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Asia-Pacific Network for Global Change Research

Asia-Pacific Network for Global Change Research

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Peer-reviewed publication

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

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.