Kelkar, Kaytan Anand (2017-12). Mass Movement Phenomena in the Western San Juan Mountains, Colorado. Master's Thesis. Thesis uri icon

abstract

  • Mass movement is an integral part of the evolution of hillslope morphology, which poses a potential hazard to human activity in mountainous terrain. The San Juan Mountains of southwestern Colorado have an ongoing legacy of slope instability as a result of a complex geologic setting compounded by high-relief topography. Although, landslide studies in the area have focused on the documentation of triggers for slope failure and field mapping, inadequate investigation of components responsible for susceptibility to mass movement still exists. The area was last extensively mapped for mass movement deposits during the 1970s, since then landslide studies have not been undertaken. Therefore, this leads one to ask major questions pertaining to the risk from mass movement in the San Juan Mountains: What are the major components that cause slopes to fail in the San Juan Mountains? And what is the distribution of surficial phenomena, which indicate potential hazards from slope failure? The aforementioned questions were addressed by fulfilling the following objectives: 1) Identify various components associated with slope failure in the San Juan Mountains; 2) Map areas susceptible to mass movement; and 3) Map features of mass movement in the area. To accomplish these objectives, a 3D Geographic Information Systems (GIS)-based weighted overlay approach was utilized to map susceptibility to landslides. The weighted overlay method was applied in two-phases, including a heuristic approach and a Principal Component Analysis (PCA) technique. This weighted overlay integrated six terrain variables: slope and slope length, aspect, geology, vegetation cover, and soil drainage. A surficial geomorphological map at a scale of 1:3,000 was constructed, to map the surficial extent of geomorphic phenomenon in the region. The findings of this study suggests that: 1) Aspect (48%), slope (34%), and geology (9%) have the greatest relative weighted influence on slope failure, 2) the San Juan Mountains are experiencing a general uniform rate of erosion, 3) East and west-facing slopes have the greatest areal coverage and increase the likelihood of high and very high susceptibility to landslides, 4) Class 2 slopes (22.01?- 44?) have the greatest areal coverage also increasing the likelihood for high and very high susceptibility to landslides, 5) Class 2, 3, and 4 slopes are highly correlated to high susceptibility, classes 3 and 4 are highly correlated to very high susceptibility 6) Areas within 50 m from roads are highly susceptible to landslides, 7) Talus and landslide deposits are the most widespread surficial deposits in the area 8) Mapped landforms demarcate the extents of former glaciation of the western San Juan Mountains. With growing anthropogenic influence in the area, human-induced modification of steep slopes is occurring. A study such as this, combining emerging geospatial, visualization, heuristic, deterministic, and statistical techniques will improve landslide prediction in mountain terrain.
  • Mass movement is an integral part of the evolution of hillslope morphology, which poses a potential hazard to human activity in mountainous terrain. The San Juan Mountains of southwestern Colorado have an ongoing legacy of slope instability as a result of a complex geologic setting compounded by high-relief topography. Although, landslide studies in the area have focused on the documentation of triggers for slope failure and field mapping, inadequate investigation of components responsible for susceptibility to mass movement still exists. The area was last extensively mapped for mass movement deposits during the 1970s, since then landslide studies have not been undertaken. Therefore, this leads one to ask major questions pertaining to the risk from mass movement in the San Juan Mountains: What are the major components that cause slopes to fail in the San Juan Mountains? And what is the distribution of surficial phenomena, which indicate potential hazards from slope failure?
    The aforementioned questions were addressed by fulfilling the following objectives: 1) Identify various components associated with slope failure in the San Juan Mountains; 2) Map areas susceptible to mass movement; and 3) Map features of mass movement in the area. To accomplish these objectives, a 3D Geographic Information Systems (GIS)-based weighted overlay approach was utilized to map susceptibility to landslides. The weighted overlay method was applied in two-phases, including a heuristic approach and a Principal Component Analysis (PCA) technique. This weighted overlay integrated six terrain variables: slope and slope length, aspect, geology, vegetation cover, and soil drainage. A surficial geomorphological map at a scale of 1:3,000 was constructed, to map the surficial extent of geomorphic phenomenon in the region.
    The findings of this study suggests that: 1) Aspect (48%), slope (34%), and geology (9%) have the greatest relative weighted influence on slope failure, 2) the San Juan Mountains are experiencing a general uniform rate of erosion, 3) East and west-facing slopes have the greatest areal coverage and increase the likelihood of high and very high susceptibility to landslides, 4) Class 2 slopes (22.01?- 44?) have the greatest areal coverage also increasing the likelihood for high and very high susceptibility to landslides, 5) Class 2, 3, and 4 slopes are highly correlated to high susceptibility, classes 3 and 4 are highly correlated to very high susceptibility 6) Areas within 50 m from roads are highly susceptible to landslides, 7) Talus and landslide deposits are the most widespread surficial deposits in the area 8) Mapped landforms demarcate the extents of former glaciation of the western San Juan Mountains.
    With growing anthropogenic influence in the area, human-induced modification of steep slopes is occurring. A study such as this, combining emerging geospatial, visualization, heuristic, deterministic, and statistical techniques will improve landslide prediction in mountain terrain.

publication date

  • December 2017