Incorporating Shear Resistance into Debris Flow Triggering Model Statistics

Abstract:

Current statistical post-fire debris flow triggering models consider numerous independent variables that provide predictive capacity in forecasting initiation. Such variables account for rainfall intensity, rainfall accumulation, area burned, burned intensity, geology, slope, and others. However, no variable in current utilization directly accounts for the shear stiffness, the material’s capacity to resist lateral deformation, of the sediment. Such a property when considered with the respect to the state of the loading of the sediment informs the likelihood of particle dislocation, contractive or dilative volume changes, and downslope movement that triggers debris flows. This study proposes incorporating shear wave velocity (in the form of slope-based thirty meter shear wave velocity) to account for this shear stiffness. As commonly used in seismic soil liquefaction analysis, the shear stiffness is measured via shear wave velocity which is the speed of the vertically propagating horizontal shear wave through sediment. This spatially mapped variable allows for broad coverage in the watersheds of interest. A logistic regression is then used to compare the new variable against what is currently used in predictive post-fire debris flow triggering models. We find that the new variable produces an improved predictor of triggering as it captures the essential physics of sediment failing in a shearing manner. Additional suggestions are also presented for utilizing statistical cross-validation methods to advance prediction performance.