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Landslide Hazard Zonation Mapping using MCDM Techniques – A study over Kodagu District, Karnataka
Abstract
Landslides pose significant and recurring hazards in various parts of India, particularly during the rainy season, causing extensive damage to infrastructure and loss of life. To address this issue, it is crucial to map the hazardous zones, raise awareness among local communities and guide authorities in disaster management efforts. This study aimed to develop a landslide hazard zonation map using different thematic maps such as aspect, drainage density, geology, lineament density, land use land cover, rainfall, road network, slope and soil layers. The study employing methods such as AHP and a modified power method was based on AHP for the development of landslide hazard zonation maps. The findings indicated that the PM-AHP technique yielded superior results in identifying highly risky zones. According to this method, approximately 250.65 sq.km. of the area was classified as falling within the highly risky zone.
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Kabul River Basin is one of the most significant river basins in Afghanistan from a socioeconomic perspective. Since the country is located in an arid climate zone with drastically varying climatic behavior, an effective assessment of meteorological drought is very essential to managing the limited availability of water resources. For this endeavor, the outputs of three general circulation models under two representative concentration pathways (RCP 4.5 and RCP 8.5) were used against the baseline period of 1961-1980. Different bias correction methods were applied, and the results show that the delta change method, quantile mapping method, and empirical quantile mapping all performed better for the precipitation, maximum temperature, and minimum temperature datasets, respectively. The ERA5-Land datasets and WorldClim Version 2 are used to validate the bias-corrected precipitation and temperature datasets, respectively, to determine their dependability, and the results were found to be promising. Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Deciles Index (DI), and New Drought Index (NDI) were used to assess the drought condition in the past and forecast for the future periods of the 2020s, 2050s, and 2080s. The spatial distribution of assessed drought indices was mapped using the inverse distance weighting (IDW) method. Our results revealed that moderate to extreme droughts are consistent across the entire basin. This might be because the projected annual precipitation in the river basin shows a decline of 53-65% up to the end of this century (2100), and the average annual temperature is projected to increase by 1.8 • C, 3.5 • C, and 4.8 • C, respectively, for the three future periods of the 2020s, 2050s, and 2080s. Furthermore, the results show that the drought estimated by SPI and RDI for future climate scenarios is almost the same, whereas NDI estimates frequent drought events after the 2050s. However, for moderate drought, RDI, which includes the effects of evapotranspiration, was found to be far greater than SPI under both scenarios, and NDI considering temperature and precipitation also estimates a larger number of drought years, strengthening the possibility of its occurrence in the basin. A regional comparison of drought also indicates a decrease in precipitation in future periods, predominantly in high altitudes.
An increasing trend of urban floods in India from past several years causes major damages on Indian cities. By 2050, more than half of the population in the developing countries like India are expected to migrate to urban regions. Urbanization is triggered in developing countries as people migrate to cities in search of employment opportunities resulting in formation of new slums. With high density of population concentration in cities, urban floods are triggered leading to a significant impact of human life and economy of the country. The review focuses on addressing the urban flood occurrence in India and its relationship with population growth climate change. The study also describes the impact of urban floods to the environment and integrated methodologies adopted over decades for the prediction and effective mitigation and management during a disaster event.
Geomatics is the discipline of electronically gathering, storing, processing, and delivering spatially related digital information; it continues to be one of the fastest expanding global markets, driven by technology. The British Geological Survey (BGS) geomatics capabilities have been utilized in a variety of scientific studies such as the monitoring of actively growing volcanic lava domes and rapidly retreating glaciers; coastal erosion and platform evolution; inland and coastal landslide modelling; mapping of geological structures and fault boundaries; rock stability and subsidence feature analysis, and geo-conservation. In 2000, the BGS became the first organization outside the mining industry to use Terrestrial LiDAR Scanning (TLS) as a tool for measuring change; paired with a Global Navigation Satellite System (GNSS), BGS were able to measure, monitor, and model geomorphological features of landslides in the United Kingdom (UK) digitally. Many technologies are used by the BGS to monitor the earth, employed on satellites, airplanes, drones, and ground-based equipment, in both research and commercial settings to carry out mapping, monitoring, and modelling of earth surfaces and processes. Outside BGS, these technologies are used for close-range, high-accuracy applications such as bridge and dam monitoring, crime and accident scene analysis, forest canopy and biomass measurements and military applications.
The article presents a critical review on the application of development of technology in the field of subsidence monitoring using various techniques. It consists the review of literature pertaining to causes of subsidence and their effects in coal mines with brief explanation on the various techniques to monitor the suubsidence. The accuracy of various subsidence monitoring techniques is also discussed by evolving suitablee technique for precise identification of slope failures in the coal mines. © 2018, National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.
A massive landslide wiped out the village of Malin located at 110 km from Pune city, in the Western Ghats on July
30. Mound of mud and debris that came down from a nearby hillock, swallowed up almost the entire tribal village of
around 50 families. Due to the remoteness of the village, the tragedy came to light only when the driver of the first
state transport bus reached the village a little after 7.30 am to find it uprooted. Final death toll was 153 when the
rescue operation was stopped and around 100 people were missing. This tragedy has brought the focus back on the
management –or mismanagement – of the vulnerable hills of India especially Western Ghats, Himalayas and North
Eastern states
There are many speculations about what caused such massive landslide. In this paper we are analyzing geotechnical
aspects of the catastrophe. Some of the key facts to note are, heavy rainfall before the landslide (10.8 cm on July 29)
and heavy downpour throughout the following day. This calamite is a lesson for sustainable geotechnical planning in
future to avoid massive loss of human life and property.
Detailed analysis of geotechnical facts is carried out and an attempt is made to pinpoint the cause and preventive
measures are suggested.
The Tista basin is one of the most vulnerable among the Himalayan river basins considering the occurrence
of landslides and floods. The landslides occurred in 1899, 1950, 1968, 1976, 1991, 1993, 2003, 2004,
2005, 2006, 2009, 2011 and 2015. The floods occurred during 1950, 1968, 1973, 1975, 1976, 1978, 1993,
1996, 2000, 2003 and 2015. Some of the years of landslides and floods are same. This reflects the joint
occurrence of the two hazards. Landslides occur in the hilly portion of the basin (Darjeeling Himalaya)
whereas floods occur in the plain portion of the basin (Jalpaiguri district) and the flood events occur after the
landslides because of topographic variation effect. This in turn indicates the influence of landslides on the
floods. The prominent causes of landslides in the basin are torrential rainfall, fragile geology, earthquake and
deforestation. The prominent causes of floods are sudden cloud burst, conditional basin surface morphology,
landslides and barrage, embankments and guide bunds construction.The record of consequences of these
two disasters brings in to focus the severe impact caused on the basin dynamics.
Landslides are widespread, frequent and sudden hazards that strike human lives, livestock, livelihood, living places and environment in an adverse manner leading to colossal losses and damages directly or indirectly in a cumulative way. The present paper is an attempt to compile the information related to the incidents and impacts of landslides in terms of their location, time of occurrence and losses/damaged caused to the humans, habitations and highways. The list of landslide incidences comprises 371 socioeconomically significant events with respect to the above-said point of view. It is neither complete nor exhaustive but only a representation of the facts and figures obtained from different sources like records of the revenue and disaster management departments in the hill states, reports of the Geological Survey of India and Department of Geology & Mines from the states, border roads organization, public works department, soil and water conservation departments, irrigation and flood control department, disaster management authorities, department of planning, statistics, space application centers, media reports and news archives, research publications from universities and research organizations etc. National Institute of Disaster Management in collaboration with Geological Survey of India and Central Statistical Organization has been working on a national disaster statistical system for compilation of data related to landslide disasters since the year 2007 (Parkash and Nair, 2008). However, most of the data under this project has been obtained from the GSI officials, media reports and state administration. But the initiative has given a good impetus to the efforts of data collection and compilation for landslides. The data reported in this paper clearly shows a better trend of information on landslide disasters during the years 2007-2011 compared to that gathered before the year 2007. The author has attempted to compile pertinent data on landslide disasters from the years 1800 to 2011 from all the above said sources of information / data. An examination of the available data indicates that 3971 people have been reported as killed in 248 fatal events out of 371 socioeconomically significant landslides over a period of about 300 years. It would be worthwhile to mention here that in the present study the information related to socioeconomically
Natural disasters in India, many of them related to the climate of India, cause massive losses of Indian life
and property. Droughts, flash floods, cyclones, avalanches, landslides brought on by torrential rains and
snowstorms pose the greatest threats. Landslides are common in the Lower Himalayas. Parts of the Western
Ghats also suffer from low-intensity landslides. Floods are the most common natural disaster in India. The
heavy southwest monsoon rains cause the Brahmaputra and other rivers to distend their banks, often
flooding surrounding areas. Though they provide rice paddy farmers with a largely dependable source of
natural irrigation and fertilization, the floods can kill thousands and displace millions. Excess, erratic, or
untimely monsoon rainfall may also wash away or otherwise ruin crops. Almost all of India is flood-prone,
and extreme precipitation events, such as flash floods and torrential rains, have become increasingly
common in central India over the past several decades, coinciding with rising temperatures. Mean annual
precipitation totals have remained steady due to the declining frequency of weather systems that generate
moderate amounts of rain. A natural disaster might be caused by earthquakes, flooding, volcanic eruption,
landslide, hurricanes etc. In order to be classified as a disaster it will have profound environmental effect
and/or human loss and frequently incurs financial loss. This review elucidates the natural disasters of
Tamil Nadu and its possible cause as well as the preventive/mitigation measures.
What is the treatment meted out to disasters by the government? How does the media treat the theme of recurring disasters? What is the status of information on disasters? What importance does academia give to the study and research on disasters? Only an intensive scrutiny of the answers to these questions can provide a comprehensive view of the concern for disasters in India, to do less would be a callous and careless approach to the victims of such disasters. The answers to these questions presented in this paper provide a distressing picture of the insensitivity of Indian society to disaster prevention and management.
Monitoring of Earth’s surface processes is eDciently performed by Differential SAR interferometry (DInSAR) techniques with the availability of open access Copernicus Sentinel-1A and 1B SAR data
products having 6 days temporal resolution. With over 750 landslides triggered in Kodagu district, Karnataka, India, interferometric wide swath (IW) mode Sentinel-1 datasets are used to identify landslide
locations. Interferograms from DInSAR obtained using Sentinel-1 VV polarization data are corrected using zenith total delay (ZTD) maps obtained from GACOS, which successfully assisted to identify major
landslides in the study area. Sentinel-1 DInSAR analysis has limitations over dense vegetative regions and terrain conditions (particularly in mountainous regions) due to spatial and temporal decorrelation. With the aid of InSAR time series analysis, integration of deformation recognized and land use/land cover pattern helps experts in providing near real-time mitigation measures during a disaster event.
Glacier velocity, the glacier's health indicator, is an emerging research interest in global warming among the scientific community over the current decade. As per scientific reports, due to their stable and advanced nature, the glaciers of Karakoram are exclusive. The present study focuses on understanding the temporal velocity variability of the Siachen Glacier, Shyok Basin, Karakoram using SAR datasets, in the perspective of the difficulties in estimating the glacier velocity over the inaccessible Karakoram Mountain. For the hydrological year 2017-18, 30 sentinel-1 derived interferograms using the DInSAR technique were analyzed to obtain Line Of Sight velocity. The transient velocity of the glacier reflects separate patterns within the glacier for different seasons due to the thermodynamic and orographic system over the glacier surface. In azimuth and range direction, the projected annual LOS velocity to a two-dimensional surface velocity is estimated to be around 103.8 ± 3.1 m/year.
India ranks first in the world in terms of fatal landslides. Large vulnerable area (0.42 million km2), high population density and monsoon rainfall make India’s landslide management and mitigation task difficult. Therefore, an understanding of landslide occurrences and exposure of socio-economic parameters on a national scale is essential to prioritise landslide mitigation efforts. In this paper, a database of 45,334 landslides (polygons) in India mapped by the National Remote Sensing Centre (NRSC) during the 1998–2018 period was compiled and catalogued in a WebGIS platform. High-resolution satellite data such as IRS PAN+LISS-III, Resourcesat LISS-IV Mx, Cartosat, WorldView, Pleiades and GeoEye were used to map landslides as small as 12 m2 to as big as 1,390,350 m2. GIS analysis using the landslide inventory revealed interesting results about control, exposure and pattern of landslide occurrences in India. The Northwest Himalayas contribute 66.5% of landslides in India, followed by the Northeast Himalayas (18.8%) and the Western Ghats (14.7%). The Greater Himalayan sequence consisting of high-grade metamorphic rocks has a considerable control (32%), and the Main Central Thrust is the major regional structure controlling (12%) landslides in India. In the Northeast Himalayas, the size of landslides and the slope gradient controlling landslide occurrence are less in comparison to the Northwest Himalayas and the Western Ghats. Landslides in the Western Ghats are triggered with a lesser amount of rainfall than the Himalayan regions. Exposure analysis using four key socio-economic parameters in the 145 hilly districts shows that Rudraprayag district is most affected by landslides in India. The understanding derived using the landslide database on a national scale will help to prioritise and strengthen landslide disaster risk reduction strategies in India.
This book focuses on the spatial distribution of landslide hazards of the Darjeeling Himalayas. Knowledge driven methods and statistical techniques such as frequency ratio model (FRM), information value model (IVM), logistic regression model (LRM), index overlay model (IOM), certainty factor model (CFM), analytical hierarchy process (AHP), artificial neural network model (ANN), and fuzzy logic have been adopted to identify landslide susceptibility. In addition, a comparison between various statistical models were made using success rate cure (SRC) and it was found that artificial neural network model (ANN), certainty factor model (CFM) and frequency ratio based fuzzy logic approach are the most reliable statistical techniques in the assessment and prediction of landslide susceptibility in the Darjeeling Himalayas. The study identified very high, high, moderate, low and very low landslide susceptibility locations to take site-specific management options as well as to ensure developmental activities in theDarjeeling Himalayas.
Particular attention is given to the assessment of various geomorphic, geotectonic and geohydrologic attributes that help to understand the role of different factors and corresponding classes in landslides, to apply different models, and to monitor and predict landslides. The use of various statistical and physical models to estimate landslide susceptibility is also discussed. The causes, mechanisms and types of landslides and their destructive character are elaborated in the book. Researchers interested in applying statistical tools for hazard zonation purposes will find the book appealing.
Development of Synthetic Aperture Radar (SAR) based satellites provide remedies to major geohazards under critical situations around the world. Sentinel 1A mission with the revisit period of 12 days helps to serve the objective in an effective manner. With the availability of Interferometric Wide Swath (IW) mode, Sentinel 1A mission is capable of monitoring the surface deformation using InSAR techniques. On November 12th, 2017, an earthquake with a magnitude of 7.3 occurred in the Iran/Iraq border lead to the enormous disaster reaching over 500 victims. The study focuses on measuring the deformation caused due to earthquakes by using Differential SAR Interferometry (DInSAR). VV polarization of Sentinel Data and SRTM DEM are used as an input to GMTSAR for the development of interferogram. Based on the results obtained, it is found that a maximum of 85.1 cm deformation occurred and nearly 1500 km2 of the area is severely affected.
Landslides are considered as one of the most common natural hazards occurring in the Nilgiris since immemorial time that leads to the tremendous loss of human life, property and economy. In this study, landslide hazard zonation (LHZ) map for the Nilgiris district located in the state of Tamil Nadu, was prepared using various thematic layers such as Precipitation, Slope, Geology, Aspect, Land cover, Distance from road, Lineament Density, Distance from river, Elevation. The results obtained by adopting analytical hierarchy process (AHP) for updation of LHZ map found that nearly 52.5% of the total district area falls under risk zone in which 6% of the regions is fall under highly risk zone. Comparison the LHZ map with the inventory data, data it is found that nearly 90% of the landslides fall under hazardous zone.
Landslides are one of the most important and major natural hazards that mankind is facing all over the world. This phenomenon is very common in the hilly regions of the Nilgiris Dt, Tamilnadu. This paper tries to analyse various factors that influences landslides in this region. This initial study marks the first attempt to find a integrated solution to arrive a suitable landslide mitigation measure.
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