Deciphering controls for debris-flow erosion derived from a LiDAR-recorded extreme event and a calibrated numerical model (Roßbichelbach, Germany)

Andreas Dietrich, Michael Krautblatter

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Debris flows are among the most destructive and hazardous mass movements on steep mountains. An understanding of debris-flow erosion, entrainment and resulting volumes is a key requirement for modelling debris-flow propagation and impact, as well as analysing the associated risks. As quantitative controls of erosion and entrainment are not well understood, total volume, runout and impact energies of debris flows are often significantly underestimated. Here, we present an analysis of geomorphic change induced by an erosive debris-flow event in the German Alps in June 2015. More than 50 terrestrial laser scans of a 1.2 km long mountain torrent recorded geomorphic change in comparison to an airborne laser scan performed in 2007. Errors were calculated using a spatial variable threshold based on the point density of airborne laser scanning and terrestrial laser scanning and the slope of the digital elevation models. Highest erosion rates approach 5.0 m3/m2 (mean 0.6 m3/m2). During the event 9550 ± 1550 m3 was eroded whereas only 650 ± 150 m3 was deposited in the channel. Velocity, flow pressure, momentum and shear stress were calculated using a carefully calibrated RAMMS Debris Flow model including material entrainment. Here we present a linear regression model relating debris-flow erosion rates to momentum and shear stress with an R2 up to 68%. Channel transitions from bedrock to loose debris sections cause excessive erosion up to 1 m3/m2 due to previously unreleased random kinetic energy now available for erosion.

Original languageEnglish
Pages (from-to)1346-1361
Number of pages16
JournalEarth Surface Processes and Landforms
Volume44
Issue number6
DOIs
StatePublished - May 2019

Keywords

  • LiDAR
  • change detection
  • debris flow
  • erosion processes
  • numerical model

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