Using a Deep Learning Framework to Forecast Reservoir Water Availability in India
Kuzma, Samantha, Kruitwagen, Lucas, Arderne, Christopher, Goswami, Sahana, Goyal, Anupriya, Lees, Thomas, Thalheimer, Lisa and Basak, Samrat (2023). Using a Deep Learning Framework to Forecast Reservoir Water Availability in India. World Resources Institute.
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Sub-type Technical report Author Kuzma, Samantha
Kruitwagen, Lucas
Arderne, Christopher
Goswami, Sahana
Goyal, Anupriya
Lees, Thomas
Thalheimer, Lisa
Basak, SamratTitle Using a Deep Learning Framework to Forecast Reservoir Water Availability in India Publication Date 2023-06-29 Place of Publication Washington D.C. Publisher World Resources Institute Pages 24 Language eng Abstract This paper introduces a machine learning-based model to forecast reservoir water volumes in India. In areas with high water stress, having access to timely information on forecasted water availability could help decision-makers avoid the risk of acute water-driven power outages and advocate for long-term, water-prudent policies and management. This forecast can flag when drought-like conditions threaten water supply, but should not be used to inform reservoir management operations. UNBIS Thesaurus INDIA Keyword Forecasting
Machine learning
Water securityCopyright Holder The Authors Copyright Year 2023 Copyright type Creative commons DOI 10.46830/writn.21.00088 -
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