INTRODUCTION
Movement of a mass of rock, debris, or earth down a slope resulting geomorphic make over of earth surface and this active process contributes to erosion and landscape evolution is often referred as landslide [1,2]. This could be due to the temporal conjunction of several factors [3-5], such as: (i) the quasi-static variables, which contribute to landslide susceptibility, such as geology, slope characteristics (gradient, slope aspect, elevation, etc.), geotechnical properties, and long-term drainage patterns, etc.; and (ii) the dynamic variables, which tend to trigger landslides in an area of a given landslide susceptibility, such as rainfall and earthquakes.
Depending on quasi static and triggering factors, landslides vary in composition as well as in the rate of movement (0.5x10-6 to 5x103 mm/sec). Landslides in vulnerable zones in India have lead to large scale loss of life and property [6]. In this context, identification, mapping and monitoring of landslide susceptible pockets would help in the mitigation as well as in the rehabilitation. These vulnerable pockets can be identified by by both direct and indirect techniques based on significance of causative factors in inducing instability. The assumptions that are generally made in identifying landslide hazard susceptibility (LHS) regions [7, 8] are: Occurrence of landslides follows past history in the region depending on geological, geomorphological, hydrogeological and climatic conditions. Identification of LHS involves dividing the region into zones depending on degrees of stability, significance of causative factors inducing instability, etc.
Identification and mapping of LHS zones aid in delineating unstable hazard-prone areas, so that environmental mitigation measures can be initiated. This also helps planners to choose favourable locations for site development projects. Even if the hazardous areas can not be avoided altogether, their recognition in the initial stages of planning will help to adopt suitable precautionary remedial measures.
Identification of LHS and mapping: Quasi static variables and dynamic variables are considered for likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model. In this regard, slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. [9] Other attempts considering lithology, slope angle, bedding attitude along with dynamic variable like rainfall [10]; distance from faults, parallelism between the fractures and the landslide scarps, land use, lithology, distance from the streams, orientation and steepness of slopes, orientation of layers compared to the slope [11]; slope, aspect, and curvature of topography, texture, material, drainage, and effective soil thickness and type, age, diameter, and density of timber, lithology, land use in probability and logistic regression methods [12]; geological structure of foliation, slope aspect and slope of the topography for frequency ratio analysis [13]; slope, curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter in ANN and frequency ratio methods [12-16]; rainfall, slope angle, aspect, curvature, lithology, superficial deposits, geomorphology, and land use in the probabilistic evaluation of landslide hazard [17]; slope angle, slope aspect, slope curvature, slope length, distance from drainage, distance from lineaments, lithology, and land use and geomorphology in frequency ratio method [18].
The objective of the study is identification and mapping landslide prone zones of Sharavathi downstream using frequency ratio analysis. The Sharavathi river basin is situated in Central Western Ghats. Due to undulating terrain coupled with high intensity rainfall, ghats are prone to landslides causing significant damage to property and agriculture. Most of the episodes are triggered by rainfall with the changes in land cover. Effort is made to identifify landslide susceptible regions.