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Full-Text Articles in Statistical Models
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Master's Theses
Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …
Coastal Wetland Dynamics Under Sea-Level Rise And Wetland Restoration In The Northern Gulf Of Mexico Using Bayesian Multilevel Models And A Web Tool, Tyler Hardy
Master's Theses
There is currently a lack of modeling framework to predict how relative sea-level rise (SLR), combined with restoration activities, affects landscapes of coastal wetlands with uncertainties accounted for at the entire northern Gulf of Mexico (NGOM). I developed such a modeling framework – Bayesian multi-level models to study the spatial pattern of wetland loss in the NGOM, driven by relative RSLR, vegetation productivity, tidal range, coastal slope, and wave height – all interacting with river-borne sediment availability, indicated by hydrological regimes. These interactions have not been comprehensively investigated before. I further modified this model to assess the efficacy of restoration …