the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides
Abstract. The development of an early warning system for landslides due to rainfall has become an indispensable part for landslide risk mitigation. This paper explains the application of the hydrological FLaIR (Forecasting of Landslides Induced by Rainfall) model, correlating rainfall amount and landslide events. The FLaIR model comprises of two modules: RL (Rainfall-Landslide) which correlates rainfall and landslide occurrence and RF (Rainfall-Forecasting) which allows simulation of future rainfall events. The model can predetermine landslides based on identification of mobility function Y(.) which links actual rainfall and incidence of landslide occurrence. The critical value of mobility function was analyzed using 1st July 2015 event and applying it to 2016 monsoon to validate the results. These rainfall thresholds presented can be improved with intense hourly rainfall and landslide inventory data. This paper describes the details of the model and its performance for the study area.
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This preprint has been retracted.
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Preprint
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Interactive discussion
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RC1: 'The manuscript should be significantly improved. Major revisions are requested', Anonymous Referee #1, 08 Sep 2017
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SC1: 'Interactive comment on " Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides" by Abhirup Dikshit and Neelima Satyam', Abhirup Dikshit, 26 Sep 2017
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RC2: 'some revisions before publication', Anonymous Referee #1, 10 Oct 2017
- AC1: 'Response to comments', Abhirup Dikshit, 11 Oct 2017
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RC2: 'some revisions before publication', Anonymous Referee #1, 10 Oct 2017
-
SC1: 'Interactive comment on " Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides" by Abhirup Dikshit and Neelima Satyam', Abhirup Dikshit, 26 Sep 2017
-
RC3: 'Revision', Anonymous Referee #2, 13 Oct 2017
- AC2: 'Interactive Comments', Abhirup Dikshit, 24 Oct 2017
Interactive discussion
-
RC1: 'The manuscript should be significantly improved. Major revisions are requested', Anonymous Referee #1, 08 Sep 2017
-
SC1: 'Interactive comment on " Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides" by Abhirup Dikshit and Neelima Satyam', Abhirup Dikshit, 26 Sep 2017
-
RC2: 'some revisions before publication', Anonymous Referee #1, 10 Oct 2017
- AC1: 'Response to comments', Abhirup Dikshit, 11 Oct 2017
-
RC2: 'some revisions before publication', Anonymous Referee #1, 10 Oct 2017
-
SC1: 'Interactive comment on " Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides" by Abhirup Dikshit and Neelima Satyam', Abhirup Dikshit, 26 Sep 2017
-
RC3: 'Revision', Anonymous Referee #2, 13 Oct 2017
- AC2: 'Interactive Comments', Abhirup Dikshit, 24 Oct 2017
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Cited
6 citations as recorded by crossref.
- Identifying Geotechnical Characteristics for Landslide Hazard Indication: A Case Study in Mandi, Himachal Pradesh, India N. Mali et al. 10.1007/s12517-022-09475-8
- A combined influence of surface temperature and daily rainfall to the historical landslides occurred on 7th September 2007 over sub-Himalayan region, India S. Karmakar et al. 10.1007/s12040-023-02054-9
- Determining the Geotechnical Slope Failure Factors via Ensemble and Individual Machine Learning Techniques: A Case Study in Mandi, India N. Mali et al. 10.3389/feart.2021.701837
- Evaluation of a Tilt-Based Monitoring System for Rainfall-Induced Landslides: Development and Physical Modelling A. Paswan & A. Shrivastava 10.3390/w15101862
- Early warning system using tilt sensors in Chibo, Kalimpong, Darjeeling Himalayas, India A. Dikshit et al. 10.1007/s11069-018-3417-6
- Estimation of rainfall thresholds for landslide occurrences in Kalimpong, India A. Dikshit & D. Satyam 10.1007/s41062-018-0132-9