Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4577-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-10-4577-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| Highlight paper
| 
18 Dec 2017
Model description paper | Highlight paper |
| 18 Dec 2017
| 18 Dec 2017
The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution
Charles M. Shobe
CORRESPONDING AUTHOR
CIRES and Department of Geological Sciences, University of Colorado, Boulder, Colorado, USA
Gregory E. Tucker
CIRES and Department of Geological Sciences, University of Colorado, Boulder, Colorado, USA
Katherine R. Barnhart
CIRES and Department of Geological Sciences, University of Colorado, Boulder, Colorado, USA
Related authors
Benjamin Campforts, Charles M. Shobe, Philippe Steer, Matthias Vanmaercke, Dimitri Lague, and Jean Braun
Geosci. Model Dev., 13, 3863–3886, https://doi.org/10.5194/gmd-13-3863-2020, https://doi.org/10.5194/gmd-13-3863-2020, 2020
Short summary
Short summary
Landslides shape the Earth’s surface and are a dominant source of terrestrial sediment. Rivers, then, act as conveyor belts evacuating landslide-produced sediment. Understanding the interaction among rivers and landslides is important to predict the Earth’s surface response to past and future environmental changes and for mitigating natural hazards. We develop HyLands, a new numerical model that provides a toolbox to explore how landslides and rivers interact over several timescales.
Katherine R. Barnhart, Rachel C. Glade, Charles M. Shobe, and Gregory E. Tucker
Geosci. Model Dev., 12, 1267–1297, https://doi.org/10.5194/gmd-12-1267-2019, https://doi.org/10.5194/gmd-12-1267-2019, 2019
Short summary
Short summary
Terrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution.
Nicole M. Gasparini, Adam M. Forte, and Katherine R. Barnhart
Earth Surf. Dynam., 12, 1227–1242, https://doi.org/10.5194/esurf-12-1227-2024, https://doi.org/10.5194/esurf-12-1227-2024, 2024
Short summary
Short summary
The time it takes for a landscape to adjust to new environmental conditions is critical for understanding the impacts of past and future environmental changes. We used different computational models and methods and found that predicted times for a landscape to reach a stable condition vary greatly. Our results illustrate that reporting how timescales are measured is important. Modelers should ensure that the measurement technique addresses the question.
Jeffrey Keck, Erkan Istanbulluoglu, Benjamin Campforts, Gregory Tucker, and Alexander Horner-Devine
Earth Surf. Dynam., 12, 1165–1191, https://doi.org/10.5194/esurf-12-1165-2024, https://doi.org/10.5194/esurf-12-1165-2024, 2024
Short summary
Short summary
MassWastingRunout (MWR) is a new landslide runout model designed for sediment transport, landscape evolution, and hazard assessment applications. MWR is written in Python and includes a calibration utility that automatically determines best-fit parameters for a site and empirical probability density functions of each parameter for probabilistic model implementation. MWR and Jupyter Notebook tutorials are available as part of the Landlab package at https://github.com/landlab/landlab.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
Nat. Hazards Earth Syst. Sci., 24, 2359–2374, https://doi.org/10.5194/nhess-24-2359-2024, https://doi.org/10.5194/nhess-24-2359-2024, 2024
Short summary
Short summary
Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 h) needed for decision-making. This work takes an initial step toward a near-real-time postfire debris-flow inundation hazard assessment product.
Francis K. Rengers, Samuel Bower, Andrew Knapp, Jason W. Kean, Danielle W. vonLembke, Matthew A. Thomas, Jaime Kostelnik, Katherine R. Barnhart, Matthew Bethel, Joseph E. Gartner, Madeline Hille, Dennis M. Staley, Justin K. Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
Nat. Hazards Earth Syst. Sci., 24, 2093–2114, https://doi.org/10.5194/nhess-24-2093-2024, https://doi.org/10.5194/nhess-24-2093-2024, 2024
Short summary
Short summary
Every year the U.S. Geological Survey produces 50–100 postfire debris-flow hazard assessments using models for debris-flow likelihood and volume. To refine these models they must be tested with datasets that clearly document rainfall, debris-flow response, and debris-flow volume. These datasets are difficult to obtain, but this study developed and analyzed a postfire dataset with more than 100 postfire storm responses over a 2-year period. We also proposed ways to improve these models.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 24, 1459–1483, https://doi.org/10.5194/nhess-24-1459-2024, https://doi.org/10.5194/nhess-24-1459-2024, 2024
Short summary
Short summary
Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Luke A. McGuire, Scott W. McCoy, Odin Marc, William Struble, and Katherine R. Barnhart
Earth Surf. Dynam., 11, 1117–1143, https://doi.org/10.5194/esurf-11-1117-2023, https://doi.org/10.5194/esurf-11-1117-2023, 2023
Short summary
Short summary
Debris flows are mixtures of mud and rocks that can travel at high speeds across steep landscapes. Here, we propose a new model to describe how landscapes are shaped by debris flow erosion over long timescales. Model results demonstrate that the shapes of channel profiles are sensitive to uplift rate, meaning that it may be possible to use topographic data from steep channel networks to infer how erosion rates vary across a landscape.
Francis K. Rengers, Luke A. McGuire, Katherine R. Barnhart, Ann M. Youberg, Daniel Cadol, Alexander N. Gorr, Olivia J. Hoch, Rebecca Beers, and Jason W. Kean
Nat. Hazards Earth Syst. Sci., 23, 2075–2088, https://doi.org/10.5194/nhess-23-2075-2023, https://doi.org/10.5194/nhess-23-2075-2023, 2023
Short summary
Short summary
Debris flows often occur after wildfires. These debris flows move water, sediment, and wood. The wood can get stuck in channels, creating a dam that holds boulders, cobbles, sand, and muddy material. We investigated how the channel width and wood length influenced how much sediment is stored. We also used a series of equations to back calculate the debris flow speed using the breaking threshold of wood. These data will help improve models and provide insight into future field investigations.
Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Benjamin Campforts, Tian Gan, Katherine R. Barnhart, Albert J. Kettner, Irina Overeem, Scott D. Peckham, Lynn McCready, and Jaia Syvitski
Geosci. Model Dev., 15, 1413–1439, https://doi.org/10.5194/gmd-15-1413-2022, https://doi.org/10.5194/gmd-15-1413-2022, 2022
Short summary
Short summary
Scientists use computer simulation models to understand how Earth surface processes work, including floods, landslides, soil erosion, river channel migration, ocean sedimentation, and coastal change. Research benefits when the software for simulation modeling is open, shared, and coordinated. The Community Surface Dynamics Modeling System (CSDMS) is a US-based facility that supports research by providing community support, computing tools and guidelines, and educational resources.
Kelly Kochanski, Gregory Tucker, and Robert Anderson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-205, https://doi.org/10.5194/tc-2021-205, 2021
Manuscript not accepted for further review
Short summary
Short summary
Falling snow does not life flat. When blown by the wind, it forms elaborate structures, like dunes. Where these dunes form, they change the way heat flows through the snow. This can accelerate sea ice melt and climate change. Here, we use both field observations obtained during blizzards in Colorado and simulations performed with a state-of-the-art model, to quantify the impact of snow dunes on Arctic heat flows.
Benjamin Campforts, Charles M. Shobe, Philippe Steer, Matthias Vanmaercke, Dimitri Lague, and Jean Braun
Geosci. Model Dev., 13, 3863–3886, https://doi.org/10.5194/gmd-13-3863-2020, https://doi.org/10.5194/gmd-13-3863-2020, 2020
Short summary
Short summary
Landslides shape the Earth’s surface and are a dominant source of terrestrial sediment. Rivers, then, act as conveyor belts evacuating landslide-produced sediment. Understanding the interaction among rivers and landslides is important to predict the Earth’s surface response to past and future environmental changes and for mitigating natural hazards. We develop HyLands, a new numerical model that provides a toolbox to explore how landslides and rivers interact over several timescales.
Katherine R. Barnhart, Eric W. H. Hutton, Gregory E. Tucker, Nicole M. Gasparini, Erkan Istanbulluoglu, Daniel E. J. Hobley, Nathan J. Lyons, Margaux Mouchene, Sai Siddhartha Nudurupati, Jordan M. Adams, and Christina Bandaragoda
Earth Surf. Dynam., 8, 379–397, https://doi.org/10.5194/esurf-8-379-2020, https://doi.org/10.5194/esurf-8-379-2020, 2020
Short summary
Short summary
Landlab is a Python package to support the creation of numerical models in Earth surface dynamics. Since the release of the 1.0 version in 2017, Landlab has grown and evolved: it contains 31 new process components, a refactored model grid, and additional utilities. This contribution describes the new elements of Landlab, discusses why certain backward-compatiblity-breaking changes were made, and reflects on the process of community open-source software development.
Alison R. Duvall, Sarah A. Harbert, Phaedra Upton, Gregory E. Tucker, Rebecca M. Flowers, and Camille Collett
Earth Surf. Dynam., 8, 177–194, https://doi.org/10.5194/esurf-8-177-2020, https://doi.org/10.5194/esurf-8-177-2020, 2020
Short summary
Short summary
In this study, we examine river patterns and the evolution of the landscape within the Marlborough Fault System, South Island, New Zealand, where the Australian and Pacific tectonic plates collide. We find that faulting, uplift, river capture and the long-lived nature of the drainage network all dictate river patterns at this site. Based on these results and a wealth of previous geologic studies, we propose two broad stages of landscape evolution over the last 25 million years of orogenesis.
Kelly Kochanski, Robert S. Anderson, and Gregory E. Tucker
The Cryosphere, 13, 1267–1281, https://doi.org/10.5194/tc-13-1267-2019, https://doi.org/10.5194/tc-13-1267-2019, 2019
Short summary
Short summary
Wind-blown snow does not lie flat. It forms dunes, ripples, and anvil-shaped sastrugi. These features ornament much of the snow on Earth and change the snow's effects on polar climates, but they have rarely been studied. We spent three winters watching snow move through the Colorado Front Range and present our findings here, including the first time-lapse videos of snow dune and sastrugi growth.
Katherine R. Barnhart, Rachel C. Glade, Charles M. Shobe, and Gregory E. Tucker
Geosci. Model Dev., 12, 1267–1297, https://doi.org/10.5194/gmd-12-1267-2019, https://doi.org/10.5194/gmd-12-1267-2019, 2019
Short summary
Short summary
Terrainbento 1.0 is a Python package for modeling the evolution of the surface of the Earth over geologic time (e.g., thousands to millions of years). Despite many decades of effort by the geomorphology community, there is no one established governing equation for the evolution of topography. Terrainbento 1.0 thus provides 28 alternative models that support hypothesis testing and multi-model analysis in landscape evolution.
Gregory E. Tucker, Scott W. McCoy, and Daniel E. J. Hobley
Earth Surf. Dynam., 6, 563–582, https://doi.org/10.5194/esurf-6-563-2018, https://doi.org/10.5194/esurf-6-563-2018, 2018
Short summary
Short summary
This article presents a new technique for computer simulation of slope forms. The method provides a way to study how events that disturb soil or turn rock into soil add up over time to produce landforms. The model represents a cross section of a hypothetical landform as a lattice of cells, each of which may represent air, soil, or rock. Despite its simplicity, the model does a good job of simulating a range of common of natural slope forms.
Ronda Strauch, Erkan Istanbulluoglu, Sai Siddhartha Nudurupati, Christina Bandaragoda, Nicole M. Gasparini, and Gregory E. Tucker
Earth Surf. Dynam., 6, 49–75, https://doi.org/10.5194/esurf-6-49-2018, https://doi.org/10.5194/esurf-6-49-2018, 2018
Short summary
Short summary
We develop a model of annual probability of shallow landslide initiation triggered by soil water from a hydrologic model. Our physically based model accommodates data uncertainty using a Monte Carlo approach. We found elevation-dependent patterns in probability related to the stabilizing effect of forests and soil and slope limitation at high elevations. We demonstrate our model in Washington, USA, but it is designed to run elsewhere with available data for risk planning using the Landlab.
Abigail L. Langston and Gregory E. Tucker
Earth Surf. Dynam., 6, 1–27, https://doi.org/10.5194/esurf-6-1-2018, https://doi.org/10.5194/esurf-6-1-2018, 2018
Short summary
Short summary
While vertical incision in bedrock rivers is widely implemented in landscape evolution models, lateral erosion is largely ignored. This makes current models unfit to explain the formation of wide bedrock valleys and strath terraces. In this study we present a fundamental advance in the representation of lateral erosion of bedrock rivers in a landscape evolution model. The model results show a scaling relationship between valley width and drainage area similar to that found in natural systems.
Jordan M. Adams, Nicole M. Gasparini, Daniel E. J. Hobley, Gregory E. Tucker, Eric W. H. Hutton, Sai S. Nudurupati, and Erkan Istanbulluoglu
Geosci. Model Dev., 10, 1645–1663, https://doi.org/10.5194/gmd-10-1645-2017, https://doi.org/10.5194/gmd-10-1645-2017, 2017
Short summary
Short summary
OverlandFlow is a 2-dimensional hydrology component contained within the Landlab modeling framework. It can be applied in both hydrology and geomorphology applications across real and synthetic landscape grids, for both short- and long-term events. This paper finds that this non-steady hydrology regime produces different landscape characteristics when compared to more traditional steady-state hydrology and geomorphology models, suggesting that hydrology regime can impact resulting morphologies.
Daniel E. J. Hobley, Jordan M. Adams, Sai Siddhartha Nudurupati, Eric W. H. Hutton, Nicole M. Gasparini, Erkan Istanbulluoglu, and Gregory E. Tucker
Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, https://doi.org/10.5194/esurf-5-21-2017, 2017
Short summary
Short summary
Many geoscientists use computer models to understand changes in the Earth's system. However, typically each scientist will build their own model from scratch. This paper describes Landlab, a new piece of open-source software designed to simplify creation and use of models of the Earth's surface. It provides off-the-shelf tools to work with models more efficiently, with less duplication of effort. The paper explains and justifies how Landlab works, and describes some models built with it.
Gregory E. Tucker, Daniel E. J. Hobley, Eric Hutton, Nicole M. Gasparini, Erkan Istanbulluoglu, Jordan M. Adams, and Sai Siddartha Nudurupati
Geosci. Model Dev., 9, 823–839, https://doi.org/10.5194/gmd-9-823-2016, https://doi.org/10.5194/gmd-9-823-2016, 2016
Short summary
Short summary
This paper presents a new Python-language software library, called CellLab-CTS, that enables rapid creation of continuous-time stochastic (CTS) cellular automata models. These models are quite useful for simulating the behavior of natural systems, but can be time-consuming to program. CellLab-CTS allows users to set up models with a minimum of effort, and thereby focus on the science rather than the software.
K. R. Barnhart, I. Overeem, and R. S. Anderson
The Cryosphere, 8, 1777–1799, https://doi.org/10.5194/tc-8-1777-2014, https://doi.org/10.5194/tc-8-1777-2014, 2014
Related subject area
Solid Earth
Reconciling surface deflections from simulations of global mantle convection
Three-dimensional analytical solution of self-potential from regularly polarized bodies in a layered seafloor model
A fast surrogate model for 3D Earth glacial isostatic adjustment using Tensorflow (v2.8.0) artificial neural networks
CitcomSVE 3.0: A Three-dimensional Finite Element Software Package for Modeling Load-induced Deformation for an Earth with Viscoelastic and Compressible Mantle
Accelerated pseudo-transient method for elastic, viscoelastic, and coupled hydro-mechanical problems with applications
A new global marine gravity model NSOAS24 derived from multi-satellite sea surface slopes
Empirical Modeling of Tropospheric Delays and Uncertainty
ShellSet v1.1.0 parallel dynamic neotectonic modelling: a case study using Earth5-049
FastIsostasy v1.0 – a regional, accelerated 2D glacial isostatic adjustment (GIA) model accounting for the lateral variability of the solid Earth
Automatic adjoint-based inversion schemes for geodynamics: reconstructing the evolution of Earth's mantle in space and time
GEOMAPLEARN 1.0: Detecting geological structures from geological maps with machine learning
Benchmarking the accuracy of higher-order particle methods in geodynamic models of transient flow
REHEATFUNQ (REgional HEAT-Flow Uncertainty and aNomaly Quantification) 2.0.1: a model for regional aggregate heat flow distributions and anomaly quantification
A new temperature–photoperiod coupled phenology module in LPJ-GUESS model v4.1: optimizing estimation of terrestrial carbon and water processes
High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies
Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1)
Modelling detrital cosmogenic nuclide concentrations during landscape evolution in Cidre v2.0
IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water
Simulation of a fully coupled 3D glacial isostatic adjustment – ice sheet model for the Antarctic ice sheet over a glacial cycle
AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling
PySubdiv 1.0: open-source geological modeling and reconstruction by non-manifold subdivision surfaces
Reconstructing tephra fall deposits via ensemble-based data assimilation techniques
ClinoformNet-1.0: stratigraphic forward modeling and deep learning for seismic clinoform delineation
Addressing challenges in uncertainty quantification: the case of geohazard assessments
DeepISMNet: three-dimensional implicit structural modeling with convolutional neural network
Towards automatic finite-element methods for geodynamics via Firedrake
MagmaFOAM-1.0: a modular framework for the simulation of magmatic systems
A global, spherical finite-element model for post-seismic deformation using Abaqus
SMAUG v1.0 – a user-friendly muon simulator for the imaging of geological objects in 3-D
CliffDelineaTool v1.2.0: an algorithm for identifying coastal cliff base and top positions
Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm
Structural, petrophysical, and geological constraints in potential field inversion using the Tomofast-x v1.0 open-source code
Spatial agents for geological surface modelling
RHEA v1.0: Enabling fully coupled simulations with hydro-geomechanical heterogeneity
Modelling of faults in LoopStructural 1.0
PALEOSTRIPv1.0 – a user-friendly 3D backtracking software to reconstruct paleo-bathymetries
LoopStructural 1.0: time-aware geological modelling
Sub3DNet1.0: a deep-learning model for regional-scale 3D subsurface structure mapping
Analytical solutions for mantle flow in cylindrical and spherical shells
Towards a model for structured mass movements: the OpenLISEM hazard model 2.0a
GO_3D_OBS: the multi-parameter benchmark geomodel for seismic imaging method assessment and next-generation 3D survey design (version 1.0)
PLUME-MoM-TSM 1.0.0: a volcanic column and umbrella cloud spreading model
HydrothermalFoam v1.0: a 3-D hydrothermal transport model for natural submarine hydrothermal systems
Synthetic seismicity distribution in Guerrero–Oaxaca subduction zone, Mexico, and its implications on the role of asperities in Gutenberg–Richter law
A new open-source viscoelastic solid earth deformation module implemented in Elmer (v8.4)
CobWeb 1.0: machine learning toolbox for tomographic imaging
pygeodyn 1.1.0: a Python package for geomagnetic data assimilation
IMEX_SfloW2D 1.0: a depth-averaged numerical flow model for pyroclastic avalanches
A multilayer approach and its application to model a local gravimetric quasi-geoid model over the North Sea: QGNSea V1.0
Development of an automatic delineation of cliff top and toe on very irregular planform coastlines (CliffMetrics v1.0)
Conor P. B. O'Malley, Gareth G. Roberts, James Panton, Fred D. Richards, J. Huw Davies, Victoria M. Fernandes, and Sia Ghelichkhan
Geosci. Model Dev., 17, 9023–9049, https://doi.org/10.5194/gmd-17-9023-2024, https://doi.org/10.5194/gmd-17-9023-2024, 2024
Short summary
Short summary
We wish to understand how the history of flowing rock within Earth's interior impacts deflection of its surface. Observations exist to address this problem, and mathematics and different computing tools can be used to predict histories of flow. We explore how modeling choices impact calculated vertical deflections. The sensitivity of vertical motions at Earth's surface to deep flow is assessed, demonstrating how surface observations can enlighten flow histories.
Pengfei Zhang, Yi-an Cui, Jing Xie, Youjun Guo, Jianxin Liu, and Jieran Liu
Geosci. Model Dev., 17, 8521–8533, https://doi.org/10.5194/gmd-17-8521-2024, https://doi.org/10.5194/gmd-17-8521-2024, 2024
Short summary
Short summary
Our study proposes a three-dimensional analytical solution for the self-potential (SP) method to detect seafloor massive sulfide deposits. Using the mirror image method, we derived formulas for the SP generated by polarized bodies in layered media. We conducted experiments with a simulated environment and compared the results with our theoretical predictions. The findings confirmed a high degree of accuracy, demonstrating the reliability of our approach for faster and precise SP modeling.
Ryan Love, Glenn A. Milne, Parviz Ajourlou, Soran Parang, Lev Tarasov, and Konstantin Latychev
Geosci. Model Dev., 17, 8535–8551, https://doi.org/10.5194/gmd-17-8535-2024, https://doi.org/10.5194/gmd-17-8535-2024, 2024
Short summary
Short summary
A relatively recent advance in glacial isostatic adjustment modeling has been the development of models that include 3D Earth structure, as opposed to 1D structure. However, a major limitation is the computational expense. We have developed a method using artificial neural networks to emulate the influence of 3D Earth models to affordably constrain the viscosity parameter space. Our results indicate that the misfits are of a scale such that useful predictions of relative sea level can be made.
Tao Yuan, Shijie Zhong, and Geruo A
EGUsphere, https://doi.org/10.5194/egusphere-2024-3200, https://doi.org/10.5194/egusphere-2024-3200, 2024
Short summary
Short summary
Earth and other planets deform visco-elastically under various forces. Numerical modeling is critical in understanding the nature of various dynamic deformation processes. This article introduces a newly developed, open-source package, CitcomSVE-3.0, which efficiently solves the visco-elastic deformation of planetary bodies. We present benchmark results against a semi-analytical code. With its accuracy and efficiency, CitcomSVE could advance research in planetary and climatic sciences.
Yury Alkhimenkov and Yury Y. Podladchikov
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-160, https://doi.org/10.5194/gmd-2024-160, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The Accelerated Pseudo-Transient (APT) method is an efficient way to solve partial differential equations, particularly well-suited for parallel computing. This paper explores the APT method's effectiveness in solving elastic, viscoelastic, and hydro-mechanical problems, focusing on quasi-static conditions in 1D, 2D, and 3D. The study examines the best numerical settings for fast and accurate solutions. The paper shows how the APT can handle complex problems in high-resolution models.
Shengjun Zhang, Xu Chen, Runsheng Zhou, and Yongjun Jia
EGUsphere, https://doi.org/10.5194/egusphere-2024-2307, https://doi.org/10.5194/egusphere-2024-2307, 2024
Short summary
Short summary
NSOAS24, a new global marine gravity model derived from multi-satellite altimetry missions, represents a significant advancement over its predecessor NSOAS22. Through optimized processing procedures, NSOAS24 resolves previous issues and demonstrates improved accuracy. Compared to NSOAS22, it shows a reduction of approximately 0.7 mGal in standard deviation when validated against recent shipborne data. Notably, its accuracy now rivals internationally recognized models DTU21 and V32.1.
Jungang Wang, Junping Chen, and Yize Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1803, https://doi.org/10.5194/egusphere-2024-1803, 2024
Short summary
Short summary
GNSS is widely used for real-time monitoring and early warning of geohazard. Accurate modeling of tropospheric delays is critical to achieving high-precision GNSS solutions, and using external delay values can improve real-time GNSS convergence time. Current empirical delay models only provide the delay but not the uncertainty. We propose a global empirical delay model with the corresponding uncertainty, and demonstrate its benefits in accelerating GNSS positioning convergence.
Jon B. May, Peter Bird, and Michele M. C. Carafa
Geosci. Model Dev., 17, 6153–6171, https://doi.org/10.5194/gmd-17-6153-2024, https://doi.org/10.5194/gmd-17-6153-2024, 2024
Short summary
Short summary
ShellSet is a combination of well-known geoscience software packages. It features a simple user interface and is optimised through the addition of a grid search input option (automatically searching for optimal models within a defined N-dimensional parameter space) and the ability to run multiple models in parallel. We show that for each number of models tested there is a performance benefit to parallel running, while two examples demonstrate a use case by improving an existing global model.
Jan Swierczek-Jereczek, Marisa Montoya, Konstantin Latychev, Alexander Robinson, Jorge Alvarez-Solas, and Jerry Mitrovica
Geosci. Model Dev., 17, 5263–5290, https://doi.org/10.5194/gmd-17-5263-2024, https://doi.org/10.5194/gmd-17-5263-2024, 2024
Short summary
Short summary
Ice sheets present a thickness of a few kilometres, leading to a vertical deformation of the crust of up to a kilometre. This process depends on properties of the solid Earth, which can be regionally very different. We propose a model that accounts for this often-ignored heterogeneity and run 100 000 simulation years in minutes. Thus, the evolution of ice sheets is modeled with better accuracy, which is critical for a good mitigation of climate change and, in particular, sea-level rise.
Sia Ghelichkhan, Angus Gibson, D. Rhodri Davies, Stephan C. Kramer, and David A. Ham
Geosci. Model Dev., 17, 5057–5086, https://doi.org/10.5194/gmd-17-5057-2024, https://doi.org/10.5194/gmd-17-5057-2024, 2024
Short summary
Short summary
We introduce the Geoscientific ADjoint Optimisation PlaTform (G-ADOPT), designed for inverse modelling of Earth system processes, with an initial focus on mantle dynamics. G-ADOPT is built upon Firedrake, Dolfin-Adjoint and the Rapid Optimisation Library, which work together to optimise models using an adjoint method, aligning them with seismic and geologic datasets. We demonstrate G-ADOPT's ability to reconstruct mantle evolution and thus be a powerful tool in geosciences.
David Oakley, Christelle Loiselet, Thierry Coowar, Vincent Labbe, and Jean-Paul Callot
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-35, https://doi.org/10.5194/gmd-2024-35, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
In this work, we develop two automated workflows for identifying fold structures on geological maps using machine learning. In one method, we identify map patterns suggestive of folding based on pre-defined rules and apply a clustering algorithm to group those from the same fold together. In the other, we train a convolutional neural network to identify folds based on a set of training examples. We apply both methods to a set of synthetic maps and to real-world maps from two locations in France.
Rene Gassmöller, Juliane Dannberg, Wolfgang Bangerth, Elbridge Gerry Puckett, and Cedric Thieulot
Geosci. Model Dev., 17, 4115–4134, https://doi.org/10.5194/gmd-17-4115-2024, https://doi.org/10.5194/gmd-17-4115-2024, 2024
Short summary
Short summary
Numerical models that use simulated particles are a powerful tool for investigating flow in the interior of the Earth, but the accuracy of these models is not fully understood. Here we present two new benchmarks that allow measurement of model accuracy. We then document that better accuracy matters for applications like convection beneath an oceanic plate. Our benchmarks and methods are freely available to help the community develop better models.
Malte Jörn Ziebarth and Sebastian von Specht
Geosci. Model Dev., 17, 2783–2828, https://doi.org/10.5194/gmd-17-2783-2024, https://doi.org/10.5194/gmd-17-2783-2024, 2024
Short summary
Short summary
Thermal energy from Earth’s active interior constantly dissipates through Earth’s surface. This heat flow is not spatially uniform, and its exact pattern is hard to predict since it depends on crustal and mantle properties, both varying across scales. Our new model REHEATFUNQ addresses this difficulty by treating the fluctuations of heat flow within a region statistically. REHEATFUNQ estimates the regional distribution of heat flow and quantifies known structural signals therein.
Shouzhi Chen, Yongshuo H. Fu, Mingwei Li, Zitong Jia, Yishuo Cui, and Jing Tang
Geosci. Model Dev., 17, 2509–2523, https://doi.org/10.5194/gmd-17-2509-2024, https://doi.org/10.5194/gmd-17-2509-2024, 2024
Short summary
Short summary
It is still a challenge to achieve an accurate simulation of vegetation phenology in the dynamic global vegetation models (DGVMs). We implemented and coupled the spring and autumn phenology models into one of the DGVMs, LPJ-GUESS, and substantially improved the accuracy in capturing the start and end dates of growing seasons. Our study highlights the importance of getting accurate phenology estimations to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.
Dechao An, Jinyun Guo, Xiaotao Chang, Zhenming Wang, Yongjun Jia, Xin Liu, Valery Bondur, and Heping Sun
Geosci. Model Dev., 17, 2039–2052, https://doi.org/10.5194/gmd-17-2039-2024, https://doi.org/10.5194/gmd-17-2039-2024, 2024
Short summary
Short summary
Seafloor topography, as fundamental geoinformation in marine surveying and mapping, plays a crucial role in numerous scientific studies. In this paper, we focus on constructing a high-precision seafloor topography and bathymetry model for the Philippine Sea (5° N–35° N, 120° E–150° E), based on shipborne bathymetric data and marine gravity anomalies, and evaluate the reliability of the model's accuracy.
Octavi Gómez-Novell, Bruno Pace, Francesco Visini, Joanna Faure Walker, and Oona Scotti
Geosci. Model Dev., 16, 7339–7355, https://doi.org/10.5194/gmd-16-7339-2023, https://doi.org/10.5194/gmd-16-7339-2023, 2023
Short summary
Short summary
Knowing the rate at which earthquakes happen along active faults is crucial to characterize the hazard that they pose. We present an approach (Paleoseismic EArthquake CHronologies, PEACH) to correlate and compute seismic histories using paleoseismic data, a type of data that characterizes past seismic activity from the geological record. Our approach reduces the uncertainties of the seismic histories and overall can improve the knowledge on fault rupture behavior for the seismic hazard.
Sébastien Carretier, Vincent Regard, Youssouf Abdelhafiz, and Bastien Plazolles
Geosci. Model Dev., 16, 6741–6755, https://doi.org/10.5194/gmd-16-6741-2023, https://doi.org/10.5194/gmd-16-6741-2023, 2023
Short summary
Short summary
We present the development of a code to simulate simultaneously the dynamics of landscapes over geological time and the evolution of the concentration of cosmogenic isotopes in grains throughout their transport from the slopes to the river outlets. This new model makes it possible to study the relationship between the detrital signal of cosmogenic isotope concentration measured in sediment and the erosion--deposition processes in watersheds.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, and Samantha Engwell
Geosci. Model Dev., 16, 6309–6336, https://doi.org/10.5194/gmd-16-6309-2023, https://doi.org/10.5194/gmd-16-6309-2023, 2023
Short summary
Short summary
We present version 2 of the numerical code IMEX-SfloW2D. With this version it is possible to simulate a wide range of volcanic mass flows (pyroclastic avalanches, lahars, pyroclastic surges), and here we present its application to transient dilute pyroclastic density currents (PDCs). A simulation of the 1883 Krakatau eruption demonstrates the capability of the numerical model to face a complex natural case involving the propagation of PDCs over the sea surface and across topographic obstacles.
Caroline J. van Calcar, Roderik S. W. van de Wal, Bas Blank, Bas de Boer, and Wouter van der Wal
Geosci. Model Dev., 16, 5473–5492, https://doi.org/10.5194/gmd-16-5473-2023, https://doi.org/10.5194/gmd-16-5473-2023, 2023
Short summary
Short summary
The waxing and waning of the Antarctic ice sheet caused the Earth’s surface to deform, which is stabilizing the ice sheet and mainly determined by the spatially variable viscosity of the mantle. Including this feedback in model simulations led to significant differences in ice sheet extent and ice thickness over the last glacial cycle. The results underline and quantify the importance of including this local feedback effect in ice sheet models when simulating the Antarctic ice sheet evolution.
Baoyi Zhang, Linze Du, Umair Khan, Yongqiang Tong, Lifang Wang, and Hao Deng
Geosci. Model Dev., 16, 3651–3674, https://doi.org/10.5194/gmd-16-3651-2023, https://doi.org/10.5194/gmd-16-3651-2023, 2023
Short summary
Short summary
We propose a Hermite–Birkhoff radial basis function (HRBF) formulation, AdaHRBF, with an adaptive gradient magnitude for continuous 3D stratigraphic potential field (SPF) modeling of multiple stratigraphic interfaces. In the linear system of HRBF interpolants constrained by the scattered on-contact attribute points and off-contact attitude points of a set of strata in 3D space, we add a novel optimization term to iteratively obtain the true gradient magnitude.
Mohammad Moulaeifard, Simon Bernard, and Florian Wellmann
Geosci. Model Dev., 16, 3565–3579, https://doi.org/10.5194/gmd-16-3565-2023, https://doi.org/10.5194/gmd-16-3565-2023, 2023
Short summary
Short summary
In this work, we propose a flexible framework to generate and interact with geological models using explicit surface representations. The essence of the work lies in the determination of the flexible control mesh, topologically similar to the main geological structure, watertight and controllable with few control points, to manage the geological structures. We exploited the subdivision surface method in our work, which is commonly used in the animation and gaming industry.
Leonardo Mingari, Antonio Costa, Giovanni Macedonio, and Arnau Folch
Geosci. Model Dev., 16, 3459–3478, https://doi.org/10.5194/gmd-16-3459-2023, https://doi.org/10.5194/gmd-16-3459-2023, 2023
Short summary
Short summary
Two novel techniques for ensemble-based data assimilation, suitable for semi-positive-definite variables with highly skewed uncertainty distributions such as tephra deposit mass loading, are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption in Chile. The deposit spatial distribution and the ashfall volume according to the analyses are in good agreement with estimations based on field measurements and isopach maps reported in previous studies.
Hui Gao, Xinming Wu, Jinyu Zhang, Xiaoming Sun, and Zhengfa Bi
Geosci. Model Dev., 16, 2495–2513, https://doi.org/10.5194/gmd-16-2495-2023, https://doi.org/10.5194/gmd-16-2495-2023, 2023
Short summary
Short summary
We propose a workflow to automatically generate synthetic seismic data and corresponding stratigraphic labels (e.g., clinoform facies, relative geologic time, and synchronous horizons) by geological and geophysical forward modeling. Trained with only synthetic datasets, our network works well to accurately and efficiently predict clinoform facies in 2D and 3D field seismic data. Such a workflow can be easily extended for other geological and geophysical scenarios in the future.
Ibsen Chivata Cardenas, Terje Aven, and Roger Flage
Geosci. Model Dev., 16, 1601–1615, https://doi.org/10.5194/gmd-16-1601-2023, https://doi.org/10.5194/gmd-16-1601-2023, 2023
Short summary
Short summary
We discuss challenges in uncertainty quantification for geohazard assessments. The challenges arise from limited data and the one-off nature of geohazard features. The challenges include the credibility of predictions, input uncertainty, and assumptions’ impact. Considerations to increase credibility of the quantification are provided. Crucial tasks in the quantification are the exhaustive scrutiny of the background knowledge coupled with the assessment of deviations of assumptions made.
Zhengfa Bi, Xinming Wu, Zhaoliang Li, Dekuan Chang, and Xueshan Yong
Geosci. Model Dev., 15, 6841–6861, https://doi.org/10.5194/gmd-15-6841-2022, https://doi.org/10.5194/gmd-15-6841-2022, 2022
Short summary
Short summary
We present an implicit modeling method based on deep learning to produce a geologically valid and structurally compatible model from unevenly sampled structural data. Trained with automatically generated synthetic data with realistic features, our network can efficiently model geological structures without the need to solve large systems of mathematical equations, opening new opportunities for further leveraging deep learning to improve modeling capacity in many Earth science applications.
D. Rhodri Davies, Stephan C. Kramer, Sia Ghelichkhan, and Angus Gibson
Geosci. Model Dev., 15, 5127–5166, https://doi.org/10.5194/gmd-15-5127-2022, https://doi.org/10.5194/gmd-15-5127-2022, 2022
Short summary
Short summary
Firedrake is a state-of-the-art system that automatically generates highly optimised code for simulating finite-element (FE) problems in geophysical fluid dynamics. It creates a separation of concerns between employing the FE method and implementing it. Here, we demonstrate the applicability and benefits of Firedrake for simulating geodynamical flows, with a focus on the slow creeping motion of Earth's mantle over geological timescales, which is ultimately the engine driving our dynamic Earth.
Federico Brogi, Simone Colucci, Jacopo Matrone, Chiara Paola Montagna, Mattia De' Michieli Vitturi, and Paolo Papale
Geosci. Model Dev., 15, 3773–3796, https://doi.org/10.5194/gmd-15-3773-2022, https://doi.org/10.5194/gmd-15-3773-2022, 2022
Short summary
Short summary
Computer simulations play a fundamental role in understanding volcanic phenomena. The growing complexity of these simulations requires the development of flexible computational tools that can easily switch between sub-models and solution techniques as well as optimizations. MagmaFOAM is a newly developed library that allows for maximum flexibility for solving multiphase volcanic flows and promotes collaborative work for in-house and community model development, testing, and comparison.
Grace A. Nield, Matt A. King, Rebekka Steffen, and Bas Blank
Geosci. Model Dev., 15, 2489–2503, https://doi.org/10.5194/gmd-15-2489-2022, https://doi.org/10.5194/gmd-15-2489-2022, 2022
Short summary
Short summary
We present a finite-element model of post-seismic solid Earth deformation built in the software package Abaqus for the purpose of calculating post-seismic deformation in the far field of major earthquakes. The model is benchmarked against an existing open-source post-seismic model demonstrating good agreement. The advantage over existing models is the potential for simple modification to include 3-D Earth structure, non-linear rheologies and alternative or multiple sources of stress change.
Alessandro Lechmann, David Mair, Akitaka Ariga, Tomoko Ariga, Antonio Ereditato, Ryuichi Nishiyama, Ciro Pistillo, Paola Scampoli, Mykhailo Vladymyrov, and Fritz Schlunegger
Geosci. Model Dev., 15, 2441–2473, https://doi.org/10.5194/gmd-15-2441-2022, https://doi.org/10.5194/gmd-15-2441-2022, 2022
Short summary
Short summary
Muon tomography is a technology that is used often in geoscientific research. The know-how of data analysis is, however, still possessed by physicists who developed this technology. This article aims at providing geoscientists with the necessary tools to perform their own analyses. We hope that a lower threshold to enter the field of muon tomography will allow more geoscientists to engage with muon tomography. SMAUG is set up in a modular way to allow for its own modules to work in between.
Zuzanna M. Swirad and Adam P. Young
Geosci. Model Dev., 15, 1499–1512, https://doi.org/10.5194/gmd-15-1499-2022, https://doi.org/10.5194/gmd-15-1499-2022, 2022
Short summary
Short summary
Cliff base and top lines that delimit coastal cliff faces are usually manually digitized based on maps, aerial photographs, terrain models, etc. However, manual mapping is time consuming and depends on the mapper's decisions and skills. To increase the objectivity and efficiency of cliff mapping, we developed CliffDelineaTool, an algorithm that identifies cliff base and top positions along cross-shore transects using elevation and slope characteristics.
Holly Kyeore Han, Natalya Gomez, and Jeannette Xiu Wen Wan
Geosci. Model Dev., 15, 1355–1373, https://doi.org/10.5194/gmd-15-1355-2022, https://doi.org/10.5194/gmd-15-1355-2022, 2022
Short summary
Short summary
Interactions between ice sheets, sea level and the solid Earth occur over a range of timescales from years to tens of thousands of years. This requires coupled ice-sheet–sea-level models to exchange information frequently, leading to a quadratic increase in computation time with the number of model timesteps. We present a new sea-level model algorithm that allows coupled models to improve the computational feasibility and precisely capture short-term interactions within longer simulations.
Jérémie Giraud, Vitaliy Ogarko, Roland Martin, Mark Jessell, and Mark Lindsay
Geosci. Model Dev., 14, 6681–6709, https://doi.org/10.5194/gmd-14-6681-2021, https://doi.org/10.5194/gmd-14-6681-2021, 2021
Short summary
Short summary
We review different techniques to model the Earth's subsurface from geophysical data (gravity field anomaly, magnetic field anomaly) using geological models and measurements of the rocks' properties. We show examples of application using idealised examples reproducing realistic features and provide theoretical details of the open-source algorithm we use.
Eric A. de Kemp
Geosci. Model Dev., 14, 6661–6680, https://doi.org/10.5194/gmd-14-6661-2021, https://doi.org/10.5194/gmd-14-6661-2021, 2021
Short summary
Short summary
This is a proof of concept and review paper of spatial agents, with initial research focusing on geomodelling. The results may be of interest to others working on complex regional geological modelling with sparse data. Structural agent-based swarming behaviour is key to advancing this field. The study provides groundwork for research in structural geology 3D modelling with spatial agents. This work was done with NetLogo, a free agent modelling platform used mostly for teaching complex systems.
José M. Bastías Espejo, Andy Wilkins, Gabriel C. Rau, and Philipp Blum
Geosci. Model Dev., 14, 6257–6272, https://doi.org/10.5194/gmd-14-6257-2021, https://doi.org/10.5194/gmd-14-6257-2021, 2021
Short summary
Short summary
The hydraulic and mechanical properties of the subsurface are inherently heterogeneous. RHEA is a simulator that can perform couple hydro-geomechanical processes in heterogeneous porous media with steep gradients. RHEA is able to fully integrate spatial heterogeneity, allowing allocation of distributed hydraulic and geomechanical properties at mesh element level. RHEA is a valuable tool that can simulate problems considering realistic heterogeneity inherent to geologic formations.
Lachlan Grose, Laurent Ailleres, Gautier Laurent, Guillaume Caumon, Mark Jessell, and Robin Armit
Geosci. Model Dev., 14, 6197–6213, https://doi.org/10.5194/gmd-14-6197-2021, https://doi.org/10.5194/gmd-14-6197-2021, 2021
Short summary
Short summary
Fault discontinuities in rock packages represent the plane where two blocks of rock have moved. They are challenging to incorporate into geological models because the geometry of the faulted rock units are defined by not only the location of the discontinuity but also the kinematics of the fault. In this paper, we outline a structural geology framework for incorporating faults into geological models by directly incorporating kinematics into the mathematical framework of the model.
Florence Colleoni, Laura De Santis, Enrico Pochini, Edy Forlin, Riccardo Geletti, Giuseppe Brancatelli, Magdala Tesauro, Martina Busetti, and Carla Braitenberg
Geosci. Model Dev., 14, 5285–5305, https://doi.org/10.5194/gmd-14-5285-2021, https://doi.org/10.5194/gmd-14-5285-2021, 2021
Short summary
Short summary
PALEOSTRIP has been developed in the framework of past Antarctic ice sheet reconstructions for periods when bathymetry around Antarctica differed substantially from today. It has been designed for users with no knowledge of numerical modelling and allows users to switch on and off the processes involved in backtracking and backstripping. Applications are broad, and it can be used to restore any continental margin bathymetry or sediment thickness and to perform basin analysis.
Lachlan Grose, Laurent Ailleres, Gautier Laurent, and Mark Jessell
Geosci. Model Dev., 14, 3915–3937, https://doi.org/10.5194/gmd-14-3915-2021, https://doi.org/10.5194/gmd-14-3915-2021, 2021
Short summary
Short summary
LoopStructural is an open-source 3D geological modelling library with a model design allowing for multiple different algorithms to be used for comparison for the same geology. Geological structures are modelled using structural geology concepts and techniques, allowing for complex structures such as overprinted folds and faults to be modelled. In the paper, we demonstrate automatically generating a 3-D model from map2loop-processed geological survey data of the Flinders Ranges, South Australia.
Zhenjiao Jiang, Dirk Mallants, Lei Gao, Tim Munday, Gregoire Mariethoz, and Luk Peeters
Geosci. Model Dev., 14, 3421–3435, https://doi.org/10.5194/gmd-14-3421-2021, https://doi.org/10.5194/gmd-14-3421-2021, 2021
Short summary
Short summary
Fast and reliable tools are required to extract hidden information from big geophysical and remote sensing data. A deep-learning model in 3D image construction from 2D image(s) is here developed for paleovalley mapping from globally available digital elevation data. The outstanding performance for 3D subsurface imaging gives confidence that this generic novel tool will make better use of existing geophysical and remote sensing data for improved management of limited earth resources.
Stephan C. Kramer, D. Rhodri Davies, and Cian R. Wilson
Geosci. Model Dev., 14, 1899–1919, https://doi.org/10.5194/gmd-14-1899-2021, https://doi.org/10.5194/gmd-14-1899-2021, 2021
Short summary
Short summary
Computational models of Earth's mantle require rigorous verification and validation. Analytical solutions of the underlying Stokes equations provide a method to verify that these equations are accurately solved for. However, their derivation in spherical and cylindrical shell domains with physically relevant boundary conditions is involved. This paper provides a number of solutions. They are provided in a Python package (Assess) and their use is demonstrated in a convergence study with Fluidity.
Bastian van den Bout, Theo van Asch, Wei Hu, Chenxiao X. Tang, Olga Mavrouli, Victor G. Jetten, and Cees J. van Westen
Geosci. Model Dev., 14, 1841–1864, https://doi.org/10.5194/gmd-14-1841-2021, https://doi.org/10.5194/gmd-14-1841-2021, 2021
Short summary
Short summary
Landslides, debris flows and other types of dense gravity-driven flows threaten livelihoods around the globe. Understanding the mechanics of these flows can be crucial for predicting their behaviour and reducing disaster risk. Numerical models assume that the solids and fluids of the flow are unstructured. The newly presented model captures the internal structure during movement. This important step can lead to more accurate predictions of landslide movement.
Andrzej Górszczyk and Stéphane Operto
Geosci. Model Dev., 14, 1773–1799, https://doi.org/10.5194/gmd-14-1773-2021, https://doi.org/10.5194/gmd-14-1773-2021, 2021
Short summary
Short summary
We present the 3D multi-parameter synthetic geomodel of the subduction zone, as well as the workflow designed to implement all of its components. The model contains different geological structures of various scales and complexities. It is intended to serve as a tool for the geophysical community to validate imaging approaches, design acquisition techniques, estimate uncertainties, benchmark computing approaches, etc.
Mattia de' Michieli Vitturi and Federica Pardini
Geosci. Model Dev., 14, 1345–1377, https://doi.org/10.5194/gmd-14-1345-2021, https://doi.org/10.5194/gmd-14-1345-2021, 2021
Short summary
Short summary
Here, we present PLUME-MoM-TSM, a volcanic plume model that allows us to quantify the formation of aggregates during the rise of the plume, model the phase change of water, and include the possibility to simulate the initial spreading of the tephra umbrella cloud intruding from the volcanic column into the atmosphere. The model is first applied to the 2015 Calbuco eruption (Chile) and provides an analytical relationship between the upwind spreading and some characteristic of the volcanic column.
Zhikui Guo, Lars Rüpke, and Chunhui Tao
Geosci. Model Dev., 13, 6547–6565, https://doi.org/10.5194/gmd-13-6547-2020, https://doi.org/10.5194/gmd-13-6547-2020, 2020
Short summary
Short summary
We present the 3-D hydro-thermo-transport model HydrothermalFoam v1.0, which we designed to provide the marine geosciences community with an easy-to-use and state-of-the-art tool for simulating mass and energy transport in submarine hydrothermal systems. HydrothermalFoam is based on the popular open-source platform OpenFOAM, comes with a number of tutorials, and is published under the GNU General Public License v3.0.
Marisol Monterrubio-Velasco, F. Ramón Zúñiga, Quetzalcoatl Rodríguez-Pérez, Otilio Rojas, Armando Aguilar-Meléndez, and Josep de la Puente
Geosci. Model Dev., 13, 6361–6381, https://doi.org/10.5194/gmd-13-6361-2020, https://doi.org/10.5194/gmd-13-6361-2020, 2020
Short summary
Short summary
The Mexican subduction zone along the Pacific coast is one of the most active seismic zones in the world, where every year larger-magnitude earthquakes shake huge inland cities such as Mexico City. In this work, we use TREMOL (sThochastic Rupture Earthquake ModeL) to simulate the seismicity observed in this zone. Our numerical results reinforce the hypothesis that in some subduction regions single asperities are responsible for producing the observed seismicity.
Thomas Zwinger, Grace A. Nield, Juha Ruokolainen, and Matt A. King
Geosci. Model Dev., 13, 1155–1164, https://doi.org/10.5194/gmd-13-1155-2020, https://doi.org/10.5194/gmd-13-1155-2020, 2020
Short summary
Short summary
We present a newly developed flat-earth model, Elmer/Earth, for viscoelastic treatment of solid earth deformation under ice loads. Unlike many previous approaches with proprietary software, this model is based on the open-source FEM code Elmer, with the advantage for scientists to apply and alter the model without license constraints. The new-generation full-stress ice-sheet model Elmer/Ice shares the same code base, enabling future coupled ice-sheet–glacial-isostatic-adjustment simulations.
Swarup Chauhan, Kathleen Sell, Wolfram Rühaak, Thorsten Wille, and Ingo Sass
Geosci. Model Dev., 13, 315–334, https://doi.org/10.5194/gmd-13-315-2020, https://doi.org/10.5194/gmd-13-315-2020, 2020
Short summary
Short summary
We present CobWeb 1.0, a graphical user interface for analysing tomographic images of geomaterials. CobWeb offers different machine learning techniques for accurate multiphase image segmentation and visualizing material specific parameters such as pore size distribution, relative porosity and volume fraction. We demonstrate a novel approach of dual filtration and dual segmentation to eliminate edge enhancement artefact in synchrotron-tomographic datasets and provide the computational code.
Loïc Huder, Nicolas Gillet, and Franck Thollard
Geosci. Model Dev., 12, 3795–3803, https://doi.org/10.5194/gmd-12-3795-2019, https://doi.org/10.5194/gmd-12-3795-2019, 2019
Short summary
Short summary
The pygeodyn package is a geomagnetic data assimilation tool written in Python. It gives access to the Earth's core flow dynamics, controlled by geomagnetic observations, by means of a reduced numerical model anchored to geodynamo simulation statistics. It aims to provide the community with a user-friendly and tunable data assimilation algorithm. It can be used for education, geomagnetic model production or tests in conjunction with webgeodyn, a set of visualization tools for geomagnetic models.
Mattia de' Michieli Vitturi, Tomaso Esposti Ongaro, Giacomo Lari, and Alvaro Aravena
Geosci. Model Dev., 12, 581–595, https://doi.org/10.5194/gmd-12-581-2019, https://doi.org/10.5194/gmd-12-581-2019, 2019
Short summary
Short summary
Pyroclastic avalanches are a type of granular flow generated at active volcanoes by different mechanisms, including the collapse of steep pyroclastic deposits (e.g., scoria and ash cones) and fountaining during moderately explosive eruptions. We present IMEX_SfloW2D, a depth-averaged flow model describing the granular mixture as a single-phase granular fluid. Benchmark cases and preliminary application to the simulation of the 11 February pyroclastic avalanche at Mt. Etna (Italy) are shown.
Yihao Wu, Zhicai Luo, Bo Zhong, and Chuang Xu
Geosci. Model Dev., 11, 4797–4815, https://doi.org/10.5194/gmd-11-4797-2018, https://doi.org/10.5194/gmd-11-4797-2018, 2018
Short summary
Short summary
A multilayer approach is parameterized for model development, and the multiple layers are located at different depths beneath the Earth’s surface. This method may be beneficial for gravity/manget field modeling, which may outperform the traditional single-layer approach.
Andres Payo, Bismarck Jigena Antelo, Martin Hurst, Monica Palaseanu-Lovejoy, Chris Williams, Gareth Jenkins, Kathryn Lee, David Favis-Mortlock, Andrew Barkwith, and Michael A. Ellis
Geosci. Model Dev., 11, 4317–4337, https://doi.org/10.5194/gmd-11-4317-2018, https://doi.org/10.5194/gmd-11-4317-2018, 2018
Short summary
Short summary
We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain.
Cited articles
Adams, J. M., Gasparini, N. M., Hobley, D. E. J., Tucker, G. E., Hutton, E. W. H., Nudurupati, S. S., and Istanbulluoglu, E.: The Landlab v1.0 OverlandFlow component: a Python tool for computing shallow-water flow across watersheds, Geosci. Model Dev., 10, 1645–1663, https://doi.org/10.5194/gmd-10-1645-2017, 2017.
Amos, C. B., and Burbank, D. W.: Channel width response to differential uplift, J. Geophys. Res., 112, F02010, https://doi.org/10.1029/2006JF000672, 2007.
Armitage, J. J., Duller, R. A., Whittaker, A. C., and Allen, P. A.: Transformation of tectonic and climatic signals from source to sedimentary archive, Nat. Geosci., 4, 231–235, https://doi.org/10.1038/NGEO1087, 2011.
Attal, M., Tucker, G. E., Whittaker, A. C., Cowie, P. A., and Roberts, G. P.: Modeling fluvial incision and transient landscape evolution: influence of dynamic channel adjustment, J. Geophys. Res., 113, F03013, https://doi.org/10.1029/2007JF000893, 2008.
Beaumont, C., Fullsack, P., and Hamilton, J.: Erosional control of active compressional orogens, in: Thrust Tectonics, edited by: McClay, K. R., Chapman Hall, New York, 1–18, https://doi.org/10.1007/978-94-011-3066-0_1, 1992.
Beer, A. R., Turowski, J. M., and Kirchner, J. W.: Spatial patterns of erosion in a bedrock gorge, J. Geophys. Res.-Earth, 122, 191–214, https://doi.org/10.1002/2016JF003850, 2017.
Braun, J. and Sambridge, M.: Modeling landscape evolution on geological time scales: a new method based on irregular spatial discretization, Basin Res., 9, 27–52, https://doi.org/10.1046/j.1365-2117.1997.00030.x, 1997.
Braun, J., and Willett, S. D.: A very efficient, O(n), implicit and parallel method to solve the stream power equation governing fluvial incision and landscape evolution, Geomorphology, 180–181, 170–179, https://doi.org/10.1016/j.geomorph.2012.10.008, 2013.
Buffington, J. M., and Montgomery, D. R.: A systematic analysis of eight decades of incipient motion studies, with special reference to gravel-bedded rivers, Water Resour. Res., 33, 1993–2029, https://doi.org/10.1029/97wr03190, 1997.
Carretier, S., Martinod, P., Reich, M., and Godderis, Y.: Modelling sediment clasts transport during landscape evolution, Earth Surf. Dynam., 4, 237–251, https://doi.org/10.5194/esurf-4-237-2016, 2016.
Chatanantavet, P. and Parker, G.: Experimental study of bedrock channel alleviation under varied sediment supply and hydraulic conditions, Water Resour. Res., 44, W12446, https://doi.org/10.1029/2007WR006581, 2008.
Chatanantavet, P. and Parker, G.: Physically based modeling of bedrock incision by abrasion, plucking, and macroabrasion, J. Geophys. Res., 114, F04018, https://doi.org/10.1029/2008JF001044, 2009.
Cook, K. L., Turowski, J. M., and Hovius, N.: A demonstration of the importance of bedload transport for fluvial bedrock erosion and knickpoint propagation, Earth Surf. Proc. Land., 38, 683–695, https://doi.org/10.1002/esp.3313, 2013.
Coulthard, T. J., Macklin, M. G., and Kirkby, M. J.: A cellular model of Holocene upland river basin and alluvial fan evolution, Earth Surf. Proc. Land., 27, 269–288, https://doi.org/10.1002/esp.318, 2002.
Coulthard, T. J., Neal, J. C., Bates, P. D., Ramirez, J., de Almeida, G. A. M., and Hancock, G. R.: Integrating the LISFLOOD-FP 2-D hydrodynamic model with the CAESAR model: implications for modelling landscape evolution, Earth Surf. Proc. Land., 38, 1897–1906, https://doi.org/10.1002/esp.3478, 2013.
Davy, P. and Lague, D.: Fluvial erosion/transport equation of landscape evolution models revisited, J. Geophys. Res.-Earth, 114, F03007, https://doi.org/10.1029/2008JF001146, 2009.
DiBiase, R. A. and Whipple, K. X.: The influence of erosion thresholds and runoff variability on the relationships among topography, climate, and erosion rate, J. Geophys. Res., 116, F04036, https://doi.org/10.1029/2011JF002095, 2011.
Ferguson, R. I., Sharma, B. P., Hardy, R. J., Hodge, R. A., and Warburton, J.: Flow resistance and hydraulic geometry in contrasting reaches of a bedrock channel, Water Resour. Res., 53, 2278–2293, https://doi.org/10.1002/2016WR020233, 2017.
Finnegan, N. J., Roe, G., Montgomery, D. R., and Hallet, B.: Controls on the channel width of rivers: Implications for modeling fluvial incision of bedrock, Geology, 33, 229–232, https://doi.org/10.1130/G21171.1, 2005.
Flintham, T. P., and Carling, P. A.: The prediction of mean bed and wall boundary shear in uniform and compositely rough channels, in: International Conference on River Regime, 18–20 May 1988, edited by: White, W. R., John Wiley, New York, 267–287, 1988.
Fowler, A. C., Kopteva, N., and Oakley, C.: The formation of river channels, SIAM J. Appl. Math., 67, 1016–1040, https://doi.org/10.1137/050629264, 2007.
Gasparini, N. M., Bras, R. L., and Whipple, K. X.: Numerical modeling of non-steady-state river profile evolution using a sediment-flux-dependent incision model, Geol. Soc. Am. Spec. Pap., 398, 127–141, https://doi.org/10.1130/2006.2398(08), 2006.
Gasparini, N. M., Whipple, K. X., and Bras, R. L.: Predictions of steady state and transient landscape morphology using sediment-flux-dependent river incision models, J. Geophys. Res., 112, F03S09, https://doi.org/10.1029/2006JF000567, 2007.
Graf, W. L., Wohl, E., Sinha, T., and Sabo, J. L.: Sedimentation and sustainability of western American reservoirs, Water Resour. Res., 46, W12535, https://doi.org/10.1029/2009WR008836, 2010.
Hancock, G. S. and Anderson, R. S.: Numerical modeling of fluvial strath-terrace formation in response to oscillating climate, Geol. Soc. Am. Bull., 114, 1131–1142, 2002.
Hancock, G. S., Anderson, R. S., and Whipple, K. X.: Beyond power: Bedrock river process and form, in rivers over rock: fluvial processes in Bedrock Channels, edited by: Tinkler, K. J. and Wohl, E. E., Geophys. Monogr. Ser., 107, 35–60, https://doi.org/10.1029/GM107p0035, 1998.
Hancock, G. S., Small, E. E., and Wobus, C. W.: Modeling the effects of weathering on bedrock-floored channel geometry, J. Geophys. Res., 116, F03018, https://doi.org/10.1029/2010JF001908, 2011.
Hilton, R. G.: Climate regulates the erosional carbon export from the terrestrial biosphere, Geomorphology, 277, 118–132, https://doi.org/10.1016/j.geomorph.2016.03.028, 2017.
Hobley, D. E. J., Sinclar, H. D., Mudd, S. M., and Cowie, P. A.: Field calibration of sediment flux dependent river incision, J. Geophys. Res., 116, F04017, https://doi.org/10.1029/2010JF001935, 2011.
Hobley, D. E. J., Adams, J. M., Nudurupati, S. S., Hutton, E. W. H., Gasparini, N. M., Istanbulluoglu, E., and Tucker, G. E.: Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics, Earth Surf. Dynam., 5, 21–46, https://doi.org/10.5194/esurf-5-21-2017, 2017.
Hodge, R. A.: Sediment processes in bedrock-alluvial rivers: research since 2010 and modeling the impact of fluctuating sediment supply on sediment cover, in: Gravel-bed Rivers: Gravel Bed Rivers and Disasters, Wiley-Blackwell, Oxford, UK, 639–670, 2017.
Hodge, R. A. and Hoey, T. B.: Upscaling from grain-scale processes to alluviation in bedrock channels using a cellular automaton model, J. Geophys. Res., 117, F01017, https://doi.org/10.1029/2011JF002145, 2012.
Hodge, R. A., Hoey, T. B., and Sklar, L. S.: Bed load transport in bedrock rivers: the role of sediment cover in grain entrainment, translation, and deposition, J. Geophys. Res., 116, F04028, https://doi.org/10.1029/2011JF002032, 2011.
Howard, A. D.: A detachment-limited model of drainage-basin evolution, Water Resour. Res., 30, 2261–2285, https://doi.org/10.1029/94wr00757, 1994.
Howard, A. D.: Long profile development of bedrock channels: Interaction of weathering, mass wasting, bed erosion, and sediment transport, in: rivers over rock: fluvial processes in Bedrock Channels, edited by: Tinkler, K. J. and Wohl, E. E., Geophys. Monogr. Ser., 107, 297–319, https://doi.org/10.1029/GM107p0297, 1998.
Inoue, T., Izumi, N., Shimizu, Y., and Parker, G.: Interaction among alluvial cover, bed roughness, and incision rate in purely bedrock and alluvial-bedrock channel, J. Geophys. Res.-Earth, 119, 2123–2146, https://doi.org/10.1002/2014JF003133, 2014.
Inoue, T., Iwasaki, T., Parker, G., Shimizu, Y., Izumi, N., Stark, C. P., and Funaki, J.: Numerical simulation of effects of sediment supply on bedrock channel morphology, J. Hydraul. Eng., 142, 04016014, https://doi.org/10.1061/(ASCE)HY.1943-7900.0001124, 2016.
Inoue, T., Parker, G., and Stark, C. P.: Morphodynamics of a bedrock-alluvial meander bend that incises as it migrates outward: Approximate solution of permanent form, Earth Surf. Proc. Land., 42, 1342–1354, https://doi.org/10.1002/esp.4094, 2017.
Johnson, J. P. L.: A surface roughness model for predicting alluvial cover and bed load transport rate in bedrock channels, J. Geophys. Res.-Earth Surf., 119, 2147–2173, https://doi.org/10.1002/2013JF003000, 2014.
Johnson, J. P. L.: Gravel threshold of motion: a state function of sediment transport disequilibrium?, Earth Surf. Dynam., 4, 685–703, https://doi.org/10.5194/esurf-4-685-2016, 2016.
Johnson, J. P. L., Whipple, K. X., Sklar, L. S., and Hanks, T. C.: Transport slopes, sediment cover, and bedrock channel incision in the Henry Mountains, Utah, J. Geophys. Res., 114, F02014, https://doi.org/10.1029/2007JF000862, 2009.
Johnson, K. N. and Finnegan, N. J.: A lithologic control on active meandering in bedrock channels, Geol. Soc. Am. Bull., 127, 1766–1776, https://doi.org/10.1130/B31184.1, 2015.
Kean, J. W. and Smith, J. D.: Flow and boundary shear stress in channels with woody bank vegetation, in Riparian vegetation and fluvial geomorphology, edited by: Bennett, S. J. and Simon, A., Water Sci. Appl., 8, 237–252, https://doi.org/10.1029/008WSA17, 2004.
Kirchner, J. W., Dietrich, W. E., Iseya, F., and Ikeda, H.: The variability of critical shear-stress, friction angle, and grain protrusion in water-worked sediments, Sedimentology, 37, 647–672, https://doi.org/10.1111/j.1365-3091.1990.tb00627.x, 1990.
Lague, D.: Reduction of long-term bedrock incision efficiency by short-term alluvial cover intermittency, J. Geophys. Res., 115, F02011, https://doi.org/10.1029/2008JF001210, 2010.
Lague, D., Crave, A., and Davy, P.: Laboratory experiments simulating the geomorphic response to tectonic uplift, J. Geophys. Res., 108, 2008, https://doi.org/10.1029/2002JB001785, 2003.
Lague, D., Hovius, N., and Davy, P.: Discharge, discharge variability, and the bedrock channel profile, J. Geophys. Res., 110, F04006, https://doi.org/10.1029/2004JF000259, 2005.
Lajeunesse, E., Devauchelle, O., Lachaussée, F., and Claudin, P.: Bedload transport in laboratory rivers: the erosion-deposition model, in: Gravel-bed Rivers: Gravel Bed Rivers and Disasters, Wiley-Blackwell, Oxford, UK, 415–438, 2017.
Lamb, M. P., Dietrich, W. E., and Sklar, L. S.: A model for fluvial bedrock incision by impacting suspended and bed load sediment, J. Geophys. Res., 113, F03025, https://doi.org/10.1029/2007JF000915, 2008.
Leopold, L. B. and Maddock, T.: The hydraulic geometry of stream channels and some physiographic implications, US Geol. Sure. Prof. Pap. 252, US Geological Survey, Washington, D.C., 1953.
Masteller, C. C. and Finnegan, N. J.: Interplay between grain protrusion and sediment entrainment in an experimental flume, J. Geophys. Res.-Earth, 122, 274–289, https://doi.org/10.1002/2016JF003943, 2017.
McEwan, I. and Heald, J.: Discrete particle modeling of entrainment from flat uniformly sized sediment beds, J. Hydraul. Eng., 127, 588–597, https://doi.org/10.1061/(ASCE)0733-9429(2001)127:7(588), 2001.
Murphy, B. P., Johnson, J. P. L., Gasparini, N. M., and Sklar, L. S.: Chemical weathering as a mechanism for the climatic control of bedrock river incision, Nature, 532, 223–227, https://doi.org/10.1038/nature17449, 2016.
Nelson, P. A. and Seminara, G.: Modeling the evolution of bedrock channel shape with erosion from saluting bed load, Geophys. Res. Lett., 38, L17406, https://doi.org/10.1029/2011GL048628, 2011.
Nelson, P. A. and Seminara, G.: A theoretical framework for the morphodynamics of bedrock channels, Geophys. Res. Lett., 39, L06408, https://doi.org/10.1029/2011GL050806, 2012.
Nelson, P. A., Venditti, J. G., Dietrich, W. E., Kirchner, J. W., Ikeda, H., Iseya, F., and Sklar, L. S.: Response of bed surface patchiness to reductions in sediment supply, J. Geophys. Res.-Earth, 114, F02005, https://doi.org/10.1029/2008jf001144, 2009.
Paola, C. and Voller, V. R.: A generalized Exner equation for sediment mass balance, J. Geophys. Res., 110, F04014, https://doi.org/10.1029/2004JF000274, 2005.
Parker, G.: Surface-based bedload transport relation for gravel rivers, J. Hydraul. Res., 28, 417–436, https://doi.org/10.1080/00221689009499058, 1990.
Prancevic, J. P. and Lamb, M. P.: Unraveling bed slope from relative roughness in initial sediment motion, J. Geophys. Res.-Earth, 120, 474–489, https://doi.org/10.1002/2014jf003323, 2015.
Shobe, C. M.: GitHub Repository: SPACE example drivers and documentation, Figshare, https://doi.org/10.6084/m9.figshare.5193478, 2017.
Shobe, C. M., Tucker, G. E., and Anderson, R. S.: Hillslope-derived blocks retard river incision, Geophys. Res. Lett., 43, 5070–5078, https://doi.org/10.1002/2016GL069262, 2016.
Shobe, C. M., Hancock, G. S., Eppes, M. C., and Small, E. E.: Field evidence for the influence of weathering on rock erodibility and channel form in bedrock rivers, Earth Surf. Proc. Land., 42, 1997–2012, https://doi.org/10.1002/esp.4163, 2017.
Sklar, L. S., and Dietrich, W. E.: River longitudinal profiles and bedrock incision models: stream power and the influence of sediment supply, in rivers over rock: fluvial processes in Bedrock Channels, edited by: Tinkler, K. J. and Wohl, E. E., Geophys. Monger. Ser., 107, 237–260, https://doi.org/10.1029/GM107p0237, 1998.
Sklar, L. S. and Dietrich, W. E.: Sediment and rock strength controls on river incision into bedrock, Geology, 29, 1087–1090, 2001.
Sklar, L. S. and Dietrich, W. E.: A mechanistic model for river incision into bedrock by saltating bed load, Water Resour. Res., 40, W06301, https://doi.org/10.1029/2003WR002496, 2004.
Small, E. E., Blom, T., Hancock, G. S., Hynek, B. M., and Wobus, C. W.: Variability of rock erodibility in bedrock-floored stream channels based on abrasion mill experiments, J. Geophys. Res.-Earth, 120, 1455–1469, https://doi.org/10.1002/2015JF003506, 2015.
Smith, T. R. and Bretherton, F. P.: Stability and the conservation of mass in drainage basin evolution, Water Resour. Res., 8, 1506–1529, https://doi.org/10.1029/WR008i006p01506, 1972.
Snyder, N. P., Whipple, K. X., Tucker, G. E., and Merritts, D. J.: Importance of a stochastic distribution of floods and erosion thresholds in the bedrock river incision problem, J. Geophys. Res., 108, 2117, https://doi.org/10.1029/2001JB001655, 2003a.
Snyder, N. P., Whipple, K. X., Tucker, G. E., and Merritts, D. J.: Channel response to tectonic forcing: Field analysis of stream morphology and hydrology in the Mendocino triple junction region, northern California, Geomorphology, 53, 97–127, https://doi.org/10.1016/S0169-555X(02)00349-5, 2003b.
Stark, C. P.: A self-regulating model of bedrock river channel geometry, Geophys. Res. Let., 33, L04402, https://doi.org/10.1029/2005GL023193, 2006.
Stock, J. D. and Montgomery, D. R.: Geologic constraints on bedrock river incision using the stream power law, J. Geophys. Res., 104, 4983–4993, https://doi.org/10.1029/98JB02139, 1999.
Tomkin, J. H., Brandon, M. T., Pazzaglia, F. J., Barbour, J. R., and Willett, S. D.: Quantitative testing of bedrock incision models for the Clearwater River, NW Washington State, J. Geophys. Res., 108, 2308, https://doi.org/10.1029/2001JB000862, 2003.
Tucker, G. E.: Drainage basin sensitivity to tectonic and climatic forcing: implications of a stochastic model for the role of entrainment and erosion thresholds, Earth Surf. Proc. Land., 29, 185–205, https://doi.org/10.1002/esp.1020, 2004.
Tucker, G. E.: Natural experiments in landscape evolution, Earth Surf. Proc. Land., 34, 1450–1460, https://doi.org/10.1002/esp.1833, 2009.
Tucker, G. E., Hobley, D. E. J., Hutton, E., Gasparini, N. M., Istanbulluoglu, E., Adams, J. M., and Nudurupati, S. S.: CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab, Geosci. Model Dev., 9, 823–839, https://doi.org/10.5194/gmd-9-823-2016, 2016.
Turowski, J. M.: Stochastic modeling of the cover effect and bedrock erosion, Water Resour. Res., 45, W03422, https://doi.org/10.1029/2008WR007252, 2009.
Turowski, J. M. and Hodge, R.: A probabilistic framework for the cover effect in bedrock erosion, Earth Surf. Dynam., 5, 311–330, https://doi.org/10.5194/esurf-5-311-2017, 2017.
Turowski, J. M., Lague, D., Crave, A., and Hovius, N.: Experimental channel response to tectonic uplift, J. Geophys. Res., 111, F03008, https://doi.org/10.1029/2005JF000306, 2006.
Turowski, J. M., Lague, D., and Hovius, N.: Cover effect in bedrock abrasion: A new derivation and its implications for the modeling of bedrock channel morphology, J. Geophys. Res., 112, F04006, https://doi.org/10.1029/2006JF000697, 2007.
Turowski, J. M., Lague, D., and Hovius, N.: Response of bedrock channel width to tectonic forcing: insights from a numerical model, theoretical considerations, and comparison with field data, J. Geophys. Res., 114, F03016, https://doi.org/10.1029/2008JF001133, 2009.
Valla, P. G., van der Beek, P. A., and Lague, D.: Fluvial incision into bedrock: insights from morphometric analysis and numerical modeling of gorges incising glacial hanging valleys (Western Alps, France), J. Geophys. Res.-Earth, 115, F02010, https://doi.org/10.1029/2008JF001079, 2010.
van der Beek, P., and Bishop, P.: Cenozoic river profile development in the Upper Lachlan catchment (SE Australia) as a test of quantitative fluvial incision models, J. Geophys. Res., 108, 2309, https://doi.org/10.1029/2002JB002125, 2003.
Whipple, K. X.: Bedrock rivers and the geomorphology of active orogens, Annu. Rev. Earth Pl. Sc., 32, 151–185, https://doi.org/10.1146/annurev.earth.32.101802.120356, 2004.
Whipple, K. X. and Tucker, G. E.: Dynamics of the stream-power river incision model: implications for height limits of mountain ranges, landscape response timescales, and research needs, J. Geophys. Res., 104, 17661–17674, https://doi.org/10.1029/1999JB900120, 1999.
Whipple, K. X. and Tucker, G. E.: Implications of sediment-flux-dependent river incision models for landscape evolution, J. Geophys. Res., 107, 2039, https://doi.org/10.1029/2000JB000044, 2002.
Whipple, K. X., Hancock, G. S., and Anderson, R. S.: River incision into bedrock: mechanics and relative efficacy of plucking, abrasion, and cavitation, Geol. Soc. Am. Bull., 112, 490–503, 2000.
Whittaker, A. C., Cowie, P. A., Attal, M., Tucker, G. E., and Roberts, G. P.: Bedrock channel adjustment to tectonic forcing: implications for predicting river incision rates, Geology, 35, 103–106, https://doi.org/10.1130/G23106A.1, 2007.
Wilcock, P. R. and McArdell, B. W.: Partial transport of a sand/gravel sediment, Water Resour. Res., 33, 235–245, https://doi.org/10.1029/96WR02672, 1997.
Willgoose, G. R., Bras, R. L., and Rodriguez-Iturbe, I.: A physically based coupled network growth and hillslope evolution model: 1, Theory, Water Resour. Res., 27, 1671–1684, https://doi.org/10.1029/91WR00935, 1991.
Wobus, C. W., Tucker, G. E., and Anderson, R. S.: Self-formed bedrock channels, Geophys. Res. Lett., 33, L18408, https://doi.org/10.1029/2006GL027182, 2006.
Wobus, C. W., Kean, J. W., Tucker, G. E., and Anderson, R. S.: Modeling the evolution of channel shape: Balancing computational efficiency with hydraulic fidelity, J. Geophys. Res., 113, F02004, https://doi.org/10.1029/2007JF000914, 2008.
Wohl, E. and David, G. C. L.: Consistency of scaling relations among bedrock and alluvial channels, J. Geophys. Res.-Earth, 113, F04013, https://doi.org/10.1029/2008JF000989, 2008.
Yanites, B. J. and Tucker, G. E.: Controls and limits on bedrock channel geometry, J. Geophys. Res., 115, F04019, https://doi.org/10.1029/2009JF001601, 2010.
Zhang, L., Parker, G., Stark, C. P., Inoue, T., Viparelli, E., Fu, X., and Izumi, N.: Macro-roughness model of bedrock–alluvial river morphodynamics, Earth Surf. Dynam., 3, 113–138, https://doi.org/10.5194/esurf-3-113-2015, 2015.
Short summary
Rivers control the movement of sediment and nutrients across Earth's surface. Understanding how rivers change through time is important for mitigating natural hazards and predicting Earth's response to climate change. We develop a new computer model for predicting how rivers cut through sediment and rock. Our model is designed to be joined with models of flooding, landslides, vegetation change, and other factors to provide a comprehensive toolbox for predicting changes to the landscape.
Rivers control the movement of sediment and nutrients across Earth's surface. Understanding how...
