13 Jan 2023
 | 13 Jan 2023
Status: a revised version of this preprint is currently under review for the journal NHESS.

Numerical model derived intensity-duration thresholds for early warning of rainfall-induced debris flows in the Himalayas

Srikrishnan Siva Subramanian, Piyush Srivastava, Ali Pulpadan Yunus, Tapas Ranjan Martha, and Sumit Sen

Abstract. Debris flows triggered by rainfall are catastrophic geohazards that occur compound during extreme events. Early warning systems for shallow landslides and debris flows at the territorial-scale use thresholds of rainfall Intensity-Duration (ID). ID thresholds are defined using hourly rainfall. Due to instrumental and operational challenges, current early warning systems have difficulty forecasting sub-daily time series of weather for landslides in the Himalayas. Here, we present a framework that employs a spatio-temporal numerical model preceded by the weather research and forecast (WRF) model for analysing debris flows induced by extreme rainfall. The WRF model runs at 1.8 km * 1.8 km resolution to produce hourly rainfall. The hourly rainfall is then used as an input boundary condition in the spatio-temporal numerical model for debris flows. The models are first calibrated using the debris flows in the Kedarnath catchment that occurred during the 2013 North India Floods. Various precipitation intensities based on the glossary of the India Meteorological Department (IMD) are set and parametric numerical simulations are run identifying ID thresholds of debris flows. Our findings suggest that the WRF model combined with the debris flow numerical model shall be used to establish ID thresholds in territorial landslide early warning systems (Te-LEWS).

Srikrishnan Siva Subramanian et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-297', Anonymous Referee #1, 10 Feb 2023
    • AC1: 'Reply on RC1', Srikrishnan Siva Subramanian, 29 Jun 2023
  • RC2: 'Comment on nhess-2022-297', Anonymous Referee #2, 03 Mar 2023
    • AC2: 'Reply on RC2', Srikrishnan Siva Subramanian, 30 Jun 2023

Srikrishnan Siva Subramanian et al.

Srikrishnan Siva Subramanian et al.


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Short summary
Rainfall intensity-duration (ID) thresholds can aid in the prediction of natural disasters. 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 model (WRF) with a regionally distributed numerical model for debris flows to analyse and predict intense rainfall-induced landslides in the Himalayas.