Debris flow magnitudes: a global catalog

The episodic occurrence of debris flow events in response to stochastic precipitation and wildfire events makes hazard prediction challenging. Previous work has shown that frequency-magnitude distributions of non-fire-related debris flows follow a power law, but less is known about the distribution of post-fire debris flows. As a first step in parameterizing hazard models, we use frequency-magnitude distributions and cumulative distribution functions to compare volumes of post-fire debris flows to non-fire-related debris flows. Due to the large number of events required to parameterize frequency-magnitude distributions, and the relatively small number of post-fire event magnitudes recorded in the literature, we collected data on 73 recent post-fire events in the field. The resulting catalog of 988 debris flow events is presented as an appendix to this article. We found that the empirical cumulative distribution function of post-fire debris flow volumes is composed of smaller events than that of non-fire-related debris flows. In addition, the slope of the frequency-magnitude distribution of post-fire debris flows is steeper than that of non-fire-related debris flows, evidence that differences in the post-fire environment tend to produce a higher proportion of small events. We propose two possible explanations: 1) post-fire events occur on shorter return intervals than debris flows in similar basins that do not experience fire, causing their distribution to shift toward smaller events due to limitations in sediment supply, or 2) fire causes changes in resisting and driving forces on a package of sediment, such that a smaller perturbation of the system is required in order for a debris flow to occur, resulting in smaller event volumes.

Results of Closed-Flow Column Experiments (zip-archive 2.3 MB)

The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to observations of the solute breakthrough in column outflow experiments. This parameters uncertainty can be approached by the application of multiple experimental designs such as column experiments in open-flow mode and the recently proposed closed-flow mode. Latter are characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow. Depending on the experimental conditions, the solute concentration in the solution supply vessel and the effluent follows a damped sinusoidal oscillation. As a result, the closed-flow experiment provides additional observables in the breakthrough curve. The evaluation of these emergent features allows intrinsic control over boundary conditions and impacts the uncertainty of parameters in inverse modeling. We present a comprehensive sensitivity analysis to illustrate the potential application of closed-flow experiments. We show that the sensitivity with respect to the apparent dispersion can be controlled by the experimenter leading to a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude for optimal settings. With these finding we are also able to reduce the equifinality found for situations, where rate-limited interactions impede a proper determination of the apparent dispersion and rate coefficients. Furthermore, we show the expected breakthrough curve for equilibrium and kinetic sorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. This renders the closed-flow mode a useful complementary approach to classical column experiments.