Philippine Journal of Science 147 (2): 301-316, June 2018 ISSN 0031 - 7683 Date Received: 11 Aug 2017

A GIS-Based Earthquake Damage Prediction in Different Earthquake Models: A Case Study at the University of the Los Baños, Philippines

Ibnu Rusydy1,3,*, Decibel V. Faustino-Eslava2, Umar Muksin3,5, Richelle Gallardo-Zafra4, 4 6 7 8 Jedidiah Joel C. Aguirre , Nathaniel C. Bantayan , Lubna Alam , and Shruthi Dakey

1Department of Geological Engineering, Faculty of Engineering, Syiah Kuala University, Banda Aceh, Indonesia 2School of Environmental Science and Management, University of the Philippines, Los Baños, Laguna, Philippines 3Tsunami and Disaster Mitigation Research Center, Syiah Kuala University, Banda Aceh, Indonesia 4Department of Civil Engineering, University of Philippines Los Baños, Laguna, Philippines 5Department of Physics, Faculty of Sciences, Syiah Kuala University, Banda Aceh, Indonesia 6College of Forestry and Natural Resources, University of the Philippines, Los Baños, Laguna, Philippines 7LESTARI, Universiti Kebangsaan Malaysia (UKM), Selangor, Malaysia 8Visvesvaraya National Institute of Technology, Maharashtra, India

The University of the Philippines Los Baños (UPLB) is located in an earthquake-prone region and there are numerous earthquake sources that can possibly cause an earthquake at any magnitude anytime. A study of the earthquake damage prediction in several earthquake magnitude and time scenarios in GIS model analysis has been conducted for the UPLB’s campus. This study aims to produce several scenarios of the earthquake models and an intensity map for UPLB’s campus; to determine the damage ratio of the buildings and its distribution in different earthquake scenarios; and to estimate the casualty in the UPLB’s community; as well as to validate the earthquake model with historical earthquakes in the Philippines. Data preparation included the earthquake scenario model using shallow crustal shaking attenuation to produce an intensity map on the bedrock and the surface after site coefficient correction. The earthquake model in different scenarios is generated from the West Valley Fault (with Segment IV as the assumed locus). The damage ratio in different types of buildings was calculated using fragility curves of buildings of the Philippines. Population data of each building in different occupancy times, damage ratios, and injury ratios is used to compute the number of the injured due to an earthquake. The results reveal that UPLB’s building are subject to intensity range of MMI (Modified Mercalli Intensity) 6.7-8.1 due to 6.1-7.7 Mw earthquake coming from different sources along the West Valley Fault. The worst event of an earthquake is 7.7 Mw from Segment IV, which can cause 32-51% damage to buildings and injure 12-24.6% of a building population in a daytime (2 PM) event and injure 8-158 students in a dormitory at 2 AM (nighttime). The validation process shows that the mean square error between the calculated intensity and the actual intensity in the Philippines is 0.35.

Key words: damage prediction, earthquake, earthquake loss scenario, GIS, UPLB

*Corresponding author: [email protected]

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INTRODUCTION hazard assessment that incorporates both historical earthquakes and active faults in the Philippines. The study The safety of a university is the most pressing need for successfully produced a peak ground acceleration (PGA) students, lecturers, and university members. Universities map of the Philippines in the expected event of 475-year have several types of buildings with different purposes recurrence (10% in 50 years) and occasional events of (academic, services, administrative, and dormitory), some 100-year recurrence (39% in 50 years). The PGA map of which become more vulnerable compared to other is a macrozonation map based on the acceleration in the buildings when an earthquake occurs. The Philippines bedrock; to build a microzonation map, one needs to experiences many destructive earthquakes in various parts determine the surface ground shaking. For , of the country. One of the most remembered earthquakes Miura and co-authors (2008) conducted earthquake is the 1990 Central earthquake with magnitude damage estimation due to an earthquake scenario and of Ms = 7.8 (Kojima et al. 1992; Wieczorek et al. 1992). estimated the seismic performance of a building based on Therefore, studying earthquake damage prediction in an expert judgment. The damage ratio of the structure is several scenarios becomes necessary to decrease the calculated from the fragility curve that varies with each vulnerability and increase the capacity of the community building, and the distributions of the destroyed buildings in the future. are calculated by considering the damage ratios and the To study building damage prediction in several earthquake building inventory. scenarios based on Geographic Information System In this study, the ArcGIS software was used to transform (GIS) analysis, it is necessary to estimate the earthquake all parameters into actionable information. All parameters intensity in several scenarios of magnitudes and the – such as geological map, amplification map based on source of the earthquake from the fault close to the study standard penetrating test (SPT) data, several earthquake area. This earthquake intensity or ground shaking is the scenarios’ map in MMI, the fault map, and the type of primary factor that causes building damage compared building maps – are converted to shape files. All the maps to liquefaction, landslide, and seismic bearing capacity were classified and used to calculate the damage ratio of (Cinicioglu et al. 2007). The second process is to evaluate UPLB’s buildings, damage distribution, and loss analysis. the damage ratio based on the seismic performance in Modified Mercalli Intensity (MMI) of each building and the fragility curve in a different type of structures, which Tectonics and Seismicity of the Study Area is proposed by Tingatinga and co-authors (2013). The third The Philippines is located in one of the most seismically step in this study is to calculate the damage distribution active regions of Asia. Several significant and destructive and the number of damaged buildings from the damage earthquakes have occurred almost in every part of the ratio and buildings inventory data at the University of the country. The earthquake of 1990 in with Philippines Los Baños (UPLB). magnitude of Ms 7.8 was the greatest earthquake for the people of the Philippines. The Philippines has many Earthquake damage prediction using the systematic earthquake sources, such as the Philippine Trench, built GIS method was proposed by Miura and co-authors by of the western edge of the Philippine Sea (2008), Hashemi and Alesheikh (2011), and Karimzadeh Plate below the Eurasian Plate; this trench is the primary and co-authors (2014). The method involved several source of earthquakes and causes the Philippines to be geological data such as geological map, groundwater, classified as an earthquake-prone country (Kojima et sedimentological map, alluvial thickness, microtremor al. 1992; Wieczorek et al. 1992; Torregosa et al. 2001). dataset, and earthquake catalog. For an earthquake The trench extends from the south of Island to scenario, deterministic seismic hazard analysis (DSHA) Luzon Island in the north for a distance of about 1,400 uses the ArcGIS toolset. Karimzadeh and co-authors km and is seismically active (Galgana et al. 2007). The (2014) argue that the DSHA method is accurate where the other sources of earthquakes are the Philippine Fault Zone tectonic setting is reasonably active and well located. To (PFZ), , and West Valley Fault System estimate the building damage ratio, Karimzadeh and co- (WVFS), which roughly parallel the Philippine Trench. authors (2014) used the fragility curve in a different type of buildings as a function of MMI and they estimated the The PFZ formed due to oblique convergence between casualty ratio from historical earthquakes in the study area. the and the Eurasian Plate (Rowlett & Kelleher 1976; Besana & Ando 2005; Rimando & In the Philippines, numerous studies on earthquake Knuepfer 2006). The PFZ is an active sinistral fault that engineering, including damage prediction, simulation, extends from Mindanao to Luzon Island in a distance and site response, were carried out by several researchers. over 1,600 km long (Rimando & Knuepfer 2006). From Torregosa and co-authors (2001) conducted a strong the southeastern part of Luzon, the PFZ traverses into ground motion simulation technique based on seismic the Ragay Gulf zone and continues southeastward to the

302 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB eastern part of Burias Island; approximately 10 major historical earthquakes occurred along this area (Rowlett & Kelleher 1976). Besana and Ando (2005) noted that the PFZ in Quezon transects to the west seaward of Ticao Island and then enters the southeastern Masbate Island; continuation of the PFZ is found on the island of Leyte along the same trend. The Luzon earthquake (1990) was the most destructive earthquake that occurred in the PFZ. The Manila Trench is an active subduction zone caused by the penetration of the South China Sea plate beneath the northern Philippine Sea Plate. The 1,200-km-long Manila trench is associated with the east-dipping Benioff zone beneath Luzon (Hayes & Lewis 1985; Nguyen et al. 2014). In order to conduct modeling, Nguyen and co-workers (2014) introduced several models of seismic sources located along the Manila trench. Based on the model, an earthquake with magnitude of Mw 9.3 could occur along the Manila trench that could also cause high ground shaking. However, the most devastating seismic source for the study area originates from the VFS. The VFS is the closest earthquake source to the study area at the distance in between 20-40 km. According to Rimando and Knuepfer (2006), VFS is a dextral (right lateral) strike-slip fault with a length of 130 km extending from the south of Canlubang to the Dingalan Bay in the north striking north-northeast (NNE). There are other sources of the earthquake (e.g., Figure 1. The Valley Fault System (VFS) and its segments are directly north of the UPLB campus (black rectangle). The East Zambales fault) that can cause significant damage to VFS fault map is modified from Rimando and Knuepfer the site but fault going to model its effects in future study. (2006), while the digital elevation model dataset is from NASA 2007. Rimando and Knuepfer (2006) divided the VFS into two major fault systems: East Valley Fault System (EVFS) and WVFS. The WVFS is divided into four minor segments: The earthquake estimation of each segment is shown in Rodriguez-Taguig (segment I), Sucat-Binan (segment II), Figure 1. Binan-Sto. Domingo (segment III), and Pittland-Sungay (segment IV). The EVFS is divided into six segments: Several earthquake magnitude scenarios were considered Umiray (segment V), San Mateo-Rodriguez (segment with the termini of West Valley Fault and East Valley VI), Antipolo (segment VII), Angono (segment VIII), Fault (segments IV and X) as sources to produce a Binangonan (segment IX), and Talim Island (segment X) ground shaking model. The ground shaking or intensity (Figure 1). Pittland-Sungay segment (IV) of WVFS and is profoundly influenced by local geological characteristic Talim Island segment of EVFS are the closest faults in the or site coefficient. Different site coefficients will produce distance of about 20-30 km to this study area, and both different site responses to the earthquake, and this is based segments were recognized as active faults by Rimando on soil properties/geotechnical conditions underlying and Knuepfer (2006). buildings (Akin et al. 2011; Mohamed et al. 2013; Fabbrocino et al. 2015; Rusydy et al. 2017). Nelson and co-authors (2000) predicted that the possible magnitude of the earthquake that will be produced in this fault system is approximately 6.8-7.1 Mw. Otherwise, Rimando and Knuepfer (2006) calculated the estimation METHODOLOGY magnitude in this fault system based on empirical relationships among surface displacement, rupture length, GIS-based earthquake damage prediction is a method to and magnitude within a range of 6.1-7.5 Mw (empirical develop damage estimation including infrastructure and relationship based on length) and in the range of 7.4-7.7 human in different earthquake scenarios. In this study, Mw (empirical relationship based on displacement). the earthquake model in several scenarios is scrutinized

303 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB very well and refers to the previous neotectonic and and Rhoades (2005) developed an empirical model of paleoseismic studies of Nelson and co-authors (2000) and shaking attenuation in intensity for New Zealand. Atkinson Rimando and Knuepfer (2006). The ground shaking or and Wald (2007) created an online survey that was used intensity scenario is developed using new global shaking by USGS to determine intensity data. Different tectonic attenuation for shallow and near earthquake equation, settings have different shaking attenuations. The choice which was proposed by Allen and co-authors (2012). of the type of shaking attenuation applied in the study depends on the similarity of tectonic settings, geological characteristics, and the source of the earthquake. In this study, the researchers used the shaking attenuation that was developed by Allen and co- authors (2012) to produce earthquake intensity maps from different magnitude-source scenarios (see Figure 3). This attenuation model estimates intensities due to an earthquake with hypo central depths of less than approximately 20 km and magnitudes of 5-7.9 Mw. It Figure 2. The flowchart of earthquake damage prediction in several is therefore applicable to many earthquake generating earthquake scenarios. geologic structure in the Philippines. Called the Intensity Prediction Equations (IPEs; Allen et al. 2012), the attenuation model was developed using 13,077 Damage estimation of several types of buildings is earthquakes around the world since 1973. Of these calculated based on the fragility curve for different earthquakes, 1,613 are from Asian countries and include buildings. In the present, the Philippines has developed a historical earthquakes that occurred in the Philippines. fragility curve in a different type of buildings as a function Equation (1) is used to estimate the intensity of the of the intensity of the earthquakes in MMI; these fragility earthquake at a distance from the rupture zone. Equation curves were developed by Tingatinga and co-authors 2 was proposed by Cinicioglu and co-authors (2007) and (2013). The steps of this study are shown in Figure 2 and is used to compute the site amplification effect. the details of the methodology of this study – including data preparation, earthquake scenario, building damage (1) assessment analysis, and casualty estimation – will be explained in detail in this section. (2) Data Preparation GIS analysis for earthquake damage prediction needs several shape file data to be input into the GIS software. In the above equations, I stands for intensity in MMI, The tectonic map of Philippines obtained from Bautista M stands for magnitude of the earthquake in Mw, Rrup and Oike (2000) and the detail of Valley Fault System stands for the distance to the rupture zone in km, c is a gathered from Rimando and Knuepfer (2006) are digitized coefficient number (c0 = 3.950, c1 = 0.913, c2 = −1.107, using ArcGIS software and overlaid with Shuttle Radar and c3 = 0.813), S is the site correction, and F is the site Topography Mission (SRTM) map from NASA 2007, as amplification (Fv for a long period, Fa for a short period) shown in Figure 1. The location of active fault segments representing the amplification capacity of the local soil. and magnitude estimates are key parameters in developing Using equation (1), the researchers were able to generate the earthquake sources scenarios to be used in the the intensity map model of several earthquake scenarios modeling (see section 3.2). in different rupture zones and magnitude estimation (Figure 3). Rusydy and co-authors (2017) used equation Earthquake Scenario (1) to produce the intensity model in the Philippines. Seismology has been well developed, especially in the For the purpose of this study, the researchers assume the study of shaking attenuation in earthquake scenarios and segments closest to the site, segments IV and X, as the models. Shaking attenuation is an empirical approach loci of earthquakes along the West Valley fault and the to determine ground motion in PGA and intensity of East Valley Fault, respectively. Three scenarios involve the earthquake in MMI. Intensity values derived from segment IV of the West Valley fault as the assumed locus this approach are useful tools for the rapid and efficient of earthquakes with magnitudes 7.7 Mw (Scenario 1), communication of information on earthquake hazards and 7.2 Mw (Scenario 2), and 6.1 Mw (Scenario 3). Segment risks to the public and media (Allen et al. 2012). Dowrick X (Talim Island) fault is chosen as the source of the

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Figure 3. Intensity map (MMI) from several earthquake scenarios without any site correction: (a) intensity map of a 7.7 Mw magnitude earthquake from WMVF with Segment IV as the rupture zone, (b) 7.2 Mw magnitude earthquake from WMVF with Segment IV as the rupture zone, (c) 6.1 Mw magnitude earthquake from WMVF with Segment IV as the rupture zone, and (d) 6.5 Mw magnitude earthquake from EMVF with Segment X as the rupture zone. Digital elevation model dataset is from NASA 2007.

earthquake for Scenario IV with a magnitude of 6.5 Mw. Site Coefficient Analysis The magnitude estimates are based on segment lengths The intensity of earthquake produced from the earthquake and single-event scarp displacements determined by scenario model is intensity in the bedrock without any Rimando and Knuepfer (2006) (Figure 1). Segments IV consideration of the site coefficient or site amplification. The and X are geometric segments and are not necessarily Site coefficient, site characteristic, and shear modulus (Gmax) equivalent to rupture segments. In other words, the whole of the soil can be accurately determined from the shear wave of WMVF and the EMVF are the more likely sources of velocity (Vs). However, that parameter can also be estimated earthquakes. Rimando and Knuepfer (2006) clearly state from SPT, cone penetrating test, dilatometer test (DMT), and the distinction between these types of segment. This study pressuremeter test (PMT) (Akin et al. 2011). Because the Vs merely assumes that earthquakes shall occur along the data is not available in UPLB’s campus, this study used the segments that are closest to the site. Making the segments N-SPT and directly performed classification based on soil of the WVF and EVF that are closest to the site (Segment classification in ASCE/SEI 7-10 (2010). The amplification IV and X) as earthquake loci minimizes underestimation factor or the site coefficient (Fa for short periods and Fv for of intensity estimates. 1-second periods) represents the amplification capability of

305 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB the local soils with regard to uniform ground condition. The segments are assumed to be shallow crustal earthquakes values of Fa and Fv are from ASCE/SEI 7-10 (Minimum and therefore, will have tremendous impact in terms Design Loads for Buildings and Other Structures) (2010) of casualties and damage to buildings (Allen et al. while the PGA values (from 0.2 to 0.4) are from the PGA 2012). The resistance of buildings to ground shaking, maps of Torregosa and co-authors (2001) and Aguirre (2013). which varies from one area to another (and from one Table 1 shows the N-SPT data and amplification values for country to another), will affect the damage, injury, UPLB Campus’ soil. For this study, SE is considered for two and mortality ratios (Rusydy et al. 2017). To estimate reasons: first, the obtained borehole logs do not represent the damage ratio different type of building in the soil in the site since the depth of the boreholes does not the Philippines, Tingatinga and co-authors (2013) reach 30 m; second, the results will yield more conservative developed vulnerability curve or fragility curve based on results. However, the researchers used the N-SPT data as the ground shaking in MMI. They developed the fragility the assuming that the UPLB campus consists of pyroclastic curve using an analytic method (using nonlinear static deposit and assume almost homogeny. pushover), empirical method (post-earthquake visual surveys and damage report), heuristic method (based on expert opinion and judgment), and hybrid approach Earthquake Damage Prediction Analysis for the types of buildings of the Philippines. The type The UPLB is located at a distance of 16-24 km from of building in the research of Tingatinga and co-authors Segment X of EVFS and Segment IV of WVFS (Figure (2013) was typically similar to that proposed by FEMA 4), respectively. The earthquakes from these fault (2010). The fragility curve will show the damage ratio of the structures on a scale of 0 to 1 against the Table 1. Site coefficient (Fv and Fa) for five different soil ground shaking (Tingatinga et al. 2013). In this study, classifications based on ASCE/SEI 7-10 (2010) for PGA the researchers used the fragility curve designed by map 0.4 g. Tingatinga and co-authors (2013) in different types of Site Class SA SB SC SD SE buildings in UPLB’s campus, because this fragility curve N-SPT NA NA >50 15 to 50 <15 is developed for the buildings in the Philippines and is more comprehensive (Figure 5). Fa 0.80 1.00 1.20 1.40 1.72 Fv 0.80 1.00 1.40 1.60 2.40

Figure 4. (a) The type of building in UPLB’s campus and the location of the N-SPT borehole. (b) The N-SPT data in UPLB’s campus from Campus Planning and Development Office (CPDO) in Cantos (2015). Digital elevation model dataset is from National Mapping and Resource Information Authority (NAMRIA) of the Philippines.

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Figure 5. Fragility curve of four types of buildings in the study area as a function of intensity in MMI (Tingatinga et al. 2013).

An inventory and classification of UPLB buildings were equations used to calculate the casualty ratio; in this study, conducted by Valino (2014) and Arellano (2016). They the researchers used the equation (3) proposed by Hashemi listed 67 buildings in UPLB’s lower campus and classified and Alesheikh (2011). them into two types: (1) low-rise concrete moment frame Injured = Occupancy ratio x population x damage ratio x injury ratio. (3) (C1-L) and (2) medium-rise concrete moment frame (C1- M). The researchers updated the inventory building data In nighttime, the occupancy ratio is assumed as 1 for from 67 to 145 buildings from Valino (2014) and Arellano dormitories because all students are in the dormitory at (2016). This study found 145 buildings in UPLB’s lower this time and is considered as 0 for academic, services, campus and all those buildings were divided into three and administrative buildings. The researchers have census categories: (1) low-rise concrete moment frame (C1-L), data of the student population in the dormitories, but for (2) medium-rise concrete moment frame (C1-M), and academics, services, and administrative buildings, they (3) low-rise light wood frame (W1-L). The distribution were unable to access the data. The computation of the of the buildings in UPLB’s lower campus is shown in maximum occupant capacity method that was proposed Figure 4(a). To determine the damage ratio in a different by the NBCP (2004) can be used in consideration of peak type of building, the fragility curve in Figure 5 will be population condition, but this computation method had used, which depends on the intensity response of each uncertainties. To avoid these, it was assumed that the building in UPLB. population in all offices in the building as 100% and the casualty or injury estimate result will be in percent (%). The damage ratio of each building will yield a different casualty number because of the people trapped in the Currently, there are a few studies on the relationship collapsed or heavily damaged buildings (Hashemi & between the type of building and the number of mortalities Alesheikh 2011). The primary factor of casualty of an and injuries in the Philippines. However, there is an online earthquake is building collapse, taking into account report published by the Centers for Disease Control about 75% casualty (Coburn & Spence 2002). The and Prevention (CDC) (1990). The report examined estimation of building casualty from one earthquake to the casualty in several cities after the Luzon earthquake another is difficult. For one, the documented casualty in 1990, which was gathered by the Philippines Field data is inadequate. In most cases, available data show a Epidemiology Training Program (FETP). In city, wide range in the number of casualties. There are many the report noted that 28 buildings, 132 residences, 3 hotels, and 2 schools collapsed due to Luzon earthquake. FETP

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Table 2. The population of the students in a dormitory in UPLB. The RESULTS data was gathered from the Programmatic Environmental Performance Report and Management Plan (PEPRMP Earthquake Scenario for UPLB’s Lower Campus 2014) and Rusydy et al. (2017). Earthquake damage in UPLB campus were predicted No. Dormitories Population Source of Data under four different earthquake scenarios and at 1. Men's Residence Hall 646 PEPRMP 2014 two assumed periods of earthquake occurrence. The Women's Residence earthquake scenarios shown in Figure 3 did not consider 2. 444 PEPRMP 2014 Hall site coefficient. Using Equation (2), the researchers calculated the site coefficient for use as equation (1) input Veterinary Medicine 3. 376 Rusydy et al. (2017) to determine the surface intensity. According to ASCE/SEI Residence Hall 7-10 (2010), PGA is 0.4 and soil type will produce a site coefficient of 1.72. The calculated values for equations 4. New Dormitory 294 Rusydy et al. (2017) (1) and (2) are shown in Table 4.

5. ACCI 90 PEPRMP 2014 Scenarios I-III assume earthquake centered along the SEARCA Residence southernmost segment of WVF (Segment IV), while 6. 90 Rusydy et al. (2017) scenario IV assumed an earthquake event centered along the Hotel southernmost segment of EVF (Segment X). Scenario I is the worst-scenario for UPLB, with a magnitude of 7.7 Mw 7. ATI-NTC 126 Rusydy et al. (2017) event producing an intensity about 8.1. Though scenarios II and IV different earthquake magnitude is assumed, these 8. International House 124 PEPRMP 2014 generate similar intensity (i.e., 7.7 and 7.6 MMI) because of the shorter distance between segment IV and UPLB campus. The weakest intensity (6.7 MMI) happens in estimated the injury rate in Baguio City to be 703/100,000 scenario III, which assumes a magnitude of only 6.1 Mw. or 0.7% of the population and estimated the mortality rate as 252/100,000 or 0.252%. The FETP also collected the In this study, the site coefficient or amplification factor casualty data in , , and , but of 1.72 is considered similar in the entire building. the injury and mortality rates were less than in Baguio city. This consideration due to all the N-STP data shown the A worst-case scenario for injury and mortality ratios in similarity value and geologically, UPLB campus consist different types or buildings was developed by Hashemi of pyroclastic deposit and assume almost homogeny. GIS and Alesheikh (2011) in Tehran, Iran, which is more is used in superimposing the intensity map model (figure vulnerable to damage. Although the injury ratio is very 3) over the site coefficient map. high, it will be adjusted by the value of damage ratio and value of occupancy ratio. This injury ratio will be applied Damage Estimation and Distribution of UPLB to calculate the casualty ratio in this study as shown in Buildings Table 3, and this ratio will be the worst-case scenario of GIS analysis revealed that a magnitude of 7.7 Mw in building damage and the number of injuries. Scenario I will result in a building damage ratio in the range of 0.32-0.51 ratio or equal to 32-51% at UPLB’s Table 3. A worst-case scenario of injury ratio for different types of lower campus. Damage value of 51% influences low-rise buildings proposed by Hashemi and Alesheikh (2011). concrete moment frame (C1-L) buildings, 47% to low- No. Type of Building Injury Ratio rise light wood frame (W1-L) buildings, and 32% to 1. RC Building > 4 stories (C1-M) 0 medium-rise concrete moment frame (C1-M) buildings. 2. RC Building < 4 stories (C1-L) 0.2 In Scenario II, an earthquake with a magnitude of 7.2 Mw 3. Timber Frame Building (W1-L) 0.4 will cause building damage in the range of 20-41%, with C1-M, C1-L, and W1-L experiencing 21%, 39%, and 41%

Table 4. Earthquake scenarios and ground shaking response in the bedrock and surface for UPLB’s campus.

Earthquake Scenario Magnitude (M) Distance (Rrup) Intensity at Bedrock S Intensity at Surface I 7.7 Mw 24 Km 7.3 0.82 8.1 II 7.2 Mw 24 Km 6.9 0.82 7.7 III 6.1 Mw 24 Km 5.9 0.82 6.7 IV 6.5 Mw 16 Km 6.8 0.82 7.6

308 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB of damage. In Scenario III, 6.1 Mw earthquake will cause In loss assessment analysis, all parameters (population, 4-27% damage to UPLB’s buildings. C1-M, C1-L, and damage ratio, and intensity) are determined precisely. W1-L will incur 4%, 16%, and 27% of damage respectively. Without any detailed knowledge of how building respond The damage ratios for the building in scenario IV (18-39%) to ground shaking at different periods, these methods are almost similar to those in Scenario II. A Scenario IV could potentially add more uncertainty in loss estimate earthquake will cause 18% damage to C1-M buildings, (Allen et al. 2012). The injury estimation for the four 36% damage to C1-L buildings, and 39% damage to W1-L earthquake scenarios will be done for two different times buildings. The distribution of the damage to buildings in of the day (2 PM and 2 AM). FEMA (2010) suggested several earthquake scenarios is shown in Figure 6. using three different times (2 PM, 5 PM, and 2 AM), but this study lumped 2 PM and 5 PM together, as the university will still have activities until 5 PM. Human Injury Estimation at UPLB’s Campus

Figure 6. Distribution of damage ratio of UPLB’s buildings in several earthquake scenarios: (a) Scenario I, (b) Scenario II, (c) Scenario III, and (d) Scenario IV. Digital elevation model dataset is from the National Mapping and Resource Information Authority (NAMRIA) of the Philippines.

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Injury Prediction in Daytime (2 PM) In Scenario II, 7.8% are predicted to be injured in C1-L Daytime at 2 PM is a busy time during the day, and at this buildings, 0% in C1-M buildings, and 16.4% in W1-L specific time, many students are in their classes and the buildings. Scenario III will cause less injury; in this administrative personnel are in their offices. GIS analysis scenario, only 3.2% will be injured in C1-L buildings, using an attribute table is applied to calculate the number 0% in C1-M buildings, and 10.8% in W1-L buildings. In of injuries using formula (3) in this time scenario. The Scenario IV, the intensity of the earthquake is predicted result shown in Figure 7 concludes that if the students to be 7.6 and this will injure 7.2% in C1-L buildings, 0% and staff have no quick response and adequate access in C1-M buildings, and 15.6% in W1-L buildings. This to an evacuation zone, this condition will injure 9.8% of is a relatively high percentage of injury as the students the students or officers in C1-L buildings, 0% in C1-M and the personnel of UPLB have no adequate capacity buildings, and 18.8% in W1-L buildings in Scenario I to evacuate the buildings. To minimize vulnerability, earthquake. the authorities of UPLB have to increase the capacity

Figure 7. Percentage of injury in each building; an earthquake occurs at 2 PM in several scenarios: (a) Scenario I, (b) Scenario II, (c) Scenario III, and (d) Scenario IV. Digital elevation model dataset is from the National Mapping and Resource Information Authority (NAMRIA) of the Philippines.

310 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB of the community (students and staff) by building and and 0.75 for the UPLB hospital. For the University Police developing mitigation programs such as development of headquarters and the UPLB hospital, population was evacuation plans, conducting of earthquake drills, and estimated using the maximum occupant capacity method strengthening of building. that was proposed by the NBCP (2004). The number of injuries in the UPLB community for a nighttime event is shown in Figure 8. Loss Assessment in Nighttime (2 AM) In a nighttime event of an earthquake event, all students There are eight residences that accommodate students and are assumed to be in the dormitories of UPLB and the guests in UPLB’s campus. In all earthquake scenarios, the offices are empty. For this scenario, this study was able to Men’s Residence Hall is highly vulnerable. It is estimated compute the number of injuries from the population data that 66 students will be injured in Scenario I, 50 students shown in Table 2. The nighttime occupancy ratio is 1 for in Scenario II, 21 students in Scenario III, and 47 students all residences, 0.6 for the University Police headquarters, in Scenario IV. The SEARCA Residence Hotel, which

Figure 8. The number of injuries in each building; an earthquake occurs at 2 AM in several scenarios: (a) Scenario I, (b) Scenario II, (c) Scenario III, and (d) Scenario IV. Digital elevation model dataset is from the National Mapping and Resource Information Authority (NAMRIA) of the Philippines.

311 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB accommodates 90 guests, and the New Dormitory are the crustal historical earthquakes in the Philippines. The most safer places to stay. In the UPLB hospital, the maximum memorable and destructive shallow crustal earthquake is number of medical patients, doctors, staff, and relatives (Figure 9). of patients is predicted to be 100 people, and at nighttime, this population is expected to decrease. The predicted The Luzon earthquake occurred on 16 Jul 1990 in the number of injured people is five in scenario I, four in central part of Luzon Island, Philippines. This earthquake scenario II, two in scenario III, and four in scenario IV. had a magnitude (Ms) of 7.8 and occurred along a shallow crustal active fault. This earthquake had a left-lateral strike-slip source mechanism. The ground rupture had a Earthquake Model Validation from Historical length of 120 km. At least 1,283 people were killed due Earthquakes to the collapse of multistory buildings (Wieczorek et al. The accuracy of the earthquake model is the main factor 1992; Punongbayan et al. (2001). According to Kojima for earthquake damage prediction and it should be and co-authors (1992) and Ohmachi and Nakamura validated with historical earthquakes in the region. The (1992), the major cause of the damage was associated with earthquake model is very sensitive to the earthquake ground shaking, liquefaction, and poor building quality. magnitude and the shaking attenuation equation and it Kojima and co-authors (1992) recorded that different cities has to be validated. The Philippines hosts numerous large- respond with different intensities of the ground shaking magnitude shallow crustal earthquakes. The IPEs equation and this depends on the site coefficient and distance to the proposed by Allen and co-authors (2012) was used in this rupture zone. Kojima and co-authors (1992) investigated study in developing earthquake scenarios. Because of the Rossi-Forel intensity scale and noted that Baguio city this condition, one has to validate these IPEs by shallow

Figure 9. Rupture zone of 1990 Luzon earthquake and Intensity map produced using IPEs. The rupture zone is after Punongbayan and co-authors (2001). Digital elevation model dataset is from NASA 2007.

312 Philippine Journal of Science Rusydy et al.: GIS-Based Earthquake Vol. 147 No. 2, June 2018 Damage Prediction at UPLB experienced VIII-IX intensity, and Dagupan city hand, intensity VI of the Rossi-Forel scale is similar to experienced VIII intensity, and Cabanatuan and Tarlac VI MMI. It is characterized by ringing of bells, stopping experienced VI-VIII intensity. of clocks, visible agitation of shrubs and trees, moving of some heavy furniture, a few instances of fallen plaster, and According to Ohmachi and Nakamura (1992), Baguio City slight damage to very old or poorly built structures. The has an amplification factor (Fv) in the range of 3-7, with mean square error between the calculated intensity and an average of 5. This amplification factor is derived from the actual intensity using IPEs in the Philippines is 0.35. microtremor measurement around Baguio City. In Dagupan City, Ohmachi and Nakamura (1992) found the amplification In term of damage, the 16 Jul 1990 Luzon Earthquake to be in the range of 1-4, with an average of 3. In Agoo caused many damaged building along the city close to the City, they measured 18 points of microtremor and from earthquake source. The damage ratio yield in this study the measurement, they found that the amplification factor refers to the fragility curve developed by Tingatinga and in Agoo city was in the range of 2-8, with an average of 4. co-authors (2013). The researchers validated their model intensity and the damage ratio model with the actual data Table 5 shows the comparison between the calculated of Luzon earthquake. The damage building information of MMI using IPEs and the intensities obtained by Kojima 1990 Luzon earthquake has been archived well. Booth and and co-authors (1992). The intensities obtained by Kojima co-authors (1991) has reported the visual damage of building and co-authors (1992) are given in terms of the Rossi- (photos) each effected zone. These photos used to classify Forel intensity scale and are converted as MMI intensity the structural damage of building. The visual classification units. The Rossi-Forel intensity scale is the first seismic of structural damage refers to Okada and Takai (2000). The intensity scale and is still used in the Philippines. This result of damage ratio validation is shown in Table 6. scale ranges from I (microseismic shock) to X (shock of extreme intensity), while the MMI intensity scale is from Table 6 shows some similarity between this study’s I (not felt) to XII (total destruction). Intensity IX of the damage model and actual damage model. The actual Rossi-Forel scale will cause partial or total destruction damage model presented in range due to the variation of of some buildings, fissures in the ground, landslides, and damage in a particular city. Most of the cities experience rock falls. It is equal to intensity X of MMI where some heavy damage (0.4-0.6) to major damage (0.6-1.0) and well-built wooden buildings and most masonry and frame only in Dagupan City the building experienced moderate structures with foundations were destroyed. On the other (0.2-0.4) to heavy damage (0.4-0.6).

Table 5. The earthquake intensity comparison between IPEs calculation and actual intensity in the Rossi-Forel scale. Actual Intensity at Surface Intensity at Intensity at Distance to (Kojima et al. 1992) City Bedrock Amplif. (Fv) S Surface Rupture (Rrup) Rossi-Forel (IPEs) In MMI (IPEs) MMI scale Baguio 39 Km 6.9 7 2.9 9.8 8-9 8-11 Cabanatuan 25 Km 7.4 1.5 0.6 8.0 6-8 6-9 Dagupan 62 Km 6.5 4 2.1 8.6 8 8-9 Agoo 58 Km 6.5 4 2.1 8.6 8 8-9

Table 6. The damage comparison between this study’s damage model and actual damage from the 16 Jul 1990 Luzon Earthquake. Actual Intensity Damage Validation Intensity at at Surface Our damage Model Actual damage City Surface MMI In MMI (IPEs) (Kojima et al. C1-L C1-M W1-L C1-L C1-M W1-L 1992) Baguio 9.8 8–11 0.65 0.67 0.7 0.4-0.6 0.4-1.0 0.4-0.6 Cabanatuan 8.0 6–9 0.40 0.42 0.45 0.4-0.8 0.4-0.8 - Dagupan 8.6 8–9 0.49 0.51 0.54 0.2-0.6 0.4-0.6 - Agoo 8.6 8–9 0.49 0.51 0.54 0.4-0.6 0.4-0.6 -

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CONCLUSION Engineering, College Of Engineering And Agro- Industrial Technology, Laguna: University Of The Overall, this study successfully built several earthquake Philippines – Los Baños. 105p. scenarios and determined the worst scenario that could affect UPLB’s community during daytime and nighttime AKIN MK, STEVEN LK, TAMER T. 2011. Empirical of an earthquake event. An earthquake shaking model correlations of shear wave velocity (Vs) and penetration in MMI was developed using global applicable macro resistance (SPT-N) for different soils in an earthquake- seismic IPEs, which were designed by Allen and co- prone area (Erbaa-Turkey). Engineering Geology authors (2012). Even though it is a global shaking 119(1-2): 1-17. attenuation, this equation was built for a shallow crustal ALLEN TI, WALD DJ, WORDEN CB. 2012. Intensity earthquake or inland earthquake. In this study, the attenuation for active crustal regions. J Seismol 16(3): earthquake model produced from the VFS is a shallow 409-433. crustal source of earthquakes. This shaking attenuation shows the differences of the ground shaking in the bedrock ARELLANO CRP. 2016. Earthquake Loss Estimation in UPLB’s campus from 5.9 to 7.3 MMI and 6.7 to 8.1 For Buildings Of UPLB. [Unpublished Undergraduate MMI on the surface. In this study the UPLB campus Thesis], Department Of Civil Engineering, College Of buildings were classified into three types: C1-L, C1- Engineering And Agro-Industrial Technology, Laguna: M, and W1-L. Different types of building and ground University Of The Philippines – Los Baños. 21p. shaking will result in different damage ratios. In the ASCE/SEI 7-10. 2010. Minimum Design Loads for worst scenario (Scenario I), 126 of C1-L buildings have Buildings and Other Structures. Virginia: American 51% of damage. To avoid this condition, the authorities Society of Civil Engineers. of UPLB have to conduct retrofitting of buildings. Validation from historical earthquakes, the IPEs which ATKINSON GM, WALD DJ. 2007. "Did You Feel developed by Allen and co-authors (2012) applicable to It?" intensity data: a surprisingly good measure of be implemented in the Philippines. The IPEs also capable earthquake ground motion. Seism Res Lett 78(3): to determine the shallow crustal earthquake model and the 362-368. mean square error is 0.35. BAUTISTA MLP, OIKE K. 2000. Estimation of the In the future, a number of studies can be done to improve magnitudes and epicenters of Philippine historical the earthquake damage prediction in UPLB and in the earthquakes. Tectonophysics 317(1-2): 137-169. entire Philippines. The ground shaking response by a BESANA GM, ANDO M. 2005. The Central Philippine building depends on the site coefficient of soil beneath Fault Zone: Location of Great Earthquakes, Slow the building. The site coefficient plays a crucial role in Events and Creep Activity. Earth Planets Space 57(10): the ground shaking intensity and has to be determined 987-994. carefully. Thus, to improve the results of this study, studies of the site coefficient from shear wave velocity BOOTH ED, CHANDLER AM, WONG PKC, COBURN and microtremor data are suggested. AW. 1991. The Luzon, Philippines Earthquake Of 16 July 1990, A Field Report EEFIT. London: Earthquake Engineering Field Investigation Team Institution of Structural Engineer. 15p. ACKNOWLEDGMENTS CANTOS NHC. 2015. Seismic Risk Assessment The authors are so much grateful to the research assistant Of Uplb Buildings. [Unpublished Undergraduate (RA) of UPLB, for the technical support during staying Thesis], Department Of Civil Engineering, College Of at the UPLB. This study would not have been possible Engineering And Agro-Industrial Technology, Laguna: without the supporting funding from START International University Of The Philippines – Los Baños. 50p. Inc., in Pan-Asia Risk Reduction (PARR) Fellowship [CDC] Centers for Disease Control and Prevention. Program 2016-2017. 1990. International notes earthquake disaster - Luzon, Philippines. Retrieved from http://www.cdc.gov/ mmwr/preview/mmwrhtml/00001734.htm on 31 Aug 2016. REFERENCES CINICIOGLU SF, BOZBEY I, OZTOPRAK S, AGUIRRE JJC. 2013. Probabilistic Seismic Hazard KELESOGLU MK. 2007. An integrated earthquake Analysis of Laguna, Philippines. [Unpublished damage assessment methodology and its application for Undergraduate Thesis]. Department Of Civil two districts in Istanbul, Turkey. Engineering Geology

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