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- Title
Incorporating shear stiffness into post-fire debris flow statistical triggering models.
- Authors
Moss, R. E. S.; Lyman, N.
- Abstract
Commonly used post-fire debris flow statistical triggering models consider predictor variables that account for; rainfall intensity, rainfall accumulation, area burned, burned intensity, geology, slope, and others. These models represent the physical process of debris flow initiation and subsequent failure by quantifying near-surface soil characteristics. Shear wave velocity as a proxy for sediment shear stiffness informs the likelihood of particle dislocation, contractive or dilative volume changes, and downslope displacement that result from flow-type failures. This broadly available variable common to other hazard predictions, such as liquefaction analysis, provides good coverage in the watersheds of interest for debris flow predictions. A logistic regression is used to compare the new variable against currently used variables for predictive post-fire debris flow triggering models. We find that the new variable produces slightly improved performance in prediction of triggering while better capturing the physics of flow-type failure. Additional suggestions are presented for utilizing statistical cross-validation methods to advance prediction performance and the utility of different variables for quick assessment of likelihood during post-fire rainfall events.
- Subjects
DEBRIS avalanches; STATISTICAL models; INDEPENDENT variables; FRICTION velocity; RAINFALL; FLOOD warning systems
- Publication
Natural Hazards, 2022, Vol 113, Issue 2, p913
- ISSN
0921-030X
- Publication type
Article
- DOI
10.1007/s11069-022-05330-x