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Mass wasting caused by large-magnitude earthquakes chokes mountain rivers with several cubic kilometres of sediment. The timescale and mechanisms by which rivers evacuate small to gigantic landslide deposits are poorly known, but are critical for predicting post-seismic geomorphic hazards, interpreting the signature of earthquakes in sedimentary archives and deciphering the coupling between erosion and tectonics. Here, we use a new 2D hydro-sedimentary evolution model to demonstrate that river self-organization into a narrower alluvial channel overlying the bedrock valley dramatically increases sediment transport capacity and reduces export time of gigantic landslides by orders of magnitude compared with existing theory. Predicted export times obey a universal non-linear relationship of landslide volume and pre-landslide valley transport capacity. Upscaling these results to realistic populations of landslides shows that removing half of the total coarse sediment volume introduced by large earthquakes in the fluvial network would typically take 5 to 25 years in various tectonically active mountain belts, with little impact of earthquake magnitude and climate. Dynamic alluvial channel narrowing is therefore a key, previously unrecognized mechanism by which mountain rivers rapidly digest extreme events and maintain their capacity to incise uplifted rocks. How rivers evacuate large landslide deposits is crucial for predicting post-seismic hazards. A 2D hydro-sedimentary model demonstrates that a narrowing river channel increases sediment transport, which reduces export time by orders of magnitude.

Active faults accommodate tectonic plate motion through different slip modes, some stable and aseismic, others characterized by the occurrence of large earthquakes after long periods of inactivity. Although the slip mode estimation is of primary importance to improve seismic hazard assessment, this parameter inferred today from geodetic observations needs to be better constrained over many seismic cycles. From an analytical formulation developed for analyzing fault scarp formation and degradation in loosely consolidated material, we show that the final topographic shape generated by one earthquake rupture or by creep (i.e., continuous slip) deviates by as much as 10–20%, despite a similar cumulated slip and a constant diffusion coefficient. This result opens up the theoretical possibility of inverting, not only the cumulated slip or averaged slip rate, but also the number of earthquakes and their sizes from scarp morphologies. This approach is all the more relevant as the number of rupture events is limited. Estimating the fault slip history beyond a dozen earthquakes becomes very difficult as the effect of erosion on scarp morphology prevails. Our modeling also highlights the importance of trade-offs between fault slip history and diffusive processes. An identical topographic profile can be obtained either with a stable fault creep associated with rapid erosion, or a single earthquake rupture followed by slow erosion. These inferences, derived from the simplest possible diffusion model, are likely to be even more pronounced in nature.

Recent acceleration of sand extraction for anthropic use threatens the sustainability of this major resource. However, continental erosion and river transport, which produce sand and sediment in general, lack quantification at the global scale. Here, we develop a new geodetic method to infer the sediment discharge to ocean of the world’s largest rivers. It combines the spatial distribution of modern sedimentation zones with new high-resolution (~170 km) data from the Gravity Recovery and Climate Experiment (GRACE) mission launched in 2002. We obtain sediment discharges consistent with in situ measurements for the Amazon, Ganges-Brahmaputra, Changjiang, Indus, and Magdalena rivers. This new approach enables to quantitatively monitor the contemporary erosion of continental basins drained by rivers with large sediment discharges and paves the way toward a better understanding of how natural and anthropic changes influence landscape dynamics. Measuring rivers’ sediment discharge is critical to assess continental erosion and landscape dynamics, yet it remains a challenging task. Here the authors show that GRACE satellite helps quantifying river sediment discharge by measuring the increment in gravitational attraction due to sediment accumulation.

Assessing seismic hazards remains one of the most challenging scientific issues in Earth sciences. Deep tectonic processes are classically considered as the only persistent mechanism driving the stress loading of active faults over a seismic cycle. Here we show via a mechanical model that erosion also significantly influences the stress loading of thrust faults at the timescale of a seismic cycle. Indeed, erosion rates of about ~0.1–20 mm yr −1 , as documented in Taiwan and in other active compressional orogens, can raise the Coulomb stress by ~0.1–10 bar on the nearby thrust faults over the inter-seismic phase. Mass transfers induced by surface processes in general, during continuous or short-lived and intense events, represent a prominent mechanism for inter-seismic stress loading of faults near the surface. Such stresses are probably sufficient to trigger shallow seismicity or promote the rupture of deep continental earthquakes up to the surface. Deep tectonic processes are considered to be responsible for stress loading of faults over a seismic cycle. Here, the authors use a mechanical model to demonstrate that erosion also significantly influences the stress loading of faults on this short time scale, potentially leading to fault failure and earthquakes.

Climate change is considered as one of the main factors controlling sediment fluxes in mountain belts. However, the effect of El Niño, which represents the primary cause of inter-annual climate variability in the South Pacific, on river erosion and sediment transport in the Western Andes remains unclear. Using an unpublished dataset of Suspended Sediment Yield (SSY) in Peru (1968–2012), we show that the annual SSY increases by 3–60 times during Extreme El Niño Events (EENE) compared to normal years. During EENE, 82% to 97% of the annual SSY occurs from January to April. We explain this effect by a sharp increase in river water discharge due to high precipitation rates and transport capacity during EENE. Indeed, sediments accumulate in the mountain and piedmont areas during dry normal years, and are then rapidly mobilized during EENE years. The effect of EENE on SSY depends on the topography, as it is maximum for catchments located in the North of Peru (3–7°S), exhibiting a concave up hypsometric curve, and minimum for catchments in the South (7–18°S), with a concave down hypsometric curve. These findings highlight how the sediment transport of different topographies can respond in very different ways to large climate variability.

Tectonics and climate-driven surface processes govern the evolution of Earth’s surface topography. Topographic change in turn influences lithospheric deformation, but the elementary scale at which this feedback can be effective is unclear. Here we show that it operates in a single weather-driven erosion event. In 2009, typhoon Morakot delivered ~ 3 m of precipitation in southern Taiwan, causing exceptional landsliding and erosion. This event was followed by a step increase in the shallow (< 15 km depth) earthquake frequency lasting at least 2.5 years. Also, the scaling of earthquake magnitude and frequency underwent a sudden increase in the area where mass wasting was most intense. These observations suggest that the progressive removal of landslide debris by rivers from southern Taiwan has acted to increase the crustal stress rate to the extent that earthquake activity was demonstrably affected. Our study offers the first evidence of the impact of a single weather-driven erosion event on tectonics.

Numerical modelling offers a unique approach to understand how tectonics, climate and surface processes govern landscape dynamics. However, the efficiency and accuracy of current landscape evolution models remain a certain limitation. Here, I develop a new modelling strategy that relies on the use of 1D analytical solutions to the linear stream power equation to compute the dynamics of landscapes in 2D. This strategy uses the 1D ordering, by a directed acyclic graph, of model nodes based on their location along the water flow path to propagate topographic changes in 2D. This analytical model can be used to compute in a single time step, with an iterative procedure, the steady-state topography of landscapes subjected to river, colluvial and hillslope erosion. This model can also be adapted to compute the dynamic evolution of landscapes under either heterogeneous or time-variable uplift rate. This new model leads to slope–area relationships exactly consistent with predictions and to the exact preservation of knickpoint shape throughout their migration. Moreover, the absence of numerical diffusion or of an upper bound for the time step offers significant advantages compared to numerical models. The main drawback of this novel approach is that it does not guarantee the time continuity of the topography through successive time steps, despite practically having little impact on model behaviour.

Landslides are often triggered by catastrophic events, among which earthquakes and rainfall are the most depicted. However, very few studies have focused on the effect of atmospheric pressure on slope stability, even though weather events such as typhoons are associated with significant atmospheric pressure changes. Indeed, both atmospheric pressure changes and rainfall-induced groundwater level changes can generate large pore pressure changes. In this paper, we assess the respective impacts of atmospheric effects and rainfall over the stability of a hillslope. An analytical model of transient groundwater dynamics is developed to compute slope stability for finite hillslopes. Slope stability is evaluated through a safety factor based on the Mohr–Coulomb failure criterion. Both rainfall infiltration and atmospheric pressure variations, which impact slope stability by modifying the pore pressure of the media, are described by diffusion equations. The models were then forced by weather data from different typhoons that were recorded over Taiwan. While rainfall infiltration can induce pore pressure change up to hundreds of kilopascal, its effects are delayed in time due to flow and diffusion. To the contrary, atmospheric pressure change induces pore pressure changes not exceeding a few kilopascal, which propagates instantaneously through the skeleton before diffusion leads to an effective decay of pore pressure. Moreover, the effect of rainfall infiltration on slope stability decreases towards the toe of the hillslope and is cancelled where the water table reaches the surface, leaving atmospheric pressure change as the main driver of slope instability. This study allows for a better insight of slope stability through pore pressure analysis, and shows that atmospheric effects should not always be neglected.

Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes, and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made to develop landslide mapping methods, based on 2D satellite or aerial images, and to constrain the empirical volume–area (V–A) relationship which, in turn, would allow for the provision of indirect estimates of landslide volume. Despite these efforts, major issues remain, including the uncertainty in the V–A scaling, landslide amalgamation and the underdetection of landslides. To address these issues, we propose a new semiautomatic 3D point cloud differencing method to detect geomorphic changes, filter out false landslide detections due to lidar elevation errors, obtain robust landslide inventories with an uncertainty metric, and directly measure the volume and geometric properties of landslides. This method is based on the multiscale model-to-model cloud comparison (M3C2) algorithm and was applied to a multitemporal airborne lidar dataset of the Kaikōura region, New Zealand, following the Mw 7.8 earthquake of 14 November 2016. In a 5 km2 area, the 3D point cloud differencing method detects 1118 potential sources. Manual labeling of 739 potential sources shows the prevalence of false detections in forest-free areas (24.4 %), due to spatially correlated elevation errors, and in forested areas (80 %), related to ground classification errors in the pre-earthquake (pre-EQ) dataset. Combining the distance to the closest deposit and signal-to-noise ratio metrics, the filtering step of our workflow reduces the prevalence of false source detections to below 1 % in terms of total area and volume of the labeled inventory. The final predicted inventory contains 433 landslide sources and 399 deposits with a lower limit of detection size of 20 m2 and a total volume of 724 297 ± 141 087 m3 for sources and 954 029 ± 159 188 m3 for deposits. Geometric properties of the 3D source inventory, including the V–A relationship, are consistent with previous results, except for the lack of the classically observed rollover of the distribution of source area. A manually mapped 2D inventory from aerial image comparison has a better lower limit of detection (6 m2) but only identifies 258 landslide scars, exhibits a rollover in the distribution of source area of around 20 m2, and underestimates the total area and volume of 3D-detected sources by 72 % and 58 %, respectively. Detection and delimitation errors in the 2D inventory occur in areas with limited texture change (bare-rock surfaces, forests) and at the transition between sources and deposits that the 3D method accurately captures. Large rotational/translational landslides and retrogressive scars can be detected using the 3D method irrespective of area's vegetation cover, but they are missed in the 2D inventory owing to the dominant vertical topographic change. The 3D inventory misses shallow (< 0.4 m depth) landslides detected using the 2D method, corresponding to 10 % of the total area and 2 % of the total volume of the 3D inventory. Our data show a systematic size-dependent underdetection in the 2D inventory below 200 m2 that may explain all or part of the rollover observed in the 2D landslide source area distribution. While the 3D segmentation of complex clustered landslide sources remains challenging, we demonstrate that 3D point cloud differencing offers a greater detection sensitivity to small changes than a classical difference of digital elevation models (DEMs). Our results underline the vast potential of 3D-derived inventories to exhaustively and objectively quantify the impact of extreme events on topographic change in regions prone to landsliding, to detect a variety of hillslope mass movements that cannot be captured by 2D landslide mapping, and to explore the scaling properties of landslides in new ways.

Surface processes such as erosion and sedimentation play a critical role in crustal deformation, particularly in actively deforming orogenic belts. While these processes have been extensively studied in large-scale erosive and tectonically active regions, the specific effects of valley incision on crustal deformation, especially in tectonically inactive regions, remain poorly understood. In this study, we hypothesize that crustal deformation induced by valley incision is primarily governed by three parameters: incision velocity, crustal thickness, and the elevation difference between the plateau and the valley base level. Using two-dimensional (2D) thermomechanical models, we investigate the influence of valley incision on crustal deformation and exhumation by varying these parameters. Our results show that valley incision alone can induce significant crustal deformation, associated with lateral viscous flow in the lower crust leading to near-vertical channel flow and extensional brittle deformation in the upper crust below the valley. This deformation leads to lower-crust exhumation, within a 10 Myr time frame, if crustal thickness is greater than 50 km, the initial plateau elevation is greater than or equal to 2 km, and the long-term effective erosion rate exceeds 0.5 mm yr−1. Furthermore, while the onset of lower-crust exhumation is primarily controlled by the initial plateau elevation, the total amount of exhumed lower crust after 10 Myr strongly increases with the initial thickness of the lower crust which favors viscous flow. Moreover, natural systems that exhibit the required crustal thickness, plateau elevation, and erosion rates for lower-crustal exhumation, as highlighted in our models, also demonstrate active lower-crustal exhumation, as is the case in regions such as Nanga Parbat and Namcha Barwa. These findings offer new insights into the coupling between surface processes and deep crustal dynamics, highlighting the potential for valley incision to drive substantial crustal deformation and promote lower-crustal exhumation.