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Landslide hazard evaluation and zonation mapping in mountainous terrain
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Landslide hazard zonation (LHZ) maps are of great help to planners and field engineers for selecting suitable locations to implement development schemes in mountainous terrain, as well as, for adopting appropriate mitigation measures in unstable hazard-prone areas. A new quantitative approach has been evolved, based on major causative factors of slope instability. A case study of landslide hazard zonation in the Himalaya, adopting a landslide- hazard evaluation factor (LHEF) rating scheme, has been presented.
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... Hence, quick slope stability assessments have been developed. Several analytical methods can identify landslide-prone locations (Anbalagan 1992). They might be expert-based (qualitative), statistical, or deterministic (quantitative) (Leroi, 1997;Fall et al., 2006). ...
... Expert expertise is crucial to the heuristic approach to landslide susceptibility assessment. Using slope angle, soil type, and land use maps, geoscientists assign numerical ratings based on their expertise and prior observations of slope stability (Dai et al., 2002;Anbalagan, 1992). Although subjective, this strategy is acclaimed for its simplicity and capacity to use field data with expert insights (Fall et al., 2006;Raghuvanshi et al., 2014Raghuvanshi et al., , 2015. ...
... In the geo-dynamically active Nilgiris, landslide is a common phenomenon [1][2][3]. Landslides are the most predictable and potential geological hazards. Most of the landsides in Nilgiris occur in road-cut slopes, habitat areas and agricultural areas, causing damage to humans and the infrastructure. ...
... Two major fault systems control this ridge (eastern Punna puzha, and western Karakkodu puzha). These two discontinuities are similar to the Eastern Ghat Orogeny direction [3]. It is alien N-41 o and N-21 o, and two minor thrust zones are identified in the western slope (Fig. 14. a and b). ...
— Landslides are short-lived phenomena but can cause extraordinary changes in the landscape, destroying life and property. Mitigation and management of natural disasters are important issues. Recognising this, the United Nations in the year 2004 made gout “Learning from today’s disaster for tomorrow’s hazards”(UNISDR website). The Nadugani Hill is situated in SE of Panthalur taluk, Nilgiris District. The ghat section is 6.5 km in length. The region has moderate climatic conditions. The average rainfall in this ghat section is 3500mm. In this ghat section, two major activities, like tea plantation and heavy truck movement, lead to slope instability during heavy monsoon season. The study mainly aimed to use terrain factors and identify land susceptibility zonation. In this context, a detailed investigation was carried out using geomorphology, parent rock weathering, structural mapping, runoff and anthropogenic activities. The ghat section is covered by a thick Reserve Forest, a tea plantation and a smaller area enclosed by settlement. Hornblende biotitic gneiss and patches of charnockite in some places cover the study area. The gneissic rocks are highly fissile in nature. NE - SW fault controls the drainage systems, contributing to landslides. The structural data delineated from IRS-RS2, L-IV data and the lineaments are oriented in NE - SW. Morphology is one of the prime factors that cause which is landslides. Satellite imageries identify structural and fracture valleys in this study area. The thematic maps were converted into a digital format using ARC Map (10.2v) software. GIS-based Decision Support System provides advanced models of a system to identify land susceptibility zonation. Based on the analysis, the study area has been categorized into low, moderate, high and very high classes.
... A crucial evaluation in lithological terms is related to the degree of decomposition of the units. In his study, Anbalagan (1992) considered lithology, particularly in terms of being susceptible to erosion and weathering. This is because the researcher discovered during the field studies that quartzite, limestone, and granites are less susceptible to weathering than other units (clay, marl, and so on), and these units constitute the high slopes of the field. ...
The primary goal of the present study was to use Spatial Multi-Criterion Analysis (SMCA) management based on the integration of Analytical Hierarchical Process (AHP) and Geographic Information System (GIS) approaches to construct a landslide susceptibility mapping model for the Central Black Sea region. Four different main indicators (topography, land use-land cover, geology, and soil) were determined in the model, and maps related to them were produced using GIS. According to the present model, 10.0% of the research area was found to be in the high-risk class, whereas 30.3% were in the low and very low-risk classes. On the other hand, the medium-risk class covered more than half of the study area. Moreover, measurements were taken on a control network consisting of fifteen points, and mobility was observed to verify the model in the study area. For this purpose, the coordinates obtained from the measurements made in six different periods were compared, and the results revealed that the coordinate difference values were agreed with the model data. Finally, the landslide susceptibility mapping model showed parallel with field validation. The current study is a guide for reducing the impact of natural disasters by monitoring landslide areas.
... Assessment of landslide susceptibility (or likelihood of landslides) is the first step in this direction. Landslide susceptibility maps depict landslide threat zones considering the terrain characteristics and geo-environmental factors (Ali et al. 2018;Anbalagan 1992;Guzzetti et al. 2006;Huang et al. 2012;Zezere et al. 2017). ...
Landslide is one of the most destructive geomorphic hazards that usually occur in monsoon in the Darjeeling Himalayas. To minimize the landslide-induced causalities present study aims to assess the landslide susceptibility along a major transportation corridor, i.e., National Highway 110 (NH-110)—Darjeeling Himalayan Railway (DHR) in Darjeeling Himalayas. Geographic Information Systems (GIS)-based Multi-Criteria Decision Analysis (MCDA) approaches, i.e., Analytic Hierarchy Process (AHP) and Multi-influencing Factor (MIF) have been used for this purpose. Ten geo-environmental factors; elevation, slope, aspect, curvature, lithology, lineament density, rainfall, drainage density, topographic wetness index (TWI) and land use were identified as landslide causative factors. All the topographical and hydrological factors were extracted from a 12 m resolution TanDEM-X Digital Elevation Model (DEM). Lithology, lineament, and land use maps were prepared after interpretation of Landsat 8 OLI (2021) satellite image in conjunction with Google Earth image and intensive field survey. Landslide inventory was prepared from multi-temporal satellite images (2015–2021). The AHP-based landslide susceptibility map showed that 7.19% of the area comes under very high, 79.04% as high, 8.98% as moderate, and 4.79% as low susceptible zone. Whereas, in the MIF-based approach it is 11.38%, 81.43%, 1.80%, and 5.39%, respectively. In this study slope was identified as the most determining factor of landslide, followed by lithology, rainfall, and land use. The Receiver Operating Characteristics (ROC) curve shows that the AHP-based approach is comparatively better (0.776) than the MIF (0.757). Moreover, it can be concluded that both approaches performing well in the Himalayan terrain.
... Landslides and rock falls are known as one of the most common Natural hazards that threaten human civilization and welfare in many parts of the world. [1]. These phenomena are defined as mass (soil and rocks) movement in an unstable condition which often led massive damage to humanity as much as economic loss, financial cries even injuries or Causalities [2]. ...
Landside and Rock falls are known as the most destructive natural hazards that threaten the inviolability of Human communities and infrastructures such as houses, Dames, Tunnels, Roads, etc. Roads in the mountainous area are known more vulnerable because of different factors like route cute disturbing and mass imbalances. Kabul-Jalalabad highway is a major part of Afghanistan's transitional route that connects the central regions to the eastern part of the country. The transportation system of this route is threatened by mass movement and rockfall events. This study used nine conditional factors including slope, lithology, (TWI), road distances, LU/LC, Curvatures, slope direction (aspect), precipitation, and fault distance. two modules (Analytic hierarchical process (AHP) and Weighted overly mapping (WOM)) are used in this study, Finally, the Landslide Susceptibility Map(LSM) of both modules is Classified into five zones(very high, high, moderate, low and very low) of susceptibility in Arc GIS 10.8; after pairwise comparison in spice-logic 4.1.4 software; slope, lithology, slope direction, precipitation, and fault distance respectively identified as effective factors in landslides and rock fall susceptibility, final (LSM) of both methods shows that high and very high levels sensitivity zones Covers 21.35%, 8.43% for AHP and 40.16%, 10.72% for WOM modules respectively, Accuracy assessment of both module done based on 101 locational denoted landslides, (ROC) curve and AUC index are used to classifiers accuracy evaluation; finally AHP module known as much better than (WOM) one because of its (AUC) value that shows 0.923(Excellent) greater than 0.845(very good) (AUC) index of (WOM) module.
Malshej Ghat is one of the busiest transport corridors in Maharashtra. It is highly prone to landslides, as the region receives heavy precipitation and steep slopes along the road section. This manuscript focuses on the applicability and reliability of block size and shape classification techniques in the assessment of the stability of the road-cut rock slopes. Structurally weak zones extending along and across the road section are identified as a lineament, and accordingly, slopes are chosen for in-depth analysis. Kinematic analysis signifies that wedge failure is observed to be the most common type of failure, while planar and toppling failures are observed at places. The rock blocks which are produced as a result of the intersection of different joint sets are mainly cubic, cubic-elongated and elongated in shape, whereas platy, platy-cubic and elongated-platy blocks are very less in proportion. Volume and surface area of rock blocks play a vital role in the movement of the blocks. The rock mass is observed to be nearly poor to fair in quality; however, the numerical simulation shows that the slopes MRS-1, MRS-5, and MRS-7 are critically stable.
The present study introduces “rock slope instability score (RSIS)” a novel classification system for assessing rock slope stability. It takes into account geological and geotechnical parameters, as well as the impact of human activities and triggering parameters, which have become more frequent due to climate change and few of them have been ignored in existing classifications. The study focuses on rock slopes of various lithologies from the Indian Himalayas. The development of this new classification system is based on the examination of 81 different rock slopes from various states of the Indian Himalayas. Extensive field surveys, rock sampling, geotechnical laboratory tests, and ground measurements have been conducted at the various slope sites to establish a comprehensive scoring system for the stability assessment. The distributions of weightage to each parameter have been considered, corresponding to its degree of impact in causing slope instability. Sensitivity analysis of all defined parameters of RSIS system has revealed that the majority of the parameters exhibit a strong positive correlation, with Pearson correlation coefficients ranging from 0.74 to 0.61. However, two parameters, namely discontinuity dip and the relationship between slope & discontinuity direction, gives moderate relationship with correlation coefficient values of 0.48 and 0.41, respectively. To avoid any designer biasness in the system, several individuals gathered data set at different times. The proposed classification system has demonstrated a strong correlation with the actual slope condition, and it is quite promising. The outcome of RSIS classification for studied 81 slopes classified 2 slopes under stable condition, 21 slopes as partially stable, 44 as unstable, and 14 as completely unstable.
To date, 3D geospatial models in landslide studies are gaining less attention than other environment-related studies due to the complex integration of geotechnical and hydrological processes. The current model mostly separates the material failure from propagation due to the complexity of integrating the dynamic process with a computational framework. As for 3D slope stability analysis using DEM necessitates rather complex algorithms aimed at iteratively predicting landslides, which are tedious and yield results that do not reflect their potentialities. Hence, an attempt to model 3D fluid and landslides with an indeterminate spatial extent is required to establish a more comprehensive nature representation model. The 3D SWD FLOW data model was specially designed to represent data from the slope, rainfall and soil water infiltration into a 3D model. The methodology employs cumulative antecedent working rainfall to calculate the rainfall threshold. The factor of safety (FOS) is based on the infinite slope model applied to a theoretically identical model. 3D SWD FLOW comprises resource assessment, landslide identification, landslide analysis, forecast landslide and vulnerability assessment; while the main parameters that trigger landslides include rainfall, infiltration and FOS. 3D SWD FLOW created three primary 3D models for the triggering elements, including models based on B-Rep Solid boundry, Multi-Dimensional Arrays, Random Walk Equation, Volume of Ellipsoid and Consistent Sliding Direction. The resulting 3D SWD FLOW model were visualized through Processing-3 software platform, which indicates one of the first to attempt to model a dynamic natural landslide process with software not explicitly created for 3D models.
Landslides are a serious concern in steep terrain where severe storms are common. The magnitude of landslide risk depends not only on storms and the physical characteristics of the land, but human activities, especially agricultural practices, are important. An essential stage in the management of landslide risk and hazard is landslide hazard assessment. Landslide Hazard Zone (LHZ) choice processes include intuitive, half size, Quantification, Probability and Multi-criteria approaches. Among the various techniques used traditionally, Multivariate approaches, albeit with limitations, to assess landslide risk at a regional scale Very feasible and cost effective. Over the past two decades, landslide research has expanded use of the sophisticated tools of remote sensing and geographic information systems (GIS) to study landslide hazards.
Engineering Classification of Rock Masses for the Design of Tunnel Support An analysis of some 200 tunnel case records has revealed a useful correlation between the amount and type of permanent support and the rock mass qualityQ, with respect to tunnel stability. The numerical value ofQ ranges from 0.001 (for exceptionally poor quality squeezing-ground) up to 1000 (for exceptionally good quality rock which is practically unjointed). The rock mass qualityQ is a function of six parameters, each of which has a rating of importance, which can be estimated from surface mapping and can be updated during subsequent excavation. The six parameters are as follows; theRQD index, the number of joint sets, the roughness of the weakest joints, the degree of alteration or filling along the weakest joints, and two further parameters which account for the rock load and water inflow. In combination these parameters represent the rock block-size, the interblock shear strength, and the active stress. The proposed classification is illustrated by means of field examples and selected case records. Detailed analysis of the rock mass quality and corresponding support practice has shown that suitable permanent support can be estimated for the whole spectrum of rock qualities. This estimate is based on the rock mass quality Q, the support pressure, and the dimensions and purpose of the excavation. The support pressure appears to be a function ofQ, the joint roughness, and the number of joint sets. The latter two determine the dilatency and the degree of freedom of the rock mass. Detailed recommendations for support measures include various combinations of shotcrete, bolting, and cast concrete arches together with the appropriate bolt spacings and lengths, and the requisite thickness of shotcrete or concrete. The boundary between self supporting tunnels and those requiring some form of permanent support can be determined from the rock mass qualityQ.
This tectonic junction between the Lesser Himalaya and Siwalik molasse represents a zone along which underthrusting still occurs. Depositional terraces formed as a consequence of subrecent and historical landslides have been faulted and displaced vertically as well as horizontally in the Balia Valley, which follows the thrust. Vertical scarps and triangular facets on the hillsides, uplift and dissection by faults of terraces and landslide fans, and presence of abandoned valleys, further bear testimony to recent movements with uplift of the Siwalik domain by 30 to 80m relative to the Lesser Himalayan belt.-from Authors
This report discusses tunnel design procedures based on various rock mass classification systems. A comparison is made between the tunnel support design based on the classical Terzaghi rock load method and the support selection based on the RSR Concept, the Geomechanics Classification, and the Q- System. These classification systems are described and guidelines are given for step-by-step application of the three methods. Using an actual tunnel case history, an evaluation is made of the current design practice by comparing it with the design approaches involving the three rock mass classification systems. It is concluded that the current design practice may lead to overdesign of support, and recommendations are made for improved procedures that would ensure the construction of safe and more economical rock tunnels. Finally, a few areas are identified where more research would benefit the current tunnel design practice. This report was reprinted in FY 89 during which time a bibliography covering the appropriate literature through 1986 and a discussion of recent developments were added. (edc)
Tunnel design by rock mass classifica-tions. Pennsylvania State Univ
- Z T Bieniawski
Bieniawski, Z.T., 1979. Tunnel design by rock mass classifica-tions. Pennsylvania State Univ., USA, Tech. Rep.,
Geomorphic development across the main boundary thrust, an example from the Nainital hills in Kumaun Himalaya
- K S Valdia
- D D Joshi
- R Sanwal
- S K Tandon
Valdia, K.S., Joshi, D.D., Sanwal, R. and Tandon, S.K., 1984.
Geomorphic development across the main boundary thrust,
an example from the Nainital hills in Kumaun Himalaya.
J. Geol. Soc.Ind., 25(12):761-774.
Geomorphic development across the main boundary thrust, an example from the Nainital hills in Kumaun Himalaya
- Valdia