Articles | Volume 3, issue 4
https://doi.org/10.5194/esurf-3-483-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/esurf-3-483-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
16 Oct 2015
Research article |
| 16 Oct 2015
Topographic roughness as a signature of the emergence of bedrock in eroding landscapes
School of GeoSciences, University of Edinburgh, Edinburgh, UK
S. M. Mudd
School of GeoSciences, University of Edinburgh, Edinburgh, UK
E. T. A. Mitchard
School of GeoSciences, University of Edinburgh, Edinburgh, UK
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Cited
39 citations as recorded by crossref.
- Slope, grain size, and roughness controls on dry sediment transport and storage on steep hillslopes R. DiBiase et al. https://doi.org/10.1002/2016JF003970
- Controls on Zero‐Order Basin Morphology S. Grieve et al. https://doi.org/10.1029/2017JF004453
- Where are the outcrops? Automatic delineation of bedrock from sediments using Deep-Learning techniques A. Ganerød et al. https://doi.org/10.1016/j.acags.2023.100119
- Hillslope denudation and morphologic response to a rock uplift gradient V. Godard et al. https://doi.org/10.5194/esurf-8-221-2020
- Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes B. Purinton & B. Bookhagen https://doi.org/10.3389/feart.2021.758606
- How does grid-resolution modulate the topographic expression of geomorphic processes? S. Grieve et al. https://doi.org/10.5194/esurf-4-627-2016
- Modeling the Shape and Evolution of Normal‐Fault Facets G. Tucker et al. https://doi.org/10.1029/2019JF005305
- The grain size of sediments delivered to steep debris‐flow prone channels prior to and following wildfire A. Neely et al. https://doi.org/10.1002/esp.5819
- A nondimensional framework for exploring the relief structure of landscapes S. Grieve et al. https://doi.org/10.5194/esurf-4-309-2016
- Does soil erosion rejuvenate the soil phosphorus inventory? A. Eger et al. https://doi.org/10.1016/j.geoderma.2018.06.021
- Topographic Roughness on Forested Hillslopes: A Theoretical Approach for Quantifying Hillslope Sediment Flux From Tree Throw T. Doane et al. https://doi.org/10.1029/2021GL094987
- Land-surface parameters for spatial predictive mapping and modeling A. Maxwell & C. Shobe https://doi.org/10.1016/j.earscirev.2022.103944
- Storage and export of soil carbon and mineral surface area along an erosional gradient in the Sierra Nevada, California X. Wang et al. https://doi.org/10.1016/j.geoderma.2018.02.008
- Soil erodibility in European mountain beech forests M. Kašanin-Grubin et al. https://doi.org/10.1139/cjfr-2020-0361
- Regional insights into Upper Palaeolithic territorial strategies and the factors of habitat choice in the territory of the Hungarian Central Mountains A. Trájer https://doi.org/10.1016/j.quascirev.2024.108686
- Drainage Area, Bedrock Fracture Spacing, and Weathering Controls on Landscape‐Scale Patterns in Surface Sediment Grain Size A. Neely & R. DiBiase https://doi.org/10.1029/2020JF005560
- The problem of predicting the size distribution of sediment supplied by hillslopes to rivers L. Sklar et al. https://doi.org/10.1016/j.geomorph.2016.05.005
- Predictive mapping and assignment uncertainty with a spatially adjusted Gaussian mixture model H. Rakotonirina et al. https://doi.org/10.1016/j.cageo.2026.106184
- Bedrock fracture density controls on hillslope erodibility in steep, rocky landscapes with patchy soil cover, southern California, USA A. Neely et al. https://doi.org/10.1016/j.epsl.2019.06.011
- Supervised classification of landforms in Arctic mountains H. Mithan et al. https://doi.org/10.1002/ppp.2015
- Evaluating the accuracy of binary classifiers for geomorphic applications M. Rossi https://doi.org/10.5194/esurf-12-765-2024
- Scrutinizing gully erosion hotspots using hybridized deep‐learning analysis to avoid land degradation O. Rahmati et al. https://doi.org/10.1002/ldr.4721
- Clustering River Profiles to Classify Geomorphic Domains F. Clubb et al. https://doi.org/10.1029/2019JF005025
- Predictive modeling of bedrock outcrops and associated shallow soil in upland glaciated landscapes O. Fraser et al. https://doi.org/10.1016/j.geoderma.2020.114495
- Seismic Hazard Analyses From Geologic and Geomorphic Data: Current and Future Challenges K. Morell et al. https://doi.org/10.1029/2018TC005365
- Detection of transience in eroding landscapes S. Mudd https://doi.org/10.1002/esp.3923
- Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. https://doi.org/10.1002/esp.5943
- Hölder‐Conditioned Hypsometry: A Refinement to a Classical Approach for the Characterization of Topography C. Keylock et al. https://doi.org/10.1029/2019WR025412
- Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward G. Sofia https://doi.org/10.1016/j.geomorph.2020.107055
- Investigation of the use of topographic data derived from Pléiades imagery for high-resolution hillslope-scale morphometry V. Pellegrino et al. https://doi.org/10.1016/j.geomorph.2024.109162
- Coevolving topography, patchy soils, and forest structure M. Rossi et al. https://doi.org/10.1073/pnas.2519374123
- Evaluation of high‐resolution DEMs from satellite imagery for geomorphic applications: A case study using the SETSM algorithm A. Atwood & A. West https://doi.org/10.1002/esp.5263
- Capturing exposed bedrock in the upland regions of Great Britain: A geomorphometric focused random forest approach C. Williams et al. https://doi.org/10.1016/j.cageo.2024.105814
- The relationship between drainage density, erosion rate, and hilltop curvature: Implications for sediment transport processes F. Clubb et al. https://doi.org/10.1002/2015JF003747
- Predicting soil thickness on soil mantled hillslopes N. Patton et al. https://doi.org/10.1038/s41467-018-05743-y
- Shapley values reveal geomorphic controls on exposed bedrock-gravel differentiation X. Zhang et al. https://doi.org/10.1016/j.geoderma.2025.117525
- Capturing the complexity of soil evolution: Heterogeneities in rock cover and chemical weathering in Montana's Rocky Mountains S. Benjaram et al. https://doi.org/10.1016/j.geomorph.2022.108186
- Hilltop Curvature Increases With the Square Root of Erosion Rate E. Gabet et al. https://doi.org/10.1029/2020JF005858
- Hillslope roughness reveals forest sensitivity to extreme winds T. Doane et al. https://doi.org/10.1073/pnas.2212105120
39 citations as recorded by crossref.
- Slope, grain size, and roughness controls on dry sediment transport and storage on steep hillslopes R. DiBiase et al. https://doi.org/10.1002/2016JF003970
- Controls on Zero‐Order Basin Morphology S. Grieve et al. https://doi.org/10.1029/2017JF004453
- Where are the outcrops? Automatic delineation of bedrock from sediments using Deep-Learning techniques A. Ganerød et al. https://doi.org/10.1016/j.acags.2023.100119
- Hillslope denudation and morphologic response to a rock uplift gradient V. Godard et al. https://doi.org/10.5194/esurf-8-221-2020
- Beyond Vertical Point Accuracy: Assessing Inter-pixel Consistency in 30 m Global DEMs for the Arid Central Andes B. Purinton & B. Bookhagen https://doi.org/10.3389/feart.2021.758606
- How does grid-resolution modulate the topographic expression of geomorphic processes? S. Grieve et al. https://doi.org/10.5194/esurf-4-627-2016
- Modeling the Shape and Evolution of Normal‐Fault Facets G. Tucker et al. https://doi.org/10.1029/2019JF005305
- The grain size of sediments delivered to steep debris‐flow prone channels prior to and following wildfire A. Neely et al. https://doi.org/10.1002/esp.5819
- A nondimensional framework for exploring the relief structure of landscapes S. Grieve et al. https://doi.org/10.5194/esurf-4-309-2016
- Does soil erosion rejuvenate the soil phosphorus inventory? A. Eger et al. https://doi.org/10.1016/j.geoderma.2018.06.021
- Topographic Roughness on Forested Hillslopes: A Theoretical Approach for Quantifying Hillslope Sediment Flux From Tree Throw T. Doane et al. https://doi.org/10.1029/2021GL094987
- Land-surface parameters for spatial predictive mapping and modeling A. Maxwell & C. Shobe https://doi.org/10.1016/j.earscirev.2022.103944
- Storage and export of soil carbon and mineral surface area along an erosional gradient in the Sierra Nevada, California X. Wang et al. https://doi.org/10.1016/j.geoderma.2018.02.008
- Soil erodibility in European mountain beech forests M. Kašanin-Grubin et al. https://doi.org/10.1139/cjfr-2020-0361
- Regional insights into Upper Palaeolithic territorial strategies and the factors of habitat choice in the territory of the Hungarian Central Mountains A. Trájer https://doi.org/10.1016/j.quascirev.2024.108686
- Drainage Area, Bedrock Fracture Spacing, and Weathering Controls on Landscape‐Scale Patterns in Surface Sediment Grain Size A. Neely & R. DiBiase https://doi.org/10.1029/2020JF005560
- The problem of predicting the size distribution of sediment supplied by hillslopes to rivers L. Sklar et al. https://doi.org/10.1016/j.geomorph.2016.05.005
- Predictive mapping and assignment uncertainty with a spatially adjusted Gaussian mixture model H. Rakotonirina et al. https://doi.org/10.1016/j.cageo.2026.106184
- Bedrock fracture density controls on hillslope erodibility in steep, rocky landscapes with patchy soil cover, southern California, USA A. Neely et al. https://doi.org/10.1016/j.epsl.2019.06.011
- Supervised classification of landforms in Arctic mountains H. Mithan et al. https://doi.org/10.1002/ppp.2015
- Evaluating the accuracy of binary classifiers for geomorphic applications M. Rossi https://doi.org/10.5194/esurf-12-765-2024
- Scrutinizing gully erosion hotspots using hybridized deep‐learning analysis to avoid land degradation O. Rahmati et al. https://doi.org/10.1002/ldr.4721
- Clustering River Profiles to Classify Geomorphic Domains F. Clubb et al. https://doi.org/10.1029/2019JF005025
- Predictive modeling of bedrock outcrops and associated shallow soil in upland glaciated landscapes O. Fraser et al. https://doi.org/10.1016/j.geoderma.2020.114495
- Seismic Hazard Analyses From Geologic and Geomorphic Data: Current and Future Challenges K. Morell et al. https://doi.org/10.1029/2018TC005365
- Detection of transience in eroding landscapes S. Mudd https://doi.org/10.1002/esp.3923
- Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. https://doi.org/10.1002/esp.5943
- Hölder‐Conditioned Hypsometry: A Refinement to a Classical Approach for the Characterization of Topography C. Keylock et al. https://doi.org/10.1029/2019WR025412
- Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward G. Sofia https://doi.org/10.1016/j.geomorph.2020.107055
- Investigation of the use of topographic data derived from Pléiades imagery for high-resolution hillslope-scale morphometry V. Pellegrino et al. https://doi.org/10.1016/j.geomorph.2024.109162
- Coevolving topography, patchy soils, and forest structure M. Rossi et al. https://doi.org/10.1073/pnas.2519374123
- Evaluation of high‐resolution DEMs from satellite imagery for geomorphic applications: A case study using the SETSM algorithm A. Atwood & A. West https://doi.org/10.1002/esp.5263
- Capturing exposed bedrock in the upland regions of Great Britain: A geomorphometric focused random forest approach C. Williams et al. https://doi.org/10.1016/j.cageo.2024.105814
- The relationship between drainage density, erosion rate, and hilltop curvature: Implications for sediment transport processes F. Clubb et al. https://doi.org/10.1002/2015JF003747
- Predicting soil thickness on soil mantled hillslopes N. Patton et al. https://doi.org/10.1038/s41467-018-05743-y
- Shapley values reveal geomorphic controls on exposed bedrock-gravel differentiation X. Zhang et al. https://doi.org/10.1016/j.geoderma.2025.117525
- Capturing the complexity of soil evolution: Heterogeneities in rock cover and chemical weathering in Montana's Rocky Mountains S. Benjaram et al. https://doi.org/10.1016/j.geomorph.2022.108186
- Hilltop Curvature Increases With the Square Root of Erosion Rate E. Gabet et al. https://doi.org/10.1029/2020JF005858
- Hillslope roughness reveals forest sensitivity to extreme winds T. Doane et al. https://doi.org/10.1073/pnas.2212105120
Saved (final revised paper)
Latest update: 03 Aug 2026
Short summary
Rock is exposed at the Earth surface when erosion rates locally exceed rates of soil production. This transition is marked by a diagnostic increase in topographic roughness, which we demonstrate can be a powerful indicator of the location of rock outcrop in a landscape. Using this to explore how hillslopes in two landscapes respond to increasing erosion rates, we find that the transition from soil-mantled to bedrock hillslopes is patchy and spatially heterogeneous.
Rock is exposed at the Earth surface when erosion rates locally exceed rates of soil production....
