Debris flow, debris avalanche and flood hazards at and downstream from Mount Rainier, Washington

10.3133/ha729 ◽  
1995 ◽  
2001 ◽  
Vol 7 (3) ◽  
pp. 221-238 ◽  
Author(s):  
Oldrich Hungr ◽  
S. G. Evans ◽  
M. J. Bovis ◽  
J. N. Hutchinson

Abstract As a result of the widespread use of the landslide classifications of Varnes (1978), and Hutchinson (1988), certain terms describing common types of flow-like mass movements have become entrenched in the language of engineering geology. Example terms include debris flow, debris avalanche and mudslide. Here, more precise definitions of the terms are proposed, which would allow the terms to be retained with their original meanings while making their application less ambiguous. A new division of landslide materials is proposed, based on genetic and morphological aspects rather than arbitrary grain-size limits. The basic material groups include sorted materials: gravel, sand, silt, and clay, unsorted materials: debris, earth and mud, peat and rock. Definitions are proposed for relatively slow non-liquefied sand or gravel flows, extremely rapid sand, silt or debris flow slides accompanied by liquefaction, clay flow slides involving extra-sensitive clays, peat flows, slow to rapid earth flows in nonsensitive plastic clays, debris flows which occur in steep established channels or gullies, mud flows considered as cohesive debris flows, debris floods involving massive sediment transport at limited discharges, debris avalanches which occur on open hill slopes and rock avalanches formed by large scale failures of bedrock.


Geosphere ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 950-971 ◽  
Author(s):  
Rodolfo Díaz-Castellón ◽  
Bernard E. Hubbard ◽  
Gerardo Carrasco-Núñez ◽  
José Luis Rodríguez-Vargas

Geomorphology ◽  
2014 ◽  
Vol 226 ◽  
pp. 249-260 ◽  
Author(s):  
Nicholas T. Legg ◽  
Andrew J. Meigs ◽  
Gordon E. Grant ◽  
Paul Kennard

2003 ◽  
Author(s):  
James W. Vallance ◽  
Michelle L. Cunico ◽  
Steve P. Schilling
Keyword(s):  

2021 ◽  
Vol 27 (1) ◽  
pp. 29-41
Author(s):  
Kerry Cato ◽  
Brett Goforth

ABSTRACT Historical patterns of debris flows have been reconstructed at the town of Forest Falls in the San Bernardino Mountains using a variety of field methods (mapping flow events after occurrence, dendrochronology evidence, soil chronosequences). Large flow events occur when summer thunderstorms produce brief high-intensity rainfall to mobilize debris; however, the geomorphic system exhibits properties of non-linear response rather than being a single-event precipitation-driven process. Previous studies contrasted the relative water content of flows generated by varying-intensity summer thunderstorms to model factors controlling flow velocity and pathway of deposition. We hypothesize that sediment discharge in this geomorphic system exhibits multiple sources of complexity and present evidence of (1) thresholds of sediment delivery from sources at the higher reaches of bedrock canyons, (2) storage effects in sediment transport down the bedrock canyons, and (3) feedbacks in deposition, remobilization, and transport of sediment across the alluvial fan in dynamic channel filling, cutting, and avulsion processes. An example of the first component occurred in March 2017, when snowmelt generated a rapid translational landslide and debris avalanche of about 80,000 m3; this sediment was deposited in the bedrock canyon but moved no farther down gradient. The second component was observed when accumulation of meta-stable sediments in the bedrock canyon remained in place until fluvial erosion and subsequent debris flow provided dynamic instability to remobilize the mass downstream. The third component occurred on the alluvial fan below the bedrock canyon, where low-water-content debris flows deposited sediments that filled the active channel, raising the channel grade level to levee elevation, allowing for subsequent spread of non-channelized flows onto the fan surface and scouring new channel pathways down fan. A conceptual model of spatial and temporal complexities in this debris-flow system is proposed to guide future study for improved risk prediction.


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