Catchment Scale Landslide Monitoring and Early Warning System CatchMEWS – Devikulam, Kerala, India
The global increase in landslide occurrences, impacting millions and resulting in casualties, underscores the urgent need for robust and cost-effective early warning systems and emergency response efforts. Recent advancements in landslide early warning systems have been promising, yet the complexities of larger, dynamic, and cascading hazards demand a more comprehensive approach. This project proposes the Catchment Scale Landslide Monitoring and Early Warning System CatchMEWS to be piloted in the upper catchments of the Periyar river in Kerala’s Western Ghats. The semi-deterministic dynamic model integrates geological and real-time metro-hydrological data to understand landslide risk stages from initiation to impact. Through comprehensive investigation of causative factors and variations in triggering factors, this work aims to enhance understanding of slope instability processes. The methodology integrates local perspectives and community-centric approaches, developing a validated database of landslide events and fostering sustainable development through geospatial and machine learning techniques. This project emphasizes the importance of flexible strategies in geological hazard management, offering insights to accurately assess and predict landslide risks, develop sustainable models, and address similar challenges globally.
Amrita Team Members
- Dr. Sudesh Wadhawan
- Dr. Hemalatha T
- Balmukund Singh
- Nitin Kumar M Hari Chandana
Name of the Indian Collaborators
- KSDMA Kerala State Disaster Management Authority , Devikulam Administration, KDH Tea Estate
Name of the International Collaborators: Guido Zolezzi, Professor – University of Trento – Italy, Dept. of Civil Environmental and Mechanical Engineering, Center Agriculture Food Environment, Chairholder – UNESCO Chair in Engineering for Human and Sustainable Development, Rector’s Delegate for Cooperation and Development Coordinator of CUCS – Italian University Network for Development Cooperation
Name of the Industry Collaborators : ESRI
Product Details
- Amrita Dynamic Catchment scale landslide Risk Management Platform
- AI-based IoT system for Landslide early warnings- Catchment Specific
Proposed Future Work Details: Implementation into various other catchments for Disaster risk Reduction
Publication Details
- Wadhawan, S. K., Singh, B., & Ramesh, M. V. (2020). Causative factors of landslides 2019: case study in Malappuram and Wayanad districts of Kerala, India. Landslides, 17, 2689-2697.
- Watlet, A., Thirugnanam, H., Singh, B., Kumar M, N., Brahmanandan, D., Inauen, C., … & Ramesh, M. V. (2023). 4D electrical resistivity to monitor unstable slopes in mountainous tropical regions: an example from Munnar, India. Landslides, 20(5), 1031-1044.
- Wadhawan, S. K., Singh, B., Kumar, M. N., Vasudevan, N., & Ramesh, M. V. (2023). A Novel Application of Catchment Approach to Assessment of 2021 Rockfall and Landslides Vulnerabilities in Tirumala Hills, Andhra Pradesh, India. Journal of the Geological Society of India, 99(5), 599-606.
- Wadhawan, S. K., Singh, B., Kumar, M. N., Vasudevan, N., & Ramesh, M. V. (2022) Potential Geotourism And The Prospect Of Raising Awareness About Geoconservation Of Landslides As Geomorphosites In Munnar -Rajamala Areas, Idukki District, Kerala, India. SGAT Bulletin, Vol. 23, No. 2, pp. 20-31
Book Chapters
- Ramesh, M. V., Thirugnanam, H., Mohanan, N. K., Singh, B., Ekkirala, H. C., & Guntha, R. (2023). Community Scale Landslide Resilience: A Citizen-Science Approach. In Progress in Landslide Research and Technology, Volume 2 Issue 2, 2023 (pp. 183-196). Cham: Springer Nature Switzerland.
- Ramesh, M. V., Sudarshan, V. C., Harilal, G. T., Singh, B., Sudheer, A., & Ekkirala, H. C. (2021). Kerala floods 2018: causative factors that transformed single event to multi-hazard disaster. In Civil Engineering for Disaster Risk Reduction (pp. 61-82). Singapore: Springer Singapore.
- Ramesh, M. V., Thirugnanam, H., Singh, B., Nitin Kumar, M., & Pullarkatt, D. (2023). Landslide Early Warning Systems: Requirements and Solutions for Disaster Risk Reduction—India. In Progress in Landslide Research and Technology, Volume 1 Issue 2, 2022 (pp. 259-286). Cham: Springer International Publishing
