Preprints
https://doi.org/10.5194/egusphere-2023-1931
https://doi.org/10.5194/egusphere-2023-1931
18 Sep 2023
 | 18 Sep 2023

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley

Abstract. Communities downstream from burned steeplands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream from burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24-hour lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. Sensitivity analyses indicate that reducing uncertainty in postfire debris-flow volume prediction will have the largest impact on reducing inundation outcome uncertainty. The study results are an initial step toward an operational hazard assessment product that includes debris-flow inundation.

Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley

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-2023-1931', Anonymous Referee #1, 08 Oct 2023
    • AC1: 'Reply on RC1', Alexander Prescott, 21 Dec 2023
  • RC2: 'Comment on egusphere-2023-1931', Paul Santi, 14 Oct 2023
    • AC2: 'Reply on RC2', Alexander Prescott, 21 Dec 2023
Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley

Model code and software

Online repository for code and data used in: Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley https://doi.org/10.5281/zenodo.7838914

Alexander B. Prescott, Luke A. McGuire, Kwang-Sung Jun, Katherine R. Barnhart, and Nina S. Oakley

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Short summary
Fire can dramatically increase the risk of debris flows to downstream communities with little warning, but hazard assessments have not traditionally included estimates of inundation. We unify models developed by the scientific community to create probabilistic estimates of inundation area in response to rainfall at forecast lead times (≥ 24 hours) needed for decision-making. This work takes an initial step towards an operational postfire debris-flow inundation hazard assessment product.