Landlab contains a gridding engine which represents the model domain as a dual graph of structured quadrilaterals (e.g., raster) or irregular Voronoi polygon–Delaunay triangle mesh (e.g., regular hexagons, radially symmetric meshes, and fully irregular meshes). Landlab also contains components – modular implementations of single physical processes – and a suite of utilities that support numerical methods, input/output, and visualization. This contribution describes package development since version 1.0 and backward-compatibility-breaking changes that necessitate the new major release, version 2.0. Substantial changes include refactoring the grid, improving the component standard interface, dropping Python 2 support, and creating 31 new components – for a total of 58 components in the Landlab package. We describe reasons why many changes were made in order to provide insight for designers of future packages. We conclude by discussing lessons about the dynamics of scientific software development gained from the experience of using, developing, maintaining, and teaching with Landlab. 

The hydrologic dynamics and geomorphic evolution of watersheds are intimately coupled—runoff generation and water storage are controlled by topography and properties of the surface and subsurface, while also affecting the evolution of those properties over geologic time. However, the large disparity between their timescales has made it difficult to examine interdependent controls on emergent hydrogeomorphic properties, such as hillslope length, drainage density, and extent of surface saturation. In this study, we develop a new model coupling hydrology and landscape evolution to explore how runoff generation affects long‐term catchment evolution, and analyze numerical results using a nondimensional scaling framework. We focus on hydrologic processes dominating in humid climates where storm runoff primarily arises from shallow subsurface flow and from precipitation on saturated areas. The model solves hydraulic groundwater equations to predict the water‐table elevation given prescribed, constant groundwater recharge. Water in excess of the subsurface capacity for transport becomes overland flow, which generates shear stress on the surface and may detach and transport sediment. This affects the landscape form that in turn affects runoff generation. We show that (a) four dimensionless parameters describe the possible steady state landscapes that coevolve under steady recharge; (b) hillslope length increases with increasing transmissivity relative to the recharge rate; (c) three topographic metrics—steepness index, Laplacian curvature, and topographic index—together provide a basis for interpreting landscapes that have coevolved with runoff generated via shallow subsurface flow. Finally we discuss the possibilities and limitations for quantitative comparisons between the model results and real landscapes.