Analyzing debris flows with the statistically calibrated empirical model LAHARZ in southeastern Arizona, USA

Magirl, Christopher S.; Griffiths, Peter G.; Webb, Robert H.

doi:10.1016/j.geomorph.2010.02.022

Cited by 50 publications

(21 citation statements)

References 16 publications

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“…An alternative to modeling any single value is to calculate multiple V estimates within reasonable bounds using either the standard error of the regression model at a selected confidence interval as was done in the case study described herein, or by using a single order of magnitude as a bound for the range as described by Magirl et al (2010). For extremely large storms, or unfavorable basin conditions, modeled Vs may exceed reasonable expectations.…”

Section: Model Uncertainty and Alternative Methodsmentioning

confidence: 99%

Rocky Mountain Geo-Conference 2014

Strickland¹,

Wiltshire²,

Goss³

2014

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Section: Model Uncertainty and Alternative Methodsmentioning

confidence: 99%

Rocky Mountain Geo-Conference 2014

Strickland¹,

Wiltshire²,

Goss³

2014

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“…The rationale for the delineation of lahar-inundation hazard zones [33,34] is derived from the scaling analysis of lahar paths and statistical analysis using the LAHARZ program [35][36][37]. These analyses generate semiempirical equations that predict the inundated valley cross-sectional area (1) and the planimetric area (2) as a function of lahar volume with proportionality coefficients c and C using volcanic event data of 27 paths of lahars at nine volcanoes.…”

Section: Laharz Processingmentioning

confidence: 99%

Mapping Pyroclastic Flow Inundation Using Radar and Optical Satellite Images and Lahar Modeling

et al. 2018

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Sinabung volcano, located above the Sumatra subduction of the Indo-Australian plate under the Eurasian plate, became active in 2010 after about 400 years of quiescence. We use ALOS/PALSAR interferometric synthetic aperture radar (InSAR) images to measure surface deformation from February 2007 to January 2011. We model the observed preeruption inflation and coeruption deflation using Mogi and prolate spheroid sources to infer volume changes of the magma chamber. We interpret that the inflation was due to magma accumulation in a shallow reservoir beneath Mount Sinabung and attribute the deflation due to magma withdrawal from the shallow reservoir during the eruption as well as thermoelastic compaction of erupted material. The pyroclastic flow extent during the eruption is then derived from the LAHARZ model based on the coeruption volume from InSAR modeling and compared to that derived from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image. The pyroclastic flow inundation extents between the two different methods agree at about 86%, suggesting the capability of mapping pyroclastic flow inundation by combing radar and optical imagery as well as flow modeling.

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“…Following Mazzorana et al [12], process modeling is the first three of five steps to accurately assessing the physical vulnerability of the built environment. A range of recognized methods have been applied to different process models including empirical [7,[18][19][20][21][22][23], empirical-statistical combined with simple flow equations [24], topographic gradient-based [25], numerical-based with the integration of shallow water equations [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41], and smoothed particle hydrodynamics (SPH) or Lagrangian [42][43][44][45][46] (see References [47,48] for review). Of the numerical models, 1-(e.g., DAN-W [28]; DFEM-1D [49]) or 2-(e.g., FLO-2D [27]; RAMMS-DF [35,36]; TopRunDF [7]; MassMov2D [34]) dimensional runout modeling approaches can be adapted.…”

Section: Introductionmentioning

confidence: 99%

Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards

2018

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Sensitivity analysis (SA) describes how varying inputs to a model subsequently varies its outputs. Its inclusion can support the systematic calibration of numerical models to back-calculate intensity properties of past torrent events that would otherwise be difficult or impossible to collect during their occurrence. Sensitivity analysis for model calibration is assessed with the back-calculation of a known torrent event. In particular, FLO-2D, a cell-based numerical model, is used to simulate the 2005 debris flow event that occurred in Brienz, Switzerland. Under 4000 simulations were completed with ranges of physically reasonable parameter values. Model results were compared in 3-dimensions with both sediment deposition extents (x, y) and estimated deposition heights (z) from available post-event images. The comparisons highlighted that more accurate input and validation data, namely the flow behavior of hazardous processes and post-event deposition heights, are required to produce stronger agreements between simulated and observed results. Furthermore, the application of SA for model calibration supports systematic exploration of large parameter spaces characteristic of complex phenomena like natural hazard events. These findings demonstrated how important model input factors can be identified, which provide guidance for future data collection efforts to capture both the rheology and the spatial distribution of hazards more accurately.

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Analyzing debris flows with the statistically calibrated empirical model LAHARZ in southeastern Arizona, USA

Cited by 50 publications

References 16 publications

Rocky Mountain Geo-Conference 2014

Rocky Mountain Geo-Conference 2014

Mapping Pyroclastic Flow Inundation Using Radar and Optical Satellite Images and Lahar Modeling

Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards

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