Developing detailed landslide inventory maps of prehistoric landslides is essential to interpret the frequency and conditions under which slopes have failed. When coupled with age estimates, landslide inventories can yield better predictions for future slope failures, thereby improving hazard assessments and increasing chances for mitigation. Developing proxies for landslide age is an important area of research, but age dating prehistoric landslides can be challenging due to sparse datable organic material within landslide deposits, and to time or access constraints. In this thesis, surface roughness of the landslide deposit is used to construct a best-fit age-roughness model that quantitatively assigns age based on smoothing of the deposit with time for landslides in the Green River Valley (GRV), located in King County, Washington. Hillslopes in the valley are composed of glacial sediments and are prone to failure caused by three main triggers: over steepening caused by lateral migration of the Green River, Holocene climatic change (precipitation and temperature), and seismicity (Cascadia Subduction Zone and the Seattle Fault). We examine the distribution of landslides in the GRV using high-resolution lidar data and find a threshold relief of approximately 60 m corresponds to landslide locations. Four dated samples with ages ranging from 492 to 0 cal. BP defined age-roughness models that showed 44 to 51 of the 61 mapped landslides occurred from 5000 to 100 cal. BP, after the climate changed to cooler and wetter conditions. These 61 landslides, on average, decrease in age as you move upstream, consistent with upstream migration of a knickzone. From these age-roughness models the GRV has a recurrence interval of one landslide every 38 years since 1000 cal. BP (26 landslides/1000 years), which has implications for managing landslide hazards.
|Commitee:||Fountain, Andrew G, Burns, Scott, Perkins, Jonathan|
|School:||Portland State University|
|School Location:||United States -- Oregon|
|Source:||MAI 81/4(E), Masters Abstracts International|
|Keywords:||age dating, climate change, Landslides, prehistoric, surface roughness|
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