Articles | Volume 24, issue 2
https://doi.org/10.5194/nhess-24-465-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-465-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Feb 2024
Research article |
| 13 Feb 2024
| 13 Feb 2024
Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment
Sudhanshu Dixit
Centre of Excellence in Disaster Mitigation and Management, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India
Srikrishnan Siva Subramanian
CORRESPONDING AUTHOR
Centre of Excellence in Disaster Mitigation and Management, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India
Piyush Srivastava
Centre of Excellence in Disaster Mitigation and Management, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India
Ali P. Yunus
Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, 140306, Punjab, India
Tapas Ranjan Martha
National Remote Sensing Centre (NRSC), Indian Space Research Organisation (ISRO), Department of Space, Government of India, Balanagar, 500037, Hyderabad, Telangana, India
Sumit Sen
Centre of Excellence in Disaster Mitigation and Management, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India
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Cited
21 citations as recorded by crossref.
- Characterization and formation mechanism of the catastrophic flash flood-debris flow hazard triggered by the July 2023 extreme rainstorm in Hantai Gully of Beijing, China J. Ma et al.
- Meteorological Controls on the June 2020 Landslides of Barak Valley, Southern Assam, NE India P. Bhuyan & P. Phukon
- Decadal evolution of mass movements in a Himalayan catchment after the catastrophic 2013 Kedarnath disaster A. Sekar et al.
- Preface: Estimating and predicting natural hazards and vulnerabilities in the Himalayan region W. Schwanghart et al.
- Climate-driven hydrogeological hazards: A growing threat to Asia’s Water Tower [version 2] Y. Li et al.
- An integrated IKOA-CNN-BiGRU-Attention framework with SHAP explainability for high-precision debris flow hazard prediction in the Nujiang river basin, China H. Yang et al.
- Chronicle of destruction: the Wayanad landslide of July 30, 2024 A. Yunus et al.
- Unravelling failure mechanisms of rainfall-induced debris slides through material characterisation and reduced-scale flume experiments M. Dewrari & S. Siva Subramanian
- Systematic identification of seismic signatures from medium-intensity landslides in the Arunachal Pradesh region, Northeast India, and their accurate locations R. Singh et al.
- Coupling hydrological, geotechnical and machine learning models to enhance landslide prediction for an early warning system: application to Upper Garonne River Basin, Pyrenees, Spain F. Asurza et al.
- An Analytical Insight Into Stability Analysis of Unsaturated Multi‐Layered Slopes Subjected to Rainfall Infiltration C. Yuan et al.
- Study on meteorological risk early warning for landslides based on analysis of extreme rainfall-induced clustering landslide events: a case of Bailong River Basin in China S. Liu et al.
- A Non-Stationary Framework for Landslide Hazard Assessment Under the Extreme Rainfall Condition S. Dilama Shamsudeen et al.
- Experimental field study on the influence of underground plant roots on the initiation of gulley debris flows Y. Wang et al.
- Impact of antecedent rainfall and soil saturation on widespread debris flows in the northern Western Ghats during the 2021 extreme rainfall S. Islam et al.
- Landslide monitoring: DenseNET and image segmentation techniques to classify type and compute run-out displacement and hazard area S. Gunjan et al.
- Climate-driven hydrogeological hazards: A growing threat to Asia’s Water Tower [version 1] Y. Li et al.
- Constructing regional catchment-specific triggering threshold for runoff-generated debris flows: a case study in the Bailong River Y. Huang et al.
- Modelling and analysis of extreme weather-induced disasters in Indian North-West Himalayas S. Singh et al.
- Interpretable and Calibrated XGBoost Framework for Risk-Informed Probabilistic Prediction of Slope Stability H. Alharbi
- Integrating TRIGRS and RAMMS for the spatiotemporal prediction of rainfall induced landslides and landslide trajectory: a case study A. Musaib et al.
21 citations as recorded by crossref.
- Characterization and formation mechanism of the catastrophic flash flood-debris flow hazard triggered by the July 2023 extreme rainstorm in Hantai Gully of Beijing, China J. Ma et al.
- Meteorological Controls on the June 2020 Landslides of Barak Valley, Southern Assam, NE India P. Bhuyan & P. Phukon
- Decadal evolution of mass movements in a Himalayan catchment after the catastrophic 2013 Kedarnath disaster A. Sekar et al.
- Preface: Estimating and predicting natural hazards and vulnerabilities in the Himalayan region W. Schwanghart et al.
- Climate-driven hydrogeological hazards: A growing threat to Asia’s Water Tower [version 2] Y. Li et al.
- An integrated IKOA-CNN-BiGRU-Attention framework with SHAP explainability for high-precision debris flow hazard prediction in the Nujiang river basin, China H. Yang et al.
- Chronicle of destruction: the Wayanad landslide of July 30, 2024 A. Yunus et al.
- Unravelling failure mechanisms of rainfall-induced debris slides through material characterisation and reduced-scale flume experiments M. Dewrari & S. Siva Subramanian
- Systematic identification of seismic signatures from medium-intensity landslides in the Arunachal Pradesh region, Northeast India, and their accurate locations R. Singh et al.
- Coupling hydrological, geotechnical and machine learning models to enhance landslide prediction for an early warning system: application to Upper Garonne River Basin, Pyrenees, Spain F. Asurza et al.
- An Analytical Insight Into Stability Analysis of Unsaturated Multi‐Layered Slopes Subjected to Rainfall Infiltration C. Yuan et al.
- Study on meteorological risk early warning for landslides based on analysis of extreme rainfall-induced clustering landslide events: a case of Bailong River Basin in China S. Liu et al.
- A Non-Stationary Framework for Landslide Hazard Assessment Under the Extreme Rainfall Condition S. Dilama Shamsudeen et al.
- Experimental field study on the influence of underground plant roots on the initiation of gulley debris flows Y. Wang et al.
- Impact of antecedent rainfall and soil saturation on widespread debris flows in the northern Western Ghats during the 2021 extreme rainfall S. Islam et al.
- Landslide monitoring: DenseNET and image segmentation techniques to classify type and compute run-out displacement and hazard area S. Gunjan et al.
- Climate-driven hydrogeological hazards: A growing threat to Asia’s Water Tower [version 1] Y. Li et al.
- Constructing regional catchment-specific triggering threshold for runoff-generated debris flows: a case study in the Bailong River Y. Huang et al.
- Modelling and analysis of extreme weather-induced disasters in Indian North-West Himalayas S. Singh et al.
- Interpretable and Calibrated XGBoost Framework for Risk-Informed Probabilistic Prediction of Slope Stability H. Alharbi
- Integrating TRIGRS and RAMMS for the spatiotemporal prediction of rainfall induced landslides and landslide trajectory: a case study A. Musaib et al.
Saved (final revised paper)
Latest update: 04 May 2026
Short summary
Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards. Large-scale sediment disasters like landslides, debris flows, and flash floods happen frequently in the Himalayas because of their propensity for intense precipitation events. We provide a new framework that combines the Weather Research and Forecasting (WRF) model with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.
Rainfall intensity–duration (ID) thresholds can aid in the prediction of natural hazards....
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