33 D1. Economic, Energy, and Engineering Geology (Posters)

Saturday, 21 March 2020
8:00 AM - 12:00 PM
Grand Ballroom A–D

AUTOMATED MAPPING OF DEBRIS FLOW SITES BASED ON SURFACE ROUGHNESS OF DIGITAL ELEVATION MODELS (DEMS)

Paper number: 33-5
Program: Technical Sessions
Time: 8:00 AM – 12:00 PM

Authors

Abstract

Debris flows are a type of slope failures affecting mountainous regions covered with thick colluvial mantle. Debris flow events usually follow heavy rainfall events that trigger powerful downhill flow of rock/soil within stream channels resulting in loss of lives and property destruction. Since it is difficult to determine factors of safety against debris flow initiation, geologists and engineers evaluate slopes’ susceptibility to debris flows using statistical predictive models. These predictive models are built by studying past debris flows and their relationships with factors including intensity/amount of rainfall, availability of colluvium, slope angle and bedrock structure. Mapping previous debris flow sites is therefore an important part of susceptibility studies. The availability of high resolution bare earth digital elevation models (DEMs) has presented an opportunity to visually identify sites of previous debris flows. Visual identification can be an extremely lengthy process and we therefore propose using automated mapping techniques to efficiently locate first order streams affected by debris flows. From observations, first order streams where debris flows were initiated appear to have rough surfaces as compared to those that were not. We then used various DEM-extracted parameters to characterize roughness of first order streams on the Blue Ridge Mountains of Virginia where two major debris flow events from 1969 and 1995 took place in the recent past. The parameters include coefficient of variation of elevation, slope gradient, laplacian, and eigenvalues. All parameters showed significant differences in roughness between first order streams that were and were not affected by debris flows. We also propose a logistic regression model to identify first order streams affected by debris flows allowing a more efficient mapping methodology.

Geological Society of America Abstracts with Programs. Vol. 52, No. 2

doi: 10.1130/abs/2020SE-344666

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