Causes and Mechanisms of Flooding in Hawaiʻi

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dc.contributor.advisor Tsang, Yinphan
dc.contributor.author Huang, Yu-Fen
dc.contributor.department Natural Resources and Environmental Management
dc.date.accessioned 2024-02-26T20:13:54Z
dc.date.issued 2023
dc.description.degree Ph.D.
dc.embargo.liftdate 2026-02-23
dc.identifier.uri https://hdl.handle.net/10125/107880
dc.subject Hydrologic sciences
dc.subject Environmental science
dc.subject Atmospheric sciences
dc.subject extreme events
dc.subject flooding
dc.subject geostatistics
dc.subject hydrological model
dc.subject rainfall-runoff
dc.subject sensitivity analysis
dc.title Causes and Mechanisms of Flooding in Hawaiʻi
dc.type Thesis
dcterms.abstract Flooding often results from intense and localized nature of extreme rainfall events and poses a significant threat to communities of Hawaiʻi. This dissertation research deciphers the intricate relationship between extreme weather events and flooding within the unique context of tropical islands by advancing the rainfall dataset with best available gauge and radar data and investigating complex interactions between rainfall event characteristics and streamflow responses. First, I investigated the relationships temporally and spatially between the trends of annual maximum daily rainfall and peak streamflow. The results showed that, in general, the Hawaiian Islands experienced weaker extreme rainfall (67% of rain gauges) and streamflow (61% of stream gauges). The findings also emphasized that the annual peak streamflow cannot be fully attributed to the trends of annual maximum rainfall of one gauge per watershed. In addition, the timing of extreme rainfall and streamflow occurred earlier in the wet season during the El Niño years. Second, the high resolution (hourly, 250-m) rainfall dataset on Oʻahu has been produced by merging radar and gauge rainfall. Moreover, the advantages of the merging method, Kriging with external drift (KED) has been adopted and evaluated with storm types (i.e., Kona lows, tropical cyclones, cold fronts, and upper-level trough) and rainfall structures (i.e., stratiform or convective rainfall) within 17 severe storm events. The study highlighted that KED reduced the error from radar rainfall with an advantage on estimates of convective rainfall during severe storms. Lastly, building based on the improved rainfall datasets, the research expanded on the critical role of rainfall characteristics in influencing the magnitude of peak flow. I reconfigured WRF-Hydro, a physically-based and fully distributed hydrological model with 250m resolution, to simulate high flow events. I first evaluated the rainfall event characteristics on streamflow responses, and then I experimented the responses with designed rainfall with different spatial properties. The results underscored the significance of rainfall amount, intensity, and rainfall spatial characteristics effects on the event peak flow. In particular, rainfall spatial heterogeneity increased uncertainties of peak flow timing related to peak rainfall in small tropical watersheds. This extensive research represents a significant step forward in the quest to enhance our understanding of the complex hydrological processes and flooding dynamics in tropical island regions and provides valuable groundwork for improving flood study and forecasts that associated risks in Hawaiʻi and similar tropical island environments.
dcterms.extent 172 pages
dcterms.language en
dcterms.publisher University of Hawai'i at Manoa
dcterms.rights All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.
dcterms.type Text
local.identifier.alturi http://dissertations.umi.com/hawii:12027
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Ph.D. - Natural Resources and Environmental Management