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
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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
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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
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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.
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
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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
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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, 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 Anderson, Elizabeth K. Roberts, Stephen B. DeLong, Belize Lane, Paxton Ridgway, and Brendan P. Murphy
EGUsphere, https://doi.org/10.5194/egusphere-2023-2063, https://doi.org/10.5194/egusphere-2023-2063, 2023
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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 two year period. We also proposed ways to improve these models.
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean
EGUsphere, https://doi.org/10.5194/egusphere-2023-1892, https://doi.org/10.5194/egusphere-2023-1892, 2023
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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.
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley
EGUsphere, https://doi.org/10.5194/egusphere-2023-1931, https://doi.org/10.5194/egusphere-2023-1931, 2023
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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 hours) needed for decision-making. This work takes an initial step towards an operational postfire debris-flow inundation hazard assessment product.
Jeffrey Keck, Erkan Istanbulluoglu, Benjamin Campforts, Gregory Tucker, and Alexander Horner-Devine
EGUsphere, https://doi.org/10.5194/egusphere-2023-1623, https://doi.org/10.5194/egusphere-2023-1623, 2023
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Landslide hazards include both direct impacts associated with the runout extent of the landslide as well as secondary impacts associated with the sediment delivered to downslope channels. Numerous landslide runout and debris flow models exist but few can be used to track sediment or topographic change caused by the landslide. This paper introduces a new landslide runout model, called MassWastingRunout, that is specifically designed to meet these needs.
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
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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.
Nicole M. Gasparini, Katherine R. Barnhart, and Adam M. Forte
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2023-17, https://doi.org/10.5194/esurf-2023-17, 2023
Revised manuscript under review for ESurf
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Computational landscape evolution models (LEMs) show how landscapes change through time. There are many LEMs in the scientific community, but there are no standards for testing whether LEMs produce correct solutions or comparing output among LEMs. We present a comparison of three LEMs, illustrating both strengths and weaknesses. We hope our examples will motivate the LEM community to develop methods for inter-model comparison, which could help to avoid current and future modeling pitfalls.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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)
Benchmarking the accuracy of higher order particle methods in geodynamic models of transient flow
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IMEX_SfloW2D v2: a depth-averaged numerical flow model for volcanic gas–particle flows over complex topographies and water
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AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling
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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
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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
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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
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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.
Rene Gassmöller, Juliane Dannberg, Wolfgang Bangerth, Elbridge Gerry Puckett, and Cedric Thieulot
EGUsphere, https://doi.org/10.5194/egusphere-2023-2765, https://doi.org/10.5194/egusphere-2023-2765, 2023
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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. We here present two new benchmarks, that allow to measure the 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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Hugo Cruz-Jiménez, Guotu Li, Paul Martin Mai, Ibrahim Hoteit, and Omar M. Knio
Geosci. Model Dev., 11, 3071–3088, https://doi.org/10.5194/gmd-11-3071-2018, https://doi.org/10.5194/gmd-11-3071-2018, 2018
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One of the most important challenges seismologists and earthquake engineers face is reliably estimating ground motion in an area prone to large damaging earthquakes. This study aimed at better understanding the relationship between characteristics of geological faults (e.g., hypocenter location, rupture size/location, etc.) and resulting ground motion, via statistical analysis of a rupture simulation model. This study provides important insight on ground-motion responses to geological faults.
Fabio Crameri
Geosci. Model Dev., 11, 2541–2562, https://doi.org/10.5194/gmd-11-2541-2018, https://doi.org/10.5194/gmd-11-2541-2018, 2018
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Firstly, this study acts as a compilation of key geodynamic diagnostics and describes how to automatise them for a more efficient scientific procedure. Secondly, it outlines today's key pitfalls of scientific visualisation and provides means to circumvent them with, for example, a novel set of fully scientific colour maps. Thirdly, it introduces StagLab 3.0, a software that applies such fully automated diagnostics and state-of-the-art visualisation in the blink of an eye.
Michael Bock, Olaf Conrad, Andreas Günther, Ernst Gehrt, Rainer Baritz, and Jürgen Böhner
Geosci. Model Dev., 11, 1641–1652, https://doi.org/10.5194/gmd-11-1641-2018, https://doi.org/10.5194/gmd-11-1641-2018, 2018
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We introduce the Soil and
Landscape Evolution Model (SaLEM) for the prediction of soil parent material evolution following a lithologically differentiated approach. The GIS tool is working within the software framework SAGA GIS. Weathering, erosion and transport functions are calibrated using extrinsic and intrinsic parameter data. First results indicate that our approach shows evidence for the spatiotemporal prediction of soil parental material properties.
Karthik Iyer, Henrik Svensen, and Daniel W. Schmid
Geosci. Model Dev., 11, 43–60, https://doi.org/10.5194/gmd-11-43-2018, https://doi.org/10.5194/gmd-11-43-2018, 2018
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Igneous intrusions in sedimentary basins have a profound effect on the thermal structure of the hosting sedimentary rocks. In this paper, we present a user-friendly 1-D FEM-based tool, SILLi, that calculates the thermal effects of sill intrusions on the enclosing sedimentary stratigraphy. The motivation is to make a standardized numerical toolkit openly available that can be widely used by scientists with different backgrounds to test the effects of magmatic bodies in a wide variety of settings.
Diego Takahashi and Vanderlei C. Oliveira Jr.
Geosci. Model Dev., 10, 3591–3608, https://doi.org/10.5194/gmd-10-3591-2017, https://doi.org/10.5194/gmd-10-3591-2017, 2017
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Ellipsoids are the only bodies for which the self-demagnetization can be treated analytically. This property is useful for modelling compact orebodies having high susceptibility. We present a review of the magnetic modelling of ellipsoids, propose a way of determining the isotropic susceptibility above which the self-demagnetization must be considered, and discuss the ambiguity between confocal ellipsoids, as well as provide a set of routines to model the magnetic field produced by ellipsoids.
Hein J. van Heck, J. Huw Davies, Tim Elliott, and Don Porcelli
Geosci. Model Dev., 9, 1399–1411, https://doi.org/10.5194/gmd-9-1399-2016, https://doi.org/10.5194/gmd-9-1399-2016, 2016
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Currently, extensive geochemical databases of surface observations exist, but satisfying explanations of underlying mantle processes are lacking. We have implemented a new way to track both bulk compositions and concentrations of trace elements in a mantle convection code. In our model, chemical fractionation happens at evolving melting zones. We compare our results to a semi-analytical theory relating observed arrays of correlated Pb isotope compositions to melting age distributions.
J. Florian Wellmann, Sam T. Thiele, Mark D. Lindsay, and Mark W. Jessell
Geosci. Model Dev., 9, 1019–1035, https://doi.org/10.5194/gmd-9-1019-2016, https://doi.org/10.5194/gmd-9-1019-2016, 2016
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We often obtain knowledge about the subsurface in the form of structural geological models, as a basis for subsurface usage or resource extraction. Here, we provide a modelling code to construct such models on the basis of significant deformational events in geological history, encapsulated in kinematic equations. Our methods simplify complex dynamic processes, but enable us to evaluate how events interact, and finally how certain we are about predictions of structures in the subsurface.
A. D. Wickert
Geosci. Model Dev., 9, 997–1017, https://doi.org/10.5194/gmd-9-997-2016, https://doi.org/10.5194/gmd-9-997-2016, 2016
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Earth's lithosphere bends beneath surface loads, such as ice, sediments, and mountain belts. The pattern of this bending, or flexural isostatic response, is a function of both the loads and the spatially variable strength of the lithosphere. gFlex is an easy-to-use program to calculate flexural isostastic response, and may be used to better understand how ice sheets, glaciers, large lakes, sedimentary basins, volcanoes, and other surface loads interact with the solid Earth.
A. Folch, A. Costa, and G. Macedonio
Geosci. Model Dev., 9, 431–450, https://doi.org/10.5194/gmd-9-431-2016, https://doi.org/10.5194/gmd-9-431-2016, 2016
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We present FPLUME-1.0, a steady-state 1-D cross-section-averaged eruption column model based on the buoyant plume theory (BPT). The model accounts for plume bending by wind, entrainment of ambient moisture, effects of water phase changes, particle fallout and re-entrainment, a new parameterization for the air entrainment coefficients and a model for wet aggregation of ash particles in presence of liquid water or ice.
M. Dumon and E. Van Ranst
Geosci. Model Dev., 9, 41–57, https://doi.org/10.5194/gmd-9-41-2016, https://doi.org/10.5194/gmd-9-41-2016, 2016
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This paper presents a FOSS model called PyXRD used to improve the quantification of complex mixed-layer phyllosilicate assemblages using X-ray diffraction. The novelty of this model is the ab initio incorporation of the multi-specimen method, making it possible to share phases and their parameters across multiple specimens. We present results from a comparison of PyXRD with Sybilla v2.2.2 and a number of theoretical experiments illustrating the use of the multi-specimen set-up.
M. Mergili, J. Krenn, and H.-J. Chu
Geosci. Model Dev., 8, 4027–4043, https://doi.org/10.5194/gmd-8-4027-2015, https://doi.org/10.5194/gmd-8-4027-2015, 2015
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r.randomwalk is a flexible and multi-functional open-source GIS tool for simulating the propagation of mass movements. Mass points are routed from given release pixels through a digital elevation model until a defined break criterion is reached. In contrast to existing tools, r.randomwalk includes functionalities to account for parameter uncertainties, and it offers built-in functions for validation and visualization. We show the key functionalities of r.randomwalk for three test areas.
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...
