A depth-averaged debris-flow model that includes the effects of evolving dilatancy. II. Numerical predictions and experimental tests

Abstract

We evaluate a new depth-averaged mathematical model that is designed to simulate all stages of debris-flow motion, from initiation to deposition. A companion paper shows how the model's five governing equations describe simultaneous evolution of flow thickness, solid volume fraction, basal pore-fluid pressure and two components of flow momentum. Each equation contains a source term that represents the influence of state-dependent granular dilatancy. Here, we recapitulate the equations and analyse their eigenstructure to show that they form a hyperbolic system with desirable stability properties.To solve the equations, we use a shock-capturing numerical scheme with adaptive mesh refinement, implemented in an open-source software package we call D-Claw. As tests of D-Claw, we compare model output with results from two sets of largescale debris-flow experiments. One set focuses on flow initiation from landslides triggered by rising pore-water pressures, and the other focuses on downstream flow dynamics, runout and deposition. D-Claw performs well in predicting evolution of flow speeds, thicknesses and basal pore-fluid pressures measured in each type of experiment. Computational results illustrate the critical role of dilatancy in linking coevolution of the solid volume fraction and porefluid pressure, which mediates basal Coulomb friction and thereby regulates debris-flow dynamics.

A depth-averaged debris-flow model that includes the effects of evolving dilatancy. I. Physical basis

“…Because none of the tests involved gravity-free conditions in which an ideal limiting state with m = m min and σ e = 0 was attained, we extrapolated the data for m as a function of σ e in order to estimate the values of m min and σ 0 necessary for normalizing the data in figure 3 ( Table 1) Owing to the ability of (3.15) to mimic the data trends in figure 3, we adopt (3.14) as our definition of debris compressibility, and we infer that values 0.01 ≤ a ≤ 0.05 and 10 Pa ≤ σ 0 ≤ 1000 Pa in (3.14) are commonly suitable. Model predictions presented in our companion paper [46] help test the validity of this inference.…”

“…Here, to emphasize the main new features of our model, we omit the effects of bed curvature and focus on flows that traverse planar terrain. Our companion paper [46] addresses bed curvature effects. …”

“…Therefore, we estimate the effects ofγ on dm/dt by considering idealized deformations consisting of isotropic volume strain and homogeneous simple shearing in x − z and/or y − z planes (figure 2). This idealization yields a parsimonious model that can be tested using existing datasets [46].…”

Pre-2014 mudslides at Oso revealed by InSAR and multi-source DEM analysis

“…However, many landslides are repetitive, and therefore careful observation of critical factors, such as ground displacement, precipitation, stratigraphy, groundwater level, and stream flow, can reduce the risk of property damage and casualty loss (Anderson & Holcombe 2013). In particular, frequent observations over areas with high precipitation and deforestation can play a role in identifying the precautionary regions exposed to recurring landslides (Giannecchini et al 2012;George & Iverson 2014). Nevertheless, when a mountainous and steep region is our interest, acquiring the valuable spatio-temporal information can be challenging due to the lack of in situ data and disturbance by weather condition and rugged topography.…”

Tsunami inundation maps for Juneau, Alaska

“…In this particular event, the M w 7.1 earthquake triggered an underwater slump that produced a tsunami with a 15 m local inundation, killing almost 2,200 people (Tappin and others, 2008). After the PNG tragedy, in order to minimize future losses, a number of models to simulate water dynamics due to submarine landslides have been developed (e.g., Fine and others, 1998;Grilli and Watts, 1999;Watts and others, 2003;Lynett and Liu, 2002;Skvortsov and Bornhold, 2007;Løvholt and others, 2008;Weiss and Wünnermann, 2009;Horrillo and others, 2013;Ma and others, 2013;George and Iverson, 2014).…”