Spatial prediction of landslide susceptibility in parts of Garhwal Himalaya, India, using the weight of evidence modelling

• Published in: Environmental monitoring and assessment Vol. 187; no. 6; p. 324
• Main Authors: Guri, Pardeep Kumar, Champati ray, P. K., Patel, Ramesh Chandra
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2015; Springer Nature B.V
• Subjects: Anthropogenic factors; Atmospheric Protection/Air Quality Control/Air Pollution; Climate Change; Climate prediction; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental Management; Environmental monitoring; Environmental Monitoring - methods; Extreme weather; Geographic Information Systems; Geographical distribution; Geological hazards; Geology; Geomorphology; Humans; Hydroelectric power; Hydrology; India; Infrastructure; Land settlement; Land use; Landslides; Landslides & mudslides; Landslides - statistics & numerical data; Models, Statistical; Monitoring/Environmental Analysis; Neural networks; Remote sensing; Risk Assessment - methods; Slope stability; Statistical analysis; Statistical methods; Statistical models; Tunnel construction; India; Pakistan, Himalayas; India, Uttar Pradesh, Garhwal Region, Garhwal Himalaya; Garhwal Himalaya; Weights of Evidence (WofE); Landslide; Susceptibility
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-015-4535-1

Garhwal Himalaya in northern India has emerged as one of the most prominent hot spots of landslide occurrences in the Himalaya mainly due to geological causes related to mountain building processes, steep topography and frequent occurrences of extreme precipitation events. As this region has many pilgrimage and tourist centres, it is visited by hundreds of thousands of people every year, and in the recent past, there has been rapid development to provide adequate roads and building infrastructure. Additionally, attempts are also made to harness hydropower by constructing tunnels, dams and reservoirs and thus altering vulnerable slopes at many places. As a result, the overall risk due to landslide hazards has increased many folds and, therefore, an attempt was made to assess landslide susceptibility using ‘Weights of Evidence (WofE)’, a well-known bivariate statistical modelling technique implemented in a much improved way using remote sensing and Geographic Information System. This methodology has dual advantage as it demonstrates how to derive critical parameters related to geology, geomorphology, slope, land use and most importantly temporal landslide distribution in one of the data scarce region of the world. Secondly, it allows to experiment with various combination of parameters to assess their cumulative effect on landslides. In total, 15 parameters related to geology, geomorphology, terrain, hydrology and anthropogenic factors and 2 different landslide inventories (prior to 2007 and 2008–2011) were prepared from high-resolution Indian remote sensing satellite data (Cartosat-1 and Resourcesat-1) and were validated by field investigation. Several combinations of parameters were carried out using WofE modelling, and finally using best combination of eight parameters, 76.5 % of overall landslides were predicted in 24 % of the total area susceptible to landslide occurrences. The study has highlighted that using such methodology landslide susceptibility assessment can be carried out in vast stretches of Himalaya in short time in order to assess the impact of development as well as climate change/variability. The resultant map can play a critical role in selecting areas for remedial measures for slope stabilisation as well planning for future development of the region.