OCTOPUS Database v.2

Codilean, Alexandru T.; Munack, Henry; Saktura, Wanchese M.; Cohen, Tim J; Jacobs, Zenobia; Ulm, Sean; Hesse, Paul; Heyman, Jakob; Peters, Katharina J.; Williams, Alan N.; Saktura, Rosaria B. K.; Xue, Rui; Chishiro-Dennelly, Kai; Panta, Adhish

doi:10.5194/essd-2022-50

Cited by 3 publications

(5 citation statements)

References 31 publications

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“…We have examined the most widely used parameters applied to a set of three landscape evolution model set ups: (1) a stream-power based, advection-only model; (2) a diffusion-only model; and (3) an advection-diffusion hybrid model. We optimised the parameter values by comparing directly the catchment-averaged erosion rates predicted by our three models with a global catalogue of 10 Be-derived catchment-averaged erosion rates (Codilean et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…We conduct modelling experiments that employ randomly selected sets of LEM parameter values, and then compare our model outputs with the OCTOPUS v.2 global catalogue of 10 Be-derived catchment-averaged erosion rates (Codilean et al, 2022). In addition to apparent erosion rates (N = 4631), OCTOPUS includes topographic data and catchment morphometries.…”

Section: Be-derived Apparent Erosion Ratesmentioning

confidence: 99%

“…Here, we determine LEM parameter values that minimise the variance among 10 Be-derived apparent erosion rates in the OCTOPUS v.2 global catalogue (Codilean et al, 2022), and we analyse the capacity of LEMs to predict erosion rate given those optimised parameters. Our LEM employs the common stream power plus diffusion formulation, which is subject to important limitations, such as the neglect of fluvial deposition and mass wasting processes (e.g., Whipple and Tucker, 1999).…”

Section: Introductionmentioning

confidence: 99%

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Optimising global landscape evolution models with ¹⁰Be

Ruetenik

Jansen²,

Val³

et al. 2022

Preprint

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Abstract. By simulating erosion and deposition, landscape evolution models offer powerful insights to Earth surface processes and dynamics. These models are typically constructed from parameters describing drainage area (m), slope (n), substrate erodibility (K), hillslope diffusion (D), and a critical drainage area (Ac) that signifies the downslope transition from hillslope diffusion to advective fluvial processes. In spite of the widespread success of such models, the parameter values have high degrees of uncertainty mainly because the advection and diffusion equations amalgamate physical processes and material properties that span widely differing spatial and temporal scales. Here, we use a global catalogue of catchment-averaged cosmogenic 10Be-derived erosion (denudation) rates with the aim to optimise a set of landscape evolution models via a Monte Carlo based parameter search. We consider three model scenarios: advection-only, diffusion-only, and an advection-diffusion hybrid. In each case, we search for a parameter set that best approximates erosion rates at the global scale, and we directly compare erosion rates from the modelled scenarios with those derived from 10Be data. Optimised ranges can be defined for many LEM parameters at the global scale. In the absence of diffusion, n ~ 1.3, and with increasing diffusivity the optimal n increases linearly to a global maximum of n ~ 2. Meanwhile we find that the diffusion-only model somewhat outperforms the advection-only model and is optimised when concavity is raised to a power of 2. With these examples, we suggest that our approach provides baseline parameter estimates for large-scale studies spanning long timescales and diverse landscape properties. Moreover, our direct comparison of model-predicted versus observed erosion rates is preferable to methods that rely upon catchment-scale averaging or amalgamation of topographic metrics. We also seek to optimise K and D parameters in landscape evolution models with respect to precipitation and substrate lithology. These optimised models allow us to effectively control for topography and target specifically the relationship between erosion rate and precipitation. All models suggest a positive correlation between K or D and precipitation > 1500 mm yr–1, plus a local maximum at ~ 300 mm yr–1, which is compatible with the long-standing hypothesis that semi-arid environments are among the most erodible.

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Section: Discussionmentioning

confidence: 99%

Section: Be-derived Apparent Erosion Ratesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimising global landscape evolution models with ¹⁰Be

Ruetenik

Jansen²,

Val³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…We seek to avoid these transient basins because many bedrock rivers in them adjust their width in addition to slope during channel adjustment and affect assumed scaling relationships in the calculations above to bias the relationship between 𝐸𝐸 and 𝑘𝑘 𝑠𝑠𝑠𝑠 in equation 1 in the main text (e.g., Whittaker et al, 2007). We conduct this analysis for all basins with published 10 Be cosmogenic nuclide basin averaged erosion rates in detrital quartz from the Octopus archive (Codilean et al, 2018(Codilean et al, , 2022.…”

Section: River Profile Analysismentioning

confidence: 99%