1) The document discusses landslides in the Himalayan region of India, specifically in Kullu district. It notes that landslides frequently occur after heavy rains and have increased with more development projects destabilizing slopes. 2) The project is divided into three stages: macrozonation to map landslide risk zones, microzonation to validate the map with field studies of individual sites, and developing mitigation measures. 3) Literature on landslide types is reviewed, including definitions, common causes like heavy rain, and previous studies using remote sensing and GIS for landslide analysis and risk prediction.

1. 1
CHAPTER 1
INTRODUCTION
Landslide is sliding down of large mass of earth along the slopes to the bottom. They are
natural hazards that cause huge loss to life and property, both public and private property.
They are widespread in the Himalayan region. They occur annually in the region after heavy
rains. With the increase of human activities like developmental projects, the fragile slopes
have become unstable and pose threat to the population living in these areas.
Kullu district is a major tourist location of India and thousands of people visit the place
annually. Apart from that, it is a producer of Apple crop, other fruits and vegetables which
need to be transported to markets. Hence the road network has to be efficient and well
maintained for handling heavy traffic. It has been observed that road-cutting has led to
landslides throughout the district due to the instability of the base of the slope. Most of the
landslides occur along the roads which block the traffic for very long duration and sometimes
even take down the road along with them.This has necessitated the requirement for gathering
accurate information about the slopes, soil parameters, susceptibility of landslides, risk of
economic loss and the mitigation measures that can be applied.
We have divided our project in three main stages- Macrozonation, Microzonation and
Mitigation. Macrozonation refers to displaying the spatial distribution of landslides along
with their probability of occurrence. This is done on a large scale i.e. for the whole district,
hence the name macrozonation. The factors that contribute in triggering the landslides are
found. Their individual effect and their overall weightage is studied. Their combined effect is
calculated using the AHP process and landslide hazard zonation map is generated using GIS
system. In this map, categorization of land area is done into zones of low, medium and high
probability of landslides.
The next stage is of Microzonation. The map generated by Macrozonation is cross checked
for its reliability by comparing the zones of high risk of landslides with actual landslide
sites.In Microzonation, individual landslide sites are visited. Each failure slope is surveyed
for the type of failure pattern and soil samples are collected for each site. Testing is done on
the soil samples and its strength parameters are calculated. The parameters are fed to the
software to do the analysis.
The final stage is mitigation. The suitable mitigation measures are designed which are
feasible with respect to the local environment, climate, economy and availability of materials.
These measures must be able to protect the vulnerable slopes from failing and causing large
scale landslides.

2. 2
CHAPTER 2
OBJECTIVES
1) Macrozonation of landslide hazard in Kullu District using GIS.
2) Microzonation and geotechnical analysis of few Landslides.
3) Mitigation measures suggested for the region.
MACROZONATION MICROZONATION MITIGATION

3. 3
CHAPTER 3
LITERATURE REVIEW
3.1 GENERAL
In this chapter types of landslides, general landslide causes, and previous landslide studies in
India and around the world are briefly explained. Landslide definition from literature can be
organized into three stages:
Detection and classification of landslides, monitoring activity of existing landslides and
analysis and prediction of the slope failures in space (spatial distribution) and time (temporal
distribution. In general way, the results of an international research projects dealing with the
application of Remote Sensing and GIS in Landslide analysis and prediction of slope failures
are briefly reviewed in this chapter.
Landslides are recognized as the third type of natural disaster in terms of worldwide
importance. Due to natural conditions or man- made actions, landslides have produced
multiple human and economic losses. Individual slope failures are generally not so
spectacular or so costly as earthquakes, major floods, hurricanes or some other natural
catastrophes. Slope failures are more widespread, and over the years they may cause more
damage to properties than any other geological hazards. Most of the damages and a
considerable proportion of the human losses associated with earthquakes and meteorological
events are caused by landslides, although these damages are attributed to the main event
which leads to a substantial underestimation of the available statistical data on landslide
impact.
3.2 TYPES OF LANDSLIDES IN GENERAL
The term "landslide" describes a wide variety of processes that result in the downward and
outward movement of slope-forming materials including rock, soil, artificial fill, or a
combination of these. The materials may move by falling, toppling, sliding, spreading, or
flowing. Figure 2.1 shows a graphic illustration of a landslide, with the commonly accepted
terminology describing its features.
Figure 3.1 An idealized slump-earth flow showing commonly used nomenclature for labelling
the factors of a landslide

4. 4
The various types of landslides can be differentiated by the kinds of material involved and the
mode of movement. A classification system based on these parameters is shown in Table 3.2.
Other classification systems incorporate additional variables, such as the rate of movement
and the water, air, or ice content of the landslide material.
Table 3.1 Types of landslides and the Abbreviated version of Varnes’ classification of slope
movements (Varnes 1978)
Although landslides are primarily associated with mountainous regions, they can also occur
in areas of generally low relief. In low-relief areas, landslides occur as cut-and-fill failures
(roadway and building excavations), river bluff failures, lateral spreading landslides, collapse
of mine-waste piles (especially coal), and a wide variety of slope failures associated with
quarries and open-pit mines. The most common types of landslides are described as follows
and are illustrated in Figure 3.2.

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Figure 3.2 Illustration of major types of landslide movement
3.2.1 Slides
Although many types of mass movements are included in the general term "landslide," the
more restrictive use of the term refers only to mass movements, where there is a distinct zone
of weakness that separates the slide material from more stable underlying material.
The two major types of slides are rotational slides and translational slides.
a) Rotational slide: This is a slide in which the surface of rupture is curved concavely
upward and the slide movement is roughly rotational about an axis that is parallel to
the ground surface and transverse across the slide (Figure 3.2A).
b) Translational slide: In this type of slide, the landslide mass moves along a roughly
planar surface with little rotation or backward tilting (Figure 3.2B). A block slide is a
translational slide in which the moving mass consists of a single unit or a few closely
related units that move down slope as a relatively coherent mass (Figure 3.2C).

6. 6
3.2.2 Falls
Falls are abrupt movements of masses of geologic materials, such as rocks and boulders,
which become detached from steep slopes or cliffs (Figure 3.2D).
Separation occurs along discontinuities such as fractures, joints, and bedding planes and
movement occurs by free-fall, bouncing, and rolling.
Falls are strongly influenced by gravity, mechanical weathering, and the presence of
interstitial water.
3.2.3 Topples
Toppling failures are distinguished by the forward rotation of a unit or units about some
pivotal point, below or low in the unit, under the actions of gravity and forces exerted by
adjacent units or by fluids in cracks (Figure 3.2E).
3.2.4 Flows
There are five basic categories of flows that differ from one another in fundamental ways.
(i) Debris flow: A debris flow is a form of rapid mass movement in which a
combination of loose soil, rock, organic matter, air, and water mobilize as slurry
that flows down slope (Figure 3.2F). Debris flows include <50% fines. Debris
flows are commonly caused by intense surface-water flow, due to heavy
precipitation or rapid snowmelt that erodes and mobilizes loose soil or rock on
steep slopes. Debris flows also commonly mobilize from other types of landslides
that occur on steep slopes, are nearly saturated, and consist of a large proportion
of silt- and sand-sized material. Debris-flow source areas are often associated with
steep gullies, and debris-flow deposits are usually indicated by the presence of
debris fans at the mouths of gullies.
(ii) Debris avalanche: This is a variety of very rapid to extremely rapid debris flow
(Figure 3.2G).
(iii) Earth flow: Earth flows have a characteristic "hourglass" shape (Figure 3.2H).
The slope material liquefies and runs out, forming a bowl or depression at the
head. The flow itself is elongate and usually occurs in fine-grained materials or
clay-bearing rocks on moderate slopes and under saturated conditions. However,
dry flows of granular material are also possible.
(iv) Mudflow: A mudflow is an earth flow consisting of material that is wet enough to
flow rapidly and that contains at least 50 percent sand-, silt-, and clay-sized
particles. In some instances, for example in many newspaper reports, the
mudflows and debris flows are commonly referred to as "mudslides."
(v) Creep: Creep is the imperceptibly slow, steady, downward movement of slope-
forming soil or rock. Movement is caused by shear stress sufficient to produce
permanent deformation, but too small to produce shear failure.There are generally
three types of creep: (1) Seasonal, where movement is within the depth of soil
affected by seasonal changes in soil moisture and soil temperature. (2)
Continuous, where shear stress continuously exceeds the strength of the material,
and (3) progressive, where slopes are reaching the point of failure as other types
of mass movements.Creep is indicated by curved tree trunks, bent fences or
retaining walls, tilted poles or fences, and small soil ripples or ridges (Figure
3.2I).
3.2.5 Lateral Spreads
Lateral spreads are distinctive because they usually occur on very gentle slopes or flat terrain
(Figure 3.2J). The dominant mode of movement is lateral extension accompanied by shear or

7. 7
tensile fractures. The failure is caused by liquefaction, the process whereby saturated, loose,
cohesion less sediments (usually sands and silts) are transformed from a solid into a liquefied
state. Failure is usually triggered by rapid ground motion, such as that of experienced during
an earthquake, but can also be artificially induced.
When coherent material, either bedrock or soil, rests on materials that liquefy, the upper units
may undergo fracturing, extension and may then subside, translate, rotate, disintegrate, or
liquefy and flow off. Lateral spreading in fine-grained materials on shallow slopes is usually
progressive.
The failure starts suddenly in a small area and spreads rapidly.
Often the initial failure is a slump, but in some materials movement occurs for no apparent
reason. Combination of two or more of the above types is known as a complex landslide.
In our study area, numerous numbers of landslides have occurred in last two decades.
Himalayas experienced debris avalanche, debris flow, Rock fall, creep and translational types
of landslides have occurred.
3.3 LANDSLIDE CAUSES IN GENERAL
There are three major causes for landslides in general, i.e. geological causes, morphological
causes and human causes. They are described below.
(i) Geological causes
a) Weak or sensitive materials.
b) Weathered materials.
c) Sheared, jointed, or fissured materials.
d) Adversely oriented discontinuity (bedding, schistosity, fault, unconformity, contact, and so
forth).
e) Contrast in permeability and/or stiffness of materials.
(ii) Morphological causes
a) Tectonic or volcanic uplift
b) Glacial rebound
c) Fluvial, wave, or glacial erosion of slope toe or lateral margins
d) Subterranean erosion (solution, piping)
e) Deposition loading slope or its crest
f) Vegetation removal (by fire, drought)
g) Thawing
h) Freeze-and-thaw weathering
i) Shrink-and-swell weathering
(iii) Human causes
a) Excavation of slope or its toe
b) Loading of slope or its crest
c) Drawdown (of reservoirs)
d) Deforestation
e) Irrigation
f) Mining
g) Artificial vibration
h) Water leakage from utilities
Although there are multiple types of causes of landslides, specifically the three that cause
most of the damaging landslides around the world are these:

8. 8
3.3.1 Landslides and Water
In Himalayas, slope saturation by water is a primary cause of landslides. This effect can
occur in the form of intense rainfall, snowmelt, changes in ground-water levels, and water-
level changes along coastlines, earth dams, and the banks of lakes, reservoirs, canals, and
rivers.
Landsliding and flooding are closely allied because both are related to precipitation, runoff,
and the saturation of ground by water. In addition, debris flows and mudflows usually occur
in small, steep stream channels and often are mistaken for floods; in fact, these two events
often occur simultaneously in the same area.
Landslides can cause flooding by forming landslide dams that block valleys and stream
channels, allowing large amounts of water to back up. This causes backwater flooding and, if
the dam fails, subsequent downstream flooding. Also, solid landslide debris can "bulk" or add
volume and density to otherwise normal stream flow or cause channel blockages and
diversions creating flood conditions or localized erosion. Landslides can also cause
overtopping of reservoirs and/or reduced capacity of reservoirs to store water.
3.3.2 Landslides and Seismic Activity
Many mountainous areas that are vulnerable to landslides have also experienced at least
moderate rates of earthquake occurrence in recorded times. The occurrence of earthquakes in
steep landslide-prone areas greatly increases the likelihood that landslides will occur, due to
ground shaking alone or shaking-caused dilation of soil materials, which allows rapid
infiltration of water.
3.3.3 Landslides and Volcanic Activity
Landslides due to volcanic activity is melting of volcanic lava at a rapid rate, causing a
deluge of rock, soil, ash, and water that accelerates rapidly on the steep slopes of volcanoes.
These volcanic debris flows (also known as lahars) reach great distances, once they leave the
flanks of the volcano, and can damage structures in flat areas surrounding the volcanoes.
3.4 Review on Landslides and zonation
Landslides are natural events, but may turn into hazard and cause loss of lives and damage to
man-made and natural structures. Though there are numerous approaches to define landslide
hazards, many of the researchers have largely adopted or modified the definition given by
Varnes and IAEG.
3.4.1 Methods of landslide hazard zonation
Landslide hazard zonation is an important step in landslide investigation and landslide risk
management. Varnes and IAEG defines the term ‘zonation’ as ‘the process of division of land
surface into areas and ranking of these areas according to the degree of actual or potential
hazard from landslides or other mass movements’. Courture R explained the concept of
landslide hazard as ‘division of land into somewhat homogeneous areas or domain and their
ranking according to the degrees of actual or potential landslide susceptibility, hazard or risk
or applicability of certain landslide related regulations’.
There has been significant growth both in landslide events particularly those induced by
human activities and in number of landslide investigations in different parts of the world
(Gutierrez et al. Gokceoglu and Sezer carried out statistical assessment of international
landslide literature. They argued that publication of landslide related articles in the

9. 9
international journals has experienced exponential growth. They also pointed out that
landslide susceptibility assessment is an important part of landslide investigation and has
received more attention with highest number of publications in international journals.
Over last three decades LHZ mapping has been carried out in different parts of the world.
Several approaches have been developed for LHZ mapping such as inventory based mapping,
heuristic approach, probabilistic assessment, deterministic approach, statistical analysis and
multi criteria decision making approach.
3.4.1.1 Distribution (inventory) approach
Distribution analysis is one of the simplest qualitative approaches of LHZ mapping. It is also
known as ‘landslide inventory’. In this analysis, landslide inventory maps are produced which
portray spatial and temporal patterns of landslide distribution, type of movement, rate of
movement, type of displaced material (earth, debris or rock) etc. Landslide data are obtained
through field survey mapping, historical records, satellite images and aerial photo
interpretation. Landslide distribution and density maps provide basis for other landslide
susceptibility methods.
3.4.1.2 Statistical approach
In last few years the approach towards LHZ has been changed from heuristic (knowledge
based) approach to data driven approach (statistical approach) to minimize subjectivity in
weightage assignment procedure and produce more objective and reproducible results
Kanungo et al. Methods based on statistical analysis of geo-environmental factors related to
landslide occurrence are preferred. The statistical methods for LHZ can be grouped into two
viz. bi-variate statistical analysis and multi-variate statistical analysis.
(I) Bi-variate statistical analysis
The bi-variate statistical analysis for landslide hazard zonation compares each data layer of
causative factor to the existing landslide distribution. Weights to the landslide causative
factors are assigned based on landslide density. Frequency Analysis approach, Information
Value Model (IVM), Weights of Evidence Model, Weighted overlay model etc. are important
bi-variate statistical methods used in LHZ mapping.
a) Weights of evidence model
A Weight of Evidence is a log linear form of Bayesian probability model for landslide
susceptibility assessment that uses landslide occurrence as training points to derive prediction
outputs. It calculates both unconditional and conditional probability of landslide hazards.
This method is based on calculation of positive and negative weights to define degree of
spatial association between landslide occurrence and each explanatory variables class. The
Weights of Evidence model has been used for landslide susceptibility since 1990′s. It uses
different combinations of landslide causative factors in order to describe their interrelation
with landslide distribution.

10. 10
b) Weighted overlay method
Weighted overlay is a simple bi-variate statistical method wherein weights are assigned based
on the relationship of landslide causative factors with the landslide frequency. Sarkar et al.
developed a methodology of LHZ for Rudrapeayag district in Garhwal Himalayas, India.
Numerical weightages are assigned to causative factors on the basis of their relationships to
the landslide frequency. Finally, the data layers were overlaid to produce LHZ map.This
method is used to determine the relative importance of landslide causative factor in landslide
occurrence
c) Frequency ratio approach
Frequency ratio is one of the bi-variate statistical approaches of landslide susceptibility
assessment which is based on observed relationships between landslide distribution and each
causative factor related to landslides. This method can be used to establish spatial correlation
between landslide location and landslide explanatory factors. Frequency ratio for each sub-
class of individual causative factor is calculated based on their relationship with landslide
occurrence. Landslide Susceptibility Index (LSI) is computed by summing of frequency ratio
values of each factor.
d) Information Value Method (IVM)
Information Value Model (IVM) is a bi-variate statistical method for spatial prediction of
landslides based on relationships between landslide occurrence and related parameters. The
information values are determined for each subclass of landslide related parameter on the
basis of presence of landslide in a given mapping unit. Several studies have applied this
method for LHZ mapping.
e) BIS based LHEF method
Bureau of Indian Standards has given guidelines for macro level landslide hazard zonation
(BIS - IS 14496, Part 2) in India. BIS based Landslide Hazard Evaluation Factor (LHEF)
rating scheme for landslide susceptibility zonation is a heuristic approach to landslide hazard
assessment. According to Bureau of Indian Standards landslide hazard zonation procedure
can be performed using LHEF rating for different landslide causative factors. BIS identified
six landslide causative factors for hazard zonation viz. lithology, structure, slope
morphometry, relative relief, land use-land cover and hydrological condition. In this method,
the area under investigation is divided into small mapping units to which numerical weights
are assigned for each thematic data layer and finally TEHD (Total Estimated Hazard) is
obtained by adding weights of all variables for each mapping unit and Landslide Hazard map
is produced.
BIS based LHEF rating scheme is a very simple and cost effective method of landslide
hazard mapping. However, subjectivity in weight assignment procedure exists in this method
which can affect the level of accuracy of hazard zonation map. Moreover, this method does
not consider landslide distribution and therefore very difficult to test its validity.

11. 11
f) Fuzzy logic method
Fuzzy Logic method of landslide hazard zonation is based on bi-variate analysis wherein
each landslide explanatory variable is represented by a value between 0 and 1 based on the
degree of association of these parameters with landslide occurrence. These membership
values are then integrated using Fuzzy gama operator or Fuzzy Algebric Sum to produce
landslide hazard zonation map. Champatiray et al. applied this method to landslide
susceptibility assessment in Garhwal Himalayas.
3.4.1.3 Probabilistic approach
Probabilistic landslide hazard assessment helps to determine spatial, temporal and size
probability of landslides. Probabilistic methods of LHZ mapping bring objectivity in
assigning weights. In probabilistic approach to landslide susceptibility zonation, spatial
distribution of landslides is compared with various explanatory variables within probabilistic
framework. It includes Bayesian probability, certainty factor, favorability function etc. The
degree of relationship between each thematic data layer with landslide distribution is
transformed to a value based on probability distribution function. This approach is
quantitative but certain degree of subjectivity exists in weight assignment procedure.
3.4.1.4 Analytic Hierarchy Process approach
Landslide hazard assessment involves consideration of several landslide explanatory
variables. It is a critical task to determine relative contribution of an individual parameter in
landslide occurrence. Therefore, the application of Multi Criteria Decision making approach
(MCDA) is of utmost importance in LHZ mapping. The Analytical Hierarchy Process (AHP)
is a multi criteria decision making process of measurement through pair wise comparisons
and relies on the judgements of the experts to derive priority scales AHP operates at four
levels viz. defining problem, determination of goals and alternatives, construction of pair
wise comparison matrix, determining weights and obtaining overall priority. In LHZ,
different landslide causative factors are considered as alternatives. Absolute numbers (from 1
to 9) are assigned to each landslide related parameter based on its relative importance and
comparison matrices are constructed to compute Consistency Ratio (CR) and Consistency
Index (CI). Akgun compared landslide hazard maps produced by Logistic Regression (LR),
Multi Criteria Decision Approach (MCDA) and Likelihood Ratio Method (LRM) for Azmir,
Turkey using AUC (Area Under Curvature) method. The correlation coefficients (r) were
found to be 0.86, 0.62, 0.58 for LR*LRM, LR*MCDA and LRM*MCDA respectively. The
LRM and MCDA showed similar results. Ayalew et al. compared LSZ maps using LR and
AHP model to assess landslide hazard. The study revealed that if there is increase in number
of susceptibility classes, LR model gives more details than AHP. However when these maps
compared with landslide activity map, AHP based map performed better than LR model. In
recent times, several attempts have been made to apply GIS based AHP to map landslide
susceptibility in various parts of the world.

12. 12
3.5 Application of RS and GIS in LHZ
Extraction of relevant spatial information related to landslide occurrence is an integral part of
hazard assessment. Remotely Sensed (RS) data combined with Geographical Information
System (GIS) are proved to be effective tools for generating and processing spatial
information. The advancement in earth Observation (EO) techniques facilitate effective
landslide detection, mapping, monitoring and hazard analysis.
The review of few studies on landslide hazard assessment using RS data indicate that aerial
photographs are widely used in landslide detection and mapping. Good quality aerial
photographs help in accurate landslide detection and mapping. However, aerial photographs
may not be used in continuous landslide monitoring, since it does not prove repetitive
coverage of the same area.
Use of Digital Elevation Model (DEM) is of immense importance in landslide hazard
assessment. Several thematic data layers such as slope angle, slope aspect, curvature,
lineaments, drainage, ridges etc. can be extracted from DEM with good resolution. Landslide
hazard zonation studies in recent times have used DEM with high resolution to generate
spatial information data layers related to landslide hazards.
Geographical Information System is widely used in landslide hazard assessment especially
for generation of thematic data layers, computation of different indices, assignment of
weights, data integration and generation of LSZ maps. Several LSZ methods such as ANN,
Decision Tree model, Weighted Overlay, AHP, MCDA, IVM and physically based landslide
hazard models are GIS based models to predict landslide probability.

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CHAPTER 4
METHODOLOGY
4.1 MACROZONATION
The macrozonation was done in ARC GIS software. Each of the factors that contributed to
landslides were digitized in ARC MAP. The data was converted to raster format and values
or ratings were assigned to them. Then weightage was given to each of these maps based on
their priority and influence in causing the landslide and then these maps were overlaid one on
another to generate a landslide potential hazard map.. The technique used was statistical
approach using weighted overlay method. AHP (Analytic Hierarchy Process) was used to
calculate the weights.
4.2 MICROZONATION
Assessing the causes and factors contributing to slope movement/slope failure; surface
observations and geological mapping of slopes provide the basis for sub surface investigation
and engineering analysis that follow. Accurate interpretation of the surface feature of a
landslide can be used to evaluate the mode of movement, judge the direction and rate of
movement and estimate the geometry of the slip surface. Two landslides are studied in our
case and factor of safety is determined. Factor of Safety (F) is the ratio of shear strength of
soil divided by the shear stress required for equilibrium of slope.
F =
𝑐+ 𝜎 tan 𝜑
𝜏
where, c = cohesion intercept on Mohr-Coulomb strength diagram
𝜑 = angle of internal friction of soil
𝜎 = normal stress on slip surface
𝜏 = shear stress required for equilibrium
Landslide sites were visited in Kullu region along the Lag valley. The failed slopes were
surveyed using Total Station. Soil samples were taken from the sites to do the geotechnical
testing. Direct shear test was performed on the samples to calculate cohesion and friction
angle of the soil. Moisture content test was also done. LISCAD and AUTOCAD was used to
import the data from Total Station and generate the vertical cross section of the slide.
There are various methods for analysing slope stability and the preference was given to
simple and logical methods. Computer based software GEO-Studio was used for determining
the values of factor of safety.

14. 14
CHAPTER 5
AREA OF STUDY
Himalayan mountains with its unique topography, climate and rock composition form an
ideal laboratory for the study of slope failures. Landslides in this region of India has become
an annually recurring phenomena causing not only to degradation of land mass but also
adding miseries to the mankind. The selection criteria for the study area was based on number
of landslide incidence reported and frequent close down of this strategic route during
monsoon.
5.1 CAUSES OF LANDSLIDES IN AREA
 High Relief
 Rugged Topography
 Extreme environmental conditions
 Complex geological structures
 Varied lithological assemblages
 Active seismicity
 Plentiful and variable catastrophic precipitation
 Over exploitation of natural resources
5.2 EXTENT AND LOCATION
Kullu, or Kulu, is the capital town of the Kullu district in the Indian state of Himachal
Pradesh. The total area of Kullu is 5,503 sq. km.
It lies on the bank of Beas River. A major tributary, Sarvari, (derived from "Shiv-Baardi")
leads to the less explored and steeper Lug-valley on the west. On the east of Kullu lies a
broad mountainous ridge having the village-temples of BijliMahadev, Mounty Nag and
Pueed. Beyond the ridge lies Manikaran valley, along the Parvati river which joins Beas at
sangam in Bhuntar. On the South of Kullu lie the town of Bhuntar, Aut (leading to Anni,
Banjar and Siraj Valley) and Mandi (in Mandi district).
Historically Kullu was accessible from Shimla via Siraj valley or through passes on the west
leading to Jogindernagar and onto Kangra. To the north lies the famous town of Manali,
which through the Rohtang pass leads onto the Lahaul and Spiti Valley. Once can see an
enormous change in the climate as one climbs up the windward side of the ranges to proceed
to the leeward and much drier plateaus to the north of Manali.
Kullu is a broad open valley formed by the Beas river between Manali and Largi. This valley
is famous for its temples, beauty and its majestic hills covered with Pine and Deodar Forest
and sprawling Apple Orchards. The course of the Beas River presents a succession of
magnificent, clad with forests of Deodar, towering above trees of Pine on the lower rocky
ridges. Kullu valley is sandwiched between the PirPanjal, Lower Himalayan and Great
Himalayan range.
Lag Valley is located to the north- west of Kullu. Its coordinates are 31°58’13.2” N,
77°01’20.3” The valley conceals several virgin tourist spots, which are yet to be explored.
The valley though narrow, is fascinating. The entire valley is encased by lofty mountains and

15. 15
plenteous deodar forests. The valley can be visited between April- June and September-
November.
The region is dotted with numerous scars of current and fossil landslide of varied dimension
indicating a fragile state environment favourable for slope instability.
5.3 PHYSIOGRAPHY AND RELIEF
Kullu district situated in the lesser Himalayas between 31º20' - 32º26' north latitudes and
76º59' - 77º50’ east longitudes possesses an intricate system of mountain ranges which are
the result of successive compression movements of the earth’s crust.
The area possesses high relative or local relief which refers to the difference between the
highest and the lowest altitude in an area. The higher values indicate rapid rise in altitude and
presence of faults, lower relief signifies mature topography. A determinant of morphological
character of an area, relative relief has noteworthy alliance with landslide by acting as a
triggering factor. As a risk agent, relative relief plays a decisive role in the vulnerability of
settlements, transport network and land. In Kullu district, there is wide variation in relative
relief (map 4) ranging from low to very high. About 13.39 %, 60.13% and 26.48 % area has
low (below 200m), moderate (200-400m) and high (above 400m) relative relief respectively.
The district has very high absolute relief ranging from 750-6200 meters. The
geomorphological character of Kullu is influenced by both glacial and fluvial processes, the
area is broadly divided into glaciers & permanent snow fields, rocky/barren slopes, valley
slopes & ridges, and main valley floor.
The glaciers & permanent snow fields are found in most of the eastern parts above an
elevation of 4500 meters. The barren/rocky surfaces occupy the lower parts of glaciers and
permanent snow fields while valley slopes occupy a large part in the district and consist of
steep to moderately steep slopes, ridges and narrow valleys where slopes usually have an
inclination of 30-40 degrees. The main valley floor of River Beas is dominated by outwash
fan, alluvial fans and river terraces.
5.4 OTHER CHARACTERISTICS
5.4.1 CLIMATE
Fig. 5.1
LUG
VALLEY,
KULLU

16. 16
December and January during winter observe lowest temperatures ranging from 4°C to 20°C,
with some snowfall. Annual highest temperature in summer ranges from 25°C to 37°C during
May to August. Months of July and August are rainy because of Monsoon, having around
15 cm rainfall monthly. Climate is pleasant in October and November.
5.4.2 TEMPERATURE
The area witnesses slightly prolonged winters and short summers. From December to
February, this period is very chilly. Heavy frost occurs during this period. Snowfall generally
occurs during December and January or an early snowfall may occur in November also.
During this period, most of the parts of the Kullu remain under cover of snow. But the snow
does not remain on the ground for a long time. Max temperature is 38.8° C and minimum is
5.2° C in winter.
5.4.3 PRECIPITATION
Months of July and August are rainy because of Monsoon, having around 15 cm rainfall
monthly. The Kullu Manali segment receives most of rainfall during winter season. The
intensity of monthly rainfall rises to 35cm during monsoons which often is responsible for
triggering maximum landslides.
It is more pronouncedly in hilly areas for instance in Kullu during the winter. Heavy snows
downwind of the Rohtang often accumulate to several feet but along a narrow corridor of the
Beas River downward may receive only a few inches of the snow.
5.4.4 HYDROGEOLOGICAL CONDITIONS
Presence of forest covers and springs remain slightly damp during spring and part of
summers. Due to existence of moderate to steep slope and shallow soil development the
water table is shallowwithittle discharge. Due to presence of Beas with numerous tributaries
the ground water condition remain static throughout the season with considerable increase
during rainy season. The surface conditions change usually during rainy season and incessant
rains.
5.4.5 GEOLOGY AND LITHOLOGY
In Kullu district, a broad central zone of crystalline unfossilliferous rocks consisting of
granite, gneisses, schist and other metamorphic rocks forms the axis of the Himalayas. Five
major litho-tectonic units express the geology of the area and these are referred to as (1)
Vaikrita Group (2) Jutog Group (3) Kullu Group (4) Larji Group, and (5) Rampur Group.
The area is dissected by several major thrusts, namely Jutogh Thrust Kullu thrust and
Vaikrita thrust along with several local faults/lineaments. These thrusts are still active and
play a major role in the neo-tectonics of the area. The Jutogh thrust separates rocks belonging
to Kullu group and Jutogh group while Kullu thrust or Chail thrust defines boundary between
the rocks of Rampur-Larji group and Kullu group.
Structurally, the main Kullu Valley is a synclinorium/gently folded antiform having River
Beas following its axial plane along a fault running NNW-SSE from the upper catchment to
near Aut where it is intersected by a cross fault almost at right angles. This fault is a dextral
tear fault with a dislocation of nearly 1.5 km The rivers follow these fault traces which are
well reflected in the trellis like drainage pattern. The rivers Beas, Parbati, HurlaNala,

17. 17
SainjKhad, TirthanKhad etc. follow such fault traces. The area west of river Beas from
Bhuntar and south of Parbati River to Rampur along the course of Satluj River is very unique.
Structurally the area forms 'window in a window' structure also known as Kullu-Larji-
Rampur Window (KLRW). Here, rocks of Kullu formation thrust over rocks of Larji group as
well as Banjar group thrust over Larji group.
5.4.6 SOIL/SLOPE FORMING MATERIAL
Most of soil exposed in entire road section is made up of debris deposit and drifted soil
developed mostlyon moderate reposed slopes.In Kullu district gentle slopes (below 20°) form
nearly 1/3 (34.25%) of total area of the district and such slopes are found either along the
river’s course or on ridge tops. The moderately steep and steep slopes account for 35.35%
and 24.55% area respectively about 6 percent of the total area possesses very steep to
precipitous (above 40°) slopes. The aspect distribution in the district has an even distribution
as all eight directions have 10-15 per cent of total area .The aspect has significance in
understanding the slope stability. Usually southeast (SE) to south (S) and southwest (SW)
slopes are comparatively more prone to slope failure and sliding activities.
5.4.7 LANDSLIDE INTENSITY
Landslide is one of the most common natural hazards in Kullu district; it can be disastrous
with massive destruction to life and property and may also lead to large scale landscape
transformations occurring in the past that caused massive damage to property and
infrastructure along with human casualties in the study area. The district is also experiencing
large scale developmental activities related to hydro-power, tourism and transport networks
which are leading to terrain alteration and other negative impacts on environment.

18. 18
CHAPTER 6
MACROZONATION
6.1 WORKING IN ARC GIS
The foremost step is to know the factors that contribute to landslides. It is observed that the
major geographical and environmental factors that contribute in landslide are- Slope,
Drainage Density, Lithology, Landuse, Soil and Aspect. All these geological and
geomorphological characteristics are varied throughout the Kullu district. Hence there is
different intensity of landslide occurrence throughout the region.
Macrozonation mapping involves spatial analysis of the region to demarcate the potential
landslide zones of varying magnitude. In this spatial analysis, factors that contribute to
landslide are studied in detail. We got the thematic maps of these factors from various
sources. The geology/lithology map and soil map was obtained from the National Remote
Sensing Agency, National Bureau of Soil Survey and Landuse Planning (ICAR). These
thematic maps were scanned into GIS system and then they were converted to digital format.
The GIS system used for this purpose was ARC MAP 10 software. The scanned images of
thematic maps of soil and geology were imported and geo-referenced. Digital polygons were
drawn over these maps to represent different zones in the maps, and a database was created to
store the information of each polygon which represented a zone i.e. a part of the terrain of
Kullu with different feature of soil or geology. Satellite imagery was obtained from
LANDSAT to obtain the landuse pattern. Reclassification of the satellite imagery was done in
ARC MAP and digital format of landuse pattern was obtained.
The digital contour map of Kullu was obtained and that was used to generate Digital
Elevation Model (DEM) of Kullu, in ARC MAP. Now ARC MAP was used to generate the
degree of slope of every facet of all hills in the study area. Aspect map was also obtained and
the drainage density map, which represented the valley portion of the study area was also
obtained from DEM. All these maps were converted to raster digital format. In raster format,
every pixel has some data associated to it.
Now priority had to be assigned to each factor depending on its contribution to landslides.
Ratings were assigned based on the priority in the range 0-9. 0 indicates low hazard of
landslide and 9 indicates high hazard. For obtaining accurate ratings, various previous
research papers were studied. These ratings were confirmed by correlating by the IS code
14496 (II):1998.
6.1.1 SLOPE
Slope is the most important factor that causes landslides. Steeper the slope, more the risk of
landslides. Steep slopes were found mostly along the banks of Parvati River. Some
escarpment slopes were found in the centre and north-west of Kullu district. Flat slopes were
found along the Beas valley. Mild slopes were found in the southern Kullu.

19. 19
S.No. Slope Name Rating
1 0-15 Very gentle 1
2 15-25 Gentle 3
3 25-35 Moderately steep 5
4 35-45 Steep 7
5 >45 Escarpment 9
Table 6.1 slope subclass and rating
Fig.6.1 Slope map of district Kullu

20. 20
6.1.2 ASPECT
The aspect map was generated using DEM. Aspect refers to the direction of maximum slope
of the terrain surface. It influences the solar insolation, which is strongly related to the
distribution and density of vegetation on mountainous slopes, as vegetation provides
anchorage to the ground. The stability of the slope is also related to the aspect, the aspect thus
generated shows direction from 0° to 360°. The aspect values have been categorized into 9
directions namely N, NE, E, SE, S, SW, W, NW and flat. The aspect map is shown in the
Figure 6.2.
Fig. 6.2 Aspect map of Kullu

21. 21
Table 6.2 Aspect subclass and rating
6.1.3 DRAINAGE DENSITY
The drainage density map was again formed using the DEM. Higher the density, higher is the
probability of the slope failures in the region. Drainage cause slope cutting along the toe of
the slopes and cause its failure. The valley portion of the DEM was assumed to be occupied
with water and considered a drain. Hence more the number of valleys in a region, higher the
drainage density. The drainage density is shown in the figure 6.3.
Table 6.3 Drainage subclass and rating

22. 22
Figure 6.3 Drainage density of Kullu
6.1.4 LITHOLOGY
Quartzite, Slate, Granitoid Gneiss, Sandstone, Schist and Phyllite in the order of abundance
are the main lithological units exposed in the study area. Other rocks are Dolomite, streaky
banded gneiss, alluvium, assorted material, etc. stronger is the rock, lower is the probability
of any landslide in the area. Road cutting and tunnel boring is beneficial if it is done in the
hard rocks.
The lithology map as generated in ARC GIS is shown in the figure 6.4.

23. 23
Fig. 6.4 Lithology of Kullu
Table 6.4 Lithology subclass and rating

24. 24
6.1.5 SOIL
The type of soil structure and its minerals contribute in deciding the stability of hill slope.
The sandy soil is loose and is considered unstable for slopes. Loamy soil on the other hand is
stable as it has a little cohesive property which is absent in the sandy soil. The soil map
generated using ARC MAP is shown in the figure 6.5.
Fig 6.5 Soil map of Kullu
Table 6.5 Soil subclass and rating

25. 25
6.1.6 LANDUSE
The landuse/landcover has direct impact on the stability of hill slopes. Forest cover protects
the land from the severe climatic actions of weathering and erosion. The roots of the forest
cover bind the soil and protect it from wind and water erosion. Very thick forest cover
sometimes also add to the surcharge weight on the soil hence their effect is detrimental to
slope stability too. Hence forest cover has to be in appropriate thickness to get suitable
stability of slope. Barren and sparsely vegetated areas show faster erosion and greater
instability. Agricultural areas are generally made flat and these slopes are held by the roots of
plants. Surcharge weight is also not too much. Hence these slopes are very stable. Snow
covered slopes are most prone to avalanches and landslides. The landuse map is shown in the
figure 6.6.
Fig. 6.6 Landuse map of Kullu

26. 26
Table 6.6 Landuse subclass and rating
6.2 ANALYTIC HIERARCHY PROCESS
The pairwise comparison method was developed by Saaty (1980) in the context of Analytic
Hierarchy Process (AHP). This method involves pairwise comparison to create a ratio matrix.
It involves assessing the relative importance of criteria. Input given is pairwise comparison
and output required is relative weights. Specifically, the weights are determined by
normalizing the eigenvector associated with the maximum Eigen value of the ratio matrix.
The present work involved six parameters: slope, drainage density, lithology, landuse, soil
and aspect. It required assessing the relative importance of these. This has been done by
pairwise comparison of each of these parameters. The procedure consists of three major
steps.
6.2.1 Development of pairwise comparison matrix
The method employs an underlying scale with values from 1-9 to rate the relative preference
for two criteria, the scale has been shown in Table 6.7

27. 27
In this the assumption is made that the comparison matrix is reciprocal; that is if the criterion
A is twice as preferred to criterion B, it is concluded that the criterion B is preferred only as
one-half as much as criterion A. thus if criterion A receives a score of 2 relative to criterion
B, criterion B should receive a score of 1/2 as compared to criterion A. same logic of
pairwise comparison can be used to complete the lower left of the matrix. When comparing
anything to it, the evaluation scale should be 1, representing equally preferred criteria. This
pairwise comparison matrix of the criteria parameters was the input to the multicriteria
weighted software. Now criteria weights were computed using these score values as given in
Table 6.8.
Table 6.7 Scale for pairwise comparison
TABLE 6.8
Pairwise comparison matrix
1) Slope
2) Drainage density
3) Lithology
4) Landuse
5) Soil
6) Aspect

28. 28
6.2.2 Computation of criteria weights
The criteria weights were computed using multicriteria weighted software. The software was
very interactive and could calculate the criterion weights using a number of methods. The
computed criterion weights using AHP method are shown in Table 6.8.
6.2.3 Estimation of consistency ratio
The consistency ratio was estimated to find out the consistency of the comparison criteria. It
is based on the consistency vector, lambda and consistency index. The consistency ratio of
0.10 or less indicates a reasonable level of consistency in pairwise comparisons; if
consistency ratio is greater than 0.10, the values of the ratio are indicative of inconsistency
judgement. Consistency ratio for the weights was calculated using the multicriteria weighted
software, which gave its value as 0.047. This showed good consistency in pairwise
comparison.
All the digital maps of the factors were overlaid one on another in ARC MAP. All the layers
were integrated using arithmetic weighted overlay process. For every single point on terrain,
there exists a pixel on every map with some rating. Ratings are multiplied with corresponding
weight of each map, which are then added together to generate Landslide Potential Index
map.
LPI=∑ (WEIGHT X CLASSIFIED LAYER RATING)
This is known as macrozonation mapping.
Table 6.9
Factor and weights

29. 29
Fig. 6.7 Landslide hazard zonation map
Table 6.10 Landslide potential index

30. 30
CHAPTER 7
MICROZONATION
7.1 LABORATORY INVESTIGATION
7.1.2 CORE CUTTER METHOD:
This test is done to determine the in-situ dry density of soil by core cutter method as per IS:
2720 (Part XXIX) – 1975 .The apparatus needed for this test is
i) Cylindrical core cutter
ii) Steel dolley
iii) Steel rammer
iv) Balance, with an accuracy of 1g
v) Straight edge
vi) Square metal tray – 300mm x 300mm x 40mm
vii) Trowel
Procedure to determine the in-situ dry density of soil by Core Cutter Method
i) The internal volume (V) of the core cutter in cc should be calculated from its dimensions
which should be measured to the nearest 0.25mm.
ii) The core cutter should be weighed to the nearest gram (W1).
Fig.7.1 Core cutter apparatus
iii) A small area, approximately 30cm square of the soil layer to be tested should be exposed
and levelled. The steel dolly should be placed on top of the cutter and the latter should be

31. 31
rammed down vertically into the soil layer until only about 15mm of the dolly protrudes
above the surface, care being taken not to rock the cutter. The cutter should then be dug out
of the surrounding soil, care being taken to allow some soil to project from the lower end of
the cutter. The ends of the soil core should then be trimmed flat in level with the ends of the
cutter by means of the straightedge.
iv) The cutter containing the soil core should be weighed to the nearest gram (W2).
v) The soil core should be removed from the cutter and a representative sample should be
placed in an air-tight container and its water content (w)
REPORTING OF RESULTS
Bulk density of the soil g cc:
Y=[W2–W1]/Vg/cc
Dry density of the soil g cc:
Yd = 100Y/[100+w] g/cc
Average of at least three determinations should be reported to the second place of decimal in
g/cc
7.1.2 BOX SHEAR TEST:
The test is performed on three or four specimens from a relatively undisturbed soil sample. A
specimen is placed in a shear box which has two stacked rings to hold the sample; the contact
between the two rings is at approximately the mid-height of the sample. A confining stress is
applied vertically to the specimen, and the upper ring is pulled laterally until the sample fails,
or through a specified strain. The load applied and the strain induced is recorded at frequent
intervals to determine a stress–strain curve for each confining stress. Several specimens are
tested at varying confining stresses to determine the shear strength parameters, the soil
cohesion (c) and the angle of internal friction, commonly known as friction angle ( ). The
results of the tests on each specimen are plotted on a graph with the peak (or residual) stress
on the y-axis and the confining stress on the x-axis. The y-intercept of the curve which fits
the test results is the cohesion, and the slope of the line or curve is the friction angle.

32. 32
Fig.7.2 Shear box apparatus
DIRECT SHEAR TEST OF SOIL(IS-2720-PART-13-1986)
Fig.7.3 Shear Box Assemblies
Objective
Determination of shear strength parameters of a silty or sandy soil at known density and
moisture content.
Reference standards
Is: 2720(part 13)-1986- methods of test for soils: direct shear test.

33. 33
Equipment / apparatus
o Shear box
o Box container
o Porous stone and grid plate
o Tamper, balance , sieve(4.75 mm)
o Loading frame, proving ring, dial gauge.
Preparation sample
One kg of air dry sample passing through 4.75mm is sieve is required for this test.
Procedure
1. Shear box dimensions is measured, the box is set up by fixing its upper part to the lower part
with clamping screws, and then a porous stone is placed at the base.
2. For undrained tests, a serrated grid plate is placed on the porous stone with the serrations at
right angle to the direction of shear. For drained tests, a perforated grid is used over the
porous stone.
3. An initial amount of soil is weighed in a pan. The soil is placed into the shear box in three
layers and for each layer is compacted with a tamper. The upper grid plate, porous stone and
loading pad is placed in sequence on the soil specimen.
4. The pan is weighed again and the mass of soil used is computed.
5. The box is placed inside its container and is mounted on the loading frame. Upper half of the
box is brought in contact with the horizontal proving ring assembly. The container is filled
with water if soil is to be saturated.
6. The clamping screws is removed from the box, and set vertical displacement gauge and
proving ring gauge to zero.
7. The vertical normal stress is set to a predetermined value. For drained tests, the soil is
allowed to consolidate fully under this normal load. (avoid this step for undrained tests.)
8. The motor is started with a selected speed and shear load is applied at a constant rate of
strain. Readings of the gauges are taken until the horizontal shear load peaks and then falls, or
the horizontal displacement reaches 20% of the specimen length.
9. The moisture content of the specimen is determined after the test. The test is repeated on
identical specimens under different normal stress values.
Calculation
o The density of the soil specimen is calculated from the mass of soil and the volume of the
shear box.

34. 34
o The dial readings are converted to the appropriate displacement and load units by multiplying
with respective least counts.
o Shear strains are calculated by dividing horizontal displacements with the specimen length,
and shear stresses are obtained by dividing horizontal shear forces with the shear area.
o The shear stress versus horizontal displacement is plotted. The maximum value of shear
stress is read if failure has occurred, otherwise read the shear stress at 20% shear strain. The
maximum shear stress versus the corresponding normal stress is plotted for each test, the
cohesion and the angle of shearing resistance of the soil is determined from the graph.
Safety & precautions
o Before starting the test, the upper half of the box should be brought in contact of the proving
ring assembly.
o Before subjecting the specimen to shear, the fixing pins should be taken out.
o The rate of strain should be constant throughout the test.
7.1.3 MOISTURE CONTENT TEST
This test is done to determine the water content in soil by oven drying method as per IS: 2720
(Part II) – 1973. The water content (w) of a soil sample is equal to the mass of water divided
by the mass of solids.
Apparatus required
 Thermostatically controlled oven maintained at a temperature of 110 ± 5o.
 Weighing balance, with an accuracy of 0.04% of the weight of the soil taken
 Air-tight container made of non-corrodible material with lid.
 tongs
Fig.7.4 Moisture content apparatus
Preparation of sample:
The soil specimen should be representative of the soil mass. The quantity of the specimen
taken would depend upon the gradation and the maximum size of particles as under:

35. 35
Procedure to determine water content in soil by oven drying method
i) clean the container, dry it and weigh it with the lid (weight ‘w1‘).
Ii) take the required quantity of the wet soil specimen in the container and weigh it with the
lid (weight ‘w2‘).
Iii) place the container, with its lid removed, in the oven till its weight becomes constant
(normally for 24hrs.).
Iv) when the soil has dried, remove the container from the oven, using tongs.
V) find the weight ‘w3‘ of the container with the lid and the dry soil sample.
Reporting of results
The water content
w = [W2-W3] / [W3 -W1]*100%

36. 36
7.2 WORKING ON TOTAL STATION, AUTOCAD, LISCAD AND GEOSTUDIO
Surveying of the site was done with the help of Trimble Total Station S6 (5000 series). Basic
two operation involved are-
1. Station setup and surveying
2. Transferring the Data To Storage Device
1) STATION SETUP AND SURVEYING
A. Fix the tripod stand
B. Fix the total station on tripod
- Centre the total station with the help of optical plummet
- To focus move plummet in and out
- To make cross hair more clear rotate it
C. Mount the CU on the slot provide
D. Press the green button to turn on the total station
E. User interface is window based 4 icons appears
i. General survey
ii. Files
iii. Recycle bin
iv. Storage
F. Click general survey> new window>
i. Jobs
ii. Settings
iii. Programme files
iv. Aimil
G. Click job> new job> job name> save
H. Open job> select job >open
I. Click General survey>vx& s series> measure
J. Click measure topography> station setup
K. A leveling bubble will show on screen and level the total station with help of it.
L. After leveling, enter the values of temperature,pressure etc. so that instrument can
adjust automatically.
M. Orient the station, two options appear
i. Orientation by angle
ii. Orientation by coordinates
Now at the first station use orientation by angle:
a. Measure height of instrument and enter
b. With the help of a surveyors compass or GPS establish north direction
c. At the suitable distance along north direction fix the prism pole.
d. Click measure.
e. Various measurements are done.
f. Station is oriented

37. 37
For stations other than first (2nd, 3rd, etc.) use orientation by coordinates.
It can be done by backsighting.
a. From previous station mark three points on next station point as main station
point, two check points.
b. Now set up Total station on next main station and backsight any of the points.
c. The instrument displays the error in the measurement. If the error is small then
proceed further.
2) TRANSFERRING THE DATA TO STORAGE DEVICE
 Insert any USB device in slot provided on CU
 Copy the exported data from program files>surveying
 Paste into the storage device
 Data can also be transferred via Microsoft auto sync software directly into the
operating system.
Data is then exported to LISCAD software for further work. Contour / topographical map
was prepared by using LISCAD software. Preparation of vertical cross section were carried
out for further analysis along different alignments. The steps involved are:
1. Importing data to LISCAD from Total Station
 Task>Data conversion
 Import>User definable
 Browse .csv format file
 Click OK
 User Definable Import dialog box will appear as shown

38. 38
2. Terrain modelling
 Click on Form Model button
 Terrain Model Formation dialog box will open
 After giving the model name click on OK
 Display>Features
 Feature dialog box will open
 Click on MODEL tab
 Provide the model name and click on CONTOURS check box and then click OK
 Contours will be generated as shown

39. 39
3. Creating alignment
Task>Computation
Create>Alignment
Method>Freehand
Draw the required alignment where the section is to be cut as shown
 Task>Profile and Design
 Profile>Long Section>By alignment

40. 40
 Long Section By alignment dialog box will appear
 Provide Long Section name
 Click on Parameters tab and click on Model button under Build Profile form
 Click on Create
 Section along the alignment will appear as shown
4. Exporting to AUTO-CAD format
 Click on CAD Output button in the Menu bar
 The following dialog box will appear

41. 41
 Select Auto CAD and then click on Output to CAD.
 The exported output file has .dwg format, for analysis in Geo Studio it is converted
into .dxf format.
Fig.7.5 .dwg and .dxf format files in Auto CAD
 Format >Layers
 Layers Properties Manager dialog box will open as shown

42. 42
 Delete all the layers by clicking on Delete button except Default layer
 Create closed Poly line geometry of the required elevation
 Now click on Save As, provide the file name with extension as .dxf
Further analysis of the soil was done using GEO-Studio software. Factor of safety along the
vertical cross sections of both the landslides were determined by following below procedure:
 Open Geo Studio 2007
 Create a new project with an analysis of SLOPE
 KeyIn Analysis dialog box will open as shown
 Provide the name and select Morgenstern-Price Analysis type
 Under Slip Surface tab select Auto Locate Slip Surface Option
 File>Import Regions
 Browse .dxf file created in Auto CAD
 Click OK the file will be imported in Geo Studio Draw>Materials
 Click on KeyIn button Keyin Materials dialog box will open

43. 43
 Click on Add and select Material Model as Mohr-Colulomb
 Under Basic tab provide the Unit Weight, Cohesion and Phi value of the soil and then
close the dialog box
 Now assign the material by clicking on the area
 Tools>Solve Analyses
 Provide the file name, save the analysis and click on Start
 The result will be available in the form of Minimum Factor of Safety as shown

44. 44
CHAPTER 8
RESULTS
8.1 Core Cutter test
Diameter of core cutter = 10 cm
Height of core cutter = 12.5 cm
Volume of core cutter 𝑉 =
∏×𝐷2
×𝐻
4
V=
∏×102
×12.5
4
= 981.75 cm3
Landslide 1
Volume of core cutter
(cc)
Weight of soil
(g)
Density
(g/cc) Average Density (g/cc)
981.75 1442 1.469
1.595981.75 1659 1.69
981.75 1596 1.626
Landslide 2
Volume of core cutter
(cc)
Weight of soil
(g)
Density
(g/cc) Average Density (g/cc)
981.75 1649.5 1.68
1.668981.75 1493 1.52
981.75 1770.3 1.803
8.2 Water Content test
Landslide 1
Weight of
empty
cylinder (g)
Weight of
cylinder and wet
soil (g)
Weight of cylinder and
soil after oven drying
(g)
Weight
of water
(g)
Weight of
dry soil
(g)
Water
Content
(%)
12 38.3 33.8 4.5 21.8 22.02
17 50.8 44.9 5.9 27.9 21.15
16.8 39.5 34.5 5 17.7 28.25
Landslide 2
Weight of
empty
Weight of
cylinder and wet
Weight of cylinder and
soil after oven drying
Weight
of water
Weight of
dry soil
Water
Content

45. 45
cylinder (g) soil (g) (g) (g) (g) (%)
13.5 44.2 39 5.2 25.5 20.4
14 49 43.2 5.8 29.2 19.86
17 43.4 38.3 5.1 21.3 23.94
8.3 Shear Test
Strain Rate = 1.25 mm/min
Proving constant = 3.0053 N
L.C of dial = 0.01 mm
Volume of Shear box = L×B×H = 6cm × 6cm × 2.5cm = 90 cm3
Shear Deformation = L.C of dial × Horizontal Dial Gauge reading
Vertical Deformation = L.C of dial × Vertical Dial Gauge reading
Shear Stress =
𝑃𝑟𝑜𝑣𝑖𝑛𝑔 𝐶𝑜𝑛𝑠𝑡𝑎𝑛𝑡 ×𝑃𝑟𝑜𝑣𝑖𝑛𝑔 𝑟𝑖𝑛𝑔 𝑟𝑒𝑎𝑑𝑖𝑛𝑔
𝐶𝑜𝑟𝑟𝑒𝑐𝑡𝑒𝑑 𝐴𝑟𝑒𝑎
Dilation angle (α) = tan−1
.
𝑉𝑒𝑟𝑡𝑖𝑐𝑎𝑙 𝑑𝑒𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛
𝐻𝑜𝑟𝑖𝑧𝑜𝑛𝑡𝑎𝑙 𝑑𝑒𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛
Landslide 1
Density of soil = 1.469 g/cc
Weight of soil taken in Shear box = 1.469 × 90 = 132.21 g
Readings at normal stress = 0.5 kg/cm2
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformatio
n(mm)
Ver.
deformatio
n(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 32 0.2 -0.01 35.88 0.27 26.80
40 -2 43 0.4 -0.02 35.76 0.37 36.14
60 -3 47 0.6 -0.03 35.64 0.40 39.63
80 -1 53 0.8 -0.01 35.53 0.46 44.83
100 0 55 1 0 35.41 0.48 46.68
120 1 56 1.2 0.01 35.29 0.49 47.68
140 3 58 1.4 0.03 35.18 0.51 49.55
160 5 60 1.6 0.05 35.06 0.52 51.42
180 7 62 1.8 0.07 34.95 0.54 53.31
200 10 62 2 0.1 34.84 0.55 53.48
220 12 62 2.2 0.12 34.73 0.55 53.66
240 15 62 2.4 0.15 34.62 0.55 53.83

46. 46
260 18 62 2.6 0.18 34.50 0.55 54.00
280 19 64 2.8 0.19 34.39 0.57 55.92
300 21 66 3 0.21 34.29 0.59 57.85
320 23 60 3.2 0.23 34.18 0.54 52.76
340 25 58 3.4 0.25 34.07 0.52 51.16
360 27 56 3.6 0.27 33.96 0.51 49.55
380 29 54 3.8 0.29 33.86 0.49 47.93
400 30 53 4 0.3 33.75 0.48 47.19
420 30 51 4.2 0.3 33.64 0.46 45.56
440 31 49 4.4 0.31 33.54 0.45 43.91
460 32 47 4.6 0.32 33.44 0.43 42.24
480 33 46 4.8 0.33 33.33 0.42 41.47
500 34 45 5 0.34 33.23 0.41 40.70
520 35 45 5.2 0.35 33.13 0.42 40.82
540 35 44 5.4 0.35 33.03 0.41 40.04
560 36 43 5.6 0.36 32.93 0.40 39.25
580 36 43 5.8 0.36 32.83 0.40 39.37
600 37 42 6 0.37 32.73 0.39 38.57
620 38 42 6.2 0.38 32.63 0.39 38.68
640 39 41 6.4 0.39 32.53 0.39 37.88
660 39 41 6.6 0.39 32.43 0.39 37.99
680 39.5 40 6.8 0.395 32.34 0.38 37.18
700 39.5 40 7 0.395 32.24 0.38 37.29
720 39.5 40 7.2 0.395 32.14 0.38 37.40
740 40 39 7.4 0.4 32.05 0.37 36.57
760 40 39 7.6 0.4 31.95 0.37 36.68
780 40 39 7.8 0.4 31.86 0.38 36.79
800 40.5 39 8 0.405 31.76 0.38 36.90
820 40.5 39 8.2 0.405 31.67 0.38 37.01
840 40.5 39 8.4 0.405 31.58 0.38 37.12
860 40.5 39 8.6 0.405 31.49 0.38 37.22
880 41 39 8.8 0.41 31.40 0.38 37.33
900 41 39 9 0.41 31.30 0.38 37.44
920 41 39 9.2 0.41 31.21 0.38 37.55
940 41 39 9.4 0.41 31.12 0.38 37.66
960 41 39 9.6 0.41 31.03 0.38 37.77
980 41 39 9.8 0.41 30.95 0.39 37.88
1000 41 39 10 0.41 30.86 0.39 37.98

47. 47
Readings at normal stress = 1 kg/cm2
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformati
on(mm)
Ver.
deformati
on(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 37 0.2 -0.01 35.88 0.32 30.99
40 -2 53 0.4 -0.02 35.76 0.45 44.54
60 -3 68 0.6 -0.03 35.64 0.58 57.33
80 -3 79 0.8 -0.03 35.53 0.68 66.83
100 -2 87 1 -0.02 35.41 0.75 73.84
120 1 95 1.2 0.01 35.29 0.82 80.89
140 2 97 1.4 0.02 35.18 0.84 82.87
160 4 98 1.6 0.04 35.06 0.86 83.99
180 6 100 1.8 0.06 34.95 0.88 85.98
200 8 102 2 0.08 34.84 0.90 87.99
220 10 103 2.2 0.1 34.73 0.91 89.14
240 12 104 2.4 0.12 34.62 0.92 90.29
260 14 104 2.6 0.14 34.50 0.92 90.58
280 16 104 2.8 0.16 34.39 0.93 90.87
300 18 104 3 0.18 34.29 0.93 91.16
320 21 104 3.2 0.21 34.18 0.93 91.45
340 23 103 3.4 0.23 34.07 0.93 90.86
360 25 102 3.6 0.25 33.96 0.92 90.26
380 26 100 3.8 0.26 33.86 0.90 88.77
400 27 99 4 0.27 33.75 0.90 88.16
420 28 97 4.2 0.28 33.64 0.88 86.64
440 29 95 4.4 0.29 33.54 0.87 85.12
460 30 94 4.6 0.3 33.44 0.86 84.49
480 31 92 4.8 0.31 33.33 0.85 82.95
500 32 90 5 0.32 33.23 0.83 81.39
520 33 89 5.2 0.33 33.13 0.82 80.74
540 34 87 5.4 0.34 33.03 0.81 79.16
560 35 86 5.6 0.35 32.93 0.80 78.49
580 36 84 5.8 0.36 32.83 0.78 76.90
600 36 82 6 0.36 32.73 0.77 75.30
620 36 80 6.2 0.36 32.63 0.75 73.69
640 36 78 6.4 0.36 32.53 0.73 72.06
660 36.5 76 6.6 0.365 32.43 0.72 70.42
680 36.5 75.5 6.8 0.365 32.34 0.72 70.17
700 36.5 75 7 0.365 32.24 0.71 69.91

48. 48
720 37 74.5 7.2 0.37 32.14 0.71 69.66
740 37 74 7.4 0.37 32.05 0.71 69.39
760 37 73.5 7.6 0.37 31.95 0.70 69.13
780 37.5 73 7.8 0.375 31.86 0.70 68.86
800 37.5 72.5 8 0.375 31.76 0.70 68.59
820 37.5 72 8.2 0.375 31.67 0.70 68.32
840 38 71.5 8.4 0.38 31.58 0.69 68.05
860 38 71.5 8.6 0.38 31.49 0.70 68.24
880 38 71.5 8.8 0.38 31.40 0.70 68.44
900 38 71.5 9 0.38 31.30 0.70 68.64
920 38 71.5 9.2 0.38 31.21 0.70 68.84
940 38 71.5 9.4 0.38 31.12 0.70 69.04
960 38 71 9.6 0.38 31.03 0.70 68.75
980 38 70.5 9.8 0.38 30.95 0.70 68.47
1000 38 70 10 0.38 30.86 0.69 68.18
Readings at normal stress = 1.5 kg/cm2
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformati
on(mm)
Ver.
deformati
on(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 21 0.2 -0.01 35.88 0.18 17.59
40 -2 48 0.4 -0.02 35.76 0.41 40.34
60 -4 63 0.6 -0.04 35.64 0.54 53.12
80 -5 77 0.8 -0.05 35.53 0.66 65.14
100 -5 85 1 -0.05 35.41 0.74 72.14
120 -5 93 1.2 -0.05 35.29 0.81 79.19
140 -2 101 1.4 -0.02 35.18 0.88 86.28
160 -1 107 1.6 -0.01 35.06 0.93 91.71
180 -1 112 1.8 -0.01 34.95 0.98 96.30
200 0 119 2 0 34.84 1.05 102.65
220 2 120 2.2 0.02 34.73 1.06 103.85
240 4 120 2.4 0.04 34.62 1.06 104.18
260 6 121 2.6 0.06 34.50 1.07 105.39
280 8 121 2.8 0.08 34.39 1.08 105.73
300 10 121 3 0.1 34.29 1.08 106.06
320 13 121 3.2 0.13 34.18 1.08 106.40

49. 49
340 14 122 3.4 0.14 34.07 1.10 107.62
360 15 120 3.6 0.15 33.96 1.08 106.19
380 17 118 3.8 0.17 33.86 1.07 104.75
400 19 116 4 0.19 33.75 1.05 103.29
420 21 114 4.2 0.21 33.64 1.04 101.83
440 24 112 4.4 0.24 33.54 1.02 100.35
460 26 110 4.6 0.26 33.44 1.01 98.87
480 27 108 4.8 0.27 33.33 0.99 97.37
500 27 106 5 0.27 33.23 0.98 95.86
520 28 104 5.2 0.28 33.13 0.96 94.34
540 28 101 5.4 0.28 33.03 0.94 91.90
560 29 99 5.6 0.29 32.93 0.92 90.36
580 29 97 5.8 0.29 32.83 0.91 88.80
600 29 96 6 0.29 32.73 0.90 88.16
620 30 94 6.2 0.3 32.63 0.88 86.58
640 30 92 6.4 0.3 32.53 0.87 84.99
660 31 91 6.6 0.31 32.43 0.86 84.32
680 31 90 6.8 0.31 32.34 0.85 83.65
700 32 89 7 0.32 32.24 0.85 82.97
720 32 89 7.2 0.32 32.14 0.85 83.21
740 33 88 7.4 0.33 32.05 0.84 82.52
760 33.5 88 7.6 0.335 31.95 0.84 82.77
780 33.5 87 7.8 0.335 31.86 0.84 82.07
800 34 87 8 0.34 31.76 0.84 82.31
820 34 86 8.2 0.34 31.67 0.83 81.61
840 35 86 8.4 0.35 31.58 0.83 81.84
860 35 86 8.6 0.35 31.49 0.84 82.08
880 36 85 8.8 0.36 31.40 0.83 81.37
900 36 85 9 0.36 31.30 0.83 81.60
920 36.5 85 9.2 0.365 31.21 0.83 81.84
940 36.5 84 9.4 0.365 31.12 0.83 81.11
960 37 84 9.6 0.37 31.03 0.83 81.34
980 37 83 9.8 0.37 30.95 0.82 80.61
1000 37.5 83 10 0.375 30.86 0.82 80.84
Normal
stress
(Kpa)
Peak
Shear
stress
(KPa)
Shear
deformation
(mm)
Vertical
Deformatio
n (mm)
Dilation
angle (α )
Peak
Friction
angle (Φp)
Critica
l angle
(Φcs)
Average
Φcs
49.05 57.85 3 0.21 5.24 27 21.76 23.21

50. 50
98.1 91.45 3.2 0.21 3.78 27 23.22
147.15 108 3.4 0.14 2.35 27 24.65
Landslide 2
Density of soil = 1.68 g/cc
Weight of soil taken in Shear box = 1.68 × 90 = 151.2 g
Readings at normal stress = 0.5 kg/cm2
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformati
on(mm)
Ver.
deformati
on(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 39 0.2 -0.01 35.88 0.33 32.67
40 -2 45 0.4 -0.02 35.76 0.39 37.82
60 -3 51 0.6 -0.03 35.64 0.44 43.00
80 -4 57 0.8 -0.04 35.53 0.49 48.22
100 -5 61 1 -0.05 35.41 0.53 51.77
120 -5 65 1.2 -0.05 35.29 0.56 55.35
140 -6 66 1.4 -0.06 35.18 0.57 56.38
160 -6 67 1.6 -0.06 35.06 0.59 57.42
180 -6 68 1.8 -0.06 34.95 0.60 58.47
200 -7 69 2 -0.07 34.84 0.61 59.52
220 -7 69 2.2 -0.07 34.73 0.61 59.71
240 -7 69 2.4 -0.07 34.62 0.61 59.91
260 -7 69 2.6 -0.07 34.50 0.61 60.10
280 -7 68 2.8 -0.07 34.39 0.61 59.42
y = 0.5112x + 35.617
0
20
40
60
80
100
120
-50 0 50 100 150 200
Shearstress(KPa)
Normal stress (KPa)

51. 51
300 -7 67 3 -0.07 34.29 0.60 58.73
320 -7 66 3.2 -0.07 34.18 0.59 58.04
340 -6 65 3.4 -0.06 34.07 0.58 57.34
360 -6 64.5 3.6 -0.06 33.96 0.58 57.08
380 -5 64.5 3.8 -0.05 33.86 0.58 57.26
400 -5 64 4 -0.05 33.75 0.58 56.99
420 -4 63.5 4.2 -0.04 33.64 0.58 56.72
440 -4 63 4.4 -0.04 33.54 0.58 56.45
460 -3 62.5 4.6 -0.03 33.44 0.57 56.18
480 -3 62 4.8 -0.03 33.33 0.57 55.90
500 -2 62 5 -0.02 33.23 0.57 56.07
520 -2 61.5 5.2 -0.02 33.13 0.57 55.79
540 -1 61 5.4 -0.01 33.03 0.57 55.51
560 0 61 5.6 0 32.93 0.57 55.68
580 2 60.5 5.8 0.02 32.83 0.56 55.39
600 3 60 6 0.03 32.73 0.56 55.10
620 4 60 6.2 0.04 32.63 0.56 55.26
640 5 59.5 6.4 0.05 32.53 0.56 54.97
660 6 59 6.6 0.06 32.43 0.56 54.67
680 6 59 6.8 0.06 32.34 0.56 54.84
700 7 58.5 7 0.07 32.24 0.56 54.53
720 7 58.5 7.2 0.07 32.14 0.56 54.70
740 7 58 7.4 0.07 32.05 0.55 54.39
760 8 57.5 7.6 0.08 31.95 0.55 54.08
780 8 57 7.8 0.08 31.86 0.55 53.77
800 8 57 8 0.08 31.76 0.55 53.93
820 9 56.5 8.2 0.09 31.67 0.55 53.61
840 9 56 8.4 0.09 31.58 0.54 53.29
860 10 55.5 8.6 0.1 31.49 0.54 52.97
880 10 55 8.8 0.1 31.40 0.54 52.65
900 11 55 9 0.11 31.30 0.54 52.80
920 11 55 9.2 0.11 31.21 0.54 52.95
940 11 54.5 9.4 0.11 31.12 0.54 52.62
960 12 54.5 9.6 0.12 31.03 0.54 52.78
980 12 54.5 9.8 0.12 30.95 0.54 52.93
1000 12 54.5 10 0.12 30.86 0.54 53.08
Readings at normal stress = 1 kg/cm2

52. 52
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformati
on(mm)
Ver.
deformati
on(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 32 0.2 -0.01 35.88 0.27 27.08
40 -2 43 0.4 -0.02 35.76 0.37 36.50
60 -3 52 0.6 -0.03 35.64 0.45 44.29
80 -4 65 0.8 -0.04 35.53 0.56 55.55
100 -5 71 1 -0.05 35.41 0.61 60.87
120 -6 78 1.2 -0.06 35.29 0.68 67.09
140 -7 80 1.4 -0.07 35.18 0.70 69.04
160 -8 87 1.6 -0.08 35.06 0.76 75.32
180 -8 89 1.8 -0.08 34.95 0.78 77.31
200 -9 91 2 -0.09 34.84 0.80 79.30
220 -9 92 2.2 -0.09 34.73 0.81 80.43
240 -9 93 2.4 -0.09 34.62 0.82 81.57
260 -9 93 2.6 -0.09 34.50 0.83 81.83
280 -9 93 2.8 -0.09 34.39 0.83 82.09
300 -9 92 3 -0.09 34.29 0.82 81.46
320 -8 91 3.2 -0.08 34.18 0.82 80.83
340 -8 90 3.4 -0.08 34.07 0.81 80.20
360 -7 89 3.6 -0.07 33.96 0.80 79.56
380 -7 88 3.8 -0.07 33.86 0.80 78.91
400 -6 87 4 -0.06 33.75 0.79 78.26
420 -6 86 4.2 -0.06 33.64 0.78 77.60
440 -5 85 4.4 -0.05 33.54 0.78 76.94
460 -5 84 4.6 -0.05 33.44 0.77 76.27
480 -4 83.5 4.8 -0.04 33.33 0.77 76.05
500 -4 83 5 -0.04 33.23 0.77 75.83
520 -3 82.5 5.2 -0.03 33.13 0.76 75.60
540 -3 82 5.4 -0.03 33.03 0.76 75.38
560 -2 81.5 5.6 -0.02 32.93 0.76 75.15
580 -2 81 5.8 -0.02 32.83 0.76 74.91
600 -1 80.5 6 -0.01 32.73 0.75 74.68
620 0 80 6.2 0 32.63 0.75 74.44
640 1 79.5 6.4 0.01 32.53 0.75 74.19
660 2 79.5 6.6 0.02 32.43 0.75 74.42
680 3 79 6.8 0.03 32.34 0.75 74.17
700 4 79 7 0.04 32.24 0.75 74.39
720 5 78.5 7.2 0.05 32.14 0.75 74.14
740 6 78 7.4 0.06 32.05 0.75 73.89
760 7 77.5 7.6 0.07 31.95 0.74 73.64

53. 53
780 7 77 7.8 0.07 31.86 0.74 73.38
800 8 76.5 8 0.08 31.76 0.74 73.12
820 8 76.5 8.2 0.08 31.67 0.74 73.33
840 9 76 8.4 0.09 31.58 0.74 73.06
860 9 76 8.6 0.09 31.49 0.74 73.28
880 9 75.5 8.8 0.09 31.40 0.74 73.01
900 10 75.5 9 0.1 31.30 0.74 73.22
920 10 75 9.2 0.1 31.21 0.74 72.95
940 11 75 9.4 0.11 31.12 0.74 73.16
960 11 75 9.6 0.11 31.03 0.74 73.37
980 12 75 9.8 0.12 30.95 0.74 73.58
1000 12 75 10 0.12 30.86 0.74 73.79
Readings at normal stress = 1.5 kg/cm2
Hori. Dial
gauge
reading
Ver. Dial
gauge
reading
Proving
ring
reading
Shear
deformati
on(mm)
Ver.
deformati
on(mm)
Area
correctio
n(cm2)
Shear
stress
(kg/cm2)
Shear
stress
(Kpa)
0 0 0 0 0 36.00 0.00 0.00
20 -1 26 0.2 -0.01 35.88 0.22 21.78
40 -2 60 0.4 -0.02 35.76 0.51 50.42
60 -3 82 0.6 -0.03 35.64 0.70 69.14
80 -4 96 0.8 -0.04 35.53 0.83 81.21
100 -5 107 1 -0.05 35.41 0.93 90.81
120 -6 119 1.2 -0.06 35.29 1.03 101.33
140 -7 119 1.4 -0.07 35.18 1.04 101.66
160 -8 120 1.6 -0.08 35.06 1.05 102.85
180 -8 120 1.8 -0.08 34.95 1.05 103.18
200 -9 120 2 -0.09 34.84 1.06 103.52
220 -9 120 2.2 -0.09 34.73 1.06 103.85
240 -9 121 2.4 -0.09 34.62 1.07 105.05
260 -10 118 2.6 -0.1 34.50 1.05 102.78
280 -10 117 2.8 -0.1 34.39 1.04 102.23
300 -10 116 3 -0.1 34.29 1.04 101.68
320 -10 114 3.2 -0.1 34.18 1.02 100.24
340 -10 113 3.4 -0.1 34.07 1.02 99.68
360 -9 112 3.6 -0.09 33.96 1.01 99.11
380 -9 110 3.8 -0.09 33.86 1.00 97.64
400 -9 109 4 -0.09 33.75 0.99 97.06

54. 54
420 -8 108 4.2 -0.08 33.64 0.98 96.47
440 -8 107.5 4.4 -0.08 33.54 0.98 96.32
460 -7 107 4.6 -0.07 33.44 0.98 96.17
480 -7 106.5 4.8 -0.07 33.33 0.98 96.02
500 -6 106 5 -0.06 33.23 0.98 95.86
520 -6 106 5.2 -0.06 33.13 0.98 96.16
540 -5 105.5 5.4 -0.05 33.03 0.98 96.00
560 -5 105.5 5.6 -0.05 32.93 0.98 96.29
580 -4 105 5.8 -0.04 32.83 0.98 96.13
600 -4 105 6 -0.04 32.73 0.98 96.42
620 -3 104.5 6.2 -0.03 32.63 0.98 96.25
640 -2 104 6.4 -0.02 32.53 0.98 96.08
660 -1 103.5 6.6 -0.01 32.43 0.98 95.91
680 0 103.5 6.8 0 32.34 0.98 96.19
700 1 103 7 0.01 32.24 0.98 96.02
720 2 103 7.2 0.02 32.14 0.98 96.30
740 3 102.5 7.4 0.03 32.05 0.98 96.12
760 4 102.5 7.6 0.04 31.95 0.98 96.41
780 5 102 7.8 0.05 31.86 0.98 96.22
800 6 102 8 0.06 31.76 0.98 96.50
820 7 101.5 8.2 0.07 31.67 0.98 96.31
840 8 101.5 8.4 0.08 31.58 0.98 96.60
860 9 100.5 8.6 0.09 31.49 0.98 95.92
880 9 100.5 8.8 0.09 31.40 0.98 96.20
900 10 100 9 0.1 31.30 0.98 96.00
920 10 100 9.2 0.1 31.21 0.98 96.28
940 11 99 9.4 0.11 31.12 0.97 95.59
960 12 99 9.6 0.12 31.03 0.98 95.87
980 12 98.5 9.8 0.12 30.95 0.98 95.66
1000 13 98.5 10 0.13 30.86 0.98 95.93
Normal
stress
(Kpa)
Peak
Shear
stress
(KPa)
Shear
deformation
(mm)
Vertical
Deformation
(mm)
Dilation
angle (α )
Peak
Friction
angle (Φp)
Critica
l angle
(Φcs)
Average
Φcs

55. 55
49.05 60.1 2.6 0.07 1.54 24.64 23.1
22.7998.1 82.09 2.8 0.09 1.84 24.64 22.8
147.15 105.05 2.4 0.09 2.15 24.64 22.49
Landslide C (KN/m2) Ø
1 35.617 23.21°
2 37.463 22.79°
Table 8.1 C-Ø values of soil
y = 0.4582x + 37.463
0
20
40
60
80
100
120
-50 0 50 100 150 200
Shearstress(KPa)
Normal stress (KPa)

56. 56
8.4 Factor of Safety
Landslide 1
Landslide 2

57. 57
CHAPTER 9
MITIGATION
Landslides impact the Earth’s natural environment, including effects on (1) the morphology
of the Earth’s sub aerial and submarine surfaces; (2) forests and grasslands, and (3) habitats
of native flora and fauna. Morphologic effects are part of a general tendency of surface
degradation by mass wasting and erosion. The effects of landslides on vegetation and wildlife
are mostly negative; in some cases, they are catastrophic.
Correction of an existing landslide or the prevention of a pending landslide is a function of a
reduction in the driving forces or an increase in the available resisting forces. Any remedial
measure used must involve one or both of the above parameters. According to IUGS WG/L,
landslide remedial measures are arranged in four practical groups, namely: modification of
slope geometry, drainage, retaining structures and internal slope reinforcement.
There are different approaches to dealing with landslides, depending on needs, risks and
available funds. Stabilization measures to fully remediate landslides according to the standard
of practice often take time to investigate, design and construct and can become expensive,
particularly for large/deep slides. The standard of practice includes selecting a suitable Factor
of Safety (margin of stability). Significant stabilization measures might be required to protect
critical facilities such as dams, expensive structures and primary highway routes.
However, there are situations where full stabilization is impractical (due to size of landslide,
excessive cost, and environmental and ownership restrictions). There are alternative
mitigation options available for situations where some risk-taking may be acceptable to
owners and affected jurisdictions.
9.1 Level of Mitigation
When facilities are planned in suspected or known landslide areas, the risks should be
evaluated to determine whether satisfactory stability can be achieved through mitigation or
stabilization measures. Landslide areas could be designated “no-build” zones or “open
spaces” to avoid possible impacts. This approach is known as “Avoidance.” Jurisdictions and
owners could consider whether potential landslide risks would be acceptable and apply
mitigations to improve stability to adequate levels.
A “Do Nothing” approach might be the least expensive but should be based on an adequate
understanding of the risks and potential consequences.
The “Maintenance” approach is often used to reopen a facility (i.e., by removing debris,
patching cracks, restoring structural support, etc.) and hopefully to provide immediate
improvement in slide stability. Sometimes, the immediate maintenance does not stop the
landslide and the problem reoccurs.
“Selective Stabilization” is an approach where only a portion of the landslide is stabilized in
order to protect a facility, and the remainder of the slide is left in its marginally-stable or
unstable condition. For example, roads that are located in the upper portions of slides could
be improved by stabilizing only the upper portion of the slide mass that it rests on. The
unmitigated portion of the slide is left undeveloped unless it too receives adequate
stabilization.
“Marginal Stabilization” is an approach where, due to the large size of a slide and/or high
cost of standard stabilization, a lower ‘margin of stability’ could be considered in an attempt
to reduce the hazard level. If a “Marginal Stabilization” approach is adopted, mitigation
measures could be applied in phases until the desired reduction in movement is
accomplished, which is usually accompanied with instrument monitoring to verify the
improvement achieved.

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“Conventional Stabilization,” or “Full Remediation,” utilizes higher levels of stability margin
that are intended to account for uncertainties and potential errors in modeling the slide and
foreseeable future conditions. The intent of the conventional design stability margins is to
reduce the risk of landslide reactivation or localized instabilities and the risk to the public.
The selection of appropriate mitigation measures should be based on an assessment of risk,
uncertainty, possible consequences, constructability, environmental impacts and costs. A
final mitigation approach usually consists of a creative combination of several methods.
Environmental constraints and requirements can influence the selection and overall design of
mitigation measures. For example, a toe buttress might not be permissible if the toe of a
landslide is in a river, lake or wetland. Mitigation measures may need to comply with
aesthetic requirements of parks and scenic areas.
9.2 Biotechnical Slope Protection
Biotechnical approaches to landslide mitigation have much less impact on the environment
than traditional concrete and steel retaining structures. Biotechnical slope protection utilizes
mechanical elements (structures) in combination with biological elements (plants) to prevent
and correct slope failure and erosion with minimum impact on the environment.
When used for landslide remediation, conventional earth-retaining structures made of steel or
concrete are usually not visually pleasing or environmentally friendly. “…slope repairs often
consist of a rock blanket, gabions, concrete walls, or other conventional erosion control and
slope stability systems. These solutions are developed with more restricted views and less
understanding of the broader opportunity or environmental picture and they appear to
operate without a full appreciation for natural principles.” (Sotir, 1994, p. 191). These
traditional “hard” remedial measures are increasingly being supplanted by vegetated
composite soil/structure bodies that are environmentally friendlier, i.e., a process that has
come to be known as biotechnical slope protection. “In such work, vegetation is used as
surface protection and to augment the strength of soil in which it grows, usually combined
with naturally occurring or recycled inert materials – timber, stone, iron and steel cables and
meshes. These vegetated composite soil bodies or structures are ‘soft’ – flexible and multi
redundant statically and visually attractive. They contrast with conventional ‘hard’ slope
retention structures – rigid and discreet.” (Barker, 1995, p. 238). Common biotechnical
systems are geonets anchored by soil nails that hold in place soil seeded with grass. Also
common are geocells with seeded soils in the interstices.
Biotechnical slope protection consists of two elements:
1. Biotechnical stabilization
2. Soil bioengineering stabilization
Both of which entail the use of live materials – specifically vegetation (Gray and Sotir, 1996).
Biotechnical stabilization utilizes mechanical elements (structures) in combination with
biological elements (plants) to prevent and arrest slope failures and erosion (Gray and Leiser,
1982). Both mechanical and biological elements must function together in a complementary
manner. Soil bioengineering stabilization, on the other hand, can be regarded as a specialized
subset of biotechnical stabilization in which live plant parts, i.e., roots, stems and branches,
serve as the main structural/mechanical elements in the slope protection system (Gray and
Sotir, 1996).Biotechnical slope-protection systems blend into the landscape. They emphasize
the use of natural, locally available materials, such as soil, rock, timber, and vegetation, in
contrast to man-made materials, such as steel and concrete. The structural or mechanical
components do not visually intrude upon the environment as much as conventional earth
retaining structures (Gray and Leiser, 1982). Examples of such structures, which commonly

59. 59
incorporate vegetation into the structure itself, include log and timber cribs, gabion and rock-
breast walls, welded wire walls, and reinforced earth. Internal, tensile reinforcements
utilizing the principles of bioengineering permit construction of over steepened fill slopes to
as much as 70º (Gray and Sotir, 1992).
As noted by Gray and Sotir (1995, p. 6), “Biotechnical and soil bioengineering stabilization
offer a cost-effective and attractive approach for stabilizing slopes against erosion and
shallow mass movement. These approaches capitalize on the advantages and benefits that
vegetation offers for erosion control and slope protection.” Soil bioengineering relies mainly
on the use of native materials, such as plant stems or branches, rocks, wood, or soil.
Appropriate vegetation can be obtained from local sources of willow, alder, and other native,
easily-propagated varieties. In addition, soil bioengineering systems commonly are
environmentally compatible during the construction process because they generally require
minimal access for equipment and workers, and cause relatively minor disturbance. With
time, the bioengineering systems are visually non-intrusive and blend into the natural
surroundings. This is a favorable attribute in environmentally sensitive areas, such as parks,
riparian areas, and scenic corridors, where aesthetic quality, wildlife habitat and ecological
restoration are important (Gray and Sotir, 1996).Hence bioengineering soil stabilization is a
very suitable option for Kullu. As bioengineered structures that utilize tree species become
older, they have the added benefit that they become more stable, and eventually assist in the
natural succession and long-term colonization of forest species.
If exotic species of plants or trees are introduced, there is a real danger that they will conflict
with native plant life. Native plants are nearly always an excellent choice. In most cases,
native grasses, shrubs, and trees are used as the vegetation in bioengineering stabilization.
Willow has been very successful in many parts of the world. Clumping plants, which produce
several stems from one root, also work well. Deep-rooted plants, such as prairie plants, hold
their own on even the steepest slope. Ornamental grasses, ground cover roses and shrubs
(including shrub roses with a sprawling growth habit) work well in hillside and slope
planting. Snowberry plantation is also a good option for Kullu region.
While detailed slope stability assessments have normally been carried out by geotechnical
engineers and engineering geologists, the organic interactions between vegetation, soil, and
structures that must be evaluated in applying the technique of bioengineering stabilization are
perhaps better understood by soil scientists, agriculturists, foresters, and hydrologists
(Greenway, 1986). Thus the bioengineering approach to slope stabilization requires
cooperation of geoscience and plant-science disciplines working in parallel and in unison.

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Fig. 9.1 Geotextiles used for landslide protection
Fig. 9.2 Geocells

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CHAPTER 9
CONCLUSION
The present study demonstrates high degree of hazardousness of Kullu district of Himachal
Pradesh, India. The higher degree of landslide hazard is associated with geo-physical
elements especially slope, relative relief and lithology of the area. The presence of faults,
particularly in the vicinity of human occupancy enhances vulnerability. Vulnerability is
compounded by mindless and rampant expansion of settlement onto vulnerable land and
ambitious road construction that aids this settlement. In addition, anthropogenic activities
play a significant role in triggering such events. The past events show that these have close
association with the landuse and were confined to the built-up (roads) and agricultural lands.
The intensification of human activities, encroachment on vulnerable land, uncontrolled
settlement and rampant expansion of roads adds to landslide vulnerability.
This project has been divided into three portions: Macrozonation, Microzonation and
Mitigation. In macrozonation, we focused on application of GIS and AHP in landslide
hazard zonation mapping. The susceptibility to landslides is inherent in the natural
characteristics of the landscape and there is a definite relationship between landslide
occurrence and geo-physical setup of the area. The high slope angles, drainage density, high
local relief and geological structure produce suitable conditions for landslide occurrence; the
torrential rainfall in monsoon season is invariably the immediate trigger. Hence six factors
were taken into account for calculating the landslide risk namely-Slope, Drainage density,
Lithology, Landuse, Soil, and Aspect.
The weighted rating approach was carried out using arithmetic overlay analysis. The weights
were calculated using multicriteria weighted method-Analytical Hierarchy Process. The
resulting landslide potential index map classified different regions into zones of high,
medium or low landslide potential. The map has shown that zones of high risk of landslides
are aligned along the river courses or steep valleys of mountain ranges. Northern region of
Kullu district was more susceptible to landslide hazard as compared to southern region.
It is pertinent to note that landslide activity is largely confined to the inhabited part of the
district primarily in the vicinity of the rivers and roads and this is substantiated by field visits
and data. These are the prime locations of all human activities and this enhances the risk
potential of this disaster.
The next portion of the project was microzonation. A field visit was planned in the Kullu
district to collect the inventory of landslide sites and relate the data to the data calculated
using macrozonation analysis. A stretch of Lag valley was surveyed for landslide spots. The
failure slopes were investigated. The geological aspects like joints, joint sets, dip, strike, type
of rocks, failure type, and failure planes were investigated. The failure slope was surveyed
using Total Station. Soil samples of the failed slopes were collected for testing and doing the
further analysis.
The final portion of our project was to suggest some mitigation measures for protecting the
damaged slopes and those slopes which were at high risk of landslides, especially those
which were along the National Highway or where there was thick dwelling and hence, life of
large population at stake. The focus was made to consider the usage of non-conventional
mitigation measures like biotechnical stabilization measures or soil bioengineering

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stabilization. When used for landslide remediation, conventional earth-retaining structures
made of steel or concrete are usually not visually pleasing or environmentally friendly. Slope
repairs often consist of a rock blanket, gabions, concrete walls, or other conventional erosion
control and slope stability systems. These solutions are developed with more restricted views
and less understanding of the broader opportunity or environmental picture and they appear
to operate without a full appreciation for natural principles. These traditional “hard” remedial
measures are increasingly being supplanted by vegetated composite soil/structure bodies that
are environmentally friendlier, i.e., a process that has come to be known as biotechnical slope
protection.
Techniques in biotechnical slope stabilization are becoming popular for reducing the
environmental impact of slope-protection measures. These so-called “soft” remedial
measures not only are environmentally more “friendly” than steel and concrete retaining
structures, but they often are more economical and provide better long-term stability.

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CHAPTER 10
BRIEF BIODATA OF THE CANDIDATES
NISHANT SINGH s/o Dr. J S Chandel, belongs from Dalhousie, Himachal Pradesh. He did
his schooling from Sacred Heart Sr. Sec School, Dalhousie, securing 94.6% in 10th and
91.7% in 12th. Currently he is pursuing B.Tech in Civil Engineering from National Institute
of Technology Hamirpur, with current CGPI 8.31.
PARVEEN ATRI s/o Sh. Sham Atri, belongs from Udhampur, J&K. He did his schooling
from Happy Model Sr Sec School, Udhampur, securing 88% in 10th and 84.2% in 12th.
Currently he is pursuing B.Tech in Civil Engineering from National Institute of Technology
Hamirpur, with current CGPI 7.45.
DIPIN THAKUR s/o Sh. ManoharLal, belongs from Kullu, Himachal Pradesh. He did his
schooling from SarswatiVidyaMandir, Kullu securing 76.57% in 10th and Arunodaya Sen.
Sec. School, Kullu with 77.8% in 12th. Currently he is pursuing B.Tech in Civil Engineering
from National Institute of Technology Hamirpur, with current CGPI 6.97.
RIZUL VADHAN d/o Sh. Hem Raj Vadhan, belongs from Shimla, Himachal Pradesh. She
did her schooling from GNPS, Kanpur securing 93% in 10th and DAV Sen. Sec. School,
Shimla with 86% in 12th. Currently she is pursuing B.Tech in Civil Engineering from
National Institute of Technology Hamirpur, with current CGPI 7.43.
VIVEK SHARMA s/o Sh. Deshraj Sharma, belongs from Chamba, Himachal Pradesh. He
did his schooling from GovtSr Sec School, Khani, securing 69.5% in 10th and 55% in 12th.
Currently he is pursuing B.Tech in Civil Engineering from National Institute of Technology
Hamirpur, with current CGPI 6.4.
ANIL KUMAR s/o Sh. Kuldeep Kumar, belongs from Hamirpur, Himachal Pradesh. He did
his schooling from Dr. Y S Parmar GSSS, Dhaneta, securing 76.8% in 10th and 73.2% in 12th.
Currently he is pursuing B.Tech in Civil Engineering from National Institute of Technology
Hamirpur, with current CGPI 4.2.

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CHAPTER 11
REFERENCES
 Preparation of landslide hazard zonation maps in mountainous terrains – guidelines
(macro-zonation)
is 14496 (part 2 ) : 1998
 Application of GIS and AHP for landslide susceptible mapping- K
VENKANTESWARIU, P K SRIDHAR AND P K GARG
 Landslide Susceptibility Assessment in the Guwahati City, Assam using Analytic
Hierarchy Process (AHP) and Geographic Information System (GIS)- Phukon, P.,
Chetia, D.and Das P. Department of Geological Sciences, Guwahati University,
Guwahati
 http://bpmsg.com/academic/ahp_calc1.php?t=AHP+priorities&n=6&new=Go
 Aleotti, P. and Chowdhury, R. (1999), “Landslide Hazard Assessment: Summary
Review and New Perspectives”, Bulletins of Engineering Geology and the
Environment, 58(1), pp 21-44.
 Anbalagan, R. (1992), “Landslide Hazard Evaluation and Zonation Mapping
 CalTrans. 2000. Statewide Storm Water, Quality Practice Guidelines.
 Goldman, et al. 1986. Erosion and Sediment Control Handbook.McGraw Hill.
 TRPA. 1988. Handbook of Best Mangement Practices
 Bayer CropScience LP.
 Landslide mitigation, Engineering Geology and Geotechnical Engineering
Symposium, Logan UT, May 2006
 Landslide Mitigation Action Plan, Final Report 2014, Washington State Department
of Transportation.
 Impact of Landslides and Innovative Landslide-Mitigation Measures on the Natural
Environment, Robert L. Schuster and Lynn M. Highland, Geologic Hazards Team,
U.S. Geological Survey, Denver, Colorado, U.S.A
 Engineering Measures for Landslide Disaster Mitigation, Mihail E. Popescu(Illinois
Institute of Technology, USA), KatsuoSasahara(Kochi University, Japan)