Open AccessMulti-Hazard Risk Zonation Based on Functions Responsible for Hazards Like Landslides, Floods, Forest Fires and Earthquakes in Mandakini Valley
Author(s) -
Seema Joshi*,
J. K. Garg,
Amandeep Kaur
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e5602.018520
Subject(s) - landslide , hazard , natural hazard , geography , geographic information system , physical geography , flash flood , hazard map , hazard analysis , vulnerability (computing) , cartography , human settlement , environmental science , environmental resource management , geology , meteorology , seismology , computer science , engineering , flood myth , archaeology , ecology , computer security , aerospace engineering , biology
The Himalayas are considered youngest mountain on Earth. Region is highly vulnerable to hazards because of tectonic activity, steep slopes, highly variable altitudes and uncertain climatic conditions. As a result, key hazards experienced in the region are earthquakes, landslides, forest fires, snow/ice avalanches, flash floods and extreme rainfall events which lead to great losses to human lives and property every year. The aim of study is to find most vulnerable area in terms of multi-hazards as per UNISDR guidelines. Here, GIS based techniques were used for disaster risk assessment towards various hazards and then integrating vulnerable areas with demography to perform detailed multi-hazard zonation of the area. Various Geo-spatial and statistical techniques were used in analysis of different types of disaster risk, determining the factors affecting incidents and in preparation of multi-hazard risk maps. The work involved the qualitative study, through in depth scientific observations, study available models for early warnings, develop models using sample data and generate multi-hazard vulnerability of study area. Using advanced geo-spatial techniques, Hazard Zonation maps were generated for different hazards in the Study Area. These maps were overlaid with Socio-economic and Demographic Profile of the habitations in the study area and multi-hazard risk assessment maps were generated. On the basis of complete geo-spatial analytics and scientific models, it was derived that 74 + villages are highly prone to various disaster. Scripts were written to automate various processes. Results were verified and validated during field visits.