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<p>The Himalayan region is known for its dynamic tectonic activity, presenting significant challenges for geoscientists in detecting and understanding the active tectonic plates behavior. This study proposes the development of a generalized AI model to calculate key geomorphological parameters within the glacial-fluid river basins of the Himalayas. The motivation stems from the critical need to connect artificial intelligence with machine learning techniques to enhance the understanding of tectonic processes in this complex geological setting by analyzing geomorphological data acquired from a research paper Bali et al. (2012)&#xa0;and other sources. This research specifically focuses on the Pindari glacio-fluvial basin in and its sub basins, a region characterized by rugged terrain and high tectonic activity. The drainage network and geomorphological attributes of this basin provide a suitable testbed for modeling due to its varied elevation, complex hydrology, and well-documented tectonic features. Unlike traditional methods that rely on mathematical approaches, such as the morphological law of Horton’s and Strahler’s stream order laws, our approach focuses on developing a data-driven model capable of automatically extracting essential parameters including area, perimeter, length, and other metrics without manual calculations. By employing AI algorithms, the process of geomorphological analysis is streamlined, enabling researchers to efficiently identify and quantify the characteristics of glacial-fluid river basins associated with active tectonic activity. This innovative approach promises to revolutionize the field by providing a more accurate and comprehensive understanding of geomorphic features indicative of tectonic plate movement in the Himalayan region. This research is anticipated to significantly advance geoscience, with applications in natural hazard assessment, resource management, and infrastructure planning in tectonically active regions. It ultimately aims to deepen the understanding of the interplay between tectonic processes and geomorphological features in the Himalayas, enabling more informed decision-making and enhanced risk mitigation strategies.</p> Graphical Abstract <p></p>

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Quantifying Tectonic Influence on Himalayan Glacio-Fluvial Systems: Integrating Morphological Analysis and AI Modeling

  • 期刊论文

  • 发表日期：

    2025年6月18日

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  • Ruchira Ghosh,
  • Goutami Das,
  • Harshada Patil,
  • S. Umamaheswari,
  • P. Jayashri

摘要

The Himalayan region is known for its dynamic tectonic activity, presenting significant challenges for geoscientists in detecting and understanding the active tectonic plates behavior. This study proposes the development of a generalized AI model to calculate key geomorphological parameters within the glacial-fluid river basins of the Himalayas. The motivation stems from the critical need to connect artificial intelligence with machine learning techniques to enhance the understanding of tectonic processes in this complex geological setting by analyzing geomorphological data acquired from a research paper Bali et al. (2012) and other sources. This research specifically focuses on the Pindari glacio-fluvial basin in and its sub basins, a region characterized by rugged terrain and high tectonic activity. The drainage network and geomorphological attributes of this basin provide a suitable testbed for modeling due to its varied elevation, complex hydrology, and well-documented tectonic features. Unlike traditional methods that rely on mathematical approaches, such as the morphological law of Horton’s and Strahler’s stream order laws, our approach focuses on developing a data-driven model capable of automatically extracting essential parameters including area, perimeter, length, and other metrics without manual calculations. By employing AI algorithms, the process of geomorphological analysis is streamlined, enabling researchers to efficiently identify and quantify the characteristics of glacial-fluid river basins associated with active tectonic activity. This innovative approach promises to revolutionize the field by providing a more accurate and comprehensive understanding of geomorphic features indicative of tectonic plate movement in the Himalayan region. This research is anticipated to significantly advance geoscience, with applications in natural hazard assessment, resource management, and infrastructure planning in tectonically active regions. It ultimately aims to deepen the understanding of the interplay between tectonic processes and geomorphological features in the Himalayas, enabling more informed decision-making and enhanced risk mitigation strategies.

Graphical Abstract