Landslides, sandpiles, and self-organized criticality

Hergarten, Stefan

doi:10.5194/nhess-3-505-2003

Cited by 85 publications

(80 citation statements)

References 42 publications

(55 reference statements)

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“…Such landslide self-organization into emergent patterns is not captured in traditional cause-effect studies of landslide susceptibility. It also adds an important consideration to the discussion about landslide selforganized critical behaviour Hergarten 2003;Turcotte et al 2002). Apparently, not all landsliding potential ('metastable regions', Guzzetti et al 2002, p171) is removed by a landslide-instead first landslides appear in some cases to increase the potential for follow-up landslides.…”

Section: Do Landslides Follow Landslides?mentioning

confidence: 99%

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Samia¹,

Temme

Bregt³

et al. 2016

Landslides

142

109

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Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multitemporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10 years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.

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Section: Do Landslides Follow Landslides?mentioning

confidence: 99%

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Samia¹,

Temme

Bregt³

et al. 2016

Landslides

142

109

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“…Hovius et al, 1997;Pelletier et al, 1997;Dai and Lee, 2001;Dussauge-Peisser et al, 2002;Guzzetti et al, 2002;Hergarten, 2003;Brardinoni and Church, 2004;Brunetti et al, 2009;ten Brink et al, 2009). Historical records of coastal cliff failure statistics are relatively sparse.…”

Section: Introductionmentioning

confidence: 99%

Short-term retreat statistics of a slowly eroding coastal cliff

Young

Guza

O’Reilly

et al. 2011

Nat. Hazards Earth Syst. Sci.

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Abstract. The frequency, spatial distribution, and dimensions of coastal cliff retreats, a basic statistic underlying cliff top hazard assessment, are presented for 7.1 km of unprotected and slowly retreating coastal cliffs near Point Loma in San Diego, California, US. Using 8 airborne light detection and ranging (lidar) surveys collected over 5.5 years, 130 individual cliff edge failures (primarily rockfalls, block falls, and topples) were detected. Footprint areas varied from 3 to 268 m 2 , maximum landward retreats from 0.8 to 10 m, and alongshore lengths from 2 to 68 m. The failures with the largest landward retreats were also relatively long, and 13% of the slides accounted for 50% of the lost cliff area over the study period. On this short (5.5 years) time scale, "no change" was the most common observation (84% of the cliff edge). Probability distributions of non-zero cliff retreat during each time interval usually had a single peak between 1 and 2.5 m. Intervals with high mean retreat had elevated numbers of failure in all class sizes, and also contained the largest individual retreats. Small and medium slides tended to reoccur preferentially (relative to randomly) near previous small and medium slides, forming short-term hot spots, while large slides were less likely to reoccur near previous large slides. Cumulative distributions of landslide failure parameters (area, mean retreat, maximum retreat, and length) follow an inverse power-law for medium to large size events, similar to previously reported distributions of coastal and inland landsliding.

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“…We study Bak-TangWiesenfeld sandpile dynamics (23,24) on networks derived from real, interdependent power grids and on sparsely coupled, random regular graphs that approximate the real topologies. Sandpile dynamics are paradigms for the cascades of load, self-organized criticality, and power law distributions of event sizes that pervade disciplines, from neuronal avalanches (25)(26)(27) to cascades among banks (28) to earthquakes (29), landslides (30), forest fires (31,32), solar flares (33,34), and electrical blackouts (15). Sandpile cascades have been extensively studied on isolated networks (35)(36)(37)(38)(39)(40)(41).…”

mentioning

confidence: 99%

Suppressing cascades of load in interdependent networks

Brummitt¹,

D’Souza

Leicht

2012

Proc. Natl. Acad. Sci. U.S.A.

491

347

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Understanding how interdependence among systems affects cascading behaviors is increasingly important across many fields of science and engineering. Inspired by cascades of load shedding in coupled electric grids and other infrastructure, we study the BakTang-Wiesenfeld sandpile model on modular random graphs and on graphs based on actual, interdependent power grids. Starting from two isolated networks, adding some connectivity between them is beneficial, for it suppresses the largest cascades in each system. Too much interconnectivity, however, becomes detrimental for two reasons. First, interconnections open pathways for neighboring networks to inflict large cascades. Second, as in real infrastructure, new interconnections increase capacity and total possible load, which fuels even larger cascades. Using a multitype branching process and simulations we show these effects and estimate the optimal level of interconnectivity that balances their trade-offs. Such equilibria could allow, for example, power grid owners to minimize the largest cascades in their grid. We also show that asymmetric capacity among interdependent networks affects the optimal connectivity that each prefers and may lead to an arms race for greater capacity. Our multitype branching process framework provides building blocks for better prediction of cascading processes on modular random graphs and on multitype networks in general.vulnerability of infrastructure | complex networks

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Landslides, sandpiles, and self-organized criticality

Cited by 85 publications

References 42 publications

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Short-term retreat statistics of a slowly eroding coastal cliff

Suppressing cascades of load in interdependent networks

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