Abstract:Abstract. Computational modelling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure, but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature–models as both infrastructure and hypotheses–means that modelling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we descr… Show more
“…The model is summarized below; we refer the reader to Campforts, Shobe, et al (2020) and Shobe et al (2017) for the theoretical framework and details on the derivation. The HyLands model is integrated in the open-source Landlab modeling framework (Barnhart et al, 2020b;Hobley et al, 2017), which is part of the Community Surface Dynamics Modeling System (CSDMS) Workench (Tucker et al, 2021).…”
Section: The Hylands Landscape Evolution Modelmentioning
confidence: 99%
“…The HyLands model builds on three new components: water and sediment is routed using the PriorityFloodFlowRouter, fluvial erosion and sediment transport is calculated using the SpaceLargeScaleEroder while bedrock landsliding and sediment runout is calculated using the BedrockLandslider. These and all other Landlab components used in this paper are part of the open source Landlab modeling framework, version 2.5.0 (Barnhart et al, 2020a;Hobley et al, 2017), which is part of the Community Surface Dynamics Modeling System (Tucker et al, 2021)…”
Landslides can produce sediment at rates that exceed the maximum rate of sediment generation by weathering processes (Dixon & von Blanckenburg, 2012), and can trigger a chain of processes that alter the pathways of sediment from source to sink (Fan et al., 2019). The continuously growing data realm of remotely sensed Earth observations and analytical measurements such as cosmogenic radionuclide (CRN) derived erosion rates helps to better understand the impact of mass movements on evolving surfaces (e.g., DeLisle et al., 2022;Depicker et al., 2021). Yet, quantifying the impact of landslides on the evolution of landscapes over large spatial and temporal scales requires computational models that explicitly simulate sediment production, mobilization, and aggradation.Although topographic relief is a necessary condition for-and a dominant control on-landslide susceptibility (Pourghasemi et al., 2018), process-based understanding of how landslides shape terrain is currently lacking. Over timescales relevant to the formation of topography, landslides, and other forms of mass wasting are thought to impose an upper limit to relief based on rock strength (Schmidt & Montgomery, 1995;Selby, 1982). Landsliding is often held to effectively impose a threshold slope angle on a landscape. Threshold theory implies that
“…The model is summarized below; we refer the reader to Campforts, Shobe, et al (2020) and Shobe et al (2017) for the theoretical framework and details on the derivation. The HyLands model is integrated in the open-source Landlab modeling framework (Barnhart et al, 2020b;Hobley et al, 2017), which is part of the Community Surface Dynamics Modeling System (CSDMS) Workench (Tucker et al, 2021).…”
Section: The Hylands Landscape Evolution Modelmentioning
confidence: 99%
“…The HyLands model builds on three new components: water and sediment is routed using the PriorityFloodFlowRouter, fluvial erosion and sediment transport is calculated using the SpaceLargeScaleEroder while bedrock landsliding and sediment runout is calculated using the BedrockLandslider. These and all other Landlab components used in this paper are part of the open source Landlab modeling framework, version 2.5.0 (Barnhart et al, 2020a;Hobley et al, 2017), which is part of the Community Surface Dynamics Modeling System (Tucker et al, 2021)…”
Landslides can produce sediment at rates that exceed the maximum rate of sediment generation by weathering processes (Dixon & von Blanckenburg, 2012), and can trigger a chain of processes that alter the pathways of sediment from source to sink (Fan et al., 2019). The continuously growing data realm of remotely sensed Earth observations and analytical measurements such as cosmogenic radionuclide (CRN) derived erosion rates helps to better understand the impact of mass movements on evolving surfaces (e.g., DeLisle et al., 2022;Depicker et al., 2021). Yet, quantifying the impact of landslides on the evolution of landscapes over large spatial and temporal scales requires computational models that explicitly simulate sediment production, mobilization, and aggradation.Although topographic relief is a necessary condition for-and a dominant control on-landslide susceptibility (Pourghasemi et al., 2018), process-based understanding of how landslides shape terrain is currently lacking. Over timescales relevant to the formation of topography, landslides, and other forms of mass wasting are thought to impose an upper limit to relief based on rock strength (Schmidt & Montgomery, 1995;Selby, 1982). Landsliding is often held to effectively impose a threshold slope angle on a landscape. Threshold theory implies that
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