The GeoClaw software for depth-averaged flows with adaptive refinement

Berger, Marsha; George, David Lloyd; LeVeque, Randall J.; Mandli, Kyle T.

doi:10.1016/j.advwatres.2011.02.016

Cited by 199 publications

(174 citation statements)

References 35 publications

(57 reference statements)

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“…D-Claw is an extension of the CLAWPACK software package [34], an open-source project for solving general hyperbolic problems (e.g. [17,[35][36][37]). …”

Section: Numerical Methods and D-claw Softwarementioning

confidence: 99%

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

2014

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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.

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“…D-Claw is an extension of the CLAWPACK software package [34], an open-source project for solving general hyperbolic problems (e.g. [17,[35][36][37]). …”

Section: Numerical Methods and D-claw Softwarementioning

confidence: 99%

“…[52,53]), and later specialized for depth-averaged flows across topography, such as tsunamis and overland floods (e.g. [35][36][37]). With patch-based, blockstructured AMR, the domain is discretized on numerous rectangular grids, each associated with a given level, l = 1, .…”

Section: (B) Adaptive Mesh Refinementmentioning

confidence: 99%

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

2014

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“…A number of different adaptive grid systems have been reported in literature to achieve AMR simulations. For example, an effective block-structured AMR was introduced by Berger and Oliger (1984) and Berger and Colella (1989), which was later implemented in Berger et al (2011) for solving the shallow water equations and subsequently used by George (2011) for dam-break simulations. Due to their flexibility in performing grid adaptation, quadtree grids have been widely used to solve the shallow water equations for different applications, e.g.…”

Section: Introductionmentioning

confidence: 99%

A robust coupled model for solute transport driven by severe flow conditions

Zhang

Liang

Wang

et al. 2015

Journal of Hydro-environment Research

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This paper introduces a computationally efficient model that solves a 4 Â 4 matrix form of the hyperbolic conservation laws consisting of the 2D shallow water and advection-diffusion equations. The model allows automatic shock-capturing due to the implementation of a finite volume Godunov-type scheme featured with an HLLC approximate Riemann solver. The numerical scheme is also able to provide well-balanced solutions and maintain non-negative water depth and solute concentration for applications involving wetting and drying over complex domain topographies. Implemented on a simplified adaptive grid system, the model can save 3e17 times of computational cost without compromising solution accuracy for those simulations with predominant localised complex hydrodynamic or flow features, as demonstrated by the numerical experiments. Therefore, the current model provides a potential tool for efficient simulation of large-scale solute transport as well as flow hydrodynamics during a highly transient flood event caused by dam failure or flash flooding.

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“…Popinet and Rickard (2007) use a quadtree approach to provide dynamic adaptivity on an A grid discretization of the shallow water equations. Berger et al (2011) apply their adaptive mesh refinement (AMR) code GeoClaw to model a synthetic tsunami test case in flat geometry. GeoClaw automatically handles wetting/drying and can be extended to the sphere on longitude-latitude or other logically rectangular grids (Berger et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Adaptive wavelet simulation of global ocean dynamics using a new Brinkman volume penalization

Kevlahan

Dubos²,

Aechtner

2015

Geosci. Model Dev.

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Abstract. In order to easily enforce solid-wall boundary conditions in the presence of complex coastlines, we propose a new mass and energy conserving Brinkman penalization for the rotating shallow water equations. This penalization does not lead to higher wave speeds in the solid region. The error estimates for the penalization are derived analytically and verified numerically for linearized one-dimensional equations. The penalization is implemented in a conservative dynamically adaptive wavelet method for the rotating shallow water equations on the sphere with bathymetry and coastline data from NOAA's ETOPO1 database. This code could form the dynamical core for a future global ocean model. The potential of the dynamically adaptive ocean model is illustrated by using it to simulate the 2004 Indonesian tsunami and wind-driven gyres.

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The GeoClaw software for depth-averaged flows with adaptive refinement

Cited by 199 publications

References 35 publications

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

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

A robust coupled model for solute transport driven by severe flow conditions

Adaptive wavelet simulation of global ocean dynamics using a new Brinkman volume penalization

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