Quantitative assessment of direct and indirect landslide risk along transportation lines in southern India

Abstract

Abstract.A quantitative approach for landslide risk assessment along transportation lines is presented and applied to a road and a railway alignment in the Nilgiri hills in southern India. The method allows estimating direct risk affecting the alignments, vehicles and people, and indirect risk resulting from the disruption of economic activities. The data required for the risk estimation were obtained from historical records. A total of 901 landslides were catalogued initiating from cut slopes along the railway and road alignment. The landslides were grouped into three magnitude classes based on the landslide type, volume, scar depth, run-out distance, etc and their probability of occurrence was obtained using frequency-volume distribution. Hazard, for a given return period, expressed as the number of landslides of a given magnitude class per kilometre of cut slopes, was obtained using Gumbel distribution and probability of landslide magnitude. In total 18 specific hazard scenarios were generated using the three magnitude classes and six return periods (1, 3, 5, 15, 25, and 50 years). The assessment of the vulnerability of the road and railway line was based on damage records whereas the vulnerability of different types of vehicles and people was subjectively assessed based on limited historic incidents. Direct specific loss for the alignments (railway line and road), vehicles (train, bus, lorry, car and motorbike) was expressed in monetary value (US$), and direct specific loss of life of commuters was expressed in annual probability of death. Indirect specific loss (US$) derived from the traffic interruption was evaluated considering alternative driving routes, and includes losses resulting from additional fuel consumption, additional travel cost, loss of income to the local business, and loss of revenue to the railway department. The results indicate that the total loss, including both direct and indirect loss, from 1 to 50 years return period, varies from Correspondence to: P. Jaiswal (jaiswal@itc.nl) US$ 90 840 to US$ 779 500 and the average annual total loss was estimated as US$ 35 000. The annual probability of a person most at risk travelling in a bus, lorry, car, motorbike and train is less than 10 −4 /annum in all the time periods considered. The detailed estimation of direct and indirect risk will facilitate developing landslide risk mitigation and management strategies for transportation lines in the study area.

Quantitative estimation of landslide risk from rapid debris slides on natural slopes in the Nilgiri hills, India

“…Vulnerability for other elements at risk such as vehicles and commuters are not included in this study but were considered in another study dealing with risk of the road and railroad (Jaiswal et al, 2010a).…”

“…For bigger landslides, not all debris is accumulated on the (rail) road, as these landslides have longer run-out and part of the debris passes the (rail) road. For railroad cases, the vulnerability is set to 1 for all landslide magnitude classes except for very small landslides of less than 100 m 3 (Jaiswal et al, 2010a). Such landslides generally initiate from cut slopes.…”

“…The mapped landslides were digitized as polygons or points and entered in a geo-database of ArcGIS. The method and criteria used in identification and mapping of landslides are described in detail in Jaiswal et al (2010aJaiswal et al ( , 2011. The landslides were grouped into cut slope failures, occurring along the road and the railroad, and natural slope failures.…”

Damaging events along roads during bad weather periods: a case study in Calabria (Italy)

“…Vehicle vulnerability depends on many factors, including the following: (a) the type and size of the landslide; (b) the type of infrastructure; (c) the speed and type of vehicle (Jaiswal et al, 2010); (d) the traffic volume; (e) the length of the landslide risk section of the route; (f) the number of occupants in the car (Budetta, 2002); and (g) alertness. In several regions, all these factors are difficult to quantify due to the scarcity of both damage records and data concerning traffic.…”

“…Quantitative analyses can be performed by deterministic methods on limited road sectors for which data concerning both road characteristics and traffic volumes are available. One example, at a local scale, is shown by Jaiswal et al (2010), who performed quantitative risk estimation for four elements at risk (railway tracks, vehicles, commuters and roads) considered to be exposed to three types of landslides, characterised by both their magnitude and return period.…”