Abstract. Bedrock incision by rivers is commonly driven by the impacts of moving bedload particles. The speed of incision is modulated by rock properties, which is quantified within a parameter known as erodibility that scales the erosion rate to the erosive action of the flow. Although basic models for the geotechnical controls on rock erodibility have been suggested, large scatter and trends in the remaining relationships indicate that they are incompletely understood. Here, we conducted dedicated laboratory experiments measuring erodibility using erosion mills. In parallel, we measured uniaxial compressive strength, tensile strength, Young's modulus, bulk density, and the Poisson's ratio for the tested lithologies. We find that under the same flow conditions, erosion rates of samples from the same lithology can vary by a factor of up to 60. This indicates that rock properties that may vary over short distances within the same rock can exert a strong control on its erosional properties. The geotechnical properties of the tested lithologies are strongly cross-correlated, preventing a purely empirical determination of their controls on erodibility. The currently prevailing model predicts that erosion rates should scale linearly with Young's modulus and inversely with the square of the tensile strength. We extend this model using first-principle physical arguments, taking into account the geotechnical properties of the impactor. The extended model provides a better description of the data than the existing model. Yet, the fit is far from satisfactory. We suggest that the ratio of mineral grain size to the impactor diameter presents a strong control on erodibility that has not been quantified so far. We also discuss how our laboratory results upscale to real landscapes and long timescales. For both a revised stream power incision model and a sediment-flux-dependent incision model, we suggest that long-term erosion rates scale linearly with erodibility and that, within this theoretical framework, relative laboratory measurements of erodibility can be applied at the landscape scale.
<p>The portion of boulders considered to be rarely mobile is thought to impact the geomorphic response of landscapes to tectonic activity and climate. Recent studies demonstrated that boulders modify hillslope and river processes, implying that their long-lasting presence is consequential for landscape form. Understanding the relationship between geomorphic features and boulders thus poses vital information for extracting valuable geomorphic parameters. However, due to the scarcity of data encompassing both boulder parameters and associated hillslope and river morphologies, the impact of boulders on landscape form remains unclear. We have investigated the roles of boulders in landscape modification by conducting a laboratory experiment at a landscape scale. The experiment included an initial phase, where a fluvial topography evolved under uniform uplift and rainfall by incision into a substrate crafted of saturated silica powder. The second phase simulated landscape response to the emplacement of boulders along main trunk channels. Spheres with uniform sizes of 1.5 mm were placed along seven main trunks belonging to basins that drain the eastern experimental mountain flank, and the experiment was allowed to continue. 3D models of the evolving topography were generated every 20\30 minutes. Our analysis reveals that following the emplacement of boulders, the landscape changed its form at a range of spatial scales. At the cross-section scale, the hydraulic geometry scaling relationships were altered where boulders were present in the channel. At the catchment scale, topographic inversion was observed, with tributaries transforming into ridges. At the channel profile scale, perched reaches bounded by knickzones developed. Concurrently, the main drainage divide migrated towards the boulder-covered flank. This multitude of modifications in landscape features at a wide range of scales is interpreted to result from extensive and persistent boulder cover inhibiting local fluvial vertical erosion. The altered morphologies presumably promote a new erosional steady-state under the influence of boulder cover.</p>
Abstract Recent theoretical models and field observations suggest that fluvial bedload flux can be estimated from seismic energy measured within appropriate frequency bands. We present an application of the Tsai et al. (2012, https://doi.org/10.1029/2011gl050255 ) bedload seismic model to an ephemeral channel located in the semi‐arid southwestern US and incorporate modifications to better estimate bedload flux in this environment. To test the model, we collected streambank seismic signals and directly measured bedload flux during four flash‐floods. Bedload predictions calculated by inversion from the Tsai model underestimated bedload flux observations by one‐to‐two orders of magnitude at low stages. However, model predictions were better for moderate flow depths (>50 cm), where saltation is expected to dominate bedload transport. We explored three differences between the model assumptions and our field conditions: (a) rolling and sliding particles have different impact frequencies than saltating particles; (b) the velocity and angle of impact of rolling particles onto the riverbed differ; and (c) the fine‐grained alluvial character of this and similar riverbeds leads to inelastic impacts, as opposed to the originally conceptualized elastic impacts onto rigid bedrock. We modified the original model to assume inelastic bed impacts and to incorporate rolling and sliding by adjusting the statistical distributions of bedload impact frequency, velocity, and angle. Our modified “multiple‐transport‐mode bedload seismic model” decreased error relative to observations to less than one order of magnitude across all measured flow conditions. Further investigations in other environmental settings are required to demonstrate the robustness and general applicability of the model.
Abstract. In active mountain belts with steep terrain bedrock landsliding is a major erosional agent. In the Himalayas, landsliding is driven by annual hydro-meteorological forcing due to the summer monsoon and by rarer, exceptional events, such as earthquakes. Independent methods yield erosion rate estimates that appear to increase with sampling time, suggesting that rare, high magnitude erosion events dominate the erosional budget. Nevertheless, until now, neither the contribution of monsoon and earthquakes to landslide erosion, nor the proportion of erosion due to rare, giant landslides have been quantified in the Himalayas. We address these challenges by combining and analyzing earthquake and monsoon induced landslide inventories across different timescales. With time-series of 5 m satellite images over four main valleys in Central Nepal, we comprehensively mapped landslides caused by the monsoon from 2010 to 2018. We found no clear correlation between monsoon properties and landsliding, and a similar mean landsliding rate for all valleys, except in 2015, where the valleys affected by the earthquake featured ~ 5–8 times more landsliding than the pre-earthquake mean rate. The long-term size-frequency distribution of monsoon induced landslides (MIL) was derived from these inventories and from an inventory of landslides larger than ~ 0.1 km2 that occurred between 1972 and 2014. Using a published landslide inventory for the Gorkha 2015 earthquake, we derive the size-frequency distribution for earthquake-induced landslides (EQIL). These two distributions are dominated by infrequent, large and giant landslides, but underpredict an estimated Holocene frequency of giant landslides (> 1 km3) which we derived from a literature compilation. This discrepancy can be resolved when modelling the effect of a full distribution of earthquake of variable magnitude and considering that shallower earthquake may cause larger landslides. In this case, EQIL and MIL contribute about equally to a total long-term erosion of ~ 2 ± 0.75 mm.yr−1 in agreement with most thermochronological data. Independently of the specific total and relative erosion rates, the heavy-tailed size-frequency distribution from MIL and EQIL and the very large maximal landslide size in the Himalayas indicate that mean landslide erosion rates increase with sampling time, as has been observed for independent erosion estimates. Further, we find that the sampling time scale required for adequately capturing the frequency of the largest landslides, which is necessary for deriving long-term mean erosion rates, is often much longer than the averaging time of cosmogenic 10Be methods. This observation presents a strong caveat when interpreting spatial or temporal variability of erosion rates from this method.
Abstract. Heavy precipitation can suddenly mobilize tens to hundreds of thousands of cubic meters of sediments in steep Alpine torrents. The resulting debris flows (mixtures of water, sediments and boulders) move downstream with velocities of several meters per second and have a high destructive potential. Warning schemes for affected communities rely on raising awareness to the debris flow threat, precipitation monitoring and rapid detection methods. The latter, in particular, remain an ongoing challenge, because debris-flow-prone torrents have their catchments in steep and inaccessible terrain, where installing and maintaining instrumentation is difficult. Here, we propose a simple processing scheme for seismic network data. We use debris flow and noise seismograms from Illgraben, Switzerland, a torrent, which produces several debris flow events per year. Automatic in-situ detection is currently based on geophones mounted on concrete check dams and radar stage sensors hung above the channel. The proposed approach has the advantage that it uses seismometers, which can be installed at more accessible locations, and where a stable connection to portable phone networks is available for data communication. Our data processing uses time-averaged ground vibration amplitudes to estimate the location of the debris flow front. Applied to continuous data streams, inversion of the seismic amplitude decay eliminates the need for single-station-based detection and knowledge of the local seismic velocity model. This makes the approach suitable for automation, as seismic phase identification is unnecessary and the amplitude averaging significantly reduces data volume. We apply our approach to a small debris flow event on 19 July 2011, which was captured with a temporary monitoring network. The processing rapidly detects the debris flow event half an hour before its front arrives at the torrent mouth and 8 minutes before detection by the current alarm system. An analysis of continuous seismic records furthermore indicates that detectability of Illgraben debris flows of this size are unaffected by changing environmental and cultural seismic noise. We therefore propose that our method reliably detects initiation of the Illgraben debris flows and can thus form an important ingredient in the next generation of early warning schemes.
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