Soil moisture causes dynamic adjustments to root reinforcement that reduce slope stability

In steep soil-mantled landscapes, the initiation of shallow landslides is strongly controlled by the distribution of vegetation, whose roots reinforce the soil. The magnitude of root reinforcement depends on the number, diameter distribution, orientation and the mechanical properties of roots that cross potential failure planes. Understanding how these properties vary in space and time in forests remains a significant challenge. Here we test the hypothesis that spatio-temporal variations in root reinforcement along a hillslope occur as a function of topographic soil moisture gradients. To test this hypothesis we compared root reinforcement measurements from relatively dry, divergent noses to relatively wet, convergent hollows in the southern Appalachian Mountains, North Carolina, USA. Our initial results showed that root reinforcement decreased in areas of higher soil moisture because the tensile strength of roots decreased. A post-hoc laboratory experiment further demonstrated that root tensile strength decreased as root moisture content increased. This effect is consistent with other experiments on stem woods showing that increased water content in the cell wall decreases tensile strength. Our experimental data demonstrated that roots can adjust to changes in the external root moisture conditions within hours, suggesting that root moisture content will change over the timescale of large storm events (hours-days). We assessed the effects of the dynamic changes in root tensile strength to the magnitude of apparent cohesion within the infinite slope stability model. Slopes can be considerably less stable when precipitation-driven increases in saturated soil depth both increase pore pressures and decrease root reinforcement. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved

Shallow landslides and vegetation at the catchment scale: A perspective

Shallow, rainfall-triggered landslides are an important catchment process that affect the rate and calibre of sediment within river networks and create a significant hazard, particularly when shallow landslides transform into rapidly moving debris flows. Forests and trees modify the magnitude and rate of shallow landsliding and have been used by land managers for centuries to mitigate their effects. We understand that at the tree and slope scale root reinforcement provides a significant role in stabilising slopes, but at the catchment scale root reinforcement models only partially explain where shallow landslides are likely to occur due to the complexity of subsurface material properties and hydrology. The challenge of scaling from slopes to catchments (from 1-D to 2-D) reflects the scale gap between geomorphic process understanding and modelling, and temporal evolution of material properties. Hence, our understanding does not, as yet, provide the necessary tools to allow vegetation to be targeted most effectively for landslide reduction. This paper aims to provide a perspective on the science underpinning the challenges land and catchment managers face in trying to reduce shallow landslide hazard, manage catchment sediment budgets, and develop tools for catchment targeting of vegetation. We use our understanding of rainfall-triggered shallow landslides in New Zealand and how vegetation has been used as a tool to reduce their incidence to demonstrate key points

The application of frameworks for measuring social vulnerability and resilience to geophysical hazards within developing countries: A systematic review and narrative synthesis

Quantifying and mapping resilience and social vulnerability is a widely used technique to support risk management, with recent years seeing a proliferation of applications across the Global South. To synthesise this emerging literature, we conducted a systematic review of applications of social vulnerability and resilience frameworks in Lower and Middle Income Countries (LMICs) using the PRISMA methodology. 2152 papers were extracted from 16 databases and then screened according to our pre-defined criteria, leaving 68 studies for full text analysis. Our analysis revealed that: (1) Most studies consider vulnerability or resilience to be generic properties of social systems; (2) Few papers measured vulnerability or resilience in a way that tests whether they are relatively stable or dynamic features of social systems; (3) Many applications rely on stock applications of existing frameworks, with little adaptation to specific cultural, societal or economic contexts; (4) There is a lack of systematic validation; (5) More hypothesis-driven studies (as opposed to descriptive mapping exercises) are required in order to develop a better understanding of the mechanisms through which vulnerability and resilience shape the capacity to prepare for, respond and recover from disasters

A Fractal Framework for Channel-Hillslope Coupling

Questions of landscape scale in coupled channel-hillslope landscape evolution have been a significant focus of geomorphological research for decades. Studies to date have suggested a characteristic landscape length that marks the shift from fluvial channels to hillslopes, limiting fluvial incision and setting the length of hillslopes. The representation of real-world landscapes in slope-area plots, however, makes it challenging to identify the exact transition from hillslopes to channels, owing to the existence of an intermediary colluvial valley region. Without a rigorous explanation for the scaling of the channel hillslope transition, the use of computational models, which are forced to implement a finite grid resolution, is limited by the scaling of the physical parameters of the model relative to the grid resolution. Grid resolution is also tied to the width of channels, which is undetermined without a rigorous explanation of where channels begin. Building on existing work, we demonstrate the existence and implications of the characteristic landscape length and its relationship to grid resolution. We derive the characteristic landscape length as the horizontal length in a one-dimensional landscape evolution framework required to form an inflection point. On a two-dimensional domain, channel heads form in steady state at the characteristic area, the square of the characteristic length, independent of grid resolution. We present a box-counting fractal definition using the grid resolution, revealing that the dimension of the contributing drainage region on steady-state hillslopes is expressed as a multifractal system. In sum, channels have contributing drainage areas, therefore a dimension of two, whereas, by definition, unchannelized locations or nodes have a dimension between zero and two, so not a well-defined area. This conceptualization aligns with the observed scaling of channel width. It also importantly suggests that real-world landscapes have something analogous to the concept of a grid resolution, as this paper demonstrates. In doing so, our works clarifies several unresolved properties of channel-hillslope coupling, with potential for substantially improving the accuracy of coupled landscape evolution models in replicating landscape forms

Modification of river meandering by tropical deforestation

Tropical forests are the only forest biome to have experienced increased rates of forest loss during the past decade because of global demands for food and biofuels. The implications of such extensive forest clearing on the dynamics of tropical river systems remain relatively unknown, despite significant progress in our understanding of the role of trees in riverbank stability. Here, we document rates of deforestation and corresponding average annual rates of riverbank erosion along the freely meandering Kinabatangan River in Sabah, Malaysia, from Landsat satellite imagery spanning A.D. 1989–2014. We estimate that deforestation removed over half of the river’s floodplain forest and up to 30% of its riparian cover, which increased rates of riverbank erosion by >23% within our study reaches. Further, the correlation between the magnitude of planform curvature and rates of riverbank erosion only became strongly positive and significant following deforestation, suggesting an important role of forests in the evolution of meandering rivers, even when riverbank heights exceed the depth of root penetration

Modelling the role of material depletion, grain coarsening and revegetation in debris flow occurrences after the 2008 Wenchuan earthquake

A large amount of debris was generated by the co-seismic mass wasting associated with the 2008 Mw 7.9 Wenchuan earthquake. The abundance of this loose material along the slopes caused more frequent debris flows, triggered by less intense and/or shorter rainfalls. However, both the triggering rainfall and the debris flow frequency seem to have normalised progressively during the past decade. Although changes of rainfall thresholds for post-seismic debris flows were recorded after several major earthquakes, the factors controlling these changes remain poorly constrained. With the aid of a virtual experiment, we investigate the roles of material depletion, grain coarsening and revegetation of the co-seismic debris on the propagation and deposition of debris flows initiated by runoff, as well as their influence on the triggering rainfall thresholds. We employ a Geographic Information System (GIS)-based simulation of debris flow initiation by runoff erosion, which we first calibrate on the 14th August 2010 Hongchun gully event that occurred near the Wenchuan earthquake epicentre. We obtain, by investigating each of the aforementioned processes, changing critical rainfall intensity-duration thresholds for given debris flow runout distances. Grain coarsening appears to play a major role, which is consistent with published laboratory experiments, while material depletion and revegetation do not seem able to account alone for the actual quick decay of debris flow frequency. While the virtual experiment has proven useful in identifying the first-order controls on this decay, model improvements and verification over multiple catchments are needed to make the results useful in hazard assessments

Identifying post-earthquake debris flow hazard using Massflow

Catastrophic debris flows are common after large earthquakes and pose a significant risk for recovering communities. The depositional volume of these large debris flows is often much greater than the initiation volume, suggesting that bulking of the flow plays an important role in determining their volume, speed, and runout distance. Observations from recent earthquakes have driven progress in understanding the relationship between triggering rainfall events and the timing of post-earthquake debris flows. However, we lack an adequate mechanism for quantifying bulking and applying it within a hazard context. Here we apply a 2D dynamic debris flow model (Massflow) that incorporates a process-based expression of basal entrainment to understand how debris flow bulking may occur within post-earthquake catchments and develop hazard maps. Focussing on catchments in the epicentral area of the 2008 Mw 7.9 Wenchuan Earthquake, we first parameterised the model based on a large debris flow that occurred within the Hongchun catchment, before applying the calibrated model to adjoining catchments. A model sensitivity analysis identified three main controls on debris flow bulking; the saturation level of entrainable material along the flow pathway, and the size and position of initial mass failures. The model demonstrates that the difference between small and very large debris flows occur across a narrow range of pore-water ratios (λ). Below λ = 0.65 flows falter at the base of hillslopes and come to rest in the valley bottom, above λ = 0.70 they build sufficient mass and momentum to sustain channelised flow and transport large volumes of material beyond the valley confines. Finally, we applied the model across different catchments to develop hazard maps that demonstrate the utility of Massflow in post-earthquake planning within the Wenchuan epicentral region

The fate of sediment after a large earthquake

Large earthquakes rapidly denude hillslopes by triggering thousands of coseismic landslides. The sediment produced by these landslides is initially quickly mobilised from the landscape by an interconnected cascade of processes. This cascade can dramatically but briefly enhance local erosion rates. Hillslope and channel processes, such as landsliding and debris flows, interact to influence the total mass, caliber, and rate of sediment transport through catchments. Calculating the sediment budget of an earthquake lends insight into the nature of these interactions. Using satellite imagery derived landslide inventories, channel surveys and a literature review combined with a Monte Carlo simulation approach we present a constrained sediment budget of the first decade after the 2008 Mw7.9 Wenchuan earthquake. With this sediment budget we demonstrate that debris flows are dominant process for delivering sediment into channels and that large volumes of sediment remain in the landscape. In our study area over 88% (469.7 Mega tonnes) of the coseismically generated sediment remains on the hillslopes in 2018. Of the 12% of the sediment that was mobilised, 67% (45.2 ± 22 Mt) was mobilised by debris flows. Despite the large proportion of sediment remaining on the hillslope, the frequency of debris flows declined significantly over our observation period. The reduction in debris-flow frequency is not correlated to reductions in the frequency of triggering storms, suggesting changes in the mechanical properties of hillslope sediment may drive this observation. The stabilization of coseismically generated sediment greatly extends its residence time and may influence catchment sediment yields for centuries or millennia

Topographic and ecologic controls on root reinforcement

Shallow landslides are a significant hazard in steep, soil-mantled landscapes. During intense rainfall events, the distribution of shallow landslides is controlled by variations in landscape gradient, the frictional and cohesive properties of soil and roots, and the subsurface hydrologic response. While gradients can be estimated from digital elevation models, information on soil and root properties remains sparse. We investigated whether geomorphically controlled variations in ecology affect the spatial distribution of root cohesion by measuring the distribution and tensile strength of roots from soil pits dug downslope of 15 native trees in the southern Appalachian Mountains, North Carolina, United States. Root tensile strengths from different hardwood tree species were similar and consistently higher than the only native shrub species measured (Rhododendron maximum). Roots were stronger in trees found on noses (areas of divergent topography) relative to those in hollows (unchanneled, convergent topography) coincident with the variability in cellulose content. This cellulose variability is likely related to topographic differences in soil water potential. For all species, roots were concentrated close to the soil surface, with roots in hollows being more evenly distributed in the soil column than those on noses. Trees located on noses had higher mean root cohesion than those in hollows because of a higher root tensile force. R. maximum had the shallowest, weakest roots suggesting that recent expansion of this species due to fire suppression has likely lowered the root cohesion of some hollows. Quantification of this feedback between physiologic controls on root growth and slope hydrology has allowed us to create a curvature-based model of root cohesion that is a significant improvement on current models that assume a spatially averaged value

A hybrid machine-learning model to estimate potential debris-flow volumes

Empirical-statistical models of debris-flow are challenging to implement in environments where sedimentary and hydrologic triggering processes change through time, such as after a large earthquake. The flexible and adaptive statistical methods provided by machine learning algorithms may improve the quality of debris flow predictions where triggering conditions and the nature of sediment that can bulk flows varies with time. We developed a hybrid machine-learning model of future debris-flow volumes using a dataset of measured debris-flow volumes from 60 catchments that generated post-Wenchuan Earthquake (Mw 7.9) debris flows. We input topographic variables (catchment area, topographic relief, channel length, distance from seismic fault, and average channel gradient) and the total volume of co-seismic landslide debris into the PSO-ELM_AdaBoost machine-learning model, created by combining Extreme learning machine (ELM), particle swarm optimization (PSO) and adaptive boosting machine learning algorithm (AdaBoost). The model was trained and tested using post-2008 Mw 7.9 Wenchuan Earthquake debris flows, then applied to understand potential volumes of post-earthquake debris flows associated with other regional earthquakes (2013 Mw 6.6 Lushan Earthquake, 2010 Mw 6.9 Yushu Earthquake). We compared the PSO-ELM_Adaboost method with different machine learning methods, including back-propagation neural network (BPNN), support vector machine (SVM), ELM, PSO-ELM. The Comparative analysis demonstrated that the PSO-ELM_Adaboost method has a higher statistical validity and prediction accuracy with a mean absolute percentage error (MAPE) less than 0.10. The prediction accuracy of debris-flow volumes trigged by other earthquakes decreases to 0.11–0.16 (absolute percentage error), suggesting that once calibrated for a region this method can be applied to other regional earthquakes. This model may be useful for engineering design to mitigate the risk of large post-earthquake debris flows