Integrating Machine Learning, Land Cover, and Hydrological Modeling to Contribute Parameters for Climate Impacts on Water Resource Management
Joonghyeok Heo,
Jeongho Lee,
Yunjung Hyun
et al.
Abstract:The purpose of this study is to establish basic policies for managing the impacts of climate change on water resources using the integration of machine learning and land cover modeling. We predicted future changes in land cover within the water management and assessed its vulnerability to climate change. After confirming this vulnerability, we considered measures to improve climate resilience and presented future water resource parameters. We reviewed the finances available to promote climate projects, noting … Show more
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