The complex interplay of biological, physical, and chemical processes in pedogenesis and hillslope evolution limits our ability to predict and interpret landscape dynamics. Here, we synthesize a ...suite of observations from the steep, forested Oregon Coast Range to analyze the role of trees in topographic modification and bedrock-to-soil conversion. Using topographic data derived from airborne lidar, we demonstrate that the topographic signature of forest-driven soil and bedrock disturbance is pervasive. For length scales greater than 7.5
m, the land surface is defined by ridge-valley landforms, whereas smaller scales are dominated by pit-mound features generated by the turnover of large coniferous trees. From field surveys, the volume of bedrock incorporated in overturned rootwads increases rapidly with diameter for large conifers, reflecting the highly nonlinear increase in root biomass with tree diameter. Because trees younger than 60
years detach negligible bedrock, short timber harvest intervals may limit the extent to which root systems penetrate bedrock and facilitate bedrock fracturing and biogeochemical weathering. Using ground-penetrating radar, we show that the rootwads of large trees root achieve substantial penetration (1–3
m) into shallow bedrock. The radar transects also reveal that variations in soil thickness have characteristic length scales of 1 to 5
m, consistent with the scale of large rootwads, indicating that both the landscape surface and soil-bedrock interface exhibit a biogenic imprint. In our study area, the residence time of bedrock within dense rooting zones directly below large trees is similar to the time required for trees to occupy the entire forest floor through multiple cycles of forest succession, suggesting that biological modification of shallow bedrock is ubiquitous. Given increases in erosion rate, the ability of roots to initiate soil production may decline as bedrock exhumation through the biotic zone is rapid relative to the time required for successive forests and their associated root systems to fracture bedrock. As a result, in rapidly eroding terrain the coupling between biotic and abiotic weathering processes (such as exfoliation fracturing) may dictate the maximum rate of bedrock-to-soil conversion.
In mountainous landscapes the role of periglacial processes in producing sediment is poorly defined, despite evidence of abundant talus slopes. Ice growth in rock has long been recognized as an ...efficient erosion mechanism, but the effects have not been readily applied to landscape evolution in response to tectonic and climatic forcing. Here, we quantify how and where ice‐driven mechanical erosion occurs in cold, bedrock‐dominated landscapes using a simple one‐dimensional numerical heat flow model. In our model, ice grows by water migration to colder regions in shallow rock by the reduction in chemical potential associated with intermolecular forces between ice and mineral surfaces, a process called segregation ice growth. The depth and intensity of frost cracking is primarily dependent on mean annual temperature (MAT), with positive MAT sites characterized by intense cracking in the top meter of the rock mass and a maximum frost penetration of ∼4 m. In contrast, negative MAT areas have less intense cracking that primarily occurs at depths between 50 and 800 cm. We compare the depth and intensity of frost cracking predicted by our model with measures of the intensity of frost processes determined in three studies: The first measured the timing of rockfall in the Canadian Rockies, Niagara Escarpment, and Japanese Alps; the second analyzed scree deposits in the Southern Alps, New Zealand; and the third documented rockfall frequency in Utah. These natural examples show that rockfalls tend to nucleate at elevations that coincide with zones of intense frost cracking predicted by our model. As such, climatic variations associated with interglacial‐glacial cycles may impart a significant influence on the denudation of mountainous landscapes.
Catastrophic landslides cause billions of dollars in damages and claim thousands of lives annually, whereas slow-moving landslides with negligible inertia dominate sediment transport on many ...weathered hillslopes. Surprisingly, both failure modes are displayed by nearby landslides (and individual landslides in different years) subjected to almost identical environmental conditions. Such observations have motivated the search for mechanisms that can cause slow-moving landslides to transition via runaway acceleration to catastrophic failure. A similarly diverse range of sliding behavior, including earthquakes and slow-slip events, occurs along tectonic faults. Our understanding of these phenomena has benefitted from mechanical treatments that rely upon key ingredients that are notably absent from previous landslide descriptions. Here, we describe landslide motion using a rate- and state-dependent frictional model that incorporates a nonlocal stress balance to account for the elastic response to gradients in slip. Our idealized, one-dimensional model reproduces both the displacement patterns observed in slow-moving landslides and the acceleration toward failure exhibited by catastrophic events. Catastrophic failure occurs only when the slip surface is characterized by rate-weakening friction and its lateral dimensions exceed a critical nucleation length h* that is shorter for higher effective stresses. However, landslides that are extensive enough to fall within this regime can nevertheless slide slowly for months or years before catastrophic failure. Our results suggest that the diversity of slip behavior observed during landslides can be described with a single model adapted from standard fault mechanics treatments.
Precipitation drives seasonal velocity changes in slow-moving landslides by increasing pore-water pressure and reducing the effective normal stress along basal shear zones. This pressure change is ...often modeled as a pore-water pressure wave that diffuses through the landslide body, such that the minimum time required for landslides to respond to rainfall should vary as the square of landslide depth (which often approximates the saturated thickness) and inversely with hydraulic diffusivity. Here, we assess this model with new observations from the landslide-prone Eel River catchment, Northern California. Using satellite radar interferometry (InSAR) time series, precipitation data, and high-resolution topographic data from airborne lidar, we quantify the seasonal dynamics of 10 slow-moving landslides, which share the same lithologic, tectonic, and Mediterranean climate conditions. These slope failures have areas ranging from 0.16 to 3.1 km2, depths that vary from 8 to 40 m, and average downslope velocities of 0.2 to 1.2 m/yr. Each slide exhibits well-defined seasonal velocity changes with a periodicity of ∼1 yr and responds (i.e., accelerates) within 40 days following the onset of rainfall. Despite a five-fold variation in landslide depth, we do not detect systematic differences in response time within the resolution of our observations. Our results could imply that: 1) slides in our study area are sensitive to subtle hydrologic perturbations, 2) the ‘effective’ diffusivity governing slide behavior is much higher than field-derived values because pore pressure transmission and slide dynamics are facilitated by preferential flow paths, particularly cracks related to deformation and seasonal shrink-swell cycles, or 3) a simple one-dimensional linear diffusion model may fail to capture the three-dimensional time-dependent hydrologic changes inherent in an evolving mechanical–hydrologic system, such as a slow-moving landslide.
•Landslide velocities vary seasonally and lag onset of rainfall by 40 days.•Velocity patterns are driven by precipitation-induced changes in pore-water pressure.•Narrow range of response times belie substantial variation in landslide depth.•Slides have self-organized to maintain a narrow range of pore-water pressures.•Our observations challenge existing hydrologic models for landslides.
Frost damage is a powerful agent of geomorphic change. Cracks can grow when the ice pressure in pores reaches a threshold that depends on matrix properties and crack geometry. Mineral surfaces that ...are preferentially wetted by liquid water rather than ice are coated by premelted liquid at a pressure that is lower than the ice pressure. Because this pressure difference increases as the temperature cools, when the ice pressure is effectively pinned at the cracking threshold, temperature gradients induce gradients in liquid pressure that draw water towards colder temperatures. Porosity increases and frost damage accumulates in regions where water supplies crack growth. To apply this understanding over the large spatial and temporal scales that are relevant to evolving landscapes, we develop a simple model that tracks porosity changes. Our central assumption is that frost damage is correlated with porosity increases under conditions where frost cracking takes place. Accordingly, we account for the permeability reductions with decreased temperature that accompany ice growth along porous pathways and derive general expressions for the porosity change through time at particular depths, as well as the total porosity increase through all depths beneath a point at the ground surface over the time during which cracking occurs each year. To illustrate the resulting patterns of frost weathering, we consider a general case in which the permeability has a power law dependence on temperature and the annual surface-temperature variation is sinusoidal. We find that the degree of frost damage generally decreases with depth, except at localized depths where damage is elevated because the rock spends longer times near the threshold for cracking, leading to enhanced water supply in comparison with neighboring regions. The magnitude of the net expansion that results from porosity changes at all depths beneath the ground surface is increased for seasonal thermal cycles with larger amplitudes, with a broad maximum centered on a mean annual temperature near the threshold required for crack growth. Warmer mean annual temperatures lead to less damage because of the reduction in time during which it is cold enough for cracking, whereas colder mean annual temperatures are accompanied by reduced water supply due to the temperature dependence of permeability. All of the controlling parameters in our model are tied explicitly to physical properties that can in principle be measured independently, which suggests promise for informing geomorphic interpretations of the role of frost weathering in evolving landforms and determining erosion rates.
•New bedrock weathering model predicts porosity increases driven by frost cracking.•Permeability drop with ice formation causes flux gradients that drive cracking/damage.•Greatest damage occurs at temperatures just cold enough for ice to propagate cracks.•Climate-dependent median depth for integrated damage within approx. 2 m of surface.•Model parameters tied to physical properties, allowing for testing across sites.
Debris flows pose persistent hazards and shape high‐relief landscapes in diverse physiographic settings, but predicting the spatiotemporal occurrence of debris flows in postglacial topography remains ...challenging. To evaluate the debris flow process in high‐relief postglacial terrain, we conducted a geomorphic investigation to characterize geologic, glacial, volcanic, and land use contributions to landslide initiation across Southeast Alaska. To evaluate controls on landslide (esp. debris flow) occurrence in Sitka, we used field observation, geomorphic mapping, landslide characteristics as documented in the Tongass National Forest inventory, and a novel application of the shallow landslide model SHALSTAB to postglacial terrain. A complex geomorphic history of glaciation and volcanic activity provides a template for spatially heterogeneous landslide occurrence. Landslide density across the region is highly variable, but debris flow density is high on south‐ or southeast‐facing hillslopes where volcanic tephra soils are present and/or where timber harvest has occurred since 1900. High landslide density along the western coast of Baranof and Kruzof islands coincides with deposition of glacial sediment and thick tephra and exposure to extreme rainfall from atmospheric rivers on south‐facing aspects but the relative contributions of these controls are unclear. Timber harvest has also been identified as an important control on landslide occurrence in the region. Focusing on a subset of geo‐referenced landslides near Sitka, we used the SHALSTAB shallow landslide initiation model, which has been frequently applied in non‐glacial terrain, to identify areas of high landslide potential in steep, convergent terrain. In a validation against mapped landslide polygons, the model significantly outperformed random guessing, with area under the curve (AUC) = 0.709 on a performance classification curve of true positives vs. false positives. This successful application of SHALSTAB demonstrates practical utility for hazards analysis in postglacial landscapes to mitigate risk to people and infrastructure.
We conducted a geomorphic investigation to characterize the geomorphic histories that influence landslide initiation in postglacial terrain. Near Sitka, Southeast Alaska, we found that debris flow density is greatest on south‐ or southeast‐facing hillslopes where volcanic soils overlie till, where timber harvest has occurred since 1900, and where slope angle and contributing area are large. We also find that the topographic landslide susceptibility model SHALSTAB successfully predicts landslide‐prone areas in a postglacial landscape.
The role of fire in shaping steep, forested landscapes depends on a suite of hydrologic, biologic, and geological characteristics, including the propensity for hydrophobic soil layers to promote ...runoff erosion during subsequent rainfall events. In the Oregon Coast Range, several studies postulate that fire primarily modulates sediment production via root reinforcement and shallow landslide susceptibility, although few studies have documented post-fire geomorphic response. Here, we describe field observations and topographic analyses for three sites in the central Oregon Coast Range that burned in 1999, 2002, and 2003. The fires generated strongly hydrophobic soil layers that did not promote runoff erosion because the continuity of the layers was interrupted by pervasive discontinuities that facilitated rapid infiltration. At each of our sites, fire generated significant colluvial transport via dry ravel, consistent with other field-based studies in the western United States. Fire-driven dry ravel accumulation in low-order valleys of our Sulphur Creek site equated to a slope-averaged landscape lowering of 2.5
mm. Given Holocene estimates of fire frequency, these results suggest that fire may contribute 10–20% of total denudation across steep, dissected portions of the Oregon Coast Range. In addition, we documented more rapid decline of root strength at our sites than has been observed after timber harvest, suggesting that root strength was compromised prior to fire or that intense heat damaged roots in the shallow subsurface. Given that fire frequencies in the Pacific Northwest are predicted to increase with continued climate change, our findings highlight the importance of fire-induced dry ravel and post-fire debris flow activity in controlling sediment delivery to channels.
Largely unknown mechanisms restrain motion of clay‐rich, slow‐moving landslides that are widespread worldwide and rarely accelerate catastrophically. We studied a clayey, slow‐moving landslide ...typical of thousands in Northern California, USA, to decipher hydrologic‐mechanical interactions that modulate landslide dynamics. Similar to some other studies, observed pore‐water pressures correlated poorly with landslide reactivation and speed. In situ and laboratory measurements strongly suggested that variable pressure along the landslide's lateral shear boundaries resulting from seasonal soil expansion and contraction modulated its reactivation and speed. Slope‐stability modeling suggested that the landslide's observed behavior could be predicted by including transient swell pressure as a resistance term, whereas modeling considering only transient hydrologic conditions predicted movement five to six months prior to when it was observed. All clayey soils swell to some degree; hence, our findings suggest that swell pressure likely modulates motion of many landslides and should be considered to improve forecasts of clayey landslide initiation and mobility.
Key Points
Observed earthflow timing and speed correlated poorly with pore‐water pressure
Swelling of clayey soil increases landslide shear resistance concurrent with increasing pore‐water pressure decreasing shear resistance
The combined effects of lateral shear resistance from soil swelling and basal pore‐water pressure can explain earthflow timing and mobility
Empirical thresholds for landslide warning systems have benefitted from the incorporation of soil‐hydrologic monitoring data, but the mechanistic basis for their predictive capabilities is limited. ...Although physically based hydrologic models can accurately simulate changes in soil moisture and pore pressure that promote landslides, their utility is restricted by high computational costs and nonunique parameterization issues. We construct a deep learning model using soil moisture, pore pressure, and rainfall monitoring data acquired from landslide‐prone hillslopes in Oregon, USA, to predict the timing and magnitude of hydrologic response at multiple soil depths for 36‐hr intervals. We find that observation records as short as 6 months are sufficient for accurate predictions, and our model captures hydrologic response for high‐intensity rainfall events even when those storm types are excluded from model training. We conclude that machine learning can provide an accurate and computationally efficient alternative to empirical methods or physical modeling for landslide hazard warning.
Plain Language Summary
Rainfall‐triggered landsliding is widespread, damaging, and deadly. These landslides are also difficult to predict and require complex models to completely assess the risk of a single area. This is a time‐ and resource‐intensive process that makes it difficult to easily integrate into a system designed to give residents early warning of a potential landslide in their community. In an effort to work around these limitations, we introduce an alternative model based on artificial intelligence, which only requires a few minutes to develop and relies on easy‐to‐record information such as rainfall and soil moisture. We find this new model accurately forecasts essential information for establishing landslide risk and does so in significantly less time than similarly performing models. Therefore, when presented with the need to help inform community decision making, we encourage this type of modeling, given it takes little time to develop and produces accurate predictions of essential information for assessing community risk.
Key Points
We test the efficacy of using Deep Learning to forecast subsurface hydrologic response for hillslopes that are prone to shallow landsliding
The model produces pore pressure predictions for landslide‐relevant conditions up to 36‐hr in advance with as little as 6 months of data
Our work encourages further exploration of machine learning as part of the development of landslide warning systems
Particle motion on burned and vegetated hillslopes Roth, Danica L.; Doane, Tyler H.; Roering, Joshua J. ...
Proceedings of the National Academy of Sciences - PNAS,
10/2020, Letnik:
117, Številka:
41
Journal Article
Recenzirano
Odprti dostop
Climate change is causing increasingly widespread, frequent, and intense wildfires across the western United States. Many geomorphic effects of wildfire are relatively well studied, yet sediment ...transport models remain unable to account for the rapid transport of sediment released from behind incinerated vegetation, which can fuel catastrophic debris flows. This oversight reflects the fundamental inability of local, continuum-based models to capture the long-distance particle motions characteristic of steeplands. Probabilistic, particle-based nonlocal models may address this deficiency, but empirical data are needed to constrain their representation of particle motion in real landscapes. Here we present data from field experiments validating a generalized Lomax model for particle travel distance distributions. The model parameters provide a physically intuitive mathematical framework for describing the transition from light- to heavy-tailed distributions along a continuum of behavior as particle size increases and slopes get steeper and/or smoother. We show that burned slopes are measurably smoother than vegetated slopes, leading to 1) lower rates of experimental particle disentrainment and 2) runaway motion that produces the heavy-tailed travel distances often associated with nonlocal transport. Our results reveal that surface roughness is a key control on steepland sediment transport, particularly after wildfire when smoother surfaces may result in the preferential delivery of coarse material to channel networks that initiate debris flows. By providing a first-order framework relating the statistics of particle motion to measurable surface characteristics, the Lomax model both advances the development of nonlocal sediment transport theory and reveals insights on hillslope transport mechanics.
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