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Pervasive Knowledge and Collective Intelligence on Web and Social Media. Second EAI International Conference, PerSOM 2023, Hyderabad, India, November 24–25, 2023, Proceedings

Research Article

Effect of Global Warming on Glaciers, Rivers and Water Towers

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-66044-3_20,
        author={Sushruth Samson and Srinivas Patnaik and K. Rajesh Kannan and T. Prathima and B. R. Sreedhar},
        title={Effect of Global Warming on Glaciers, Rivers and Water Towers},
        proceedings={Pervasive Knowledge and Collective Intelligence on Web and Social Media. Second EAI International Conference, PerSOM 2023, Hyderabad, India, November 24--25, 2023, Proceedings},
        proceedings_a={PERSOM},
        year={2024},
        month={8},
        keywords={Glacier and river analysis Water Towers Machine Learning algorithms Global Water Resources},
        doi={10.1007/978-3-031-66044-3_20}
    }
    
  • Sushruth Samson
    Srinivas Patnaik
    K. Rajesh Kannan
    T. Prathima
    B. R. Sreedhar
    Year: 2024
    Effect of Global Warming on Glaciers, Rivers and Water Towers
    PERSOM
    Springer
    DOI: 10.1007/978-3-031-66044-3_20
Sushruth Samson1, Srinivas Patnaik1, K. Rajesh Kannan2,*, T. Prathima2, B. R. Sreedhar3
  • 1: Department of Artificial Intelligence and Data Science
  • 2: Department of Information Technology
  • 3: Department of Mathematics
*Contact email: rajeshkannan_it@cbit.ac.in

Abstract

This study employs machine learning algorithms to comprehensively assess the impact of global warming on glaciers, rivers, and water towers. By analyzing diverse datasets encompassing remote sensing, climate records, and hydrological data, the research aims to elucidate the intricate relationships between temperature changes and the behavior of these vital components of the Earth’s hydrological cycle. The outcomes of this investigation are poised to enhance our understanding of the far-reaching consequences of climate change on freshwater resources and facilitate informed decision-making for sustainable environmental management. The study uses several machine-learning algorithms to investigate worldwide glaciers, rivers, and water towers. The study sheds light on these crucial natural resources existing and future health, alerting people to the critical need for long-term management and conservation measures.

Keywords
Glacier and river analysis Water Towers Machine Learning algorithms Global Water Resources
Published
2024-08-13
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-66044-3_20
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