HyLands 1.0: a hybrid landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution

Campforts, Benjamin; Shobe, Charles M.; Steer, Philippe; Vanmaercke, Matthias; Lague, Dimitri; Braun, Jean

doi:10.5194/gmd-13-3863-2020

Cited by 39 publications

(42 citation statements)

References 121 publications

(217 reference statements)

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“…Comparing hillslopes in various landscapes could be easily attempted based on comprehensive landslide inventories (Tanyaš et al, 2017;Marc et al, 2018). Equation (2) would also be well-suited for landscape scale modeling of the input of various grain sizes into rivers (e.g., Benda and Dunne, 1997;Carretier et al, 2016;Neely and DiBiase, 2020) and, thus, for providing better coupling of landslide and river dynamics in landscape evolution models (Campforts et al, 2020;Egholm et al, 2013).…”

Section: The Importance Of Fragmentation and Source Materials Initial Grain Sizementioning

confidence: 99%

Controls on the grain size distribution of landslides in Taiwan: the influence of drop height, scar depth and bedrock strength

2021

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Abstract. The size of grains delivered to rivers by hillslope processes is thought to be a key factor controlling sediment transport, long-term erosion and the information recorded in sedimentary archives. Recently, models have been developed to estimate the grain size distribution produced in soil, but these models may not apply to active orogens where high erosion rates on hillslopes are driven by landsliding. To date, relatively few studies have focused on landslide grain size distributions. Here, we present grain size distributions (GSDs) obtained by grid-by-number sampling on 17 recent landslide deposits in Taiwan, and we compare these GSDs to the geometrical and physical properties of the landslides, such as their width, area, rock type, drop height and estimated scar depth. All slides occurred in slightly metamorphosed sedimentary units, except two, which occurred in younger unmetamorphosed shales, with a rock strength that is expected to be 3–10 times weaker than their metamorphosed counterparts. For 11 landslides, we did not observe substantial spatial variations in the GSD over the deposit. However, four landslides displayed a strong grain size segregation on their deposit, with the overall GSD of the downslope toe sectors being 3–10 times coarser than apex sectors. In three cases, we could also measure the GSD inside incised sectors of the landslides deposits, which presented percentiles that were 3–10 times finer than the surface of the deposit. Both observations could be due to either kinetic sieving or deposit reworking after the landslide failure, but we cannot explain why only some deposits had strong segregation. Averaging this spatial variability, we found the median grain size of the deposits to be strongly negatively correlated with drop height, scar width and depth. However, previous work suggests that regolith particles and bedrock blocks should coarsen with increasing depth, which is the inverse of our observations. Accounting for a model of regolith coarsening with depth, we found that the ratio of the estimated original bedrock block size to the deposit median grain size (D50) of the deposit was proportional to the potential energy of the landslide normalized to its bedrock strength. Thus, the studied landslides agree well with a published, simple fragmentation model, even if that model was calibrated on rock avalanches with larger volume and stronger bedrock than those featured in our dataset. Therefore, this scaling may serve for future modeling of grain size transfer from hillslopes to rivers, with the aim to better understanding landslide sediment evacuation and coupling to river erosional dynamics.

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Section: The Importance Of Fragmentation and Source Materials Initial Grain Sizementioning

confidence: 99%

Controls on the grain size distribution of landslides in Taiwan: the influence of drop height, scar depth and bedrock strength

2021

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“…CC BY 4.0 License. 1997; Carretier et al, 2016;Neely and DiBiase, 2020), and thus, to better couple landslide and river dynamics in landscape evolution models (Campforts et al, 2020;Egholm et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Comment on esurf-2021-19

Attal¹

2021

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The size of grains delivered to river by hillslopes processes is thought to be a key factor to better understand sediment transport, long-term erosion as well as sedimentary archives. Recently, models have been developed for the grain size distribution produced in soil, but they may not apply to active orogens where high erosion rates on hillslopes are driven by landsliding. Until now relatively few studies have focused on landslide grain size distributions. Here we present grain size distribution (GSD) obtained by the grid-by-number sampling on 17 recent landslide deposits in Taiwan, and we compare it to the geometrical and physical properties of the landslides, such as their width, area, rock-type, drop height and estimated depth.All slides occurred in slightly metamorphosed sedimentary units, except two, which occurred in younger unmetamorphosed shales, with rock strength expected to be 3 to 10 times weaker from their metamorphosed counterparts. We found that 4 deposits displayed a strong grain-size segregation on their deposit with downslope toe deposits 3 to 10 times coarser than apex deposits. In 3 cases, we could also measure the GSD inside the landslides that presented percentiles 3 to 10 times finer than the surface of the deposit. Both observations could be due to either kinetic sieving or deposit reworking after the landslide failure but we cannot explain why only some deposits had a strong segregation. Averaging this spatial variability we found the median grainsize of the deposits to be strongly negatively correlated to drop height, scar width and depth. However, previous work suggest that regolith particles and bedrock blocks should coarsen with increasing depth, opposite to our observation.Accounting for a model of regolith coarsening with depth, we found that the ratio of the original bedrock block size and the D50 was proportional the potential energy of the landslide normalized to its bedrock strength. Thus the studied landslides agree well with a published, simple fragmentation model, even if that model was calibrated on much larger and much stronger rock avalanches than those featured in our dataset. This scaling may thus serve for future model of grain size transfer from hillslopes to river, trying to better understand landslide sediment evacuation and coupling to river erosional dynamics.

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“…An example of a recently developed Landlab-built model is HyLands: a landscape evolution model that simulates mass wasting and sediment redistribution on hillslopes. The model was originally written in a closed-source language (Campforts et al, 2020); translating the original code into Landlab converts the original product into a fully open-source tool for the broader community and provides a new process component to simulate landsliding. The grid engine and other tools available within the Landlab library enabled efficient implementation and provide capabilities for coupling with other existing Landlab components.…”

Section: Hylands: An Example Of a Component-based Integrated Modelmentioning

confidence: 99%

“…The evolution of the alluvial fans is further visualized in the movies listed in Table 4. For details regarding the algorithms and physics supporting the HyLands component, see Campforts et al (2020).…”

Section: Hylands: An Example Of a Component-based Integrated Modelmentioning

confidence: 99%

CSDMS: a community platform for numerical modeling of Earth surface processes

et al. 2022

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

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HyLands 1.0: a hybrid landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution

Cited by 39 publications

References 121 publications

Controls on the grain size distribution of landslides in Taiwan: the influence of drop height, scar depth and bedrock strength

Controls on the grain size distribution of landslides in Taiwan: the influence of drop height, scar depth and bedrock strength

Comment on esurf-2021-19

CSDMS: a community platform for numerical modeling of Earth surface processes

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