Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling

Jones, Joshua N.; Boulton, Sarah J.; Bennett, Georgina L.; Stokes, Martin; Whitworth, Michael R. Z.

doi:10.1029/2021jf006067

Cited by 30 publications

(6 citation statements)

References 107 publications

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“…In agreement with the findings from Jones et al. (2021b), our results challenge the time‐independent assumptions (i.e., Poisson process) made by many landslide susceptibility analyses.…”

Section: Discussionsupporting

confidence: 92%

“…In addition, no notable increases in the attenuating rock fall rates were identified at these slopes immediately after the 13 June 2011 earthquake, suggesting that the 22 February 2011 earthquake was the main cause of the increase in nonseismic rockfall rates. Several other studies have found similar results where earthquake shaking has increased subsequent nonseismic landslide rates and characteristics (e.g., Jones et al., 2021; Jones et al., 2021; Kincey et al., 2021; Marc et al., 2019, 2015).…”

Section: Discussionsupporting

confidence: 54%

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Rockfall Activity Rates Before, During and After the 2010/2011 Canterbury Earthquake Sequence

et al. 2022

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The effects of strong ground shaking on hillslope stability can persist for many years after a large earthquake, leading to an increase in the rates of post earthquake land sliding. The factors that control the rate of post‐earthquake land sliding are poorly constrained, hindering our ability to reliably forecast how landscapes and landslide hazards and risk evolve. To address this, we use a unique data set comprising high‐resolution terrestrial laser scans and airborne lidar captured during and after the 2010–2011 Canterbury Earthquake Sequence, New Zealand. This earthquake sequence triggered thousands of rock falls, and rock and debris avalanches (collectively referred to as “rockfall”), resulting in loss‐of‐life and damage to residential dwellings, commercial buildings and other infrastructure in the Port Hills of Christchurch, New Zealand. This unique data set spans 5 years and includes five significant earthquakes. We used these data to (a) quantify the regional‐scale “rockfall” rates in response to these earthquakes and the postearthquake decay in rockfall rates with time; and (b) investigate the site‐specific factors controlling the location of seismic and nonseismic rockfalls using frequency ratios and logistic regression techniques. We found that rockfall rates increased significantly in response to the initial earthquake that generated the strongest shaking in the sequence—The MW 6.2 22 February 2011 event—Compared to the long‐term background rates derived from the dating of pre‐2010 talus piles at the toe of the slopes. Non seismic rockfall rates also increased immediately after the 22 February 2011 earthquake and decayed with time following a power‐law trend. About 50% of the decay back to the pre‐earthquake rockfall rates occurred within 1–5 years after the 22 February 2011 earthquake. Our results show that the short‐term decay in rockfall rates over time, after the initial earthquake, was attributed to the subsequent erosion of seismically damaged rock mass materials caused by environmental processes such as rain. For earthquake‐induced rockfall at the regional‐scale, the peak ground accelerations is the most significant variable in forecasting rockfall volume, followed by the relative height above the base of the slope. For both earthquake and non‐seismic conditions at the site‐specific scale, the probability of rockfall increases when the adjacent areas have failed previously, indicating that accrued damage preconditions localized areas of the slope for subsequent failure. Such preconditioning is a crucial factor driving subsequent rockfalls; that is, future rockfalls are likely to cluster near areas that failed in the past.

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“…In agreement with the findings from Jones et al. (2021b), our results challenge the time‐independent assumptions (i.e., Poisson process) made by many landslide susceptibility analyses.…”

Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 54%

Rockfall Activity Rates Before, During and After the 2010/2011 Canterbury Earthquake Sequence

et al. 2022

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“…Preparatory factors, such as natural slopes oversteepening by river incision and glacier debuttressing, mainly reduce the stability over time but do not cause failure or movement (McColl, 2012). Triggering factors are those that initiate failure or movement, including rainfall, earthquakes, and sharp increases in porewater pressures (Cruden and Varnes, 1996;Jones et al, 2021). The Yuting landslide is located at a transitional position from a low-relief landscape perched ~2-2.5 km above the local base level into a rapidly incising, dissected landscape in its lower reaches [Figure 6 in Ouimet et al (2007)].…”

Section: Cause and Trigger Of The Yuting Landslide-dammed Lakementioning

confidence: 99%

Reconstruction of a Holocene landslide-dammed lake in the Yalong basin, eastern Tibetan Plateau

Wang

Yang²,

Jiang³

et al. 2023

Front. Earth Sci.

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The failures of natural dams formed by landslides and glaciers in mountain areas have triggered the most destructive flood events on Earth. Outburst floods are effective agents in modifying landscapes, such as carving bedrock gorges and transporting surface masses. Reconstructing the ages and magnitudes of prehistoric landslide damming events allows us to capture the full range of frequencies and magnitudes of similar events and deepen our understanding of the interaction between large landslides and trunk rivers in tectonically active high-relief mountains. Previous studies have revealed many paleo-landslide-dammed lakes in the Yarlung Tsangpo River and its tributaries, the Jinsha River and the Min River. However, most studies associated with paleo-event reconstruction lack an estimation of the extent and volume of paleo-landslide-dammed lakes. The paleo-level of a landslide-dammed lake can be recorded in the variation in the sedimentary sequence and the geometry of the breach channel of a landslide dam. This information has not been fully exploited. In this study, we identified sedimentary evidence formed by an ancient landslide-dammed lake in the Liqiu River, a left-bank tributary of the Yalong River. The 12 exposures that we investigated mainly consist of typical clay or silt varves deposited in deep water and the Bouma sequence deposited by subaqueous turbidity flows, as well as climbing ripples that formed in a near-shore environment. Based on sedimentary analysis, we inferred that the minimal lake volume of this ancient lake was approximately 2.4 × 108 m3, corresponding to a lake level at 3,187 m a.s.l. The maximal lake extent derived from relict dam morphology reveals a lake volume of 3.2 × 108 m3 at the level of 3,200 m a.s.l. An initial drainage that occurred as the lake water overtopped the landslide dam was suggested to explain the small discrepancy in the lake level. The relict lake has remained stable over a long period of time and has accommodated continuous clay varve deposits. Furthermore, the optically stimulated luminescence dating results illustrate that the dammed lake initiated before 7.9 ka BP and persisted until at least 3.9 ka BP. The long-term cumulative coupled effect of tectonic movement and the rapid river incision rate provided favorable conditions for the failure of the Yuting landslide.

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“…Uniformitarianism still represents a fundamental component of the literature [7][8][9][10][11][12], albeit the current climate change has led us to question its present-day validity [13]. In fact, data-driven models are generally built upon the effects of past events, which may not inform on the slope response to events of different nature in the future.…”

Section: Introductionmentioning

confidence: 99%

Distinct Susceptibility Patterns of Active and Relict Landslides Reveal Distinct Triggers: A Case in Northwestern Turkey

et al. 2022

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To understand the factors that make certain areas especially prone to landslides, statistical approaches are typically used. The interpretation of statistical results in areas characterised by complex geological and geomorphological patterns can be challenging, and this makes the understanding of the causes of landslides more difficult. In some cases, landslide inventories report information on the state of activity of landslides, adding a temporal dimension that can be beneficial in the analysis. Here, we used an inventory covering a portion of Northwestern Turkey to demonstrate that active and relict landslides (that is, landslides that occurred in the past and are now stabilised) could be related to different triggers. To do so, we built two landslide susceptibility models and observed that the spatial patterns of susceptibility were completely distinct. We found that these patterns were correlated with specific controlling factors, suggesting that active landslides are regulated by current rainfalls while relict landslides may represent a signature of past earthquakes on the landscape. The importance of this result resides in that we obtained it with a purely data-driven approach, and this was possible because the active/relict landslide classification in the inventory was accurate.

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Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling

Cited by 30 publications

References 107 publications

Rockfall Activity Rates Before, During and After the 2010/2011 Canterbury Earthquake Sequence

Rockfall Activity Rates Before, During and After the 2010/2011 Canterbury Earthquake Sequence

Reconstruction of a Holocene landslide-dammed lake in the Yalong basin, eastern Tibetan Plateau

Distinct Susceptibility Patterns of Active and Relict Landslides Reveal Distinct Triggers: A Case in Northwestern Turkey

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