Vol. 12 No. 04 (2026)

Articles

பனிப்பாறை சரிவால் ஏற்படும் திடீர் வெள்ளங்களுக்கு AI அடிப்படையிலான பல்பேரிடர் முன்னெச்சரிக்கை கட்டமைப்பு: 2026 நேபாள பேரிடரை மையமாகக் கொண்ட Remote Sensing மற்றும் Digital Twin ஆய்வு

AI-Based Multi-Hazard Early Warning Framework for Glacier Collapse–Triggered Flash Floods: A Remote Sensing and Digital Twin Study of the 2026 Nepal Disaster

Dr.C.Sakthimurugan1, Dr D Mahalingam2, K Santhanam3, Dr.V.C.Srinivasan4

  1. Assistant professor in Tamil, Nandha Arts and Science College (Autonomous), Erode -638052
  2. Head, Department of library & information science, Nandha Arts And Science College.(Autonomous) Erode-52
  3. Asst.Professor, Nandha College of Education, Erode-52
  4. Administrative Officer, Nandha Arts and Science College (Autonomous), Erode. 
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Abstract

Exposing the technical limits of existing early warning systems after a devastating August 2026 flash flood in Nepal's Trisuli–Bhote Koshi basin, this paper proposes a multi-hazard early warning framework to address rising Glacial Lake Outburst Floods (GLOFs) and avalanche-induced flash floods in the climate-sensitive Himalayas. The framework combines risk prediction, GIS risk mapping, and early warning layers by using Transformer/LSTM deep learning models to integrate six distinct data sources: satellite imagery, glacier temperature, snowmelt rate, rainfall, seismic signals, and river water levels. Additionally, it incorporates Digital Twin technology for real-time basin modeling and "what-if" simulations, demonstrating through the 2026 Nepal disaster case study how lead times can be improved across South Asian Himalayan regions and similar high-risk zones.

Keywords

  • Glacial Lake Outburst Flood (GLOF)
  • Artificial Intelligence
  • Transformer
  • LSTM
  • Remote Sensing
  • Digital Twin
  • GIS Risk Map

How to cite

Dr.C.Sakthimurugan, Dr D Mahalingam, K Santhanam, & Dr.V.C.Srinivasan (2026). பனிப்பாறை சரிவால் ஏற்படும் திடீர் வெள்ளங்களுக்கு AI அடிப்படையிலான பல்பேரிடர் முன்னெச்சரிக்கை கட்டமைப்பு: 2026 நேபாள பேரிடரை மையமாகக் கொண்ட Remote Sensing மற்றும் Digital Twin ஆய்வு: AI-Based Multi-Hazard Early Warning Framework for Glacier Collapse–Triggered Flash Floods: A Remote Sensing and Digital Twin Study of the 2026 Nepal Disaster. Tamilmanam International Research Journal of Tamil Studies, 12(04), 176-197. https://doi.org/10.63300/tm12042026.15

References 15

  1. [1.] Adhikari, P., Regmi, S. R., & Shrestha, H. R. (2025). Targeted semantic segmentation of Himalayan glacial lakes using time-series SAR: Towards automated GLOF early warning. arXiv. https://doi.org/10.48550/arXiv.2512.24117
  2. [2.] Fatima, Z., Sohaib, M. A., Talha, M., Kanwal, A., Sultana, S., & Perwaiz, N. (2026). IceWatch: Forecasting glacial lake outburst floods (GLOFs) using multimodal deep learning. arXiv. https://arxiv.org/abs/2601.12330
  3. [3.] Jiang, D., Li, S., Hajnsek, I., Siddique, M. A., Hong, W., & Wu, Y. (2025). Glacial lake mapping using remote sensing geo-foundation model. International Journal of Applied Earth Observation and Geoinformation. https://www.sciencedirect.com/science/article/pii/S1569843225000184
  4. [4.] Kaushik, S., Singh, T., Joshi, P. K., & Dietz, A. J. (2022). Automated mapping of glacial lakes using multisource remote sensing data and deep convolutional neural network. International Journal of Applied Earth Observation and Geoinformation. https://www.sciencedirect.com/science/article/pii/S1569843222002734
  5. [5.] Shukla, D. P., et al. (2025). Automated mapping of glacial lakes in Himachal Pradesh using multi-source remote sensing data and machine learning. Scientific Reports, 15, Article 36619. https://doi.org/10.1038/s41598-025-20434-7
  6. [6.] Sharma, A., Thakur, V., Prakash, C., et al. (2024). Deep learning-based glacial lakes extraction and mapping in the Chandra–Bhaga Basin. Journal of the Indian Society of Remote Sensing, 52, 435–447. https://doi.org/10.1007/s12524-024-01829-x
  7. [7.] Thati, J., & Ari, S. (2026). GLSM-Net: A global-local salient mapping network for glacial lake extraction and risk assessment. Journal of the Indian Society of Remote Sensing, 54, 843–857. https://doi.org/10.1007/s12524-025-02364-z
  8. [8.] தமிழ் விக்கிப்பீடியா. (2026). செயற்கை நுண்ணறிவு. Wikimedia Foundation. https://ta.wikipedia.org/wiki/செயற்கை_நுண்ணறிவு
  9. [9.] தமிழ் விக்கிப்பீடியா. (2026). தகவல் தொடர்பு செயற்கைக்கோள். Wikimedia Foundation. https://ta.wikipedia.org/wiki/தகவல்_தொடர்பு_செயற்கைக்கோள்
  10. [10.] தமிழ்நாடு மாநில பேரிடர் மேலாண்மை ஆணையம் (TNSDMA). (n.d.). தணிப்புத் திட்டத்தின் கூறுகள். https://tnsdma.tn.gov.in/pages/view/components-of-mitigation-plan
  11. [11.] Vikaspedia. (n.d.). பேரிடர் மேலாண்மை [Disaster management]. Government of India. https://energy.vikaspedia.in/viewcontent/energy/disaster-management
  12. [12.] Wikipedia contributors. (2026). 2026 Nepal floods. Wikipedia. https://en.wikipedia.org/wiki/2026_Nepal_floods
  13. [13.] Wikipedia contributors. (2025). 2025 Nepal floods. Wikipedia. https://en.wikipedia.org/wiki/2025_Nepal_floods
  14. [14.] Wikipedia contributors. (2024). 2024 Thame flood. Wikipedia. https://en.wikipedia.org/wiki/2024_Thame_flood
  15. [15.] Wikipedia contributors. (2023). 2023 Sikkim flash floods. Wikipedia. https://en.wikipedia.org/wiki/2023_Sikkim_flash_floods