Preprints
https://doi.org/10.5194/egusphere-2023-1892
https://doi.org/10.5194/egusphere-2023-1892
18 Sep 2023
 | 18 Sep 2023

Evaluation of debris-flow building damage forecasts

Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean

Abstract. Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or volume flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on combining multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with volume flux and the D-Claw model could correctly forecast the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly forecast building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage, but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to forecast building damage, comparing debris flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.

Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1892', Polina Lemenkova, 24 Jan 2024
    • AC1: 'Response to reviewer comments: egusphere-2023-1892', Katherine Barnhart, 22 Feb 2024
  • RC2: 'Comment on egusphere-2023-1892', Polina Lemenkova, 05 Feb 2024
    • AC1: 'Response to reviewer comments: egusphere-2023-1892', Katherine Barnhart, 22 Feb 2024
  • RC3: 'Comment on egusphere-2023-1892', Anonymous Referee #2, 14 Feb 2024
    • AC1: 'Response to reviewer comments: egusphere-2023-1892', Katherine Barnhart, 22 Feb 2024
Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean

Data sets

Select model results and model input parameters for debris-flow runout model simulations of the 9 January 2018 Montecito debris flow runout event Barnhart, K. R. https://doi.org/10.5066/P9X18F2H

Katherine R. Barnhart, Christopher R. Miller, Francis K. Rengers, and Jason W. Kean

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Short summary
Debris flows are a type of fast-moving landslide that start from shallow landslides or during intense rain. Infrastructure located downstream of watersheds susceptible to debris flows may be damaged should a debris flow reach them. We present and evaluate an approach to forecast building damage caused by debris flows. We test three alternative models for simulating the motion of debris flows and find that only one can forecast the correct number and spatial pattern of damaged buildings.