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Towards establishing rainfall thresholds for a real-time landslide early warning system in Sikkim, India

  • Geethu Thottungal Harilal
  • Dhanya Madhu
  • Maneesha Vinodini RameshEmail author
  • Divya Pullarkatt
Original Paper


Sikkim, one of the Northeastern states of India, is a famous tourism spot in the Himalayas with dynamic population density. This mountainous area receives heavy rainfall and is well known for frequent shallow landslides, especially, Chandmari, which is a village, situated in Gangtok area in East Sikkim. Even though it is well known that rainfall and landslides are correlated, Sikkim lacks a well-established landslide early warning system. Such a system is important in this region because it is one of the highest landslide-prone areas in India. The current research attempts to establish rainfall thresholds as part of developing an efficient landslide early warning system for this region. The rainfall thresholds for landslides are derived based on the daily rainfall data available from India Meteorological Department (IMD) for six stations in Sikkim. Analysis of daily rainfall data and landslide events in this area between the year 1990 and 2017 is performed. An intensity–duration (I–D)-based regional rainfall threshold is derived as I = 43.26 D−0.78 (I = rainfall intensity in mm/day and D = duration in days) for the rainfall-triggered landslides in Sikkim region and a local threshold of I = 100 D−.92 was developed for the Gangtok area. Furthermore, the influence of antecedent rainfall in landslide initiation is explored by considering the daily, 3-day, 5-day, 7-day, and 20-day cumulative rainfall values associated with landslides. The proposed threshold equations and study of the effect of antecedent rainfall on landslides are intended to aid in enhancing the real-time landslide early warning system (R-LEWS) being developed for Sikkim.


Antecedent rainfall Empirical threshold Landslides Rainfall thresholds Real-time landslide early warning system (R-LEWS) 



The authors would like to express gratitude for the immense amount of motivation and guidance provided by Dr. Sri. Mata Amritanandamayi Devi, the Chancellor, Amrita Vishwa Vidyapeetham. Special thanks to Dr. G.C Khanal, Additional Director, Sikkim State Disaster Management Authority and India Meteorological Department for providing the rainfall data. The authors are thankful to Mr. Sangeeth, Mr. Nitin Kumar, Mr. Deepak, Mr. Mukundan, Mr. Arun Kumar, Mr. Balmukund, Mr. Ramesh Guntha, Prof. Balaji Hariharan, Mr. Rayudu, Mr. Ratheesh Kumar and Mr. Audhithiya Vigneswar, Amrita Vishwa Vidyapeetham for their valuable support and hard work during the EWS deployment in Sikkim.

Funding information

This work is partially funded under the project “Advancing Integrated Wireless Sensor Networks for Real-time Monitoring and Detection of Disasters” by the Ministry of Earth Sciences (MoES), Government of India.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Geethu Thottungal Harilal
    • 1
  • Dhanya Madhu
    • 1
    • 2
  • Maneesha Vinodini Ramesh
    • 1
    Email author
  • Divya Pullarkatt
    • 1
  1. 1.Amrita Center for Wireless Networks & Applications (AmritaWNA)Amrita School of Engineering, Amritapuri, Amrita Vishwa VidyapeethamKollamIndia
  2. 2.Department of PhysicsAmrita School of Arts & Sciences, Amritapuri, Amrita Vishwa VidyapeethamKollamIndia

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