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Empirical rules for debris flow travel distance : a comparison of field data

University of British Columbia

Assessment of debris flow travel distance is an essential part of landslide risk management. Confidence in applying empirical rules in conditions different from their original study area is generally small. This research provides a systematic, quantitative approach to assess the utility of an empirical-statistical tool (UBCDFLOW), originally developed for the Queen Charlotte Islands, in the Kootenay area with different geo-bio-climatic conditions. High quality ground-based debris flow volume measurements are essential for this research. A systematic traversing method is described and illustrated for two example events. It is particularly useful to analyse volume change processes (entrainment, deposition), quantify volume magnitudes and examine travel distances. Data gathered can be used to compare debris flow inventories and run a variety of empirical or dynamic analysis tools. Compared to the Queen Charlotte Islands (QCI) the Kootenay study area has different geo-bio-climatic conditions, with larger event magnitudes and travel distances. Similarities were found for dominant volume change processes as a function of slope angles. Average yield rates in the Kootenays (2 to 3m³/m) are significantly smaller than on the QCI (12 and 23 m³/m). Applicability of UBCDFLOW in the Kootenay area is evaluated based on three quantitative measures for simulation success regarding volume change process, magnitude and travel distance. The empirical rules capture the volume change process (entrainment, deposition) correctly for 80% of the lengths in the Kootenay inventory and therefore appear to be portable from the QCI location. However the regression equations overestimate the magnitude of volume change. In total, 15 out of 22 simulations terminate within 89 and 110% of the observed travel distance; the remaining 7 simulations exceed it by more than 110%. Concerns that UBCDFLOW is sensitive to variations in slope angle input (±2°) are addressed in a Monte Carlo type analysis. For 13 (of 22) events, simulation of process is found sensitive, and 11 (of 22) experience considerable uncertainty in volume estimation, which ultimately yields uncertainty of travel distance estimate. Based on confidence limits for volume estimates and travel distance exceedance probability, the Monte Carlo simulation output allows more informed decision making.

Text

2010-08-20

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/27569

Civil Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/