GEOTECHNICAL INVESTIGATION OF AMIYAN LANDSLIDE HAZARD ZONE IN HIMALAYAN REGION, UTTARANCHAL, INDIA

2005 ◽  
Author(s):  
T.N. Singh ◽  
Kripamoy Sarkar
Keyword(s):  
Landslide Hazard ◽  
Himalayan Region ◽  
Geotechnical Investigation ◽  
Hazard Zone

A multi-temporal landslide inventory and hazard zonation using relative effect method along the Mughal road Shopian, India

2021 ◽  
Vol 14 (7) ◽  
pp. 42-51
Author(s):  
Bashir Subiaya ◽  
T. Ramkumar
Keyword(s):  
Causative Factor ◽  
Statistical Technique ◽  
Relative Effect ◽  
Landslide Hazard ◽  
Landslide Inventory ◽  
Hazard Mapping ◽  
Mountain Range ◽  
Jammu And Kashmir ◽  
Hazard Zone ◽  
Effect Method

Landslide inventory and thematic data are of utmost importance in the domain of landslide hazard mapping. The union territory of Jammu and Kashmir, India surrounded by the Himalayan and the Pir-Panjal mountain range is prone to landslides and has already caused havoc at many places. The present study aims to provide the landslide inventory of the Mughal Road, Shopian, which lies in the Pir Panjal range of Kashmir valley. Multidate satellite data of the years 2008 to 2020 are utilized to create an inventory of landslides in this area.The use of high-resolution satellite imagery made it possible to delineate the shallow as well as the deep landslides along the roadside where they occur frequently. To understand the landslide causes, a statistical technique, relative effect method has been implemented in this study. This method helped in mapping the hazard zone areas. The relative effect of each causative factor on landslides is determined by calculating the ratio of coverage and slide which were analyzed in GIS environment. The resulting landslide hazard zone map has been classified as very low, low, moderate, high and very high zones. Out of the total area, 12.62% is critical to landslides, 21.45% is highly prone and 24.84% is moderately prone while 21.94% is low and 19.13% is very low prone to landslides. The outcome of this susceptibility modeling will be beneficial for handling and monitoring the forthcoming landslides as well as the fortification of the general public and environmental hazards of the study area. It will also help the planners in the development around the study area.

scholarly journals Landslide Hazard Zonation and Evaluation Around Debre Markos Town, NW Ethiopia—A GIS-Based Statistical Approach

2021 ◽  
Author(s):  
Dawit Asmare Manderso
Keyword(s):  
Research Area ◽  
Landslide Hazard ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
Zonation Map ◽  
Hazard Zone ◽  
High Hazard ◽  
Debre Markos ◽  
Moderate Hazard ◽  
Very High

Abstract The main goal of this research was to perform a landslide hazard zonation and evaluation around Debre Markos town, North West Ethiopia, found about 300 km from the capital city Addis Ababa. To achieve the aim, a GIS-based probabilistic statistical technique was used to rate the governing factors, followed by geoprocessing in the GIS setting to produce the landslide hazard zonation map. In this research, eight internal causative and external triggering factors were selected: slope material (lithology and soil mass), elevation, aspect, slope, land use land cover, curvature, distance to fault, and distance to drainage. Data were collected from field mapping, secondary maps, and digital elevation models. Systematic and detailed fieldwork had been done for image interpretation and inventory mapping. Accordingly, the past landslides map of the research area was prepared. All influencing factors were statistically analyzed to determine their relationship to previous landslides. The results revealed that 17.15% (40.60 km2), 25.53% (60.45 km2), 28.04% (66.39 km2), 18.93% (44.83 km2), and 10.36% (24.54 km2) of the research area falls under no hazard, low hazard, moderate hazard, high hazard, and very high hazard respectively. The validation of the landslide hazard zonation map reveals that 1%, 2%, 3%, and 94% of past landslides fall in no hazard zone, low hazard, moderate hazard zone, and high hazard or very high hazard zones respectively. The validation of the landslide hazard zonation map thus, it has been adequately demonstrated that the adopted approach has produced acceptable results. The defined hazard zones can practically be utilized for land management and infrastructure construction in the study area.

scholarly journals LANDSLIDE HAZARD ZONATION STUDY IN EASTERN INDIAN HIMALAYAN REGION

2017 ◽  
Vol 3 (1) ◽  
pp. 35-46
Author(s):  
Manmohan Singh Rawat ◽  
Rajendra Dobhal ◽  
Varun Joshi ◽  
Yaspal Sundriyal
Keyword(s):  
Landslide Hazard ◽  
Himalayan Region ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
Indian Himalayan Region

scholarly journals Landslide hazard and risk zonation of Thankot – Chalnakhel area,

1970 ◽  
Vol 31 ◽  
pp. 43-50 ◽  
Author(s):  
Pradeep Paudyal ◽  
Megh Raj Dhital
Keyword(s):  
Landslide Hazard ◽  
Geographical Information ◽  
Hazard Map ◽  
Risk Map ◽  
Risk Zonation ◽  
Hazard Zone ◽  
Risk Zones ◽  
Vulnerability Map ◽  
Landslide Hazard Map ◽  
Moderate Hazard

The rocks in the Thankot–Chalnakhel area constitute the Chandragiri Range bordering the Kathmandu valley. The Phulchauki Group of rocks comprise its steep and rugged south slope, whereas the gentle north slope is covered by fluvio-lacustrine deposits of the Kathmandu basin with some recent alluvial fans. During the field study, 94 landslides (covering about 0.24 sq km) were mapped. Most of them were triggered by intense rainfall within the last two years. Landslides are generally found on steep colluvial slope (25°–35°) and dry cultivated land. Based on a computer-based geographical information system, a landslide hazard map, a vulnerability map, and a risk map were prepared. The landslide hazard map shows 20% of the area under high hazard zone, 41% under moderate hazard zone, and 39% under low hazard zone. The risk map generated by combining the hazard map and vulnerability map shows 19% of the area under high and very high risk zones, 33% under moderate risk zone, and 48% under low and very low risk zones.

scholarly journals Landslide hazard assessment around MCT zone in Marsyangdi River basin, west Nepal

2017 ◽  
Vol 53 ◽  
pp. 93-98
Author(s):  
Subash Acharya ◽  
Dinesh Pathak
Keyword(s):  
Logistic Regression ◽  
River Basin ◽  
Hazard Assessment ◽  
Landslide Hazard ◽  
Slope Aspect ◽  
Hazard Map ◽  
Landslide Hazard Assessment ◽  
Hazard Zone ◽  
High Hazard ◽  
Landslide Hazard Map

In the hilly and mountainous terrain of Nepal, landslide is the most common natural hazard especially during prolong rainfall. Every year landslide cost lives and causes injuries. In order to address this problem, the best that can be done is to prepare the landslide hazard map of the area, apply mitigation measures and evacuate the high hazardous area, if necessary. Landslide hazard assessment is the primary tool so as to understand the nature and characteristics of the slope that are prone to failure. Logistic Regression Model is used for the preparation of landslide hazard map of the Besi Shahar-Tal area in Marsyangdi River basin in west Nepal. The causative factors such as elevation, slope, slope aspect, land use, geology, rainfall, lineament density, stream density are used. All the thematic layers of these parameters are prepared in GIS and logistic regression analysis is done by using Statistical Package for Social Science (SPSS). Five different hazard zones are separated namely very low hazard zone, low hazard zone, medium hazard zone, high hazard zone and very high hazard zone. The high hazard zone is lying along the Marsyangdi River and its tributaries.

scholarly journals Landslide Hazard Zonation and Evaluation around Debre Werk Town, North West Ethiopia

2021 ◽  
Author(s):  
Dawit Asmare ◽  
Chalachew Tesfa
Keyword(s):  
Landslide Hazard ◽  
Rating System ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
North West ◽  
Triggering Factors ◽  
Hazard Zone ◽  
North West Ethiopia ◽  
High Hazard ◽  
Moderate Hazard

Abstract The present research was conducted in the town of Debre Werk, East Gojjam, North West Ethiopia, with the ultimate aim of conducting a Landslide Hazard Zonation and Evaluation. To reach this aim, the Slope Stability Susceptibility Evaluation Parameter (SSEP) rating system was adopted to zone and evaluate the landslide status of the area. This rating system was done by considering the parameters of intrinsic and external triggering factors that cause landslides. Systematic and detailed fieldwork had been undertaken as a justification. Secondary data, on the other hand, was required to define the general conditions of the area and to gain a thorough understanding of the field of study. Ratings for intrinsic parameters in the SSEP system include slope morphometry, relative relief, slope content, geological structures/discontinuities, land use land cover, groundwater, and external parameters include erosion, seismicity, and manmade activities. Individual facet-wise ratings for intrinsic causative factors and external triggering factors ratings are summarized to evaluate the landslide hazard zonation of an environment. The sum of all causative parameter ratings will give evaluated landslide hazards (ELH). Therefore, the research was carried out by dividing the study area into 70 facets. Then 85 landslide incidents in the study area were investigated. From 85 landslides, 39 districts showed past landslides, 23 showed active landslides and the remaining 23 districts showed signs of landslides. The delineated 70 facets were categorized into 3 landslide hazard zones. There are about 73.3km2 (27.2%) of the study area within the low hazard zone, 140.8km2 (52.1%) within the moderate hazard zone, and the remaining 55.9km2 (20.7%) within the high hazard zone. Based on the findings of SSEP, it can be deduced that the present research area is highly susceptible to landslide and requires special attention during rainy seasons. Finally, the validity of the prepared LHZ map was checked by overlaying the inventory map over the produced LHZ map. The overlap map shows that 17 districts showing active landslides, 2 districts showing signs of landslides, and 5 districts showing past landslide activities fall into high hazard zones. Likewise, 5 districts showing active landslides, 3 districts showing signs of landslides, and 28 districts showing past landslides fall into moderate hazard zones. The remaining 1 district showing active landslides, 18 districts showing signs of landslides, and 6 districts showing past landslide activities fall into moderate hazard zones.

Landslide hazard zone mapping using Information Value model: the case of Gidole Landslide, Southern Ethiopia

2020 ◽  
Author(s):  
Filagot Mengistu Walle ◽  
Karuturi Venkata Suryabhagavan ◽  
Tarun Raghuvanshi ◽  
Elias Lewi
Keyword(s):  
Causative Factor ◽  
Landslide Hazard ◽  
Information Value ◽  
Southern Ethiopia ◽  
Causative Factors ◽  
Hazard Zone ◽  
Information Value Model ◽  
High Hazard ◽  
Value Model ◽  
Factor Maps

<p>Landslide hazard is becoming serious environmental constraints for the developmental activities in the highlands of Ethiopia. With the current infrastructure development, urbanization, rural development, and with the present landslide management system, it is predictable that the frequency and magnitude of landslide and losses due to such hazards would continue to increase. In the present study landslide hazard zone mapping were carried out in and around Gidole Town in Southern Ethiopia. The main objective of the study was to map landslide hazard zone using Information Value Bi-variant statistical model.  For landslide hazard zonation of the study area six causative factors namely; aspect, slope angle, elevation, Lithology, Normalized Deference Vegetation Index (NDVI) and land-use and land-cover were considered. The landslide inventory mapping for the present study area was carried out through field observations and Google Earth image interpretation. Later, Information value was calculated based on the influence of causative factors on past landslide. The distribution of landslide over each causative factor maps was obtained and analyzed. Weights for the class with in these causative factor maps was obtained using information value model. Distribution of landslide in the study area was largely governed by aspect of southwest facing, slope angel of 30-45<sup>o</sup>, elevation of 1815–2150m, NDVI of 0.27−0.37, Lithology of colluvial deposit and land-use and land-cover of agricultural land. The landslide hazard zonation map shows that 78.38km<sup>2</sup> (36.3%) area fall within very low hazard (VLH) zone, 72.85km<sup>2</sup> (34.2%) of the area fall within low hazard (LH) zone, 12.78 km<sup>2</sup> (6.6%), 32.72 km<sup>2</sup> (15.4%) and 15.89 km<sup>2</sup> (7.5%) of the area falls into very high hazard (VHH), high hazard (HH) and moderate hazard (MH), respectively. Further, validation of LHZ map with past landslide inventory data shows that 92.3% of the existing landslides fall in very high hazard (VHH) and high hazard (VHH) zone. Thus, it can safely be concluded that the hazard zones delineated in the present study validates with the past landslide data and the potential zone depicted can reasonably be applied for the safe planning of the area.</p><p><strong>Key words</strong>: Landslide, Gidole, Landslide hazard zone, Information Value model</p>

Causes and extent of environmental impacts of landslide hazard in the Himalayan region: a case study of Murree, Pakistan

2010 ◽  
Vol 57 (2) ◽  
pp. 413-434 ◽  
Author(s):  
Atta-ur-Rahman ◽  
Amir Nawaz Khan ◽  
Andrew E. Collins ◽  
Fareen Qazi
Keyword(s):  
Environmental Impacts ◽  
Landslide Hazard ◽  
Himalayan Region

scholarly journals Analysis Geological and Geophysical Data for Prediction Landslide Hazard Zone with Weight of Evidence Method in Pacitan District East Java

2018 ◽  
Vol 2 (1) ◽  
pp. 117-123
Author(s):  
Radhitya Adzan Hidayah ◽  
Nurul Dzakiya
Keyword(s):  
Data Analysis ◽  
Posterior Probability ◽  
Structural Data ◽  
Landslide Hazard ◽  
Geophysical Data ◽  
Weight Of Evidence ◽  
Rock Density ◽  
Probability Map ◽  
Hazard Zone ◽  
Moderate Hazard

Pacitan district have an interesting anomaly. Every time mostly impacted by disaster especially landslide. Landslides in their various forms are common hazard in mountainous terrain, especially in seismically active areas and regions of high rainfall. Landslides are one of the most common natural hazards in the Southern Range East Java terrain, causing widespread damage to property and infrastructure, besides the loss of human lives almost every year. The aim of this study predicted the potential landslide using Weight of Evidence Method. The geological data used lithological data, structural data, contour data and, alteration. Results from this data analysis are six evidence maps, such as NE-SW lineament, NW-SE lineament, host rock, heat source, kaolinite alteration and iron oxide alteration maps. The geophysical data analysis the distribution of rock density to interpretation the landslides. Evidence maps were analyzed by weight of evidence methods to result in favorable maps where the validity was tested using conditional independence (CI), the pairwise and overall tests. Then, the analyses produced a posterior probability map of the landslide. Posterior probability map (mineral potential maps) was validated by checking field. Posterior probability map (after validation) or favorable map predicted approximately favorable zone and non-favourable zones. Favorable zones of Potential Landslide Hazard Zonation, are divided into three classes. They are high-potensial hazard, moderate hazard and low hazard.   Keywords: Pacitan, GIS, Weight of Evidence, Landslide

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