A regional scale quantitative risk assessment for landslides: case of Kumluca watershed in Bartin, Turkey

Erener, Arzu; Düzgün, H. B. Sebnem

doi:10.1007/s10346-012-0317-9

Cited by 56 publications

(29 citation statements)

References 50 publications

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“…. Examples of recent studies dealing with analysis of distributed landslide risk for different types of physical infrastructures Jaiswal et al (2011), and Erener and Düzgün (2013). In landslide risk assessment for the transportation sector, a major role is played by analyzing the vehicle risk or the risk of loss of life (e.g., Ko Ko et al 2005;Dorren et al 2009;Li et al 2009;Ferlisi et al 2012;Michoud et al 2012), whereas potential property losses received little scientific attention so far (e.g., Zêzere et al 2007;Jaiswal et al 2010;Bründl et al 2012).…”

Section: Ex-ante Assessmentsmentioning

confidence: 98%

Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Klose

2015

Springer Theses

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Section: Ex-ante Assessmentsmentioning

confidence: 98%

Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Klose

2015

Springer Theses

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“…Landslide hazard assessment usually prepared to answer the question regarding the location "where a landslide will occur" and time "when and how frequent a landslide will occur." In most of the cases due to data scarcity, some researchers considered susceptibility map as the only component of hazard map (Chau et al 2004), while, in some cases, the three components of hazard probability (i.e., spatial, temporal, and magnitude) have been multiplied directly, as they presume an independent relationship between each of these variables (Erener and Düzgün 2013;Lucà et al 2014;Nefeslioglu and Gokceoglu 2011).…”

Section: P T Of Landslide Hazardmentioning

confidence: 99%

“…In this study, the landslide hazard assessment was obtained by multiplying the two main independent components: (1) the P S of the occurrence of the triggering condition that results in a landslide and (2) the P T of the occurrence of the triggering condition that results in a landslide (Erener and Düzgün 2013;Guzzetti et al 2005) (Eq. 5).…”

Section: P T Of Landslide Hazardmentioning

confidence: 99%

Estimation of rainfall threshold and its use in landslide hazard mapping of Kuala Lumpur metropolitan and surrounding areas

2014

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This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations located in highly urbanized areas of Kuala Lumpur metropolis. Six rainfall gauges were selected, and the study area was divided into six zones according to rainfall gauges: Taman Desa Station (TD-KL), Genting Klang (GK-KL), LDG Edinburgh Station (LDGE-KL), SG Raya Hulu Langat Station (SRHL-Slg), Puchong Drop Station (PD-Slg), and Bukit Antarabangsa (BTA-Slg). After the threshold analysis was conducted for different periods (10, 15, and 30days) in each station, reliability index test was conducted to optimize the best threshold that limits the predicted events along the study period for each region. Second, the threshold analysis results were used as input in the Poisson probability model to estimate landslide temporal probability (P T ). Third, the spatial probability (P S ) analysis was prepared by using the evidential belief function multiplied by the P T to obtain the hazard maps for 1-, 3-, and 5-year scenarios. Finally, a validation process was conducted to test the prediction performance of the resultant hazard map for a 1-and 2-year prediction by using the landslide inventory of 2012 to early 2014, which was not included in the modeling of the hazard map. Results showed a valid correlation between the high and moderate hazardous areas for the six zones. The predicted hazard maps indicated a quantitative assessment of the prone areas and proved to be a valid disaster management tool. The produced hazard maps may play a vital role as input component in risk analysis.

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“…In the last decade, various researchers have constructed daily versus antecedent rainfall plots to assess the temporal aspect of landslide occurrence (Bai et al 2014;Jaiswal and van Westen 2009) and the coupling with the spatial aspect for the elaboration of hazard maps Nat Hazards (Bui et al 2013;Althuwaynee et al 2014) and risk maps (Erener and Duzgun 2013). As given in Table 1, a common practice is to evaluate several techniques for the same study area in order to determine which one yields the best predictive performance (Chleborad et al 2006;Dahal and Hasegawa 2008;Kanungo and Sharma 2014;Zezêre et al 2015).…”

Section: Considerations For the Construction Of Daily Versus Antecedementioning

confidence: 99%

Establishing rainfall frequency contour lines as thresholds for rainfall-induced landslides in Tegucigalpa, Honduras, 1980–2005

Garcia-Urquia

2016

Nat Hazards

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In this paper, a method to derive rainfall thresholds based on the relationship between daily and the antecedent rainfall up to 6 days prior to landslide occurrence is proposed for the analysis of 134 landslide days in Tegucigalpa, Honduras, during the years 1980-2005. Based on a simple graphical procedure, rainfall frequency contour lines have been drawn in the daily versus antecedent rainfall plots to connect rainfall combinations relatively having the same frequency of occurrence. A two-bound threshold has been established: Below the lower bound, rainfall events are so frequent that any landslide day may only occur due to a significant anthropogenic disturbance, while, above the upper bound, rainfall alone is capable of inducing landslide days. Contour lines originating at the same daily rainfall value in all plots were then grouped together to form a threshold set, for which the number of well-predicted landslide days and false alarms was determined. It has been determined that 16 and 84 landslide days have fallen below the lower bound and above the upper bound, respectively. In addition, this method has been proven effective in the distinction between days with and without landslides, since it has led to a 23 % reduction in the number of false alarms per well-predicted landslide day when compared to a previously established threshold line for Tegucigalpa.

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A regional scale quantitative risk assessment for landslides: case of Kumluca watershed in Bartin, Turkey

Cited by 56 publications

References 50 publications

Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Estimation of rainfall threshold and its use in landslide hazard mapping of Kuala Lumpur metropolitan and surrounding areas

Establishing rainfall frequency contour lines as thresholds for rainfall-induced landslides in Tegucigalpa, Honduras, 1980–2005

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