Probabilistic prediction of post-fire debris-flow runout and implications for prefire assessments of post-fire hazards

Background

Debris-flow runout modeling is a valuable component of the prefire assessment of post-fire hazards. The application and benefits of runout modeling are limited by uncertainty in debris-flow volume as well as model parameters related to flow mobility.

Aims

In this study, we assess and reduce the uncertainty associated with flow-mobility parameters by calibrating a debris-flow runout model to 12 runoff-generated debris flows in the western United States.

Methods

For each debris flow, we determined optimal flow-mobility parameters using back analyses and generated a posterior distribution of the parameters using a Bayesian approach. We assessed the relative sensitivity of the model to the flow-mobility parameters, rainfall intensification and fire burn severity when applied to three post-fire debris flows.

Key results

Yield strength, one of the flow-mobility parameters, exhibits a negative, linear relationship with soil clay content. Modeled area inundated is most sensitive to the flow-mobility parameters, followed by a rainfall intensification factor.

Conclusions

Well-constrained flow-mobility parameters will improve post-fire debris-flow runout modeling, though prefire assessments of post-fire hazards could also benefit from accounting for the effects of rainfall intensification.

Implications

This study improves our ability to simulate debris-flow runout and assess associated hazards.