Fatal landslides in Europe

Haque, Ubydul; Blum, Philipp; Silva, Paula F. da; Andersen, Peter C.; Pilz, Jürgen; Chalov, Sergey; Malet, J. P.; Auflič, Mateja Jemec; Andres, Norina; Poyiadji, Eleftheria; Lamas, Pedro Calé da Cunha; Zhang, Wenyi; Peshevski, Igor; Pétursson, Halldór G.; Kurt, Tayfun; Dobrev, Nikolai; García-Davalillo, Juan Carlos; Halkia, Matina; Ferri, Stefano; Gaprindashvili, George; Engström, Johanna; Keellings, David

doi:10.1007/s10346-016-0689-3

Cited by 260 publications

(125 citation statements)

References 17 publications

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“…Haque et al 2016) that did not used detailed data on damaging landslides for such a long time as the Disaster database.…”

Section: Resultsmentioning

confidence: 99%

“…Landslides activity usually causes direct human impacts (fatalities, injuries), but the quantitative assessment of landslide societal risk has been developed in a limited number of studies performed at global (Petley 2012), European (Haque et al 2016) and national scales (Guzzetti 2000;Salvati et al 2010;Pereira et al 2016). …”

Section: Introductionmentioning

confidence: 99%

“…For instance, the EM-DAT only record disasters that have caused at least 10 fatalities, while the DISASTER database includes every landslide that caused fatalities regardless of their number. EM-DAT underestimates the numbers of fatalities and the fatalities are usually associated to the triggering event, such as earthquake, storm and floods (Haque et al 2016).…”

Section: Introductionmentioning

confidence: 99%

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Landslide Societal Risk in Portugal in the Period 1865–2015

Pereira

Zêzere

Quaresma

2017

Advancing Culture of Living With Landslides

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In Portugal, social impacts caused by landslides occurred in the period 1865-2015 are gathered in the DISASTER database. This database includes social consequences (fatalities, injuries, missing people, evacuated people and homeless people) caused by landslides documented in newspapers. The DISASTER database contains 291 damaging landslides that caused 238 fatalities. In this work we aim to: (i) analyse the spatio-temporal analysis of damaging landslides occurred in the last 150 years; (ii) analyse the frequency and the temporal evolution of fatal landslides; (iii) analyse the spatio-temporal distribution of landslide fatalities; (iv) identify the most deadly landside types; (v) verify gender tendencies in landslide mortality; and (vi) evaluate the individual and societal risk. Individual risk is evaluated computing mortality rates for landslides, which are calculated based on the annual average population and the annual average of fatalities. The societal risk is evaluated by plotting the annual frequency of landslide cases that generated fatalities. The results demonstrate the absence of any exponential growth in time of both landslide cases and landslide mortality in Portugal. The highest number of landslide cases and related mortalities occurred in the period of 1935-1969 in relation to very wet years. Most of landslide fatalities mainly occurred in the north of the Tagus valley where the geologic and geomorphologic conditions are more prone to landslides. The Lisbon area registered a mortality hotspot, which is explained by natural conditions combined with the high exposure of population to landslide risk. Falls and flows were responsible for the highest number of fatalities associated with landslides. Males were found to have the highest frequency of fatalities. In conclusion, the spatial patterns of landslide mortality can be related to the unequal distribution of predisposing conditions to landslides, changes in the land use and exposure and social vulnerability to landslide hazards.

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“…Haque et al 2016) that did not used detailed data on damaging landslides for such a long time as the Disaster database.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Landslide Societal Risk in Portugal in the Period 1865–2015

Pereira

Zêzere

Quaresma

2017

Advancing Culture of Living With Landslides

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“…In our particular case, almost one quarter of territory of Slovenia is subjected to landslides (Komac & Ribičič, 2006). According to technical reports and bulletins of the Administration for Civil Protection and Disaster Relief from 1991 to 2014, landslides claimed 15 people, disrupted communication and transportation on many roads and have caused considerable damage and economic loss (HAQUE et al, 2016).…”

Section: Introductionmentioning

confidence: 90%

Landslide prediction system for rainfall induced landslides in Slovenia (Masprem)

Auflič¹,

Šinigoj²,

Krivic³

et al. 2016

Geologija

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In this paper we introduce a landslide prediction system for modelling the probabilities of landslides through time in Slovenia (Masprem). The system to forecast rainfall induced landslides is based on the landslide susceptibility map, landslide triggering rainfall threshold values and the precipitation forecasting model. Through the integrated parameters a detailed framework of the system, from conceptual to operational phases, is shown. Using fuzzy logic the landslide prediction is calculated. Potential landslide areas are forecasted on a national scale (1: 250,000) and on a local scale (1: 25,000) for five selected municipalities where the exposure of inhabitants, buildings and different type of infrastructure is displayed, twice daily. Due to different rainfall patterns that govern landslide occurrences, the system for landslide prediction considers two different rainfall scenarios (M1 and M2). The landslides predicted by the two models are compared with a landslide inventory to validate the outputs. In this study we highlight the rainfall event that lasted from the 9th to the 14th of September 2014 when abundant precipitation triggered over 800 slope failures around Slovenia and caused large material damage. Results show that antecedent rainfall plays an important role, according to the comparisons of the model (M1) where antecedent rainfall is not considered. Although in general the landslides areas are over-predicted and largely do not correspond to the landslide inventory, the overall performance indicates that the system is able to capture the crucial factors in determining the landslide location. Additional calibration of input parameters and the landslide inventory as well as improved spatially distributed rainfall forecast data can further enhance the model's prediction. IzvlečekV članku predstavljamo sistem za napovedovanje verjetnosti nastanka plazov v času v Sloveniji (Masprem). Sistem napovedovanja plazov, ki se bodo sprožili zaradi padavin, je osnovan na karti verjetnosti pojavljanja plazov, sprožilnih/mejnih količin padavin za posamezne geološke enote ter modelskih napovedi padavin. Preko vključenih parametrov je prikazan potek dela, od idejne do operativne stopnje. Pri izračunu napovedovanja plazov je bila uporabljena mehka logika. Območja nastanka možnih plazov se računajo dvakrat dnevno, in sicer na državni ravni (v merilu 1:250.000) ter na lokalni ravni (merilo 1:25.000), kjer se za pet izbranih občin računa izpostavljenost prebivalcev, objektov in infrastrukture. Zaradi različnega vpliva padavin na pojav plazov, sistem napovedovanja upošteva dva različna scenarija za padavine (M1 in M2). Plazovi, ki jih napovedujeta ta dva modela, so primerjani z plazovi v bazi plazov, z namenom preverjanja ujemanja in validacije. Posebej so obravnavane obsežne padavine med 9. in 14. septembrom 2014, ki so botrovale sprožiti preko 800 plazov po celotni Sloveniji ter povzročile veliko gmotno škodo. Rezultati modelov kažejo, da so predhodne padavine pomembne pri napovedovanju. Kar je razvidno iz rezu...

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“…), acoustic propagation, or direct mechanical action on the slide mass (Aradian et al 2002;Juanico et al 2008;Montrasio et al 2016). Granular slides can cause catastrophic damage through their bulk motion (Haque et al 2016), but they can also have drastic indirect effects, with slides impacting into bodies of water producing significant tsunamis (Heller et al 2008). This can lead to secondary hazards such as unintentional dam formation (Chang et al 2011), dam overtopping (Yavari-Ramshe and Ataie-Ashtiani 2016), or flooding of nearby coastal areas or settlements (Glimsdal et al 2016).…”

Section: Introductionmentioning

confidence: 99%

A laboratory-numerical approach for modelling scale effects in dry granular slides

2018

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Granular slides are omnipresent in both natural and industrial contexts. Scale effects are changes in physical behaviour of a phenomenon at different geometric scales, such as between a laboratory experiment and a corresponding larger event observed in nature. These scale effects can be significant and can render models of small size inaccurate by underpredicting key characteristics such as flow velocity or runout distance. Although scale effects are highly relevant to granular slides due to the multiplicity of length and time scales in the flow, they are currently not well understood. A laboratory setup under Froude similarity has been developed, allowing dry granular slides to be investigated at a variety of scales, with a channel width configurable between 0.25 and 1.00 m. Maximum estimated grain Reynolds numbers, which quantify whether the drag force between a particle and the surrounding air act in a turbulent or viscous manner, are found in the range 10 2 − 10 3 . A discrete element method (DEM) simulation has also been developed, validated against an axisymmetric column collapse and a granular slide experiment of Hutter et al. (Acta Mech 109:127-165, 1995), before being used to model the present laboratory experiments and to examine a granular slide of significantly larger scale. This article discusses the details of this laboratory-numerical approach, with the main aim of examining scale effects related to the grain Reynolds number. Increasing dust formation with increasing scale may also exert influence on laboratory experiments. Overall, significant scale effects have been identified for characteristics such as flow velocity and runout distance in the physical experiments. While the numerical modelling shows good general agreement at the medium scale, it does not capture differences in behaviour seen at the smaller scale, highlighting the importance of physical models in capturing these scale effects.

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Fatal landslides in Europe

Cited by 260 publications

References 17 publications

Landslide Societal Risk in Portugal in the Period 1865–2015

Landslide Societal Risk in Portugal in the Period 1865–2015

Landslide prediction system for rainfall induced landslides in Slovenia (Masprem)

A laboratory-numerical approach for modelling scale effects in dry granular slides

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