| Abstract Submission No. | ABS-3.1-0147 |
| Title of Abstract | Monitoring Himalayan Landslides with Time Series InSAR: A pilot study towards a dynamic landslide monitoring framework |
| Authors | Dinesh Kumar Sahadevan*, Anand Kumar Pandey |
| Organisation | CSIR-National Geophysical Research Institute |
| Address | 266, Geochemistry building, CSIR-NGRI, Hyderabad Hyderabad, Telangana, India Pincode: 500007 E-mail: dineshrsgis@gmail.com |
| Country | India |
| Presentation | Oral |
| Abstract | The Himalayan region is experiencing an alarming increase in extreme rainfall events, exacerbated by rapid infrastructure development. These factors are destabilizing fragile mountain slopes and intensifying the frequency of landslides and land subsidence. Uttarakhand has emerged as one of the most vulnerable states in the Himalaya, where active tectonics, weak lithology, and rapid urban expansion interact with climatic extremes to amplify slope hazards. This study presents a pilot analysis of active landslide and subsidence processes in the Chamoli district (~1,000 km²) using time-series Interferometric Synthetic Aperture Radar (InSAR). Sentinel-1 SAR datasets (2016- 2024) were processed with the Small Baseline Subset (SBAS) technique to extract millimetre-scale deformation rates. Four critical sites were identified: Topovan, Sonla, Gopeshwar, and Longsi. Topovan has experienced catastrophic subsidence since 2021, with some areas near Joshimath exhibiting -20cm/yr., Sonla exhibited persistent creeping movements (-4 cm/yr.) that intensified during monsoon peaks, Gopeshwar showed localized instabilities (-5 cm/yr.) along steep urban slopes, while Longsi, a historically unstable region, recorded continuous deformation (-10cm/yr.) with sharp accelerations following high-intensity rainfall. By linking rainfall anomalies with InSAR-derived deformation, this study highlights the decisive role of extreme precipitation in shaping Himalayan landslide dynamics. The findings underscore the limitations of static landslide hazard zonation, which often fails to capture slow-onset or rainfall-accelerated instabilities. Instead, integrating time series InSAR with rainfall datasets offers a scalable pathway toward dynamic landslide monitoring frameworks. The case studies further demonstrate how hydrological forcing reactivates metastable slopes, with deformation persisting well beyond rainfall episodes. This pilot analysis provides actionable insights for disaster preparedness in Chamoli and establishes the foundation for a state-wide landslide monitoring system across Uttarakhand. Results reveal a strong temporal and spatial coupling between rainfall extremes and slope instability, underscoring the need for continuous monitoring in the Himalayan context. |
| Keywords | InSAR, Landslide, Extreme rainfall, Slope instability, Geo-hazards |