An Estimation of Earthquake Impact to Population in Makassar by Probabilistic Approach
ISSN: 0852-0682, EISSN: 2460-3945
, 30 2 20 6: 58- 65 20 6 -N -N 4 0
An Estimation of Earthquake Impact to Population in Makassar by
Probabilistic Approach
Bambang Sunardi* and Sulastri
Research and Development Center, Indonesia Meteorological Climatological and Geophysical
Agency
)Jl. Angkasa 1 No. 2 Kemayoran, Jakarta 10720
Corresponding author (e-mail: bambang.sunardi@bmkg.go.id)
Abstract.
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Keywords:
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1. Introduction
area of Makassar approximately 175.77 Makassar is the capital city of South 2 km , includes 11 islands in Makassar Strait
Sulawesi province and the largest city plus sea area of approximately 100 km² in eastern Indonesia. It is located on the (makassarkota.go.id). southwestern coast of Sulawesi Island.
In opposite with its strategic position,
0DNDVVDU LV WKH ÀIWK PHWURSROLWDQ LQ Makassar also cannot be separated from
Indonesia, following Jakarta, Surabaya, HDUWKTXDNH KD]DUG 0DNDVVDU KDV D PHGLXP
Bandung and Medan. Makassar has a ULVN FODVV RQ (DUWKTXDNH 'LVDVWHU 5LVN strategic position, because it is located at Index Regency / City, which is contained
WKH FURVVURDGV RI WUDIÀF IURP VRXWK DQG in Indeks Resiko Bencana Indonesia (IRBI) north in Sulawesi Island, also from western
/ Indonesian Disaster Risk Indexes 2013 to eastern regions and from northern and
:
04 E E
I S S
issued by BNPB (Ruswandi et. al., 2014). $OWKRXJK LWV HDUWKTXDNH GLVDVWHU ULVN FODVV LV moderate, Makassar has very decisive position in Indonesia development, especially in Eastern Indonesia. For this reason, study related to
HDUWKTXDNH KD]DUG DQG ULVN RI 0DNDVVDU QHHG
WR EH GRQH 9DULRXV VWXGLHV DERXW HDUWKTXDNH in Indonesia has been done, but many of them only focused on the physical aspect of HDUWKTXDNH 3DQGLWD HW DO $OLI HW DO
9DULRXV VWXGLHV OLQNLQJ HDUWKTXDNH hazard and population have been conducted. 'HOO· $FTXD HW DO FRQGXFWHG D VWXG\ using remote sensing method to obtain spatial data of buildings and population to be used in the global exposure database for WKH PRGHOLQJ RI JOREDO HDUWKTXDNHV :DQJ HW al. (2012) connected the physical condition of the environment, social conditions and human expectations to calculate the capacity of the population (population carrying capacity / 3&& LQ IDFLQJ HDUWKTXDNH $OOHQ HW DO created a shakemap atlas (in PGA form) and population exposure catalog, which the data FDQ EH XVHG WR ÀQG WKH GHJUHH RI YXOQHUDELOLW\ RI D FRXQWU\ WR HDUWKTXDNH KD]DUG
Liu and Wang (2015) studied the differences LQ KXPDQ YXOQHUDELOLW\ WR HDUWKTXDNH KD]DUG between rural and urban areas. Rahman et al.
(2015) combines physical and social factors in calculating the vulnerability of society to HDUWKTXDNHV DQG ÀUHV $UD DVVHVVHG WKH ULVN RI HDUWKTXDNH KD]DUG IRU WKH SRSXODWLRQ temporally. He divided into working days, holidays, Ramadhan, and busy days, also distinguished between day and night. This
VWXG\ LV PRVW VLPLODU WR *XSWD HW DO ZKLFK connected the population and PGA values.
7KLV VWXG\ LV D ÀUVW VWHS LQ GHWHUPLQLQJ VHLVPLF vulnerability, human exposure, population carrying capacity and the determination of seismic risk.
This study aims to determine the population of Makassar City threatened by WKH SUREDELOLVWLF HDUWKTXDNH KD]DUG 7KH HDUWKTXDNH KD]DUGV ZLOO EH FDOFXODWHG DW peak ground acceleration (PGA) and spectral DFFHOHUDWLRQ DW WZR VSHFLÀF SHULRGV 7 DQG T=1 second. Generally, this study combines WZR W\SHV RI GDWD SUREDELOLVWLF HDUWKTXDNH hazard and population of Makassar.
2. Research Method
The area of study bounded by Makassar Strait in the west, Kepulauan Pangkajene in the north, Maros in the east and Gowa in the south. It is geographically located between Ļ ļ Ļ ļ (DVW DQG Ļ ļ Ļ ļ 6RXWK 7KH DUHD RI VWXG\ was shown in Figure 1.
Figure 1.
The area of study E E
I S S
7 VHFRQG UHVSHFWLYHO\ (DFK HDUWKTXDNH hazard map generated will split Makassar City into several areas with different acceleration values, expressed in g (gravitational force of the earth).
An overview of Makassar population in 2013 can be seen in Figure 2. We could see that the Makassar, Mariso and Mamajang sub districts got highest population density, while Biringkanaya, Tamalanrea and Manggala sub districts got the lowest density. According to these, Makassar, Mariso, and Mamajang can be FODVVLÀHG DV XUEDQ DUHDV ZKLOH %LULQJ .DQD\D Tamalanrea, and Manggala as rural areas.
probability of intensity , that exceed the value of i DW D UHYLHZHG ORFDWLRQ RI DQ HDUWKTXDNH event with a magnitude M and distance to hypocenter R, and 3 [, L] is the probability of intensity , that exceed the value of i. In this study, PSHA was analysis for 2% exceeded SUREDELOLW\ LQ \HDUV RU HTXLYDOHQW ZLWK \HDUV HDUWKTXDNH UHWXUQ SHULRG DGMXVW WR modern seismic regulations as well as NEHRP $6&( ,%& DQG 61, which refers to ASCE 7 -10 (Imran, 2010).
3 [, L|m and r] is the conditional
is distance to hypocenter distribution function,
f
r
Makassar City is part of Sulawesi Island. Based on their formation, this island can be divided into four zones, i.e. West Sulawesi, East Sulawesi, Banggai-Sula and Central Sulawesi. They were united in Miocene- Pliocene era caused by interaction between
Estimation number of people threatened E\ WKH SUREDELOLVWLF HDUWKTXDNH KD]DUG in Makassar is conducted by overlaying HDUWKTXDNH KD]DUG PDS ZLWK SRSXODWLRQ data. Population data used in calculation was obtained from Central Board of Statistic of Makassar, Makassar in Figures, 2013. The reason for the use of Makassar in Figures 2013 and not Makassar in Figures for 2014 was due to population data can be obtained up to the village level. Makassar in Figures 2013 contains demographic data for the city of Makassar in 2012, while the current year at this time was in 2015. The assumption used here is the population growth rate for the city of Makassar
(DUWKTXDNH KD]DUG IRU 0DNDVVDU ZDV determined by combining probabilistic HDUWKTXDNH KD]DUG PDS ZLWK DGPLQLVWUDWLYH map of Makassar. Administrative map derived from RBI map of Makassar 1: 25,000 Scale. This SUREDELOLVWLF HDUWKTXDNH KD]DUG PDS LV EDVHG on peak ground acceleration (PGA) and spectral DFFHOHUDWLRQ DW WZR VSHFLÀF SHULRGV 7 DQG
3UREDELOLVWLF HDUWKTXDNH KD]DUG DQDO\VLV
The data processing includes creating D KRPRJHQHRXV PDJQLWXGH HDUWKTXDNH data, separating the mainshock from its foreshocks and aftershocks, also analyzing WKH FRPSOHWHQHVV RI HDUWKTXDNH GDWD 7KH QH[W VWDJH LV HDUWKTXDNH VRXUFH PRGHOLQJ based on geological and tectonic conditions DQG FKDUDFWHUL]LQJ HDUWKTXDNH VRXUFH
7KH QH[W VWHS LV FROOHFWLQJ HDUWKTXDNH GDWD KDYLQJ WKHVH FULWHULD PDJQLWXGH 0Z DQG D maximum radius of 500 km from Makassar. It ZDV XQGHU DVVXPSWLRQ WKDW HDUWKTXDNHV ZLWK magnitude Mw < 5 and a radius of over 500 km ZLOO QRW JLYH D VLJQLÀFDQW LPSDFW RU OHVV OLNHO\ to cause damage.
VRXUFHV ZKLFK LQÁXHQFH LQ 0DNDVVDU HLWKHU subduction, faults and background sources.
7R FDOFXODWH SUREDELOLVWLF HDUWKTXDNH KD]DUG ÀUVW VWHS LV LGHQWLI\ HDUWKTXDNH
VWUXFWXUDO HOHPHQWV WKDW FDQ WULJJHU HDUWKTXDNH at Sulawesi, i.e Walanae fault, Makassar thrust, Lawanopo fault, Tolo thrust, Matano fault, Poso fault, Sula fault, Batui thrust, Palu Koro fault, Gorontalo fault, Sulawesi Sea subduction plate and Maluku subduction plate (Irsyam et al., 2010).
3DFLÀF DQG $XVWUDOLDQ SODWHV WR $VLDQ SODWH (Kaharudin et al., 2011). The interaction of the three plates could be the cause of the geological GLVDVWHU LQ 6XODZHVL VXFK DV HDUWKTXDNHV tsunamis, volcanic eruptions and ground movements. There are at least 12 tectonic and
2WKHU VXE GLVWULFWV FDQ EH FODVVLÀHG VXE XUEDQ areas, those are between urban and rural areas.
UHTXLUHG DSSURSULDWH DWWHQXDWLRQ IXQFWLRQV IRU
(DUWKTXDNH KD]DUG DQDO\VLV ZDV FRQGXFWHG using Probabilistic Seismic Hazards Analysis (PSHA), by using total probability concept &RUQHOO DV GHÀQHG LQ HTXDWLRQ
HDUWKTXDNH KD]DUGV DQDO\VLV DQG PDQDJLQJ uncertainty elements with logic-tree. By using D ORJLF WUHH HDUWKTXDNH VRXUFH SDUDPHWHUV DQG attenuation models can be accommodated with appropriate weights.
(1) with f m is magnitude distribution function,
E E
The last step is to state the estimated number of Makassar people threatened E\ HDUWKTXDNH KD]DUG LQ D SHUFHQWDJH )RU example, to state the percentage of estimated SRSXODWLRQ WKUHDWHQHG E\ HDUWKTXDNH KD]DUG RI 0.1 g, the formula used is as follow.
The estimated number of people affected E\ SUREDELOLVWLF HDUWKTXDNH KD]DUG ZLOO EH discussed at these conditions.
As stated before, the probabilistic HDUWKTXDNH KD]DUG RI 0DNDVVDU &LW\ ZDV PDGH at three conditions, peak ground acceleration 3*$ DQG VSHFWUDO DFFHOHUDWLRQ DW WZR VSHFLÀF periods T=0.2 and T=1 second respectively.
Based on Makassar in Figures 2013, the SRSXODWLRQ RI 0DNDVVDU LV SHRSOH The population density per village of Makassar varies widely, ranging from 752 persons/ km 2 to 258,000 persons/km 2 . The highest population density is in Makassar sub district and the lowest population density is in Biringkanaya sub district (northernmost). Population density of Makassar City was shown in Figure 2.
Figure 2. Population densities of Makassar City
of estimated population threatened by HDUWKTXDNH KD]DUG RI J 3 (0.1 J) is the total of estimated number of people threatened E\ HDUWKTXDNH KD]DUG RI J DQG 3 is the total population.
J) is the estimated percentage
(3) With E (0.1
' WKUHWHDQHG E\ J HDUWKTXDNH hazard, and $' is total area of Village '.
I S S
Village
of people in Village ' threatened by 0.1 g HDUWKTXDNH KD]DUG $ (0.1 J) is the area of
3 (0.1 J) is the estimated number
(2) With
VR WR ÀQG WKH QXPEHU RI LQKDELWDQWV RI WKH village with different acceleration value used the comparison of area. For example, to search how many endangered populations of 0.1 g for village ', the formula used is as follows.
Estimation number of people threatened E\ HDUWKTXDNHV ZDV FDOFXODWHG IRU HYHU\ YLOODJH in Makassar. It is assumed that the population of each village distributed homogeneously,
almost the same for all regions of Makassar, so even if calculations using population data in 2013, but it still can be applied for 2015.
3. Results and Discussions
E E
I S S
Spectral acceleration value at T = 0.2
DIIHFWHG E\ HDUWKTXDNH KD]DUG ZLWK DFFHOHUDWLRQ
VHFRQGV UDQJHG IURP WR J 7KH VWXG\ area was divided into three classes, i.e. area acceleration between 0.29 to 0.31 g, between WR J DQG EHWZHHQ WR J respectively. Spectral acceleration value at T = 0.2 seconds is the highest acceleration among all periods. Estimation of population WKUHDWHQHG E\ HDUWKTXDNH KD]DUG DW WKHVH conditions have a similar pattern to PGA result, but differ in percentage of the area and the percentage of population, as shown in Figure 4. Around 18.37% of area with relatively low acceleration spectra between 0.29 to 0.31 g, covered Tamalate, southern parts of Mariso, Mamajang, and Rappocini respectively. The percentage of population DIIHFWHG E\ HDUWKTXDNH KD]DUG DW DFFHOHUDWLRQ between 0.29 to 0.31 g approximately 19.73% of total population. Area with acceleration between 0.31 to 0.33 g reached 44.01%, included Ujung Tanah, Tallo, Wajo, Bontoala, Ujung Pandang, Makassar, Panakkukang, southwest of Tamalanrea, most of Manggala, Rappocini, Mamajang and Mariso. The percentage of SRSXODWLRQ DIIHFWHG E\ HDUWKTXDNH KD]DUG with acceleration between 0.31 to 0.33 g was
ZLWK DFFHOHUDWLRQ EHWZHHQ WR J UHDFKHG FRYHULQJ %LULQJ .DQD\D DQG QRUWKHUQ of Tamalanrea. The percentage of population
EHWZHHQ WR J DSSUR[LPDWHO\ RI total population.
Spectral acceleration value at T = 1 second RI 0DNDVVDU UDQJHG EHWZHHQ WR J The study area also divided into three, i.e. area acceleration between 0.13 to 0.14 g, between 0.14 WR J DQG EHWZHHQ WR J UHVSHFWLYHO\ as shown in Figure 5. At T = 1 second period, DERXW WKUHH TXDUWHUV RI WKH DUHD DQG WKUHH TXDUWHUV RI WKH SRSXODWLRQ LV WKUHDWHQHG E\ HDUWKTXDNH KD]DUG EHWZHHQ WR J DQG WKH UHVW LQ GDQJHU RI HDUWKTXDNH KD]DUG between 0.13 to 0.14 g in the south, and between WR J LQ WKH QRUWK $URXQG RI WKH SRSXODWLRQ DIIHFWHG E\ WKH HDUWKTXDNH hazard with acceleration between 0.14 to 0.15 g, covered Ujung Tanah, Wajo, Bontoala, Tallo, Tamalanrea, Panakkukang, Makassar, Ujung Pandang, mostly of Biring Kanaya, western of Manggala, northern parts of Rappocini, Mamajang and Mariso respectively. While RI SRSXODWLRQ DIIHFWHG E\ HDUWKTXDNH hazard with acceleration between 0.13 to 0.14 g covered Tamalate, southern of Rappocini and northeast of Manggala. The remaining 2.5% of
DSSUR[LPDWHO\ RI WRWDO SRSXODWLRQ $UHD
WKH SRSXODWLRQ DIIHFWHG E\ HDUWKTXDNH KD]DUG
DFFHOHUDWLRQ VSHFWUD RI WR J FRYHUHG D small area of Biring Kanaya.
Figure 3.
3HDN JURXQG DFFHOHUDWLRQ 3*$ HVWLPDWHG DUHD DQG D௺HFWHG SRSXODWLRQ
E E
I S S Figure 4.
6SHFWUDO DFFHOHUDWLRQ DW 7 VHFRQGV HVWLPDWHG DUHD DQG D௺HFWHG SRSXODWLRQ Figure 5.
6SHFWUDO DFFHOHUDWLRQ DW 7 VHFRQG HVWLPDWHG DUHD DQG D௺HFWHG SRSXODWLRQ
7KH SDWWHUQ RI SUREDELOLVWLF HDUWKTXDNH hazard as shown in Figure 3, Figure 4 and Figure 5 showed low ground accelerations values in the south, especially in Tamalate sub district. Further north increased and reached the highest value in the north, in Biringkanaya sub district. The existence of Walanae fault in northeast Makassar is the reason why PGA values relatively tend to rise toward northeast. Walanae fault is an active
IDXOW ORFDWHG DSSUR[LPDWHO\ NP IURP Makassar City (Rante, 2015). The calculation result of maximum ground acceleration based on historical seismicity indicated that Walanae
IDXOW JDYH WKH KLJKHVW LPSDFW WR HDUWKTXDNH hazard compared to other seismic sources E E
I S S
around Makassar City (Makassar thrust, if the city development move to Biringkanaya, Lawanopo fault, Matano fault, Poso fault, Palu- more costs are needed to make a more resistant Koro fault). building. Both Tamalate and Biring Kanaya sub districts are rural areas, but the Tamalate got
4. Conclusion
the lowest and Biringkanaya got the highest Study on estimation of Makassar City
VHLVPLF JURXQG DFFHOHUDWLRQ 7KH FRQFHTXHQF\ population threatened by probabilistic is that the Biringkanaya people should build
HDUWKTXDNH KD]DUG RYHUOD\ PHWKRG RI WKH PRUH UHVLVWDQW EXLOGLQJ WR HDUWKTXDNH LI
SUREDELOLVWLF HDUWKTXDNH KD]DUGV PDS DQG WKH\ ZDQW WR PLQLPL]H WKH HDUWKTXDNH LPSDFWV population data successfully performed on
7KH HGXFDWLRQ DERXW HDUWKTXDNH KD]DUG LWV peak ground acceleration (PGA), spectral impacts, and how to minimalize the effects acceleration at period T=0.2 seconds and should be given, especially to people in
T=1 second respectively. Each result gave Biringkanaya . different acceleration values, but have a similar
The urban areas which are located next to the pattern, i.e. a low acceleration values lies in FHQWUDO RI 0DNDVVDU JRW WKH PHGLXP HDUWKTXDNH the south, especially in Tamalate sub district. hazard, when compared with other areas in
Further north increased and reached the Makassar. For a growing city like Makassar, it highest value in the sub district Biringkanaya. needs spaces for the regional development. To
Other conclusions is urban area of Makassar minimize the the cost of buildings and other which is the concentration of the population, facilities, the city development should expand UHFHLYHG WKH PHGLXP HDUWKTXDNH KD]DUG ZKHQ to Tamalate. If there is another consideration compared with other areas in Makassar City. about the city developmet, in another words
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$UD 6 ,PSDFW RI WHPSRUDO SRSXODWLRQ GLVWULEXWLRQ RQ HDUWKTXDNH ORVV HVWLPDWLRQ D FDVH study on Sylhet, Bangladesh.
,QW - 6FL 'LVDVWHU 5LVN
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/LX - DQG :DQJ 6 $QDO\VLV RI WKH GLIIHUHQWLDWLRQ LQ KXPDQ YXOQHUDELOLW\ WR HDUWKTXDNH
KD]DUGV EHWZHHQ UXUDO DQG XUEDQ DUHDV FDVH VWXGLHV LQ :HQFKXDQ (DUWKTXDNH
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