Description
Evaluating the impact of weight exerted by settled snow (i.e., snow load) on structures poses numerous statistical challenges, including missing data, biased distribution parameters, and the influence of climate change. This dissertation aims to address challenges related to the use both direct and indirect measurements of snow load (or equivalently, snow water equivalent), as well as the anticipated impact of climate change on future extreme snow loads. The first paper within this dissertation investigates short-term snow loads by comparing various techniques for estimating extreme values of short-term snow accumulations. Additionally, the first paper includes a comparative analysis of short-term and long-term snow accumulations, revealing significant differences in snow load accumulation patterns across geographical regions. The second paper focuses on bias correction in the scale parameter of the generalized extreme value distribution describing extreme snow loads in situations where the snow load is estimated indirectly using snow depth data. The bias correction is accomplished using bootstrap techniques when some of the snow load data is only approximated, rather than directly measured. We demonstrate the effectiveness of our approach in correcting scale parameter bias, as evidenced by simulation studies and real-life snow data. In the third paper, we incorporate the effects of climate change in the snow load estimation process and discuss the implications of considering the effects of climate change in snow load design. Our findings indicate that most locations in the United States have a reduced risk of snow-induced structural failure in a future climate. However, other locations appear to have an increased risk of structure failure, though there is no agreement among climate models as to which areas are at increased risk. Together, these interconnected papers refine methods for characterizing extreme snow accumulations and address the statistical complexities of estimating design snow loads for both current and future conditions.
Author ORCID Identifier
https://orcid.org/0000-0002-3899-5643
https://orcid.org/0000-0002-2853-0455
Document Type
Dataset
DCMI Type
Dataset
File Format
.txt, .xlsx, .csv, .tif, .json, .r
Publication Date
9-9-2024
Funder
The National Oceanic and Atmospheric Administration (NOAA)
Publisher
Utah State University
Award Number
NOAA award # 3076731
Methodology
This deposit includes the dataset, model, R functions, and R scripts used in the aforementioned dissertation. The dissertation is divided into three papers, with separate folders containing the code for Papers 1, 2, and 3.
Language
eng
Disciplines
Data Science | Earth Sciences
License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Pomeyie, Kenneth and Bean, Brennan, "Supplementary files for "Impact of Snow Accumulation on Structural Integrity: Present and Future Perspectives"" (2024). Browse all Datasets. Paper 237.
https://digitalcommons.usu.edu/all_datasets/237