Landslide triggering by rain infiltration

Iverson, Richard M.

doi:10.1029/2000wr900090

Cited by 1,660 publications

(1,347 citation statements)

References 30 publications

Supporting

Mentioning

1,273

Contrasting

Unclassified

Order By: Relevance

“…The model performs an infinite-slope stability calculation accounting for the pressure head response C(Z,t) to a time-varying rainfall input on the ground surface I Z (t). Specifically, the infiltration process is simulated considering the 1D analytic solution of Richards' equation as well as described by Iverson (2000). In the most recent version of the program (Baum et al 2008), TRIGRS was expanded to address infiltration also into unsaturated soils, then assuming a two-layer system consisting of a saturated zone (with the possible presence of a capillary fringe) and an unsaturated zone that extends to the ground surface ( Figure 6).…”

Section: Theoretical Basis Of Trigrs Modelmentioning

confidence: 99%

“…Despite numerous slope stability models have been developed (e.g. Montgomery and Dietrich 1994;Iverson 2000;Borga et al 2002;Liao et al 2011;Formetta et al 2014;Ho and Lee 2016;Thiery et al 2017), the fundamental controls leading to slope failure driven by rainfall are still not well quantified (Borja et al 2012), and thus the improvement of current models is still an important research topic (Chang et al 2008). The difficulty of building up reliable mathematical models lies in the numerous variables involved in the triggering process, such as spatial and temporal rainfall variability, mechanical and hydraulic soil properties, slope morphology, vegetation coverage, initial soil suction and moisture (Greco et al 2010).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Shallow landslide initiation on terraced slopes: inferences from a physically based approach

Schilirò

Cevasco

Esposito

et al. 2018

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

In the last years, great efforts have been made to improve the assessment of the temporal and spatial occurrence of rainfall-induced shallow landslides. Therefore, in this paper we used a physically based stability model (TRIGRS) in order to reproduce the landslide event occurred in the Monterosso catchment (Cinque Terre, Eastern Liguria, Italy) on 25 October 2011. The input parameters of the numerical model have been evaluated taking into account the land-use setting and paying specific attention to the evaluation of the spatial variation of soil thickness on terraced areas. The resulting safety factor maps have been compared with the inventory map of the landslides triggered during the event. The simulation results, which have been obtained also considering four different spatial resolutions of the digital terrain model, emphasize the influence of land use in shallow landslide occurrence and indicate the importance of a realistic spatial variation of soil thickness to enhance the reliability of the model. Finally, different triggering scenarios have been defined using hourly rainfall values statistically derived from historical data. The results indicate the proneness of the area to shallow landsliding, given that rainfall events with a relatively low return period (e.g. 25 years) can trigger numerous slope failures.

show abstract

Section: Theoretical Basis Of Trigrs Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Shallow landslide initiation on terraced slopes: inferences from a physically based approach

Schilirò

Cevasco

Esposito

et al. 2018

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

show abstract

“…Often, a conspicuous lag time between the peak landslide motion and the peak precipitation could be seen, which have been widely accepted by many landslide studies [15]. For example, Iverson observed a lag time of five to eight days at Minor Creek [45], Hilley et al found a lag time of about three months between the onset of the rainy season and a sharp increase in sliding velocity at Berkeley Hills [46], and Zhao et al found the lag time of the Boulder Creek slide to be about one to two months [10]. However, due to the long revisit period of the ALOS data, discontinuous monitoring results, and uneven monitoring intervals, the accurate lag time for the Guanling landslide is difficult to determine in this study.…”

Section: Trigger Factormentioning

confidence: 96%

Application of InSAR Techniques to an Analysis of the Guanling Landslide

et al. 2017

View full text Add to dashboard Cite

Abstract:On the afternoon of 28 June 2010, an enormous landslide occurred in the Gangwu region of Guanling County, Guizhou Province. In order to better understand the mechanism of the Guanling landslide, archived ALOS/PALSAR data was used to acquire the deformation prior to the landslide occurrence through stacking and time-series InSAR techniques. First, the deformation structure from InSAR was compared to the potential creep bodies identified using the optical remote sensing data. A strong consistency between the InSAR detected deformed regions and the creep bodies detected from optical remote sensing images was achieved. Around 10 creep bodies were suffering from deformation. In the source area, the maximum pre-slide mean deformation rate along the slope direction reached 160 mm/year, and the uncertainty of the deformation rates ranged from 15 to 34 mm/year. Then, the pre-slide deformation at the source area was analyzed in terms of the topography, geological structure, and historical rainfall records. Through observation and analysis, the deformation pattern of one creep body located within the source area can be segmented into three sections: a creeping section in the front, a locking section in the middle, and a cracking section in the rear. These sections constitute one of the common landslide modes seen in the south-west of China. This study concluded that a sudden shear failure in the locking segment of one creeping body located within the source area was caused by a strong rainstorm, which triggered the Guanling landslide.

show abstract

“…These two models point to local surface gradient and specific contributing area as primary topographic controls on shallow landsliding (Montgomery and Dietrich, 1994). Iverson (2000) highlights limitations to the hydrologic assumptions used in this model, but still recognizes the importance of local slope and specific contributing area in setting the antecedent soil moisture conditions that modulate the impact of transient periods of high-intensity rainfall on slope stability. We thus use a function of local slope and specific contributing area (that of Montgomery and Dietrich (1994), with soil parameters held uniform), as a topographic index of slope stability.…”

Section: Topographymentioning

confidence: 99%

Time, space, and episodicity of physical disturbance in streams

Miller

Luce

Benda³

2003

Forest Ecology and Management

View full text Add to dashboard Cite

Storm-driven episodes of gully erosion and landsliding produce large influxes of sediment to stream channels that have both immediate, often detrimental, impacts on aquatic communities and long-term consequences that are essential in the creation and maintenance of certain channel and riparian landforms. Together, these effects form an important component of river ecosystems. In this paper, we describe issues involved in characterizing and predicting the frequency, magnitude, spatial extent, and synchrony of these sediment influxes. The processes that drive sediment fluxes exhibit spatial and temporal variability over a large range of scales. Disregard of this variability can have unanticipated consequences for efforts to quantify process rates, as we illustrate using landslide densities observed for a storm event in western Oregon. Multiple factors interact to create the temporal and spatial patterns of erosional and mass-wasting events that affect stream channels. Fires, in particular, enhance susceptibility to erosional and mass-wasting processes, and thus affect the timing and magnitude of sedimentmobilizing events. We use examples from west-central Idaho to show how fires, storms, and topography interact to create spatially distinct patches of intense erosional activity. We require quantitative descriptions of these controlling factors to make quantitative predictions of how differences or changes in topography, fire regime, and climate will affect the regime of sediment fluxes. The stochastic and heterogeneous nature of these factors leads us to quantify them in probabilistic terms. The effects of future fire and storm sequences are governed in part by the past sequence of events over time frames spanning centuries and spatial extents spanning entire river basins. Empirical characterization of past events poses a considerable challenge, given that our observational record typically spans several decades at most. Numerical models that simulate multiple event sequences provide an alternative means for estimating the influence of antecedent conditions and for quantifying the role of different controlling factors. #

show abstract

Landslide triggering by rain infiltration

Cited by 1,660 publications

References 30 publications

Shallow landslide initiation on terraced slopes: inferences from a physically based approach

Shallow landslide initiation on terraced slopes: inferences from a physically based approach

Application of InSAR Techniques to an Analysis of the Guanling Landslide

Time, space, and episodicity of physical disturbance in streams

Contact Info

Product

Resources

About