The Art of Landslides: How Stochastic Mass Wasting Shapes Topography and Influences Landscape Dynamics

Abstract

Landslides can produce sediment at rates that exceed the maximum rate of sediment generation by weathering processes (Dixon & von Blanckenburg, 2012), and can trigger a chain of processes that alter the pathways of sediment from source to sink (Fan et al., 2019). The continuously growing data realm of remotely sensed Earth observations and analytical measurements such as cosmogenic radionuclide (CRN) derived erosion rates helps to better understand the impact of mass movements on evolving surfaces (e.g., DeLisle et al., 2022;Depicker et al., 2021). Yet, quantifying the impact of landslides on the evolution of landscapes over large spatial and temporal scales requires computational models that explicitly simulate sediment production, mobilization, and aggradation.Although topographic relief is a necessary condition for-and a dominant control on-landslide susceptibility (Pourghasemi et al., 2018), process-based understanding of how landslides shape terrain is currently lacking. Over timescales relevant to the formation of topography, landslides, and other forms of mass wasting are thought to impose an upper limit to relief based on rock strength (Schmidt & Montgomery, 1995;Selby, 1982). Landsliding is often held to effectively impose a threshold slope angle on a landscape. Threshold theory implies that

Tectonic advection of contacts enhances landscape transience

“…For example, channel steepness depends heavily on streamflow direction (Figure 9). Although this behavior is quite pronounced in our models, it might be less pronounced in models incorporating both landslides and sediment dynamics (Campforts et al, 2022) (i.e., due to increased stochasticity). In our models, the exposure of the weak unit also causes a gradual decline in the channel steepness of the strong unit (Figures 11 and S8).…”

“…Although this behavior is quite pronounced in our models, it might be less pronounced in models incorporating both landslides and sediment dynamics (Campforts et al, 2022) (i.e., due to increased stochasticity).…”

“…This possibility could be significant, as other studies have proposed the maintenance of topographic relief in the Appalachian Mountains through lithospheric delamination or changes in mantle dynamics (Gallen et al, 2013; Miller et al, 2013) or subsidence within the Gulf of Mexico and western Atlantic Ocean driving flexural uplift and tilting of the Appalachians (Liu, 2014). Additionally, lateral channel migration can trigger landslides, and such autogenic perturbations can drive landscape erosion and relief over long periods (Campforts et al, 2022; de Lavaissière et al, 2022; Hasbargen & Paola, 2000; Scheingross et al, 2020). Are novel and complex dynamics required to explain landscapes like the Appalachians, or can the internal dynamics of landscapes themselves offer sufficient explanations?…”

Rapid topographic growth of the Taiwan orogen since ~1.3–1.5 Ma

“…We cannot exclude the possibility that the shift to highly depleted organic δ 2 H n C29 values reflect an increase in the proportion of high-elevation organic matter due to nonuniform erosion processes affected observed δ 2 H n C29 values. Hillslope processes such as landslides that produce sediment from high-elevation regions are likely to become more frequent as the height of an orogen increases ( 36 , 39 , 40 ). The high energy system represented by the conglomerates may capture a shift to greater mass wasting/erosion from these high-elevation regions of the orogen.…”

Debris‐Flow Process Controls on Steepland Morphology in the San Gabriel Mountains, California

“…Stock and Dietrich (2006) formulated a possible debris‐flow incision model, but they also emphasized the importance of improving parameterizations for debris‐flow dynamics within landscape evolution models to work toward a validated debris‐flow GTL. Some works have found that it is possible to produce longitudinal profiles with slope‐invariant steepland valley bottoms by using modified versions of fluvial GTLs such as the stream power incision model that incorporates episodic fluvial floods (e.g., DiBiase & Whipple, 2011; Lague, 2014; Lague & Davy, 2003), by placing steep valleys under the control of hillslope processes (e.g., DiBiase et al., 2012; Ouimet et al., 2009), or including stochastic bedrock landsliding in landscape evolution models (e.g., Campforts et al., 2022). Other processes that may result in deviations from power‐law slope‐area scaling include lower entrainment thresholds required to transport sediment at steep slopes and low drainage areas (e.g., Lamb et al., 2008; Prancevic et al., 2014; Recking, 2009), rapid weathering on steep slopes as topographic stresses produce bedrock fractures (e.g., Li & Moon, 2021; Moon et al., 2017; Neely & DiBiase, 2020; St. Clair et al., 2015), and downstream changes in the width of geomorphically effective flows, including water‐dominated floods and debris flows (Alessio et al., 2021; Neely & DiBiase, 2023; Yanites, 2018).…”