Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-3863-2020
© Author(s) 2020. 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-13-3863-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HyLands 1.0: a hybrid landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution
Benjamin Campforts
CORRESPONDING AUTHOR
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany
Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder, CO, USA
Charles M. Shobe
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany
Philippe Steer
Géosciences Rennes – UMR 6118, CNRS, Université de Rennes, Rennes, France
Matthias Vanmaercke
Département de Géographie, UR SPHERES, Université de Liège, Liège, Belgium
Dimitri Lague
Géosciences Rennes – UMR 6118, CNRS, Université de Rennes, Rennes, France
Jean Braun
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Potsdam, Germany
Institute of Earth and Environmental Science, Universität Potsdam, Potsdam, Germany
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Matthew C. Morriss, Benjamin Lehmann, Benjamin Campforts, George Brencher, Brianna Rick, Leif S. Anderson, Alexander L. Handwerger, Irina Overeem, and Jeffrey Moore
Earth Surf. Dynam., 11, 1251–1274, https://doi.org/10.5194/esurf-11-1251-2023, https://doi.org/10.5194/esurf-11-1251-2023, 2023
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Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
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Earth Surf. Dynam., 11, 259–285, https://doi.org/10.5194/esurf-11-259-2023, https://doi.org/10.5194/esurf-11-259-2023, 2023
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Anne Felsberg, Jean Poesen, Michel Bechtold, Matthias Vanmaercke, and Gabriëlle J. M. De Lannoy
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Earth Surf. Dynam., 10, 473–492, https://doi.org/10.5194/esurf-10-473-2022, https://doi.org/10.5194/esurf-10-473-2022, 2022
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M. Letard, A. Collin, D. Lague, T. Corpetti, Y. Pastol, and A. Ekelund
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Earth Surf. Dynam., 10, 301–327, https://doi.org/10.5194/esurf-10-301-2022, https://doi.org/10.5194/esurf-10-301-2022, 2022
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Liesa Brosens, Benjamin Campforts, Gerard Govers, Emilien Aldana-Jague, Vao Fenotiana Razanamahandry, Tantely Razafimbelo, Tovonarivo Rafolisy, and Liesbet Jacobs
Earth Surf. Dynam., 10, 209–227, https://doi.org/10.5194/esurf-10-209-2022, https://doi.org/10.5194/esurf-10-209-2022, 2022
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Obtaining accurate information on the volume of geomorphic features typically requires high-resolution topographic data, which are often not available. Here, we show that the globally available 12 m TanDEM-X DEM can be used to accurately estimate gully volumes and establish an area–volume relationship after applying a correction. This allowed us to get a first estimate of the amount of sediment that has been mobilized by large gullies (lavaka) in central Madagascar over the past 70 years.
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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Maxime Mouyen, Romain Plateaux, Alexander Kunz, Philippe Steer, and Laurent Longuevergne
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-233, https://doi.org/10.5194/gmd-2021-233, 2021
Preprint withdrawn
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LAPS is an easy to use Matlab code that allows simulating the transport of particles in the ocean without any programming requirement. The simulation is based on publicly available ocean current velocity fields and allows to output particles spatial distribution and trajectories at time intervals defined by the user. After explaining how LAPS is working, we show a few examples of applications for studying sediment transport or plastic littering. The code is available on Github.
Philippe Steer
Earth Surf. Dynam., 9, 1239–1250, https://doi.org/10.5194/esurf-9-1239-2021, https://doi.org/10.5194/esurf-9-1239-2021, 2021
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How landscapes respond to tectonic and climatic changes is a major issue in Earth sciences. I have developed a new model that solves for landscape evolution in two dimensions using analytical solutions. Compared to numerical models, this new model is quicker and more accurate. It can compute in a single time step the topography at equilibrium of a landscape or be used to describe its evolution through time, e.g. during changes in tectonic or climatic conditions.
Thomas G. Bernard, Dimitri Lague, and Philippe Steer
Earth Surf. Dynam., 9, 1013–1044, https://doi.org/10.5194/esurf-9-1013-2021, https://doi.org/10.5194/esurf-9-1013-2021, 2021
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Both landslide mapping and volume estimation accuracies are crucial to quantify landscape evolution and manage such a natural hazard. We developed a method to robustly detect landslides and measure their volume from repeat 3D point cloud lidar data. This method detects more landslides than classical 2D inventories and resolves known issues of indirect volume measurement. Our results also suggest that the number of small landslides classically detected from 2D imagery is underestimated.
Thomas Croissant, Robert G. Hilton, Gen K. Li, Jamie Howarth, Jin Wang, Erin L. Harvey, Philippe Steer, and Alexander L. Densmore
Earth Surf. Dynam., 9, 823–844, https://doi.org/10.5194/esurf-9-823-2021, https://doi.org/10.5194/esurf-9-823-2021, 2021
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Nabil Hocini, Olivier Payrastre, François Bourgin, Eric Gaume, Philippe Davy, Dimitri Lague, Lea Poinsignon, and Frederic Pons
Hydrol. Earth Syst. Sci., 25, 2979–2995, https://doi.org/10.5194/hess-25-2979-2021, https://doi.org/10.5194/hess-25-2979-2021, 2021
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Efficient flood mapping methods are needed for large-scale, comprehensive identification of flash flood inundation hazards caused by small upstream rivers. An evaluation of three automated mapping approaches of increasing complexity, i.e., a digital terrain model (DTM) filling and two 1D–2D hydrodynamic approaches, is presented based on three major flash floods in southeastern France. The results illustrate some limits of the DTM filling method and the value of using a 2D hydrodynamic approach.
Arthur Depicker, Gerard Govers, Liesbet Jacobs, Benjamin Campforts, Judith Uwihirwe, and Olivier Dewitte
Earth Surf. Dynam., 9, 445–462, https://doi.org/10.5194/esurf-9-445-2021, https://doi.org/10.5194/esurf-9-445-2021, 2021
Short summary
Short summary
We investigated how shallow landslide occurrence is impacted by deforestation and rifting in the North Tanganyika–Kivu rift region (Africa). We developed a new approach to calculate landslide erosion rates based on an inventory compiled in biased © Google Earth imagery. We find that deforestation increases landslide erosion by a factor of 2–8 and for a period of roughly 15 years. However, the exact impact of deforestation depends on the geomorphic context of the landscape (rejuvenated/relict).
Maxime Bernard, Philippe Steer, Kerry Gallagher, and David Lundbek Egholm
Earth Surf. Dynam., 8, 931–953, https://doi.org/10.5194/esurf-8-931-2020, https://doi.org/10.5194/esurf-8-931-2020, 2020
Short summary
Short summary
Detrital thermochronometric age distributions of frontal moraines have the potential to retrieve ice erosion patterns. However, modelling erosion and sediment transport by the Tiedemann Glacier ice shows that ice velocity, the source of sediment, and ice flow patterns affect age distribution shape by delaying sediment transfer. Local sampling of frontal moraine can represent only a limited part of the catchment area and thus lead to a biased estimation of the spatial distribution of erosion.
Cited articles
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. a
Andrews, D. J. and Hanks, T. C.: Scarp degraded by linear diffusion: Inverse
solution for age, J. Geophys. Res., 90, 10193,
https://doi.org/10.1029/JB090iB12p10193, 1985. a
Armitage, J. J., Whittaker, A. C., Zakari, M., and Campforts, B.: Numerical modelling of landscape and sediment flux response to precipitation rate change, Earth Surf. Dynam., 6, 77–99, https://doi.org/10.5194/esurf-6-77-2018, 2018. a
Attal, M., Tucker, G. E., Whittaker, A. C., Cowie, P. A., and Roberts, G. P.:
Modelling fluvial incision and transient landscape evolution: Influence of
dynamic Channel adjustment, J. Geophys. Res.-Earth,
113, 1–16, https://doi.org/10.1029/2007JF000893, 2008. a
Baum, R. L., Godt, J. W., and Savage, W. Z.: Estimating the timing and
location of shallow rainfall-induced landslides using a model for transient,
unsaturated infiltration, J. Geophys. Res., 115, F03013,
https://doi.org/10.1029/2009JF001321, 2010. a
Beaumont, C., Fullsack, P., and Hamilton, J.: Erosional control of active
compressional orogens, in: Thrust Tectonics, Springer
Netherlands, Dordrecht, 1–18, https://doi.org/10.1007/978-94-011-3066-0_1, 1992. a, b
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. a
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty
estimation in mechanistic modelling of complex environmental systems using
the GLUE methodology, J. Hydrol., 249, 11–29,
https://doi.org/10.1016/S0022-1694(01)00421-8, 2001. a
Burbank, D., Meigs, A., and Brozović, N.: Interactions of growing folds
and coeval depositional systems, Basin Res., 8, 199–223,
https://doi.org/10.1046/j.1365-2117.1996.00181.x, 1996. a
Burbank, D. W.: Rates of erosion and their implications for exhumation,
Mineral. Mag., 66, 25–52, https://doi.org/10.1180/0026461026610014, 2002. a
Burbank, D. W. and Anderson, R. S.: Tectonic Geomorphology, John Wiley &
Sons, Ltd, Chichester, UK, https://doi.org/10.1002/9781444345063, 2011. a
Campforts, B.: BCampforts/pub_hylands_campforts_etal_GMD: pub_hylands_campforts_etal_GMD (Version v1.03), Zenodo, https://doi.org/10.5281/zenodo.3714182, 2020a. a
Campforts, B.: BCampforts/topotoolbox: topotoolbox-v2.4-HyLands-v1.0 (Version v2.4-HyLands-v1.0), Zenodo, https://doi.org/10.5281/zenodo.3712439, 2020i. a
Campforts, B. and Govers, G.: Keeping the edge: A numerical method that avoids
knickpoint smearing when solving the stream power law, J. Geophys. Res.-Earth, 120, 1189–1205,
https://doi.org/10.1002/2014JF003376, 2015. a
Campforts, B., Vanacker, V., Vanderborght, J., Baken, S., Smolders, E., and
Govers, G.: Simulating the mobility of meteoric 10 Be in the landscape
through a coupled soil-hillslope model (Be2D), Earth Planet. Sc.
Lett., 439, 143–157, https://doi.org/10.1016/j.epsl.2016.01.017, 2016. a, b
Campforts, B., Schwanghart, W., and Govers, G.: Accurate simulation of transient landscape evolution by eliminating numerical diffusion: the TTLEM 1.0 model, Earth Surf. Dynam., 5, 47–66, https://doi.org/10.5194/esurf-5-47-2017, 2017. a, b
Campforts, B., Vanacker, V., Herman, F., Vanmaercke, M., Schwanghart, W., Tenorio, G. E., Willems, P., and Govers, G.: Parameterization of river incision models requires accounting for environmental heterogeneity: insights from the tropical Andes, Earth Surf. Dynam., 8, 447–470, https://doi.org/10.5194/esurf-8-447-2020, 2020. a, b, c
Carretier, S., Tolorza, V., Regard, V., Aguilar, G., Bermúdez, M. A.,
Martinod, J., Guyot, J. L., Hérail, G., and Riquelme, R.: Review of
erosion dynamics along the major N-S climatic gradient in Chile and
perspectives, Geomorphology, 300, 45–68,
https://doi.org/10.1016/j.geomorph.2017.10.016, 2018. a
Champel, B.: Growth and lateral propagation of fault-related folds in the
Siwaliks of western Nepal: Rates, mechanisms, and geomorphic signature,
J. Geophys. Res., 107, 2111, https://doi.org/10.1029/2001JB000578, 2002. a, b, c, d
Claessens, L., Schoorl, J., and Veldkamp, A.: Modelling the location of
shallow landslides and their effects on landscape dynamics in large
watersheds: An application for Northern New Zealand, Geomorphology, 87,
16–27, https://doi.org/10.1016/j.geomorph.2006.06.039, 2007. a, b, c, d
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. a
Coulthard, T. J., Neal, J. C., Bates, P. D., Ramirez, J., de Almeida, G. A. M.,
and Hancock, G. R.: Integrating the LISFLOOD-FP 2D 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. a
Croissant, T., Lague, D., Steer, P., and Davy, P.: Rapid post-seismic
landslide evacuation boosted by dynamic river width, Nat. Geosci., 10,
680–684, https://doi.org/10.1038/ngeo3005, 2017. a, b
Croissant, T., Steer, P., Lague, D., Davy, P., Jeandet, L., and Hilton, R. G.:
Seismic cycles, earthquakes, landslides and sediment fluxes: Linking
tectonics to surface processes using a reduced-complexity model,
Geomorphology, 339, 87–103, https://doi.org/10.1016/j.geomorph.2019.04.017, 2019. a, b, c
Dahlquist, M. P., West, A. J., and Li, G.: Landslide-driven drainage divide
migration, Geology, 46, 403–406, https://doi.org/10.1130/G39916.1, 2018. a
Davy, P., Croissant, T., and Lague, D.: A precipiton method to calculate river
hydrodynamics, with applications to flood prediction, landscape evolution
models, and braiding instabilities, J. Geophys. Res.-Earth, 122, 1491–1512, https://doi.org/10.1002/2016JF004156, 2017. a
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. a, b
Dussauge, C., Grasso, J.-R., and Helmstetter, A.: Statistical analysis of
rockfall volume distributions: Implications for rockfall dynamics, J. Geophys. Res.-Sol. Ea., 108, https://doi.org/10.1029/2001JB000650,
2003. a
Fan, L., Lehmann, P., McArdell, B., and Or, D.: Linking rainfall-induced
landslides with debris flows runout patterns towards catchment scale hazard
assessment, Geomorphology, 280, 1–15, https://doi.org/10.1016/j.geomorph.2016.10.007,
2017. a
Fan, X., Scaringi, G., Korup, O., West, A. J., Westen, C. J., Tanyas, H.,
Hovius, N., Hales, T. C., Jibson, R. W., Allstadt, K. E., Zhang, L., Evans,
S. G., Xu, C., Li, G., Pei, X., Xu, Q., and Huang, R.: Earthquake‐Induced
Chains of Geologic Hazards: Patterns, Mechanisms, and Impacts, Rev.
Geophys., 57, 421–503, https://doi.org/10.1029/2018RG000626, 2019. a
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.:
The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004,
https://doi.org/10.1029/2005RG000183, 2007. a, b, c, d
Ferrier, K. L., Huppert, K. L., and Perron, J. T.: Climatic control of bedrock
river incision, Nature, 496, 206–209, https://doi.org/10.1038/nature11982, 2013. a
Finnegan, N. J., Hallet, B., Montgomery, D. R., Zeitler, P. K., Stone, J. O.,
Anders, A. M., and Yuping, L.: Coupling of rock uplift and river incision in
the Namche Barwa-Gyala Peri massif, Tibet, Geol. Soc. Am.
Bull., 120, 142–155, https://doi.org/10.1130/B26224.1, 2008. a, b
Furbish, D. J. and Roering, J. J.: Sediment disentrainment and the concept of
local versus nonlocal transport on hillslopes, J. Geophys. Res.-Earth, 118, 937–952, https://doi.org/10.1002/jgrf.20071, 2013. a
Gallen, S. F., Clark, M. K., and Godt, J. W.: Coseismic landslides reveal
near-surface rock strength in a high-relief, tectonically active setting,
Geology, 43, 11–14, https://doi.org/10.1130/G36080.1, 2015. a, b
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. a, b
George, D. L.: Adaptive finite volume methods with well-balanced Riemann
solvers for modeling floods in rugged terrain: Application to the Malpasset
dam-break flood (France, 1959), Int. J. Numer. Meth.
Fl., 66, 1000–1018, https://doi.org/10.1002/fld.2298, 2011. a
Glade, R. C., Shobe, C. M., Anderson, R. S., and Tucker, G. E.: Canyon shape
and erosion dynamics governed by channel-hillslope feedbacks, Geology, 47,
650–654, https://doi.org/10.1130/G46219.1, 2019. a, b, c, d
Guns, M. and Vanacker, V.: Shifts in landslide frequency-area distribution
after forest conversion in the tropical Andes, Anthropocene, 6, 75–85,
https://doi.org/10.1016/j.ancene.2014.08.001, 2014. a, b
Guzzetti, F., Malamud, B. D., Turcotte, D. L., and Reichenbach, P.: Power-law
correlations of landslide areas in central Italy, Earth Planet.
Sc. Lett., 195, 169–183, https://doi.org/10.1016/S0012-821X(01)00589-1, 2002. a, b
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., and Galli, M.:
Estimating the quality of landslide susceptibility models, Geomorphology,
81, 166–184, https://doi.org/10.1016/j.geomorph.2006.04.007, 2006. a
Hancock, G. S. and Anderson, R. S.: Numerical modeling of fluvial
strath-terrace formation in response to oscillating climate, GSA Bulletin, 114, 1131–1142,
https://doi.org/10.1130/0016-7606(2002)114<1131:NMOFST>2.0.CO;2, 2002. a
Hobley, D. E., Sinclair, H. D., Mudd, S. M., and Cowie, P. A.: Field
calibration of sediment flux dependent river incision, J. Geophys. Res.-Earth, 116, F04017,
https://doi.org/10.1029/2010JF001935, 2011. a
Horton, P., Jaboyedoff, M., Rudaz, B., and Zimmermann, M.: Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale, Nat. Hazards Earth Syst. Sci., 13, 869–885, https://doi.org/10.5194/nhess-13-869-2013, 2013. a
Hovius, N., Stark, C. P., and Allen, P. A.: Sediment flux from a mountain belt
derived by landslide mapping, Geology, 25, 231–234,
https://doi.org/10.1130/0091-7613(1997)025<0231:SFFAMB>2.3.CO;2, 1997. a, b, c
Hovius, N., Stark, C. P., Hao‐Tsu, C., and Jiun‐Chuan, L.: Supply and
Removal of Sediment in a Landslide‐Dominated Mountain Belt: Central Range,
Taiwan, J. Geol., 108, 73–89, https://doi.org/10.1086/314387, 2000. a
Hovius, N., Meunier, P., Lin, C. W., Chen, H., Chen, Y. G., Dadson, S., Horng,
M. J., and Lines, M.: Prolonged seismically induced erosion and the mass
balance of a large earthquake, Earth Planet. Sc. Lett., 304,
347–355, https://doi.org/10.1016/j.epsl.2011.02.005, 2011. a
Howard, A. D. and Kerby, G.: Channel changes in badlands, GSA Bulletin, 94, 739–752,
https://doi.org/10.1130/0016-7606(1983)94<739:CCIB>2.0.CO;2, 1983. a, b
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour.
Res., 36, 1897–1910, https://doi.org/10.1029/2000WR900090, 2000. a, b
Iverson, R. M. and George, D. L.: Modelling landslide liquefaction, mobility
bifurcation and the dynamics of the 2014 Oso disaster, Géotechnique,
66, 175–187, https://doi.org/10.1680/jgeot.15.LM.004, 2016. a
Kean, J. W. and Smith, J. D.: Flow and boundary shear stress in channels with
woody bank vegetation, Water Sci. Appl., 8,
237–252, 2004. a
Keefer, D. K.: Landslides caused by earthquakes, GSA Bulletin, 95, 406–421,
1984. a
Keefer, D. K.: Investigating landslides caused by earthquakes – A historical
review, Surv. Geophys., 23, 473–510, https://doi.org/10.1023/A:1021274710840,
2002. a
Keefer, D. K. and Larsen, M. C.: Assessing Landslide Hazards, Science, 316,
1136–1138, https://doi.org/10.1126/science.1143308, 2007. a
King, G. E., Herman, F., Lambert, R., Valla, P. G., and Guralnik, B.:
Multi-OSL-thermochronometry of feldspar, Quatern. Geochronol., 33,
76–87, https://doi.org/10.1016/j.quageo.2016.01.004, 2016. a, b
Kirby, E. and Whipple, K. X.: Expression of active tectonics in erosional
landscapes, J. Struct. Geol., 44, 54–75,
https://doi.org/10.1016/j.jsg.2012.07.009, 2012. a
Korup, O.: Large landslides and their effect on sediment flux in South
Westland, New Zealand, Earth Surf. Proc. Land., 30, 305–323,
https://doi.org/10.1002/esp.1143, 2005. a, b
Korup, O.: Rock type leaves topographic signature in landslide-dominated
mountain ranges, Geophys. Res. Lett., 35, L11402,
https://doi.org/10.1029/2008GL034157, 2008. a
Korup, O., Clague, J. J., Hermanns, R. L., Hewitt, K., Strom, A. L., and
Weidinger, J. T.: Giant landslides, topography, and erosion, Earth
Planet. Sc. Lett., 261, 578–589, https://doi.org/10.1016/j.epsl.2007.07.025,
2007. a, b, c
Korup, O., Densmore, A. L., and Schlunegger, F.: The role of landslides in
mountain range evolution, Geomorphology, 120, 77–90,
https://doi.org/10.1016/j.geomorph.2009.09.017, 2010. a
Lague, D.: Reduction of long-term bedrock incision efficiency by short-term
alluvial cover intermittency, J. Geophys. Res.-Earth, 115, F02011,
https://doi.org/10.1029/2008JF001210, 2010. a, b, c
Lague, D.: The stream power river incision model: evidence, theory and
beyond, Earth Surf. Proc. Land., 39, 38–61,
https://doi.org/10.1002/esp.3462, 2014. a
Lague, D., Hovius, N., and Davy, P.: Discharge, discharge variability, and the
bedrock channel profile, J. Geophys. Res.-Earth,
110, F04006, https://doi.org/10.1029/2004JF000259, 2005. a
Larsen, I. J., Montgomery, D. R., and Korup, O.: Landslide erosion controlled
by hillslope material, Nat. Geosci., 3, 247–251,
https://doi.org/10.1038/ngeo776, 2010. a, b
Li, G., West, A. J., Densmore, A. L., Hammond, D. E., Jin, Z., Zhang, F., Wang,
J., and Hilton, R. G.: Connectivity of earthquake-triggered landslides with
the fluvial network: Implications for landslide sediment transport after the
2008 Wenchuan earthquake, J. Geophys. Res.-Earth,
121, 703–724, https://doi.org/10.1002/2015JF003718, 2016. a
Lin, G.-W., Chen, H., Chen, Y.-H., and Horng, M.-J.: Influence of typhoons and
earthquakes on rainfall-induced landslides and suspended sediments
discharge, Eng. Geol., 97, 32–41,
https://doi.org/10.1016/j.enggeo.2007.12.001, 2008. a
Malamud, B. D. and Turcotte, D. L.: Self-organized criticality applied to
natural hazards, Nat. Hazards, 20, 93–116,
https://doi.org/10.1023/A:1008014000515, 1999. a, b
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide
inventories and their statistical properties, Earth Surf. Proc.
Land., 29, 687–711, https://doi.org/10.1002/esp.1064, 2004. a
Marc, O., Hovius, N., Meunier, P., Uchida, T., and Hayashi, S.: Transient
changes of landslide rates after earthquakes, Geology, 43, 883–886,
https://doi.org/10.1130/G36961.1, 2015. a
Marc, O., Stumpf, A., Malet, J.-P., Gosset, M., Uchida, T., and Chiang, S.-H.: Initial insights from a global database of rainfall-induced landslide inventories: the weak influence of slope and strong influence of total storm rainfall, Earth Surf. Dynam., 6, 903–922, https://doi.org/10.5194/esurf-6-903-2018, 2018. a, b
Marc, O., Behling, R., Andermann, C., Turowski, J. M., Illien, L., Roessner, S., and Hovius, N.: Long-term erosion of the Nepal Himalayas by bedrock landsliding: the role of monsoons, earthquakes and giant landslides, Earth Surf. Dynam., 7, 107–128, https://doi.org/10.5194/esurf-7-107-2019, 2019. a
Meunier, P., Hovius, N., and Haines, A. J.: Regional patterns of
earthquake-triggered landslides and their relation to ground motion,
Geophys. Res. Lett., 34, L20408, https://doi.org/10.1029/2007GL031337, 2007. a, b
Milliman, J. D. and Meade, R. H.: World-Wide Delivery of River Sediment to the
Oceans, J. Geol., 91, 1–21, https://doi.org/10.1086/628741, 1983. a
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the
topographic control on shallow landsliding, Water Resour. Res., 30,
1153–1171, https://doi.org/10.1029/93WR02979, 1994. a, b
Montgomery, D. R. and Gran, K. B.: Downstream variations in the width of
bedrock channels, Water Resources Research, 37, 1841–1846,
https://doi.org/10.1029/2000WR900393, 2001. a
Mudd, S. M.: Detection of transience in eroding landscapes, Earth Surf.
Proc. Land., 42, 24–41, https://doi.org/10.1002/esp.3923, 2017. a
Niemi, N. A., Oskin, M., Burbank, D. W., Heimsath, A. M., and Gabet, E. J.:
Effects of bedrock landslides on cosmogenically determined erosion rates,
Earth Planet. Sc. Lett., 237, 480–498,
https://doi.org/10.1016/j.epsl.2005.07.009, 2005. a
Ouimet, W. B., Whipple, K. X., Crosby, B. T., Johnson, J. P., and Schildgen,
T. F.: Epigenetic gorges in fluvial landscapes, Earth Surf. Proc.
Land., 33, 1993–2009, https://doi.org/10.1002/esp.1650, 2008. a
Page, M. J., Reid, L. M., and Lynn, I. H.: New Zealand Hydrological Society
Sediment production from Cyclone Bola landslides, Waipaoa catchment,
J. Hydrol., 38, 289–308, 1999. a
Paola, C. and Voller, V. R.: A generalized Exner equation for sediment mass
balance, J. Geophys. Res.-Earth, 110, 1–8,
https://doi.org/10.1029/2004JF000274, 2005. a
Parker, R. N., Hales, T. C., Mudd, S. M., Grieve, S. W. D., and Constantine,
J. A.: Colluvium supply in humid regions limits the frequency of
storm-triggered landslides, Sci. Rep., 6, 34438,
https://doi.org/10.1038/srep34438, 2016. a
Pelletier, J. D.: Minimizing the grid-resolution dependence of flow-routing
algorithms for geomorphic applications, Geomorphology, 122, 91–98,
https://doi.org/10.1016/j.geomorph.2010.06.001, 2010. a
Pfeiffer, A. M., Finnegan, N. J., and Willenbring, J. K.: Sediment supply
controls equilibrium channel geometry in gravel rivers, P.
Natl. Acad. Sci. USA, 114, 3346–3351, https://doi.org/10.1073/pnas.1612907114,
2017. a
Roback, K., Clark, M. K., West, A. J., Zekkos, D., Li, G., Gallen, S. F.,
Chamlagain, D., and Godt, J. W.: The size, distribution, and mobility of
landslides caused by the 2015 Mw7.8 Gorkha earthquake, Nepal, Geomorphology,
301, 121–138, https://doi.org/10.1016/j.geomorph.2017.01.030, 2018. a
Robinson, T. R., Rosser, N. J., Densmore, A. L., Williams, J. G., Kincey, M. E., Benjamin, J., and Bell, H. J. A.: Rapid post-earthquake modelling of coseismic landslide intensity and distribution for emergency response decision support, Nat. Hazards Earth Syst. Sci., 17, 1521–1540, https://doi.org/10.5194/nhess-17-1521-2017, 2017. a
Roering, J. J., Kirchner, J. W., and Dietrich, W. E.: Evidence for nonlinear,
diffusive sediment transport on hillslopes and implications for landscape
morphology, Water Resources Research, 35, 853–870,
https://doi.org/10.1029/1998WR900090, 1999. a, b
Scherler, D., DiBiase, R. A., Fisher, G. B., and Avouac, J.-P.: Testing
monsoonal controls on bedrock river incision in the Himalaya and Eastern
Tibet with a stochastic-threshold stream power model, J. Geophys.
Res.-Earth, 122, 1389–1429, https://doi.org/10.1002/2016JF004011, 2017. a
Schwanghart, W. and Scherler, D.: Short Communication: TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences, Earth Surf. Dynam., 2, 1–7, https://doi.org/10.5194/esurf-2-1-2014, 2014. a, b, c
Schwanghart, W., Bernhardt, A., Stolle, A., Hoelzmann, P., Adhikari, B. R.,
Andermann, C., Tofelde, S., Merchel, S., Rugel, G., Fort, M., and Korup, O.:
Repeated catastrophic valley infill following medieval earthquakes in the
Nepal Himalaya, Science, 351, 147–150, https://doi.org/10.1126/science.aac9865, 2016. a
Seidl, M. A. and Dietrich, W. E.: The problem of channel erosion into
bedrock, Catena Supplement, 23, 101–124, 1992. a
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. a, b, c, d
Shobe, C. M., Tucker, G. E., and Barnhart, K. R.: The SPACE 1.0 model: a Landlab component for 2-D calculation of sediment transport, bedrock erosion, and landscape evolution, Geosci. Model Dev., 10, 4577–4604, https://doi.org/10.5194/gmd-10-4577-2017, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Shobe, C. M., Tucker, G. E., and Rossi, M. W.: Variable‐Threshold Behavior
in Rivers Arising From Hillslope‐Derived Blocks, J. Geophys. Res.-Earth, 123, 1931–1957, https://doi.org/10.1029/2017JF004575, 2018. a, b
Sidle, R. C. and Ochiai, H.: Landslides: Processes, Prediction, and Land Use,
Water Resources Monograph, American Geophysical Union, Washington, D. C.,
https://doi.org/10.1029/WM018, 2006. a
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. a
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.-Sol. Ea., 108,
2388, https://doi.org/10.1029/2001JB001655, 2003. a
Stark, C. P. and Hovius, N.: The characterization of landslide size
distributions, Geophys. Res. Lett., 28, 1091–1094,
https://doi.org/10.1029/2000GL008527, 2001. a, b
Taylor, D.: Fundamentals of Soil Mechanics, Wiley, New York, 1948. a
Tenorio, G. E., Vanacker, V., Campforts, B., Álvarez, L., Zhiminaicela,
S., Vercruysse, K., Molina, A., and Govers, G.: Tracking spatial variation
in river load from Andean highlands to inter-Andean valleys, Geomorphology,
308, 175–189, https://doi.org/10.1016/j.geomorph.2018.02.009, 2018. a
Tofelde, S., Duesing, W., Schildgen, T. F., Wickert, A. D., Wittmann, H.,
Alonso, R. N., and Strecker, M.: Effects of deep-seated versus shallow
hillslope processes on cosmogenic
10Be concentrations
in fluvial sand and gravel, Earth Surf. Proc. Land., 43,
3086–3098, https://doi.org/10.1002/esp.4471,
2018. a
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. a
Tucker, G. E. and Hancock, G. R.: Modelling landscape evolution, Earth
Surf. Proc. Land., 35, 28–50, https://doi.org/10.1002/esp.1952, 2010. a
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. a
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. a
Van Asch, T., Buma, J., and Van Beek, L.: A view on some hydrological
triggering systems in landslides, Geomorphology, 30, 25–32,
https://doi.org/10.1016/S0169-555X(99)00042-2, 1999. a
Van Rompaey, A. J. J. and Govers, G.: Data quality and model complexity for
regional scale soil erosion prediction, Int. J.
Geogr. Inf. Sci., 16, 663–680,
https://doi.org/10.1080/13658810210148561, 2002. a
Wang, J., Jin, Z., Hilton, R. G., Zhang, F., Densmore, A. L., Li, G., and West,
A. J.: Controls on fluvial evacuation of sediment from earthquake-triggered
landslides, Geology, 43, 115–118, https://doi.org/10.1130/G36157.1, 2015. a
Wang, W., Godard, V., Liu-Zeng, J., Scherler, D., Xu, C., Zhang, J., Xie, K.,
Bellier, O., Ansberque, C., and de Sigoyer, J.: Perturbation of fluvial
sediment fluxes following the 2008 Wenchuan earthquake, Earth Surf.
Proc. Land., 42, 2611–2622, https://doi.org/10.1002/esp.4210, 2017. a
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.-Sol.
Ea., 104, 17661–17674, https://doi.org/10.1029/1999JB900120, 1999. a, b, c
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,
https://doi.org/10.1130/0016-7606(2000)112<490:RIIBMA>2.0.CO;2, 2000. a
Willgoose, G., Bras, R. L., and Rodrigueziturbe, I.: Results from a New Model
of River Basin Evolution, Earth Surf. Proc. Land., 16,
237–254, https://doi.org/10.1002/esp.3290160305, 1991. a
Wobus, C., Whipple, K. X., Kirby, E., Snyder, N., Johnson, J., Spyropolou, K.,
Crosby, B., and Sheehan, D.: Tectonics from topography: Procedures, promise,
and pitfalls, in: Tectonics, Climate, and Landscape Evolution, Geological Society of America, 398,
55–74, https://doi.org/10.1130/2006.2398(04), 2006. a, b
Wyllie, D. C. and Mah, C. W.: Rock Slope Engineering, CRC Press,
https://doi.org/10.1201/9781315274980, 2017. a
Yanites, B. J.: The Dynamics of Channel Slope, Width, and Sediment in Actively
Eroding Bedrock River Systems, J. Geophys. Res.-Earth, 123, 1504–1527, https://doi.org/10.1029/2017JF004405, 2018. a
Yanites, B. J., Tucker, G. E., and Anderson, R. S.: Numerical and analytical
models of cosmogenic radionuclide dynamics in landslide-dominated drainage
basins, J. Geophys. Res., 114, F01007,
https://doi.org/10.1029/2008JF001088, 2009. a
Zhang, J., van Westen, C. J., Tanyas, H., Mavrouli, O., Ge, Y., Bajrachary, S., Gurung, D. R., Dhital, M. R., and Khanal, N. R.: How size and trigger matter: analyzing rainfall- and earthquake-triggered landslide inventories and their causal relation in the Koshi River basin, central Himalaya, Nat. Hazards Earth Syst. Sci., 19, 1789–1805, https://doi.org/10.5194/nhess-19-1789-2019, 2019.
a
Zhang, L., Stark, C., Schumer, R., Kwang, J., Li, T., Fu, X., Wang, G., and
Parker, G.: The Advective‐Diffusive Morphodynamics of Mixed
Bedrock‐Alluvial Rivers Subjected to Spatiotemporally Varying Sediment
Supply, J. Geophys. Res.-Earth, 123, 1731–1755,
https://doi.org/10.1029/2017JF004431, 2018. a
Zhou, S., Ouyang, C., An, H., Jiang, T., and Xu, Q.: Comprehensive study of
the Beijing Daanshan rockslide based on real-time videos, field
investigations, and numerical modeling, Landslides, 17, 1217–1231,
https://doi.org/10.1007/s10346-020-01345-2, 2020. a
Short summary
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.
Landslides shape the Earth’s surface and are a dominant source of terrestrial sediment....