15
3. RESULTS
Data Evaluation
To determine earthquake hazard areas relevant literatures were sought. Several factors were considered in arriving at the determine earthquake hazard
areas in feasibility site for nuclear power plants. This is of great importance to consider the nature of what is to be sited. In this study, by taking into account the
conditions of Bangka Island, six criteria were selected, they are:
1. Slope map Slope is an important factor while considering the ease of engineering
construction and susceptibility to landsliding caused by earthquake. The slope map was produced from SRTM Digital Elevation Model DEM of the study area.
By considering the suggestions in the literature, slope map is classified into four groups. The groups and related rankings are shown in Table 7. The final map
ready for analysis is shown in Figure 6.
According to Table 7, Bangka Island are dominantly located on slopes between 0 and 9 , and were assigned as the flat class by approximately 93.68
from slope area total. By using slope map, area identified as earthquake hazardous areas can be determined. Related to earthquake hazard areas, slope between 16
and greater 20 are classified as high to very high hazard areas.
Table 7 Classes produced for slope according to the earthquake hazard areas Slope
Area Ha Percentage
– 9 10
– 15 16
– 20 20
1.093.865 68.354
5.112 2.740
93.68 5.85
0.44 0.02
Total 1.167.605
100 Based on Figure 6, it can be seen that earthquake hazard areas occurred on
slope greater than 20 . Mostly of high earthquake risk is distributed on slope between 16 and greater 20 which called high step topography. Topography is
one of important parameters because of high of place is describe by high hazard area. According to the Figure 6 earthquake hazardous areas is mostly in east part
of Bangka Island. It can be proven that earthquake hazard is related to steeper slope. Steep slopes can be particularly hazardous during and after earthquakes.
16
Figure 6 Classes determined for slope according to earthquake hazard areas 2. Fault Distance
The faults are digitized from 1:250,000 scaled geological maps. The main idea of this map is the proximity to the fault passing through the study area shown
in Figure 7. Faults are the structural features which describe a zone of weakness with relative movement, along which earthquake area susceptibility is higher. It
has generally been observed that the probability of earthquake occurrence increases at sites close the faults, which do not only affect the surface material
structures but also make contribution to terrain permeability causing slope instability.
Table 8 Fault distance area Distance
Area Ha Percentage
– 30 km 30
– 50 km 50 km
1.167.605 -
- 100
- -
Total 1.167.605
100
17
Figure 7 Fault distance map Locations which are far from the fault line are safer than closer ones
relatively, in the scope of nuclear power plant. Buffer zone is considered for each distance level and they are converted into raster data having fault distance
classification values. Based on the vector layer of faults from geological map, the distance of all pixels from nearest fault was calculated, and then the earthquake
hazard areas as a function of fault distance. Three different buffer areas were identified within study area to determine the degree to which the faults affected
the earthquake hazard. The hazard areas percentage in each buffer zone is given in Table 8 which shows that 100 percent of the Bangka Island is closely located
within 30 km of the buffer zone.
3. Lithology Lithology is one main factors influencing the type and the intensity of the
earthquake ground shaking. The parameter lithology is related to the resistance to earthquake hazard. Information on the lithology was derived from a series of
1:250.000 maps produced by the Indonesia Geological Department. Maps were successively vectorized and lithologies assigned to geographical areas as attributes
connected with vector polygons. Figure 8 shows the simplified lithological map of the study region. This map was recompiled and simplified for the purpose of
determine earthquake hazard areas analysis.
18 Table 9 Lithology of research area
Lithology Age Area Ha
Percentage Quarternary 2.5 Myrs
Tertiary 2.5 ≤ Age ≥ 75 Myrs Basement Rock 75 Myrs
359.592 768.424
39.589 30.80
65.81 3.39
Total 1.167.605
100 According to Bealand, 1996, Lithology are grouped into 3 three classes:
Quartenary in age less than 2.5 million least hazardous, Tertiary in age from 2.5 million years to 75 million years Quite hazardous and Basement rock in age
more than 75 million years Not very hazardous.
Based on Table 9 earthquake hazard areas highly concentrated in the tertiary age 65.81 and hazardous areas is less in the basement rock category
3.39 and in the quatenary rock age classes 30.80 . Figure 8 showing that the Bangka Island most dominant lithology tertiary age, where hazard level is
quite hazardous scattered throughout the island.
Figure 8 Lithology Map 4. Earthquake Intensity
Earthquakes occur when stresses in the Earth exceed the rock’s strength to resist, thus causing the sudden rupture of rocks and displacement along a surface
called a fault. The fault may already have existed or may be newly created by the
19 earthquake rupture. Energy from the fault rupture is transmitted as seismic waves
that cause nearly all damaging earthquake effects. The earthquake intensity scale is the most familiar index to indicate the
strength of ground shaking andor how an area will be affected by an earthquake. Descriptions of the severity of earthquake ground shaking at any place may be
given using intensity scales such as the Modified Mercalli Intensity scale. The Modified Mercalli MM scale describes the strength of shaking by categorizing
the effects of an earthquake through damage to buildings, landsliding, liquefaction, soil cracking and other types of ground failure, and the reactions of
people and animals.
It is very important to estimate the distribution of seismic intensities for regional earthquake damages prediction about future big earthquake. The seismic
intensity is strongly influenced by subsurface ground condition and basement irregular boundary condition. The distributions of the estimation maximum
earthquake intensity in Bangka Island based on calculate using Dowrick attenuation is shown in Figure 9. Figure 9 shows the maximum intensity
earthquake which can occur and indicates that most of Bangka Island is at none to very light damage risk.
It can be seen from the figure that the characteristics of intensity distribution in Bangka Island are that the intensity was high in the north 0.79
and most of the Island is almost low 99.21. The general trend of earthquake damage in the Bangka area was that damage was more serious in the plain area
and less in the hilly area.
Estimation of earthquake intensity has been used by the formula provided by Dowrick et.al.1999 by decreasing intensity with epicentral distance. The zone
of maximum intensity 6 MMI was located at the nort part Bangka Island. Intensity zone was calculated for 1.167.605 Hectare in an area having 1.158.307
Hectare with maximum intensity V, 9.298 Hectare with intensity 6, respectively Table 10.
The distribution of earthquakes is called seismicity. Seismicity is highest along relatively narrow belts that coincide with plate boundaries. This makes sense,
since plate boundaries are zones along which lithospheric plates move relative to one another.
Table 10 Classification of earthquake intensity area MMI
Area Ha Percentage
I, II, III, IV, V VI, VII
VIII, IX X, XI, XII
1.158.307 9.298
- -
99.21 0.79
- -
Total 1.167.605
100
20
Figure 9 Earthquake intensity map
5. Microtremor Classification or zoning of ground conditions is important in the
earthquake damage estimation because ground conditions directly affect seismic amplification of ground shaking. This study adopts ground condition based on the
microtremor measurement. These measurement correspond to the predominant period and amplification factors of each soil type. It is very effective to consider
ground conditions when conducting precise damage estimation.
Horizontal vertical spectral ratio HVSR spectrum obtained from analysis of microtremor signal recording using geopsy software. This process can be
determined values A Amplification factor and fo predominant period for each measurement point. The dominant period map is classified into 4 four classes:
rock T 0.2 sec, hard soil 0.2 ≤ T 0.4 sec, medium soil 0.4 ≤ T 0.6 sec and soft soil T=0.6 sec. Table 11 shows the most predominant period at hard soil
66.81 followed by medium soil 21.25 and hard rock 11.94. Figure 10 shows distribution of T where the distribution of predominant period frequencies
is relatively uniform, ranging from 0.61 to 8.60 Hz at all point measurement. Figure 10 described that the hard soil with natural periods
0.2 ≤ T 0.4 sec is covering the entire research area and other only small parts.
21 Table 11 Predominant period area
Natural Periods Area Ha
Percentage T 0.2 sec
0.2 ≤ T 0.4 sec 0.4 ≤ T 0.6 sec
T ≥ 0.6 sec
139.426 780.082
248.097
- 11.94
66.81 21.25
- Total
1.167.605 100
Dominant frequency value fo is useful parameter in planning and
development. In building planning fo values should not be equal to the frequency of the building so that the building can withstand from an earthquake. Fo value
from structures must be estimated properly so as not to have the same fo value from the site, as it will resonance during the earthquake. This will lead to an
increase in the vibration caused by earthquake. In addition, the very low value of fo will be very susceptible to high-rise buildings of the vibration waves of long
period earthquakes. Results of this study shown that fo values are relatively low because it has a value less than 10 Hz. However, to prevent the damaging effects
of earthquakes, development in nuclear power plant should consider the value of the existing dominant frequency.
Figure 10 Predominant period map
22 Soil amplification is a main factor influencing the distribution of damage
and causalities in urban area when large earthquake occur. In this research, the classification of amplification factors is grouped into 4 four classes: very low
hazard, low hazard, moderate hazard and relative high hazard based on amplification factor A or peak ratio HVSR spectrum. Very low hazard is the
region of amplification factor from 1.0 to 2.5, low hazard is the region of amplification factor value from 2.5 to 3.5, and moderate hazard is the region of
amplification factor with value ranging from 3.5 to 4.5 and relative high hazard amplification factor or peak HVSR spectrum ranging from 4.5 to 7.0.
Table 12 Amplification factor area Amplifications
Area Ha Percentage
1.0 – 2.5
2.5 – 3.5
3.5 – 4.5
4.5 – 7.0
110.638 203.753
248.581 604.635
9.48 17.45
21.29 51.78
Total 1.167.605
100
Figure 11 Amplification factor map
23 Table 12 shows that the most amplification factor is located in 4.5-7.0
region 51.78 followed by 3.5-4.5 region 21.29, 2.5-3.5 region 17.45 and 1.0-2.5 region 9.48. From the analysis of the spectrum of HV can be seen
that he study are has a peak value HVSR at intervals of values from 0.8 to 1.5. Contour map HVSR peak value A is shown in Figure 11. High amplification
factor was found almost all area. Figure 11 described that the highest amplification factor are distributed in the southern area and northern area. This
map shows areas where the earthquake hazard is increased due to amplification of ground motion.
HVSR peak value or amplification factor A correlated with the damage caused by the earthquake. If an area has a low predominant period value and high
value of amplification factor will produce a high level of damage to buildings. From the data obtained, the values of amplification factor and predominant period
at all points of measurement are values varied. It is pointed out that the areas of nuclear power plant not have high levels building damage that caused by an
earthquake.
Analysis
In order to determine earthquake hazard areas of the study areas Simple Additive weighting SAW method was applied. Simple additive weighting also
known as weighted linear combination or scoring method is a simple and the most often used multi attribute technique. The six map layers, each of which defines a
criterion necessary to be considered in determine earthquake hazard areas were prepared. Combining and weighting the six layers was accomplished using the
raster calculator.
Simple Additive Weighting SAW is found easy to apply and it is quite widely applied in real world, however, it is criticized for having little theoretical
foundation and its ignorance of the definition of the units of measurements. The first step is to give identifying the criteria and decision rules of each thematic
map. Such criteria were used as indicators for determine earthquake hazard areas that are prone to future earthquake damage. A set six criteria and decision rules
are derived from field survey data, cartographic maps and literature review. Such criteria were classified into geological, geophysical and terrain characteristic. The
selected geological criteria are the rock type and the faults. The geophysical criteria are the dominant periods and amplification factors. The terrain
characteristic criterion is represented by the slope. The selected set of criteria and decision rules are explained in bellow:
-
Lithology : The younger age of rock is more damage effect to earthquake hazard Bealand,1996
- Fault distance : Closely fault distance is more damage effect to earthquake
hazard Mohsen, et.al.,2012 -
Earthquake Intensity : Higher earthquake Intensities are more damage effect to earthquake hazard FEMA, 2001
- Dominant Period : Higher natural periods are more damage effect to
earthquake hazard Molas, et.al,2005 -
Amplification factor : The higher the factor of amplification the more damage effect to earthquake hazard Kamal et.al, 2006
24 -
Slope : Steeper slope angles are more damage effect to earthquake hazard Andrian,2009
After the decision rule and criteria are designed, the assigned weight and rank values for the layersclasses of each layerclasses, according to relative importance
of that layerclasses to earthquake hazard areas map. In the assigning of weight and rank values, inverse weighting and ranking criteria is used as given in table
below:
Table13 Classification of weight values Malczewski,1999
Weight Classification
1 2
3 4
5 6
7 8
9 Equal importance
Equal to moderately importance Moderate importance
Moderate to strong importance Strong importance
Strong to very strong importance Very strong importance
Very to extremely strong importance extremely strong importance
Table 14 Classification of rank values
Rank Classification
1 2
3 4
Low Hazard Moderate Hazard
High Hazard Very High Hazard
The assigned weight and rank values for the layerclasses of the study area based on geological and geophysical expert’s judgment are given in Table 13. As
can be observed from the table, the most important layer was defined as the fault distance followed by the earthquake intensity, dominant period, amplification
factors, lithology and slope layer in decreasing order of importance. In the determination of the weight values, the fault distance layer has been given the
greatest value because of an earthquake is caused by the sudden release of slowly
accumulating strain energy along the a fault within the earth’s crust. It means that a fault is present near or within the land parcel and may pose a risk of surface
rupture to existing or future structure. earthquake intensity is the second most important parameter. Furthermore, predominant period, amplification factor,
lithology and slope are the third, fourth, fifth and sixth important parameters. The determination criteria for assigned rank value in Table 15 are explained below for
each layer:
25 a.
The ranking values for the classes of fault distance layer are 4 for very high earthquake hazard potential, the ranking for the high earthquake hazard
potential classes as 3, since there is still a danger of earthquake hazard, but no as the very high earthquake hazard potential class.
b. The rank values for the classes of the earthquake intensity are assigned as 4 to
the prone areas and 1 to the safe areas, so that the most favorable class is ranked far from unsafe class.
c. In the dominant period layer the classed are sorted according to their soil
behavior as rock, hard soil, medium soil and soft soil. The rangkings are given 4,3,2, and 1 respectively.
d. In the amplification layer, the classes are ranked as 4, 3,2 and 1 for high
hazard, moderate hazard, low hazard and very low hazard classes, respectively.
e. The ranking values for the classes of the lithology layer are 4 and 1 for the
most and the least hazardous classes respectively. The ranking of the intermediate lithology class is assigned as 3, since, with the simple additional
precautions, this class can also be suitable for determine earthquake hazard area.
f. The ranking values for the classes of slope layer are given as 4 and 1 for the
high and low hazard slope classes respectively.
Table 15 Assigned weight and rank values for the classes of the study area
Currently, there is no standardization for making weight and rank for
determine earthquake hazard areas in Indonesia. Because the weight and rank
26 values are given on different scales, they must be standardized to a common
dimensionless unit. The simplest formula for standardizing the raw data is to divide each raw score by the maximum value for a given criterion Malezewski,
1999. Standardization is important, because the scores of the criteria are given on different scales, they must be standardized to a common dimensionless unit.
Hence, the rank values of the classes were standardized according to the relative distance between the origin and the maximum rank value, using the following
formula:
X
ij
=
X
ij
X
j max
6 Where
X
ij
is the standardized rank value for the ith class for the jth layer.
X
ij
is the rank value, and
X
j max
is the maximum rank value for the jth layer. On the other hand, the weight values were normalized by dividing each
weight by the sum of the weights. Thus the sum of the normalized weight values was equal to 1. After the standardization of values in each map layer, the criterion
weights and ranks were defined as shown in Table 16.
Table 16 Standardized rank values and normalized weight values
27 To obtained the determine earthquake hazard areas map; the technique of
overlaying of index maps was used. When overlaying the index maps, equation 2.3 was used and the earthquake hazard areas map was obtained for the study area
with index values ranging from 0.25 low earthquake hazard areas to 1 very high hazard areas to earthquake.
The earthquake hazard areas map of the study area was categorized in three resultant classes as: High damage areas, moderate damage areas and low
damage areas Table 17. Areas of high damage are those with slopes steeper, high amplification factor, high period dominant, quarternary litology,high
earthquake intensity or short fault distance. The boundary conditions for three categories were evaluated according to the expert judgment taking into
consideration the score distribution by means of discrete histograms. The output map produce by the method of SAW is given in Figure 12. The even weighted
approach yielded a classification of earthquake hazardous areas over the study area. In the varied weighted approach, a total weight was computed from the sum
of three respective components for each polygon Slope, Lithology, Fault distance, Amplification Factors, Predominant period and earthquake intensity
making up the study area.
Table 17 Total Score Classification of Earthquake Hazard Areas
Classification of Earthquake Hazard Areas
Rating Score
High Damage areas Moderate Damage areas
Low damage areas 0.75
– 1.00 0.50
– 0.75 0.25
– 0.75 The areas to the south and west are generally either low or of medium
hazardous to earthquakes. According to Table 18 it can be seen clearly that moderate level of earthquake hazard is dominantly found on Bangka Island with
809.735 Ha or 69.35 totally of study area. Earthquake prone area distributed at the east part of Bangka islands. Exactly earthquake prone area is located in several
districts such as Bangka Barat, Bangka Selatan and Bangka with totally 221.692 Ha.
Table 18 Classification of earthquake hazard areas Classification of earthquake
hazard areas Area Ha
Percentage High Damage areas
Moderate Damage areas Low damage areas
221.692 809.735
136.178 18.99
69.35 11.66
Total 1.167.605
100
As it can be seen from Figure 12, the areas belonging to low and moderate damage areas are very dominant while the areas with high damage areas are
28 minor. For the feasibility site for nuclear power plants were created using Simple
Additive Weighting method describe the areas is categorized moderate earthquake affect damage.
The objective of this map is to show areas of Bangka Island where the earthquake hazard is likely to be increased due to the presence of potentially
unstable slopes, and soils susceptible to amplification of ground motion. Many seismologists have said that earthquakes dont kill people,
buildings do. This is because most deaths from earthquakes are caused by buildings or other human construction falling down during an earthquake.
Earthquakes located in isolated areas far from human population rarely cause any deaths. Figure 13 is taken from a Google earth, 2011, satellite image showing the
location of the proposed nuclear power plant in South Bangka Regency. In Figure 13 an image of feasibility site for nuclear power plant it are very clear low human
population, far from volcano can be easily distinguished.
Figure 12 Earthquake hazard areas map Figure 14, is a Google Earth image, which shows areas of feasibility site for
nuclear power plant in South Bangka. From satellite image can be seen are low population and dominantly by vegetation. The following Figure 13 and Figure 14
the percentage of affected population in feasibility site Bangka Island is much lower and no significant damage areas due to infrastructure.
29 Comparison result of earthquake hazard areas map Figure 12 with the
satellite image showing the candidate sites for nuclear power plant in Bangka Island are located in areas of no significant earthquake risk.
The important of this model is that we can identify the areas which will be affected if the earthquake occurrence in Bangka Island. Such maps normally aim
providing a document that depicts the likelihood or possibility of new earthquake occurring on this island, and therefore helping to reduce futures damages.
Figure 13 Google earth image feasibility site for nuclear power plant in West Bangka
Fgure 14 Google earth image feasibility site for nuclear power plant in South Bangka
30
4. CONCLUSSION
Kategori