2021 – Application of joint probability design flood estimation in the Philippines and potential benefits in data sparse regions of Australia

David Stephens, Phillip Jordan, Peter Hill, Tim Craig, James Woolley and Bill Hakin

As part of the design of a proposed new hydropower dam (the Alimit HPP), on the island of Luzon in the Philippines, design flood estimates have been prepared using a RORB Monte Carlo approach for events up to and including the Probable Maximum Flood. Compared with Australia, the Philippines is a relatively data sparse environment, with limited rainfall gauge records and even fewer streamflow gauging stations. As such, considerable effort was required to derive design rainfall inputs for Monte Carlo simulation, including rainfall depths as well as temporal and spatial patterns.

This project made use of a number of remotely sensed data sets, including 20 years of global half hourly gridded rainfall data from NASA and global gridded estimates of rainfall intensity-frequency-duration. As part of the project, these data sets were benchmarked against local records from Luzon as well as selected Australian data sets.

This paper sets out the process used to determine design flood estimates in the Philippines, as well as summarising the usefulness of these new data sets for potential application in data sparse regions of Australia.

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