Graduate Thesis Or Dissertation
 

Post-wildfire Investigation of Civil Infrastructure Following the 2018 Camp Fire

Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/6t053p60n

Descriptions

Attribute NameValues
Creator
Abstract
  • Wildland-urban interface (WUI) communities, where forested land boundaries or intermixes with infrastructure, are quickly growing in the US. WUI communities have grown substantially from 1990 to 2010, with an increase of 12.7 million houses and 25 million people. Wildfires encroaching on WUI communities can cause damage to both above ground structures and underground utilities, severely impacting the functionality of buildings, facilities, and communities in general. Wildfires have caused unprecedented damage in the last three years, particularly in California. Specifically, the 2018 California Camp Fire was the most destructive and deadliest fire in the state’s history, destroying 90% of the housing stock in Paradise and damaging the water distribution system infrastructure, which caused contamination of the drinking water. Currently there is no consensus among the disaster science community for conducting investigations of civil infrastructure following wildfires or tools to directly measure or quantify fire exposure to infrastructure from these wildfires. The overarching goal of this thesis is to demonstrate that multi-disciplinary data collection is needed to obtain a comprehensive overview of the damages to the infrastructure and impacts of the wildfire damages on the community. During numerous reconnaissance trips to Paradise in 2019, a variety of pre- and post-fire data was collected (photographs, light detection and ranging [LiDAR] scans, drone footage, interviews, geospatial information etc.). The data collection was focused on schools, healthcare facilities, and water infrastructure as the operability of these systems has a large influence on the health, vitality, and recovery of communities following disasters. All the data collected was used to perform multi-scale investigations of infrastructure discussed in this thesis. First, the damage to schools and hospital in Paradise were documented. Common damage types that hindered reopening of facilities included damage to utilities. Then, multiple layers of geospatial data collected on the water distribution system infrastructure was spatially analyzed to determine a method for quantifying the burn severity within WUI communities, as traditional methods cater to purely wildland fires. The data was also used to show that there is a positive relationship between burn severity and the presence of contaminants in the water distribution system. Fragility functions for predicting water contamination based on burn severity are developed and can be used to predict locations of contamination in Paradise and Santa Rosa, CA. Finally, the structural behavior of one of the school buildings in Paradise is analyzed in more detail using a developed post-wildfire damage assessment methodology. Existing methods for estimating a fire within a compartment in a building are used to define a range of fire scenarios in the building. A three-dimensional finite element model of the building’s frame is then subjected to the fire curves to analyze the behavior and is compared to measured deformations from the LiDAR data.
License
Resource Type
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Rights Statement
Related Items
Funding Statement (additional comments about funding)
  • This research was funded by a DeVaan Fellowship for Clean Water Technology (2019), a Natural Hazards Center Quick Response grant, a National Science Foundation (NSF) RAPID Response grant (grant number CMMI 1917298 and 1917316), and by the Cascadia Lifelines Program.
Publisher
Peer Reviewed
Language
Embargo reason
  • Pending Publication
Embargo date range
  • 2020-09-17 to 2021-10-18

Relationships

Parents:

This work has no parents.

In Collection:

Items