An empirical-statistical model for debris flow travel distance

Fannin, R. J.; Wise, Mike

doi:10.1139/t01-030

Cited by 136 publications

(81 citation statements)

References 13 publications

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“…The mean annual precipitation in the study area exceeds 800 mm, increasing to 2000 mm above 2000 m (García-Ruiz et al, 1985). The wet season lasts from October to May, with very little rain in January and February.…”

Section: The Study Areamentioning

confidence: 90%

Debris flow characteristics and relationships in the Central Spanish Pyrenees

Lorente

Beguerı́a

Bathurst

et al. 2003

Nat. Hazards Earth Syst. Sci.

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Abstract. Unconfined debris flows (i.e. not in incised channels) are one of the most active geomorphic processes in mountainous areas. Since they can threaten settlements and infrastructure, statistical and physically based procedures have been developed to assess the potential for landslide erosion. In this study, information on debris flow characteristics was obtained in the field to define the debris flow runout distance and to establish relationships between debris flow parameters. Such relationships are needed for building models which allow us to improve the spatial prediction of debris flow hazards. In general, unconfined debris flows triggered in the Flysch Sector of the Central Spanish Pyrenees are of the same order of magnitude as others reported in the literature. The deposition of sediment started at 17.8 • , and the runout distance represented 60% of the difference in height between the head of the landslide and the point at which deposition started. The runout distance was relatively well correlated with the volume of sediment.

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Section: The Study Areamentioning

confidence: 90%

Debris flow characteristics and relationships in the Central Spanish Pyrenees

Lorente

Beguerı́a

Bathurst

et al. 2003

Nat. Hazards Earth Syst. Sci.

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“…SL strongly controls the velocity of the material mobilized by a shallow landslide, thus its capacity of travelling for long distances from the source areas (Fannin and Wise, 2001;Catani et al, 2013;Fathani et al, 2017). ASP influences the soil moisture and the vegetation growth, that can have a key role on the susceptibility of a slope to shallow failures (Van Westen et al, 2008;Jaiswal et al, 2010a).…”

Section: Predictor Variablesmentioning

confidence: 99%

“…This aspect is well described by the amount in sediment connectivity, which influences the path and the travel distance of the materials mobilized by a slope failure until reaching a potential natural or anthropogenic barrier (e.g., river or road) (Cavalli et al, 2013;Tarolli and Sofia, 2016;Persichillo et al, 2018). In this way, the landslide runout can be estimated and inserted when modelling road susceptibility without employing numerical or physical methods, which require rheological and geotechnical data not easily measurable for the slope materials (Hungr, 1995;Fannin and Wise, 2001;Pastor et al, 2014;Fan et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

Bordoni

Persichillo

Meisina

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides cause severe damage to the road network of the hit zone, in terms of both direct (partial or complete destruction of a road or blockages) and indirect (traffic restriction or the cut-off of a certain area) costs. Thus, the identification of the parts of the road network that are more susceptible to landslides is fundamental to reduce the risk to the population potentially exposed and the financial expense caused by the damage. For these reasons, this paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to being hit by shallow landslides triggered in slopes upstream from the infrastructure. This model was based on the Generalized Additive Method, where the function relating predictors and response variable is an empirically fitted smooth function that allows fitting the data in the more likely functional form, considering also non-linear relations. This work also analyzed the importance, on the estimation of the susceptibility, of considering or not the sediment connectivity, which influences the path and the travel distance of the materials mobilized by a slope failure until hitting a potential barrier such as a road. The study was carried out in a catchment of northeastern Oltrepò Pavese (northern Italy), where several shallow landslides affected roads in the last 8 years. The most significant explanatory variables were selected by a random partition of the available dataset in two parts (training and test subsets), 100 times according to a bootstrap procedure. These variables (selected 80 times by the bootstrap procedure) were used to build the final susceptibility model, the accuracy of which was estimated through a 100-fold repetition of the holdout method for regression, based on the training and test sets created through the 100 bootstrap model selection. The presented methodology allows the identification, in a robust and reliable way, of the most susceptible road sectors that could be hit by sediments delivered by landslides. The best predictive capability was obtained using a model in which the index of connectivity was also calculated according to a linear relationship, was considered. Most susceptible road traits resulted to be located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. Different land use scenarios were considered in order to estimate possible changes in road susceptibility. Land use classes of the study area were characterized by similar connectivity features. As a consequence, variations on the susceptibility of the road network according to different scenarios of distribution of land cover were limited. The results of this research demonstrate the ability of the developed methodology in the assessment of susceptible roads. This could give the managers of infrastructure information about the criticality of the different road traits, thereby allowing attention and economic budgets to be shifted towards the most critical assets, where structural and non-structur...

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“…The flume apparatus was used with a slope angle at 24?5˚, typical of a debris flow transition reach (Fannin and Wise, 2001), leading to a flat unconfined runout zone. The laser power set at around 600 mW and the frame rate of the camera at 1100 fps.…”

Section: Test Conditionsmentioning

confidence: 99%