soft soils strata in paya terubung - sungai ara catchments

LANDSLIDE HAZARD ZONATION FOR
PAYA TERUBUNG - RELAU SLOPE TERRAINS IN PENANG ISLAND
Fauziah Ahmad1, Shabri Lebai Din² and Mohd Sanusi S. Ahmad1
1
School of Civil Engineering, Universiti Sains Malaysia,
Engineering Campus, 14200 Nibong Tebal
Seberang Perai Selatan, P.Pinang
and
²Universiti Technology Mara,
Campus Arau, 02600 Arau, Perlis
KEYWORDS: GIS; Landslide Hazard; Hazard Zonation Map
ABSTRACT
Lately there are many landslide disaster cases which have been reported and most of the
occurrences are due to human factors such as extensive earth cutting, land clearing, agricultural
activities, burning, uphill developments and other due causes. A study of Paya Terubung-Relau
slope terrains which situated in between two hill ranges of Bukit Penara and Bukit Kukus at
almost in the middle part of the Penang Island was selected as the study area. The place was
selected due to its highest records of landslide occurrences in the Island and also the vast hill
development area. Geographic Information System (GIS) method was applied where the data
obtained been digitized, attributed, layered and interpolated in the process of obtaining the
hazard zonation maps. Then these Information where then used to interpreted in obtained hazard
risk assessment maps. The maps will be of beneficial where geotechnical and GIS inputs were
incorporated in the landslide analysis to the study area for the risk assessment.
1. INTRODUCTION
The tragedy of landslide occurs almost every where in Malaysia, especially within the hilly and
mountainous ranges those relate with intensive pace of development, land cutting and site
clearance to make the areas directly expose to the parameter of earth slope failures.
Penang Island known as the most rapid development zone in the north region of Malaysia
Peninsular nevertheless facing the same phenomenon and most of the cases reported occurred in
the area of Paya Terubung-Relau catchments which choose as the study area.
The main objective of this study is to evaluate the parameter of soil strata in the area relate with
their slope stability parameters using Geographic Information System (GIS) interpolation
techniques. The parameters obtained are to be used in estimating the hazard zonation maps and
risk assessment maps using the numerical-cartographical rating analysis in the GIS conceptual.
Both types of maps are not to be discussed in this paper.
2. STUDY AREA
The study area is located in southeast of the middle portion of the Penang Island. Situated in the
latitudes north of 50 20’ to 50 23’ and longitudes east of 1000 15’ to 1000 17’ of Mukim 13 and
14 of Bukit Paya Terubung, under administration district of Daerah Timur Laut area, Penang.
The approximate land covers of the area is about 20 km2 as concluded in part of Malaysian
Topographic Map Series L7010, Sheet 28a, Pulau Pinang, Malaysia at scale of 1:50000. The
location map of Penang Island includes the study area portion of Paya Terubung- Relau terrains
is illustrated in figure 1.
255000
260000
5* 29'
250000
605000
245000
590000
590000
595000
595000
600000
600000
605000
N
585000
100* 11'
245000
0
3 km
250000
100* 19'
255000
5* 16'
585000
STUDY AREA
260000
Figure1: Locality map of Penang Island and the insert portion of
Paya Terubung – Relau catchments area.
Elevation grids:
0-5m
300-400m
Road
5-50m
400-500m
50-100m
500-600m
100-200m
600-700m
200-300m
700-823m
Pekan Paya Terubung, Pekan Relau and Pekan Bukit Jambul are the landmark towns those
respectively situated in the north, south and southeast portions of where state the highest
population densities in the area.
The topography of the study area consists of two parts:
i- Rugged and rapid undulation terrains of two major hilly terrains lying on north-south
elongation in the west and east part of the area each known as Bukit Penara and Bukit Relau /
Bukit Jambul terrains and respectively record the highest point of 550 meters and 410 meters
above mean sea level.
ii- Three flat low lying lands at the elevations below 15 meters above mean sea level cover the
north, south and east portion of the study area of respectively known as Paya Terubung,
Sungai Relau and Sungai Dua fluvial catchments.
As located almost in the middle of the island the three towns mentioned on the above become the
trunk towns linking Georgetown City on the east, Balik Pulau Town on the west and Bayan
Lepas Town on the south to make the major roads of Jalan Ayer Itam, Jalan Tun Sardon, Jalan
Relau and Jalan Bukit Jambul in the study area among the heaviest link routes in the Island.
3. Data Sources
The following data were obtained and used in the GIS data layer preparation works:
i- Penang Island Topographic Map Series L7010, Sheet 28a, Pulau Pinang, at scale of 1:50000
obtained from USM library.
ii- Satellite images of IKONOS covering the study area dated July of 2002 and January of 2005
and SPOT image covering the whole State of Pulau Pinang dated January of 2005
complimented by Malaysian Centre of Remote Sensing, Kuala Lumpur, (MACRES).
iii- The data of 150 boreholes and 3 auger holes tests discovered from the soil investigation
reports supplied by Public Work Department (JKR) Penang and several civil engineering
consultants in Penang commenced upon their associate development projects within the
study area.
iv- The data of 33 auger holes and 41 JKR probes tests personally commenced on some typical
places those expected having critical ground conditions and yet to have the soil investigation
data before. The places are mostly at the steep slope and hill summits of the study area those
extremely remote and hardly accessed.
4. GIS SOFTWARES
The GIS software's used in the analytical works are:
4.1. Erdas Imagine 8.3.1
The software was used in the processes of the following:
i. Early preparations of importing, sub-setting, georeferencing (coordinating) and formatting
the map into raster layer.
ii. Digitizing and attributing works to produce a vector layer.
iii. Surfacing processes of vector layer to produce a grid (spatial) data layer.
iv. Image drape processes of performing the image into three-dimensional appearances.
4.2. Arcview GIS version 3.2
The software was used in the following processes:
i. Detail digitizing and attributing works.
ii. Editing, joining and splitting the vector entities and their attribute fields.
iii. Data layering and reclassifying works.
5. DATA PREPARATIONS
To deal with GIS all the raw data need to be prepared into the digitized data layer formats. Every
data layer contains all the corresponding dataset entities of each having its individual engineering
criteria those been concluded in the set of data layer attribute.
In determining the criteria of soils those anticipate in the instability of slopes, three types of data
layers been digitized from the corresponding data sources of the following:
i. Contour data layer at entity intervals of 50 feet been prepared using the Penang Island
topographic map. The attribute field was made based on the entities elevations.
ii. Vegetation coverage data layer contains five entities categories of very thick coverage, thick
coverage, shrub coverage, sparsely vegetated coverage and barren land digitized based on
their respective prominence appearances as observed from the satellite images. The attribute
field for the data layer was made based on such entities categories.
iii. Soil data layer contains the tests results within the dataset entities of borehole, auger holes
and JKR probes digitized based on the data of previous soil investigation reports and
personal site observation works conducted in the study area. The attribute fields of the data
layer contain the essential parameters of soil types, soft soils strata thicknesses, total soils
strata thicknesses, water tables, soils cohesions, soil internal friction angles, φ and soils
densities those obtained from the corresponding tests either at site or in the laboratory.
Figures 2, 3 and 4 below show the data layers on respective aspect of the above.
6. METHODOLOGY
The following GIS analyses have been made on the data layers of the above:
6.1 Contour data layer surfacing and grid interpolations
The contour data layer been interfaced through the steps of surfacing and grid interpolation
processes to perform a final slope map of which represent the classified range of the soil surface
slope gradients within the study area. Figures 5, 6 and 7 below show the respective appearance of
the slope map, slope tin map and drape image map produced through the processes. The
gradients of the slopes obtained are to be used in further slope stability analysis.
6.2 Vegetation coverage data layer classifications.
The classification processes been made on the vegetation coverage data layer in order to assign
the corresponding layer entities into their respective pre-defined classes. By the process the
entities within the data layer will be accomplished to the range of classes of each resumes the
same entity properties. The classes defined are as shown in table 1 below.
Table 1: Class scalar rating for vegetation coverage data layer
Earth coverage
Class
Bare land
5
Sparsely vegetated land
4
Shrub covering land
3
Thick vegetated land
2
Very thick vegetated land 1
6.3 Soil data layer attribute fields interpolation and spatial conversions.
The soils safety factors are to be the main criteria those impose the instability to the slope. Using
the field calculation in the Arcview software utility such criteria are definable and assigned as
the new attribute fields to the data layer.
The safety factors of the soils were estimated using Coppin and Richard, (1990) safety factor
approaches of the following:
6.3.1 The safety factor, Fs for cohesive-frictional type of soils:
i-
Soils within partially saturated conditions:
Fs =
ii-
(c′ + c′R ) + ( γ z - γ w z w + Sw ) cos β tan φ′
[( γ z + Sw ) sin β + d] cos β
Soils within fully saturated conditions:
Fs =
(c′ + c′R ) + [ ( γ - γ w ) z + Sw ] cos β tan φ′
[( γ z + Sw ) sin β + d] cos β
6.3.2 The safety factor for sand dominant type of soils:
i-
Soils within partially saturated conditions:
Fs =
ii-
( γ z - γ w z w + Sw ) cos β tan φ′
( γ z + Sw ) sin β + d
Soils within fully saturated conditions:
Fs =
[ ( γ - γ w ) z + Sw ] cos β tan φ′
( γ z + Sw ) sin β + d
where:
c and φ are respectively the cohesion and angle of internal friction thus related to the shear
strength parameter of the soil.
γ and z are the bulk density and thicknesses of the soil stratum.
γw and zw are water density and depth of water inside the soil.
β is the soils slope gradient which derived from the slope map.
Sw is vegetation surcharge on the soil slice per unit area resulted from the vegetation weight, W
imposes on the soil slice of length b x 1 unit width; of where Sw = W/b.
d is the disturbing force on the soil slice per unit area resulted from the wind loading, D imposes
d is disturbing force due to wind loading stress, d imposes on the soil slice of length b x 1 unit
width; where d = D / b
cR′ is soil cohesion increments due to root matrix reinforcement.
The factors of Sw, d and cR′ been determined by resuming the criteria prescribed in table 2 below
respect to the entities classes of the vegetation coverage data layer preset in 6.2.
Table 2: The values of cR′, Wand D respect to entities classes
(After Coppin and Richard, 1990)
Earth coverage
Class c′R
W
D
kN
kN
(kN/m2)
Bare land and
5
0
0
0
Sparsely vegetated land 4
Vegetated land
3
5
0.25 0
Thick and
2
6
3.8
0.1
Very thick coverage
1
6.3.3 Spatial layer conversions
Through grid conversion processes in the Arcview software utility the spatial layers of soil strata
thicknesses and soils safety factors within non-saturated and fully saturated conditions were
produced based on the corresponding attribute fields that dully prepared.
7. RESULTS AND DISCUSSION
Figures 8 and 9 below respectively indicate the spatial layer of overall thicknesses of the soft soil
strata and total soil strata deposited in the study area.
As indicated in figure 8, the soft soils strata lying in the various thicknesses from 0 to 24.3
metres whereas the figure 9 indicates the overall soils in study area deposited at the thicknesses
range between 0 to 33 metres. The soft soils been termed for the layers those indicate the
standard penetration values, N from borehole tests of less than 8 blows that belong to very soft
and soft consistencies for cohesive-frictional soils and loose to firm consistencies for sand
dominant soils.
Both categories of soils indicate the similar depositional trend of thin occurrences in the zones of
hill summits to thickest occurrences in the zones of flat valley lands in the study area. For the
overall soils spatial layer in figure 9, the thickness occurrences of 0 remarks the areas of rock
exposures.
Figures 10 and 11 below are the spatial layers of the estimated safety factors on soft soils strata
which respectively reveals under non-saturated and fully saturated conditions. Whereas figures
12 and 13 indicate the spatial layers of the estimated safety factors on the overall soils deposit in
the study area of each similarly reveals under non-saturated and fully saturated soils conditions.
The zones with safety factor of 0 indicates none existence of soil in that particular area.
By combining the spatial layers of slope map in figure 5 with each of the safety factors spatial
layer on the above, the zones of soils with respective classes of instability categories from 1 for
the most stable zone to 5 for the most unstable zone can be determined.
Figures 14 and 15 shown spatial layers of the respective categories of zones mentioned for the
soft soil strata available corresponding to non-saturated and fully saturated conditions.
8. CONCLUSION
As concluded in the analysis results the soils safety factors are among the main criteria those
directly impact the instability to the slopes. By the GIS layer overlay concept, compiling the
criteria on the above with other landslide causative parameters of drainages and geological
features, the zones of landslide susceptible areas which known as the landslide hazard zonation
can be developed.
ACKNOWLEDGEMENTS
This study been carried out as a part of the PhD research work; upon with the author would like
to express his sincerely thanks to the department of by Malaysian Centre of Remote Sensing,
Kuala Lumpur, (MACRES), Public Work Department (JKR) Penang and several civil
engineering consultants in Penang of providing the data.
References
Anbalagan, R., 1992. Landslide hazard evaluation and zonation mapping in mountainous terrain.
Engineering Geology 32, pp. 269 – 277.
Anbalagan, R. and Singh, B., 1996. Landslide hazard and risk assessment mapping of
mountainous terrains – a case study from Kumaun Himalaya, India. Engineering Geology 43, pp.
237 – 246.
Donati, L. and Turrini, M.C., 2002. An objective method to rank the importance of the factors
predisposing to landslide with the GIS methodology: application to an area of the Apennines
(Valnerina; Perugia, Italy). Engineering Geology 63, pp. 277 – 289.
Fauziah, A. et al., 2002. GIS application on slope stability. Proceeding of the 2nd IKRAM
International Geotechnical Conference, pp. 159 – 165.
Jasmi, A.T., 2003. Probabilistic landslide susceptibility analysis and verification using GIS and
remote sensing data at Penang, Malaysia. Geological Society of Malaysia 46, pp. 173 – 179.
Mahadzer, M. and Mohd, F. B., 2002. Application of aerial photos, GIS and GPS in slope
management. Proceeding of the 2nd IKRAM International Geotechnical Conference, pp. 125 –
138.
Ong, W.S., 1993. The geology and engineering geology of Pulau Pinang. Geological Survey of
Malaysia, Map Report 7.
Turrini, M.C. and Visintainer, P., 1998. Proposal of a method to define areas of landslide hazard
and application to an area of the dolomites, Italy. Engineering Geology 63, pp. 255 – 265.
50
6 50
10
0
Figure 2:
Contour layer of Paya Terubung-Relau
catchment digitized at the entity
intervals of every 50 feet.
20 0
1000
25
0
15
00
13 0 0
350
Contour line
Road
50
50
Figure 3:
Vegetation coverage data layer of the
study area.
Legend:
very thick coverage
thick coverage
shrub coverage
sparsely vegetated coverage
barren land
Road
River
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Figure 4:
Soil investigation data
layer conducted in the
study area.
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(Kilometer)
Figure 5: Slope map of the study area
Slope Gradients.
0 – 100
300 – 400
0
0
10 – 20
400 – 500
0
0
20 – 30
> 500
Road
River
N
0
1
2
(Kilometer)
Figure 6: Slope tin map of the study area
Slope Gradients.
0 – 100
300 – 400
0
0
10 – 20
400 – 500
0
0
20 – 30
> 500
Road
River
Figure 7: Drape image map of the study area
N
0
1
2
N
0
(Kilometer)
1
2
(Kilometer)
Figure 8: Spatial layer of soft soils strata Figure 9: Spatial layer of total soils strata
thicknesses in the study area.
thicknesses in the study area.
0
0 – 3m
3m – 6m
6m – 9m
9m – 13m
13m – 17m
17m – 21m
21m – 24.3m
0
0 – 3m
3m – 6m
6m – 9m
9m
14m
19m
24m
29m
–
–
–
–
–
14m
19m
24m
29m
33m
Figure 12: Spatial layer on safety Figure 13: Spatial layer on safety
factor of the whole soils strata under factor of the whole soils strata under
non-saturated condition.
fully saturated condition.
Fs = 0
Fs = 2 – 3
Fs = 0
Fs = 2 – 3
Fs = 0 – 0.5
Fs = 3 – 5.4
Fs = 0 – 0.5
Fs = 3 – 5
Fs = 0.5 – 1
Road
Fs = 0.5 – 1
Road
Fs = 1 – 2
River
Fs = 1 – 2
River
Figure 14: Spatial layer of expected
slope instability zones respect to safety
factors criteria for soft soils strata
under non-saturated condition.
Most stable zone
Stable zone
Moderate stable zone
Unstable zone
Most unstable zone
Figure 15: Spatial layer of expected
slope instability zones respect to
safety factors criteria for soft soils
strata
under
fully
saturated
condition.
Most stable zone
Stable zone
Moderate stable zone
Unstable zone
Most unstable zone