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Advanced utilization of multi-learning algorithm: ensemble super learner to map groundwater potential for potable mineral water

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Lee, Sanghoon; Kaown, Dugin; Koh, Eun-Hee; Lee, Hye-Lim; Ko, Kyung-Seok; Lee, Kang-Kun

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Geocarto International Centre
Geocarto International
© 2022 Informa UK Limited, trading as Taylor & Francis Group.Although mapping the groundwater quality is crucial for people who require groundwater with strict quality standards, the ability to take intensive measurements has been restricted by a lack of groundwater accessibility. Thus, this study aimed to estimate and map the suitability of groundwater quality for use as potable mineral water. We attempted a novel approach by targeting comprehensive qualities for a specific groundwater use and by adopting a super learner that combines multiple different learning algorithms. The super learner generated a groundwater potential map indicating a zone with a high potential for mineral water and it outperformed the base learners by 21%–74%. Estimation results designated appropriate groundwater development locations for mineral water use, and assessment of predictors determined favorable environments. Consequently, the proposed approach presented a possible method for finding groundwater with the required quality for its optimal usage. Furthermore, it provided the possibility of worldwide application.
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