









































Pa
ge

 
1

INDEXED IN



Pa
ge

 
34

American Journal of  
Geospatial Technology (AJGT)

Landslide Hazard Assessment and Distribution Mapping:
A Case from Triveni Rural Municipality, Nepal

Tej Raj Oli1*

Volume 1 Issue 1, Year 2022
ISSN: 2833-8006 (Online) 

DOI: https://doi.org/10.54536/ajgt.v1i1.468
https://journals.e-palli.com/home/index.php/ajgt

Article Information ABSTRACT

Received: August 05, 2022

Accepted: August 23, 2022

Published: August 29, 2022

An application of  GIS for landslide hazard assessment using multivariate statistical analy-
sis, mapping, and the evaluation of  the hazard maps is crucial for disaster risk reduction. 
Landslides are the rapid downward movement of  a mass of  rock, earth or artificial fill to 
the slope.  The study was conducted the Khara of  Triveni Rural municipality of  Rukum 
West district and it covers three wards (3, 4 & 5) of  rural municipality covering the total 
area of  about 33.52 square kilometres located in the Karnali province of  Nepal which is 
under the pressure of  high road construction activities. Data used to construct the landslide 
distribution map and hazard assessments were obtained from the direct field, and mapping 
using GIS. More data sources and verifications were made from the rural municipality, pub-
lished articles and journals, topographical and geological maps, google images and aerial 
photographs and other digital sources. To determine the factors and classes influencing land 
sliding, the layers of  topographic factors derived from a digital elevation model, geology, 
and land use/land covers were analyzed and the results were used for landslide distribution 
mapping and hazard analyses. From the landslide inventory of  more than 200 landslides 
that were occurred during the last five years since 2015, the landslide distribution map, land-
slide-size distribution map and hazard level of  sliding graphics were presented. Hazard map 
of  the study area shows 4.34% area lies in the high hazard level, 53.64% on moderate hazard 
level and 42.02% in low hazard level in the study area. The results would give insights to the 
landslide distribution in the area that could support rural municipality for shaping disaster 
risk reduction policies and strategies.

Keywords

Digital Source, Distribution 
Map, Ground-Truthing, 
Landslide Distribution, Hazard 
Mapping, Nepal

1 Tribhuvan University, Institute of  Forestry, Hetauda, Nepal.
* Corresponding author’s e-mail: olitejraj33@gmail.com

INTRODUCTION
Nepal is a mountainous, geologically young country that 
straddles the boundary between the Indian and Himalayan 
tectonic plates. The country is geologically young and 
still evolving. Landslides are very common occurrences 
in Nepal and are also one of  the main natural hazards 
(Dikshit, 1983). Many hill slopes in Nepal are situated on 
or adjacent to unstable slopes and old landslides, which 
are reactivated from time to time (Johs Howell, 2002). In 
Nepal, on an average 260 people lost their lives every year 
and about 30000 families have affected annually (UNDP, 
2002).
Landslide is a natural process and its occurrence is 
controlled by the geologic, geomorphologic, hydrologic 
and climatic and vegetation conditions (Khanal Keshi 
Raj, 1998). Anthropogenic activities may also reactivate 
pre-existing landslide or may also initiate entirely new 
landslides. Landslides have been identified as a source 
of  hazard which results in environmental, social or 
economic loss such as human lives, houses, vehicles, 
passengers, cultivated land, community forests and 
development infrastructures like an electric power station, 
road, and irrigation channel. Hazard is the probability 
of  occurrence of  a particularly damaging phenomenon 
whining a specified period and area because of  a set of  
existing or predicted conditions (Deoja et al., 1991).
Hazard mapping is the process by which the probability 
of  occurrence of  any damaging phenomena can be 

predicted in any given area (Markus, 1985) To conduct 
landslide hazard mapping, it is necessary to identify 
the elements at risk such as population, infrastructures, 
economic activities, environment etc. that are exposed 
to the known hazard and that are likely to be adversely 
affected by the impact of  the hazard (Pradhan, 2003).
A landslide hazard map indicates the possibility of  a 
landslide occurring in a given area. A hazard map may 
be as simple as a map which uses the location of  old 
landslides to indicates potential instability, or as complex 
as a quantitative map incorporating probabilities based 
on variables such as rainfall thresholds, slope angle, soil 
type, and level of  earthquake shaking (Varnes, 1984). In 
the hazard map, the area is divided into low, medium and 
high hazard zones. The low hazard zone is considered 
to be more stable whereas medium hazard zone may 
have a possibility of  landslide disaster. Very dangerous 
and active landslide area represents the high hazard 
zone. The sign of  instabilities occurs in the high hazard 
zone, which has a high possibility of  failure in the future 
(Ghimire, 1993). So hazard mapping is an important 
tool in predicting the probability of  occurrence of  any 
damaging phenomena within any given area. Thus, if  the 
prediction is significant, the damage to lives property and 
ecosystem can be minimized to large extent. This study 
mainly focuses on the making hazard zonation mapping 
such that preliminary measures can be applied to before 
large type of  hazard occurs.

https://doi.org/10.54536/ajgt.v1i1.468
https://journals.e-palli.com/home/index.php/ajgt
mailto:olitejraj33%40gmail.com?subject=


Pa
ge

 
35

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

LITERATURE REVIEW
Landslide presents a threat to life and livelihood 
throughout the world, ranging from minor social 
disruption to huge economic catastrophe. Most work 
on landslide hazard assessment has been site-based and 
driven by development projects and engineering concerns 
(Crozier et al., 2005). The study of  landslides has drawn 
worldwide attention mainly due to increasing awareness 
of  the socio-economic impact of  landslides, as well as the 
increasing pressure of  the urbanization on the mountain 
environment. The local geology and slope of  the area also 
have a significant effect on landslides. To minimize the loss 
due to landslide, landslide-prone areas should be identified. 
Regional and local scale landslide hazard analysis and risk 
management are essential. Landslide hazard map (LHM) 
can be useful in estimating, managing and mitigating 
landslide hazards. A region with terrain condition similar 
to the region where a landslide has occurred is considered 
to be susceptible to landslides (van Westen, 1997). Hence, 
LHM is a fundamental tool for disaster management 
activities in fragile mountainous terrains. I think that 
LHM is a cost-effective method for disaster management 
in the context of  the county like ours. It leads to proper 
land-use practices and effective watershed management 
which could result in mitigating climate-induced disaster. 

STUDY AREA
District description
Formally Western Rukum district was part of  Rukum 
district, which divided into two districts, they are: Western 
Rukum and Eastern Rukum after the state reconstruction 
of  administrative division as of  20 September 2015. 
Rukum west district is located in Karnali province (6) 
of  Nepal having coordinates of  28.63˚N 82.49˚E. The 
district is covering the total area of  1,213.49 square 
k.m (465.53 square miles) and a total population of  this 
district as of  2011 Nepal census was 154,272 individuals.
Located in the western hill, western Rukum is mostly 
composed of  hilly terrain with some basin and valley. It is 
neighbored with five districts; they area: Eastern Rukum 
in east, Jajarkot district in the west, Dolpa in north and 
Salyan and Rolpa in the south. It has six local levels.

Study Area Description
The study area lies in Triveni rural municipality of   Rukum 
West district of  Nepal and is located at the south part of  
district and south part of  local level too at coordinates of  
28.55˚N 82.43˚E. Triveni rural municipality is bordered 
by Rolpa and Salyan district at south; Salyan district, 
Chaurjahari municipality and Saniveri rural municipality 
of  Rukum at the west, Musikot municipality of  Rukum 
West at north and Rolpa district and Musikot municipality 
at east. The study area lies inside the Triveni rural 
municipality and Khara contains three wards of  Triveni 
R.M i.e ward no. 3, 4 and 5 lies in this study area (old 
Khara VDC of  Rukum district) and covering the total 
area of  about 33.52 square kilometres.

Border of  the study area:
◉ North: Simrutu bazar, Rungha Rukum.
◉ South: Rolpa district.
◉ East: Rungha, Dangchung boarder.
◉ West: Rapti high way.

Figure 1: Location map of  the study area.
The Rapti highway is passing from this study area which 
connects the other parts of  Rukum and Jajarkot district 
with lower terai district like Dang, Nepalgunj etc. Many 
small to large streams are originated and passing from 
here. Southern face of  Khara is covering by forest lands 
where many small streams are originated and passing 
from there to Triveni Khola, Khara Khola is the main 
watershed of  this reason which includes more than 15 
streams that passing from here and finally mix with Triveni 
Khola and which ultimately meets with the Sanoveri river 
of  Rukum West.

MATERIALS AND METHODS
Research Design
The research is focused on the study on landslide 
distribution and their Hazard assessment of  the Khara of  
Triveni R.M, Rukum West district, Nepal. The procedure 
of  research is shown below in Figure 2.
The research is based upon the field data collection 
together with secondary data collection. Geological maps 
and reports, articles were also reviewed. Data collection 
was done using a GPS machine, taking samples and other 
materials. Co-ordinates of  landslides were taken and their 
boundary survey was done, causative factors were also 
analyzed by direct visualization and interaction with local 
people. A field survey was focusing on data collection for 
landslide inventory and their distribution using inventory 
forms and mapping of  various factors that are mostly 
responsible for triggering landslides.

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
36

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

Figure 2: Research design.

Methodology
Both the primary and secondary data were collected 
during the research. Primary data were collected through 
a Focus group discussion and Self-observation & Figure 
Questionnaire survey while secondary data were collected 
through relevant sources. 
Primary data collection
Primary data were collected through reconnaissance 
survey, questionnaire survey, focus group discussion and 
direct observation.
Reconnaissance survey:
A reconnaissance survey was carried out to identify 
general features and existing situation of  the study area 
and also for resources allocation. Rapport building with 
government officers, students, farmers, CDG members, 
other concerned personnel and individuals was made and 
they were informed about the research to build the trust 
and to create a friendly environment for the study.
Questionnaire Survey: 
The questionnaires were pre-tested in some households 
during the preliminary survey and were finalized 
by incorporating the feedback from local people. A 
structured questionnaire survey was carried out to gather 
the required information needed to fulfil objectives. 
4% (120) households, proportionally from each ethnic 
group or caste were interviewed to gather the basic data 
using questionnaire following a simple random sampling 
method. The survey represents Brahmin/ Chettri (B/C), 
Janajati/Adhibasi and Dalits and male-female respondents. 
Head of  the family and elderly individuals were 
interviewed. Information on the total no. of  landslide 
occurred, the damage was done by it and the mitigation 
practice adopted by people themselves and other 
concerned authority all-round the year was also noted.
Focused group discussion:
 Discussions were held with poor, men and women and 

disadvantaged groups to discuss the issues related to 
study background and also to triangulate the information 
obtained from the household survey. 
Direct observation:
Direct observation was made to analyze the actual field 
situation. A systematic sampling method was used with 
4% sampling intensity to select household, representative 
to the study area. Total no. of  landslide occurred to the 
area was observed with the help of  local people and 
supported by the local government of  Triveni R.M of  
Rukum West. A landslide over five years i.e landslide that 
was occurred in 2016, 2017, 2018, 2019 and 2020 was 
observed and geocode was noted for their mapping. Total 
damage done by a landslide in various field like in the 
agricultural field, in human settlement, human property, 
damage to domestic animals and injury or death to men, 
damage to the forest area and environment and damage 
to infrastructure were analyzed and noted. The precaution 
measures, landslide hazard risk reduction measures and 
mitigation practices adopted by local people themselves 
in cooperation with local government was analyzed. The 
role of  local people, students, local government and other 
NGOs, INGOs in the landslide hazard risk reduction and 
its mitigation was also analyzed and noted.
Secondary data collection
Secondary data were collected from the various sources 
and records like- reports published by related project, 
District Agriculture Development Office, municipality, 
Division Forest Office and District Soil Conservation 
Office. Maps, journals, publications, reports of  other line 
agencies, published or unpublished and relevant literature 
were also consulted in the library and the relevant websites 
to make better understanding, interpretation and analysis 
of  the research. 

Method of  data analysis
The data were coded, categorized and fed in the computer 
and analyzed using computer software packages MS Excel 
and GIS 10.2.2. The data collected during the field works 
were categorized into separate variables as required by the 
study objectives. The data of  the study were analyzed using 
both quantitative and qualitative methods. Quantitative 
data were analyzed using descriptive statistics such as 
percentage, mean, frequency distribution, maps and use 
of  graphics whereas the qualitative data was presented by 
illustrations such as simple tables, charts, and graphs and 
in other pictorial forms. 

RESULTS
Reconnaissance survey for the location of  different 
landslides within the study area was carried out and 
landslides were located on the topographical map 
(Department of  Survey, Nepal). The landslides were also 
marked in the satellite image in Google Earth and then 
exported as *.kml files. The Google earth image with 
landslide inventory was verified during the field survey. 
The verified landslide inventory map is digitized and 
produced. 

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
37

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

Different factor maps such as elevation map, Slope map 
and Aspect map, Curvature, Geology and Land use, road 
network and stream map has been prepared and classified 
under appropriate classes.

LANDSLIDE INVENTORY AND CAUSATIVE 
FACTOR ANALYSIS
Landslide inventory map
In the study area, more than 200 landslides were recognized 
by field visit and also using the Google earth imageries. 
Landslides are distributed heterogeneously over the area. 
The distributed landslides are separated in the map as a 
landslide in the road network area, landslide in protected 
parts (protected parts: parts covering of  forest area, bush 
area and other vegetative parts) and other parts (other 
parts: parts covering of  settlement area and agricultural 
areas) as shown in Figure 3.

Figure 4: Landslide size distribution mapping.

Landslide causative factors Analysis:
The influencing factors of  landslide hazard, for this 
particular study, as represented by the slope map, aspect 
map, geology map, relief  map, and land use map are 
archived to integrate the hazard level. The precipitation 
factor is also included in this study. Geology of  the region 
has also a great deal of  control over the process of  mass 
wasting in the region, but because the study area is not 
large, the difference in geology does not look apparent. 
The major components for landslide hazards in this study 
area are shown as above.

Figure 3: Landslide distribution mapping.
The hazard level of  each landslide is also calculated in 
the map. Landslides co-ordinate points and the size of  
them was taken from field visit and Google earth pro too. 
Finally, an Arc GIS 10.2.2 is used for inventory mapping.
Landslides are also shown in the map according to their 
sizes. Total landslides that were occurred during the last 
five years have been classified into three classes according 
to their sizes:

•Small-sized landslide: area <15 square m.
•Medium-sized landslide: area between 15-50 square m.
•Large-sized landslide: area >50 square m.

Landslide size also plays a great role in its hazard mapping. 
Simply, we can consider that the hazard level of  landslide 
increases with an increase in its size. There will be more 
risk of  disaster with an increase in its size.

Figure 5: Landslide causative factors.
The influencing factors of  landslide hazard, for this 
particular study, as represented by the slope map, aspect 
map, geology map, relief  map, and land use map are 

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
38

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

archived to integrate the hazard level. The precipitation 
factor is also included in this study. Geology of  the region 
has also a great deal of  control over the process of  mass 
wasting in the region, but because the study area is not 
large, the difference in geology does not look apparent. 
The major components for landslide hazards in this study 
area are shown as above.
The main landslide causative factors of  the study area are 
described as follows:
a) Rainfall:
The maximum landslides in Khara of  Triveni rural 
municipality are due to the cause of  intensive precipitation 
during monsoon. Steep slope land, unmanaged 
agricultural system and settlement make an increase in 
soil instability and thus, makes soil layer more susceptible 
to erosion during intensive precipitation. About 29% of  
the landslides of  Khara is because of  heavy rainfall.
b) Agricultural system:
The traditional, unmanaged and without planning 
agricultural system is also the main cause of  landslides. 
People in the study area are not highly educated and local 
government has not long term vision in the agricultural 
part yet. People make terrace for planting crops but 
the crops are traditional. Traditional agriculture system 
requires more efforts, more time but production becomes 
less in both qualitative as well as in a quantitative manner. 
Due to the lack of  modern agricultural knowledge, 
modern agricultural techniques and crops suitable to a 
local place and soil type cannot be grown. Young people 
are in abroad for employment. Women, old men and 
children are unable for better education production. 
This unmanaged agricultural system is also enhanced by 
landslides hazards.

Figure 6: Slope map.

c) Slope:
The natural slopes are the primary factor to dictate the 
stability of  the terrain. The slope condition includes the 
slope angle and the slope aspect. In general, the stability 
of  the slope is the interplay of  slope angle with, material 
properties such as permeability, friction angle, and 
cohesion of  the material. The slope is divided into the 
range of: <15˚, 15˚ -30˚, 30˚-45˚ and >45˚. In the study 
area, most of  the area is occupied by the high slope area 
followed by the sloping.

Figure 7: The area occupied by different slope level.
The landslide distribution map was superimposed on 
the slope map and the areas of  a landslide in each slope 
categories were calculated. The percentages of  a landslide 
in different slope categories. High slope type (30˚-45°) 
has the dominant landslide occurrence (60%) which is the 
earthflow type and the cliff  sloping type (>45°) has 25% 
followed by the medium sloping type (15°-30°) having 
only 11% and gentle slope have only 4% of  landslides.

Figure 8: Landslide % due to different slope level.
d) Aspect:
The windward and leeward faces as well as the northern 
and southern slope of  a mountain differ in their climatic 
conditions. It is because of  the difference in the amount 
of  rainfall and sunshine received which in turn controls 
the diversity, density and the distribution of  vegetation in 
the area. All these factors control the soil type, drainage 
type and a susceptibility to mass wasting over an area.

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
39

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

Figure 9: The area occupied by different aspect.
An aspect map shows to which side a slope is directed. 
An aspect value of  zero means that the slope is facing 
the north. The distribution of  the different aspect 
categories in the area shows that the study area is found 
to be predominately facing North-West (Nw) (20%) and 
East (E) (19.5%) followed by the west (12%), North-East 
(11.5%), North(11%), South-East(11%), South(8%) and 
South-West(7%). The landslide distribution map was 
superimposed on the aspect map and area of  a landslide 
in each aspect was calculated.
Slope facing North-East is found to be the highest share 
of  landslide occurrence, followed by north facing North-
West. The percentage of  landslides in different aspects 
level is shown in Figure 10.

Figure 10: Landslide % due to different aspect level.
e) Deforestation:
Deforestation has a great impact on landslides. Forest 
area is situated in the south part of  the study area and has 
high slope land. The population is increasing rapidly and 
hence, it needs more natural resources for the livelihood 
improvement. Road construction, encroachment in 
forest area and grazing activity in forest area make soil 
unstable and results in landslides. It is increasing at a high 
level. To reduce the landslides, deforestation, grazing, 
infrastructure construction activities should be reduced 
and plantation activity should be increased.

f) River cutting:
There are many streams in the study area. Streams are 
flowing from the upper hill to lower parts and thus, the 
water flowing speed is very high and more enough to cut 
lands situated near side of  stream channel and landslide 
becomes resulted. The stream channel of  Khara of  
Triveni R.M is shown in Figure 11.

Figure 11:  Stream network map of  Khara.
g) Road construction:
In the study area, road construction is increasing rapidly. 
The Rapti High way is passing from Khara and road 
networks are constructed and still constructing in the 
study area as shown in Figure 12.
Construction of  roads in the hilly region causes more 
landslides. The roads in hilly regions become unstable 
until about 3-4 years because the land is a week and 
landslides occur in the rainy season. Road construction in 
the hilly region makes more damage to land and increase 
landslide hazard.
h) Relief:
The surface relief  is the variation in height of  the 
land surface. Different reliefs have different climatic 
conditions. Another important aspect relating relief  
and landslide hazard is that construction activities like 
roads are preferentially built along with the same relief. 
It is therefore that the landslide hazards in an area are 
observed more or less on the same relief. The distribution 
of  land in the study area in various relief  groups is shown 
in Figure 13.
i) Landuse and land cover:
The land use has also a significant role in the stability 
of  soil slope. The land covered by forest regulates 
continuous water flow and an infiltration regularly 
whereas the cultivated land affects the soil slope stability 
due to saturation of  covered soil. In the study area, the 

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
40

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

area covered by settlement area, bush, cultivation land, 
construction, forest and water body cover the area of  
11%, 13%, 35%, 7%, 30% and 4% respectively. The area 
covered by the various land-use system is shown in Figure 
14 and Figure 15.

Figure 12:  Road network of  Khara.

Figure 13: Landslide % in different relief  level.
From the distribution of  different land use categories in 
the area, the largest share of  the study area is covered by 
cultivation (35% i.e 11.73 sq.km) followed by the forest 
area (30% i.e 10.056 sq.km) while the least is covered by 
water body (4% i.e 1.34 sq km). The land cover in the 
study area is used in various ways. They are settlement, 
bush, cultivation, forest and waterbody.
The landslide map is superimposed on the land use 
map and the area of  a landslide in the different land-use 
group is calculated. The prominent occurrence of  the 
landslide is found on cultivation area (32%) followed by 
construction site (26%).

Figure 14: The area occupied by different land use.
Land under the construction site is comparatively low 
as compared to the cultivation area. The cultivation 
area bears more landslides because of  improper and 
unmanaged cultivation system and traditional crops 
and lack of  knowledge in crops cultivation and crop 
cultivation system. There is less landslide occurrence 
in the settlement area (7%) followed by waterbody site 
(10%).

Figure 15: Land use map of  Khara.
j) Internal relief:
An internal relief  map shows the local relief  that is the 
local difference in height within a unit area. It indicates 
the potential energy for erosion and a mass movement. 
Internal relief  shows the major breaks in the slope of  
the study area. Four categories of  internal relief  in meter 
have been chosen for hazard evaluation. They are:

• Low internal relief
• Medium internal relief
• High internal relief  and,
• Very high internal relief.

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
41

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

Figure 16: Landslide % at the different land-use system. 

Figure 17: The area occupied by different internal relief.
k) Other factors:
Another component of  landslide hazard mapping 
includes other construction activities other than roads, 
earthquake, mining activity and so on.

RESULT AND ANALYSIS
Hazard Map
In the study area, the landslides have been taken as the 
indicator of  slope instability process. The Universe 
Transverse Mercator (UTM) projection is used. The slope 
instability is an outcome of  a complex interaction among 
a large number of  interrelated terrain factors (Yinka, 
1988). Only some of  the crucial terrain parameters: 
such as geology, internal relief, slope, aspect, land use 
pattern have been used for instability analysis. To evaluate 
the contribution of  each factor towards landslides, 
distribution data layer were compared to various thematic 
data layers separately. The resulting total weight directly 
indicates the importance of  total weights is positive the 
factor is favourable for landslide and if  it is negative, it is 
unfavourable. Based on the clustering of  total weights, as 
well as the concentration of  instabilities, the area under 
study was divided into the low, moderate and high hazard 
categories.
The percentage of  landslides at various hazards level can 

be concluded. Three hazard level of  landslides is taken i.e 
high hazard level, medium hazard level and low hazard 
level. About 9% of  landslides are under high hazard 
level, about 23% of  landslides are under medium hazard 
level and the remaining 68% of  landslides are under low 
hazard level as shown in Figure 20.

Figure 18: Landslide slope hazard map.

Figure 19: % of  the area in different hazard level. 
The landslides that were occurred during the last 5 years 
have been classified into three categories:

i. High hazard landslide
ii. Medium hazard landslide
iii. Less hazard landslide

The hazard level is determined by direct field observation, 
support of  local people and local government. The level 
of  hazard is classified according to its level of  damage 
to the environment, human resources and the entire 
ecosystem.

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
42

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

Figure 20: Landslide % at various hazard level.

Figure 21: Landslide hazard level that was occurred.

DISCUSSION
The hazard map generated has displayed a degree of  
reliability as an overwhelming number of  active and old 
landslides scars occur on high and very hazard zone. The 
hazard assessment shows that almost 53.64% of  the study 
area lies in the moderate hazard, 42.02% of  the area lies 
in the low hazard zone and 4.34% of  study area lies in 
high hazard zone of  hazard map prepared after detail 
investigation of  the factor that might be responsible 
causes for the onset of  the landslide. This agrees with 
the fact that weak geological formations of  the slope of  
the lesser Himalayas are greatly susceptible to landslide 
hazards. Moreover, such weaker formation in our study 
area is disturbed by the construction of  roads and 
buildings. Construction of  roads and construction of  
buildings or other heavy structure through slopes makes 
it vulnerable to a mass wasting phenomenon which in 

turn increase the driving force of  slope area. From the 
field observation, it indicates that the majority of  the 
landslides in the area where human interference is more.
Human activity i.e. construction of  roads, building and 
other activity like agricultural activity is relatively high in 
moderate and lower slope area. And the other parameters 
like land use also showed the effects of  human activity on 
the stability of  the land. From the land use map analysis, 
35% of  landslide observed in the cultivation area, has the 
highest percentage of  landslide whereas, the construction 
site has an area covering of  7% and it has the second-
highest percentage of  the landslide. The study area is 
characterized by a steep slope, steeper channel course 
and fragile geology. These factors have contributed to 
frequent slope movement and intense erosion processes 
during the heavy rainfall in monsoon.  This is obvious by 
widespread landslide scars, gully development in the study 
area. The topographic and geomorphic features reflect 
the marginality and susceptibility of  the environment in 
terms of  productivity and human habitat. The growing 
population pressure has been pressurizing the marginal 
ecosystem of  the area. The expansion of  the cultivation 
land on the steep slope either encroaching the forest area 
or shrub or bushes is evident to this. 

Picture 1: Drunken tree due to steep slope.
The instability of  slope is shown by drunken trees, trees 
displaced from their normal vertical alignment. This is 
due to the slow movement of  the slope. Small subducted 
pits area found around the side of  the hill indicate the 
instability of  the hill.   

CONCLUSION
The study focused mainly on the identification distribution 
mapping of  landslides along with the classification of  the 
hazardous zone as well as the identification of  the causes 
of  the slope instability that will help divert the preventive 
work to the area of  high susceptibility indicated as high 
hazard region on the hazard zonation map. To minimize 
the implication of  natural hazards by methods such as bio-
engineering technique or immediate mechanical intrusion 
can be applied. This paper also demonstrates that the 
instability in the Khara area is due to the instability of  
the hill slope. Most of  the area lies under the moderate 
hazard zone.

ABBREVIATIONS
CDG Community Development Group
DSCW Department of Soil Conservation &                          

https://journals.e-palli.com/home/index.php/ajgt


Pa
ge

 
43

https://journals.e-palli.com/home/index.php/ajgt

Am. J. Arts. Geo. Spat. Technol. 1(1) 34-43, 2022

 Watershed   Management       
FRM Frequency Ratio Model
GIS Geographical Information System
GPS Global Positioning System
LHM Landslide Hazard Map
LSM Landslide Susceptibility Map
NRC Nepal Research Council
UNDP United Nation Development Program
VDC Village Development Committee
WOE Weight of  Evidence

REFERENCES
Crozier, M. J., & Glade, T. (2005). Landslide Hazard 

and Risk: Issues, Concepts and Approach, Landslide 
hazard and risk, pp. 1-40.

Deoja, B., Dhital, M.R., Thapa, B., & and Wagner, 
A. (1991). Landslide risk: A Case study from the 
Mountain region of  Nepal, Mountain risk engineering 
handbook, p. 857.

Dikshit, A.M. (1983). Report on Preliminary Engineering 
Geology: Investigation of  Landslide and Subsidence 
in Kera Bari character area in the Siddhartha highway, 
Kathmandu, Geology. 

Ghimire, K.K. (1993). Study of  Landslide: A case study 
of  Likhi Khola area along within the study of  a landslide 
in Nepal during the period (1950-1969), Unpublished 
dissertation Central Department of  Geology. 

Johs Howell. (2002). Roadside bio-engineering: A case 
study of  roads of  Nepal, Department of  road Nepal. 

Khanal Keshi Raj. (1998). Mass movement analysis: Mass 
movement in the lower base of  Chandragiri range South of  
Kirtipur. Unpublished dissertation Central Department 
of  Geology, Tribhuvan University. 

Markus J. (1985). Mountain Hazard Mapping in Khumbu 
Himal. Mountain Research Development, 6(1), 29-40. 

Pradhan, A.M.S. (2003). Engineering Geological Investigation 
of  Pharping-Kulekhani road alignment. Unpublished 
dissertation from Central Department of  Geology, 
Tribhuvan University Kirtipur Nepal.

Terlien, M. J., van Westen, C. J., and van Asch, T. W. 
(1995). Deterministic modelling in GIS-based 
landslide hazard assessment, USA. Engineering Geology, 
69, 331-343.

UNDP. (2002). Human Development Report: Working with 
partners in more than 160 countries, UNDP report.

van Westen, C. J. (1997). An approach for GIS-based 
statistical landslide susceptibility zonation- with a case 
study in the Himalaya, Statistical Hazard analysis, (pp. 
61-69).

Varnes, D.J. (1984). Landslide hazard zonation: A review 
of  the principle of  and practices, Commission on 
landslides of  the IAEG, UNESCO, Natural hazard, 3.

Yinka, Yan TZ. (1988). Statistical prediction model 
for slope instability of  metamorphosed rocks. 
In: Bonnard C(ed) Proc 5th Int Symp landslides, 
Lausanne. Balkema, Rotterdam, Vol.2, PP 1269-1272.

https://journals.e-palli.com/home/index.php/ajgt

