Evaluating Road Resilience to Wildfires: Case Studies of Camp and Carr Fires
Research Team: Somayeh Nassiri (lead), Changmo Kim, Ali A. Butt, Ali Zarei, Rongzong Wu, Jeremy D. Lea, and Jessica Erdahl
UC Campus(es): UC Davis
Problem Statement: Increasing wildfires in recent years have exposed California communities to greater risks. The associated impact of evacuation, rescue, and recovery operations on the physical conditions of the local and highway road network has not been sufficiently studied. This knowledge gap in capital damage impairs local officials in planning and securing federal and state funds for repair, rebuilding, and resilience to future fires.
Project Description: This project focused on two large fires, the Camp and Carr fires between 2017 and 2018. After fires, road infrastructure is crucial for safe removal of hazardous materials and waste to landfills and recycling facilities. Despite the critical role of pavements in this process, there has been little quantitative evaluation of the potential damage to pavements from truck traffic for debris removal. To address this knowledge gap, data on truck trip numbers and debris tonnage following the Camp and Carr Fires were used to calculate changes in equivalent single axle loads and traffic index over the pavement’s design life (the age at which reconstruction would be considered). Simulations were conducted on existing pavement structures to assess potential additional damage based on increased traffic indices. Pavement structural design simulations showed that out of the nine studied highways, one exhibited a reduction in cracking life of about two years from debris removal operations. However, fatigue cracking was significantly accelerated for Skyway, the major road in the Town of Paradise, failing 14.3 years before its design life. A methodology similar to the one presented in this study can be adopted in debris management planning to strategically avoid vulnerable pavements and minimize damage to the highway network.
Status: Completed
Budget: $50,000