Date of Publication


Document Type

Master's Thesis

Degree Name

Master of Science in Civil Engineering

Subject Categories

Civil Engineering


Gokongwei College of Engineering


Civil Engineering

Thesis Advisor

Renan T. Tanhueco

Defense Panel Chair

Mario P. De Leon

Defense Panel Member

Lessandro Estelito O. Garciano
Erica Elice S. Uy


There are currently no flood hazard maps available for Gumaca, and the lack of knowledge on the hazard would reduce the preparedness of the community. Typhoon Lanie/Maring had affected many people, due to a lack of pre-emptive evacuation and lack of warnings and evacuation preparedness by the local government. The availability of LiDAR-based DEMs and the continuous improvement of open-sourced models, such as HEC-HMS and HEC-RAS provides an opportunity to carry out flood hazard assessments and obtain useful insights on flood behavior. This study aims to assess the flood risk according to the flood depth and velocity criteria. A rainfall-runoff analysis and 2D flow analysis were performed to assess the flood hazard in Gumaca for a 5-, 10-, 25-, 50-, and 100-year return period. The flood conditions were mapped according to flood depth, velocity, and the depth*velocity parameters. The number of at-risk structures were estimated by counting the number of elements within the overlayed flood depth and feature extracted layers. The number of at-risk people was estimated by multiplying the average number of people per household per affected barangay.

Using the classification of D*V provided by the Australian Institute for Disaster Resilience (AIDR) (2017), it was found that majority of the structures within the floodplain are not vulnerable to failure, however, less robust buildings vi may be vulnerable to damages. The flood conditions for a 5-year return period are generally safe for people. The conditions for a 10- and 25-year return period would be unsafe for children and elderly, while conditions for return periods greater than 25 would be unsafe for all people. The D*V map gives a more detailed visualization of flood behavior since it considers two parameters. The D*V classification of AIDR acts as a simple method to determine hazardous areas, since it describes the flood behavior two-dimensionally and is a parameter that is available for mapping in software such as HEC-RAS. It was concluded that the utilization of the D*V parameter would provide useful insights on flood behavior and in identifying hazardous areas

Abstract Format






Physical Description

119 leaves, color illustrations


Floods--Philippines--Quezon Province; Flood forecasting--Philippines--Quezon Province

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