Received: 22 Oct 2017 – Accepted for review: 03 Jan 2018 – Discussion started: 11 Jan 2018
Abstract. Debris flows, a type of landslides, are not nowadays limited only to the periodic devastation of the geologically fragile Himalaya but also ubiquitous in weathered Deccan Volcanic Province of the cratonic south Indian peninsula. Comprehensive assessment of landslide hazard, pertinently, requires process-based modeling using simulation methods. Development of precipitation triggered debris flow simulation models of real events are still at a young stage in India, albeit, especially in tectonically less disturbed regions. A highly objective simulation technique has therefore been envisaged herein to model the debris flow run-out happened in Malin. This takes cues from a high- resolution DEM and other ancillary ground data including geotechnical and frictional parameters. The algorithm is based on Voellmy frictional (dry and turbulent frictional coefficients, μ and ξ respectively) parameters of debris flow with pre-defined release area identified on high-resolution satellite images like LISS-IV and Cartosat-1. The model provides critical quantitative information on flow 1) Velocity, 2) Height, 3) Momentum, and 4) Pressure along the entrainment path. The simulated velocity of about 16 m/s at mid-way the slide plummeted to 6.2 m/s at the base with intermittently increased and decreased values. The simulated maximum height was 3.9 m which gradually declined to 1.5 m near the bottom. The results can be beneficial in engineering intervention like the construction of check dams to digest the initial thrust of the flow and other remedial measures designed for vulnerable slope protection.
How to cite. Chattoraj, S. L., Champati ray, P. K., Pardeshi, S., Gupta, V., and Ketholia, Y.: 3-Dimensional modeling of 2014-Malin Landslide, Maharashtra using satellite-derived data: A quantitative approach to numerical simulation technique, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2017-382, in review, 2018.