Skip to content
Reading time: 2 minutes
Trista McKenzie, Brytne Okuhata and Diamond Tachera
From left, Trista McKenzie, Brytne Okuhata and Diamond Tachera

Research on Hawaiʻi’s freshwater resources by University of Hawaiʻi at Mānoa graduate students was featured at a recent international conference. The students and research assistants with Hawaiʻi EPSCoR‘s ʻIke Wai project presented their work at this year’s Goldschmidt 2020 conference.

ʻIke Wai from the Hawaiian words for “knowledge” and “water,” respectively, is a $20-million project to ensure Hawaiʻi’s future water security through an integrated program of research, education, community engagement and decision support.

The annual international scientific conference organized by the Geochemical Society and the European Association of Geochemistry was held virtually in June and covered several themes in geochemistry to include scientific observations in Hawaiʻi and Oceania related to climate change, coral reefs and water resources.

Three PhD candidates from the School of Ocean and Earth Science and Technology’s Department of Earth Sciences discussed their work through the ʻIke Wai project, funded by the National Science Foundation to conduct research to understand Hawaiʻi’s aquifers.

Trista McKenzie, a Hawaiʻi Data Science Institute Data Science Fellow alumni, presented a deep learning model that accurately predicts submarine groundwater discharge off of Hawaiʻi Island’s Kona coast and discussed the benefits of pairing field-based measurements with big-data-driven approaches.

Brytne Okuhata discussed a multitracer approach using radiocarbon and chlorofluorocarbons to determine fresh groundwater ages on the west side of Hawaiʻi Island. The data will be used to understand the aquifer system and to enhance their water model’s predictive capabilities allowing for better management of groundwater resources.

Diamond Tachera discussed groundwater geochemistry results from the Hualālai aquifer, located on the western side of Hawaiʻi Island. Tachera discussed how a data-driven method for a better understanding of subsurface properties is needed.

Data is currently available from the ʻIke Wai project with more data added regularly.

(NSF Award OIA #1557349)

Back To Top