Advancing regional analysis of road infrastructure exposure to fault displacement hazard: A New Zealand case study
Year: 2025
Type: article
Abstract: We developed a regional approach to quantify road infrastructure exposure to fault displacement hazard (FDH) that adopts Fault Displacement Hazard Analysis (FDHA) principles and addresses scale-specific challenges for emergency management and systems-level planning. FDH represents potential ground movement from surface-rupturing earthquakes, which can severely impact nearby infrastructure. This methodology assesses New Zealand's road network exposure and vulnerability to FDH by generating displacement curves from historical rupture data and modelling displacement around active faults using the NZ Community Fault Model. A new 1D strain measure along roads combined with normalized slip-rate data revealed areas of elevated hazard, assessed using geomorphon land classes as proxies for vulnerability. We focused on critical transport routes, particularly State Highways, identifying high-risk regions where road-fault intersections are common, faults are fast-slipping, and terrain is steep. Four high-risk areas emerged: Wellington, the Eastern North Island, the West Coast, and the Upper South Island. The Wellington region is particularly vulnerable where roads intersect the Hutt Valley and Wairarapa Faults, while sections of State Highway 6 along the Alpine Fault in the West Coast are at heightened risk. This analysis underscores the need for targeted mitigation, such as fault avoidance, strategic use of unconsolidated fill, and rapid post-event repair. Our findings provide essential insights into infrastructure resilience planning for transport and other critical systems in seismically active areas.
Authors: Joshua M. Daglish, Timothy Stahl, Andrew Howell, Liam Wotherspoon
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,200
Funders: Earthquake Commission, QuakeCoRE
OpenAlex ID: W4409017550
