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Supporting data for publication (Groundwater level forecasting using machine learning: A case study of the Baekje weir in Four Major Rivers Restoration Project, South Korea)
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| Type: | Resource | |
| Storage: | The size of this resource is 13.1 MB | |
| Created: | Mar 30, 2024 at 1:07 a.m. | |
| Last updated: | Apr 01, 2024 at 3:57 p.m. (Metadata update) | |
| Published date: | Apr 01, 2024 at 3:57 p.m. | |
| DOI: | 10.4211/hs.22b387e032844bb6ad175da22442a7e7 | |
| Citation: | See how to cite this resource | |
| Content types: | Single File Content |
| Sharing Status: | Published |
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| Views: | 340 |
| Downloads: | 19 |
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| Comments: | 1 comment |
Abstract
Understanding the impact of human-made structures on groundwater levels is crucial, with structures like dams or weirs presenting both challenges and opportunities for study. The Baekje weir in South Korea offers an unique case as it has undergone full gate openings, a condition not typically observed in weirs and reservoirs, providing a unique opportunity to simulate conditions resembling weir removal. The primary objectives include investigating groundwater level fluctuations influenced by various weir operations, proximity to the weir, and seasonal variations. The study employs observed data to simulate conditions both with and without the weir, encompassing scenarios of full gate opening. This research illuminates the intricate interplay between weir manipulations and groundwater levels, offering practical knowledge for the management of water resources in comparable hydrogeological environments. This research is part of the submission WaterResourcesResearch2022WR032779RRRR to the journal Water Resources Research, aiming to deepen our understanding of how such structures impact water resources.
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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