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Avalanche Characteristics With Distributed Acoustic Sensing Near Milford Sound/Piopiotahi, New Zealand

Snow avalanches are a major natural hazard that pose significant risks to alpine environments in terms of safety and infrastructure maintenance, and are often highly unpredictable. Fiordland’s Milford Sound/Piopiotahi is part of the Southern Alps/Kā Tiritiri o te Moana, and is characterized by heavy precipitation, steep glacier-carved topography, and rapid erosion. Milford Sound/Piopiotahi attracts over 800,000 visitors annually, with most arriving by road. State Highway 94, also known as Milford Road, the road connecting Milford Sound/Piopiotahi to the rest of New Zealand, is monitored by the Milford Road Alliance, which uses various types of observations (e.g., weather forecasts, meteorological data, webcams, infrasound sensors) to manage avalanche risk. While this system provides valuable information for hazard management, the timing and spatial accuracy of avalanche records can be limited, particularly for events occurring farther from the road or during nighttime hours.

We repurpose a dark telecommunication fiber running along Milford Road, which starts from Milford Sound/Piopiotahi and crosses several avalanche-prone regions, as part of the Fiordland Seismological Sounding of Landslides and Earthquakes (FISSLE) project. This results in a 31 km long Distributed Acoustic Sensing (DAS) array. The DAS array recorded 164 avalanches, both natural and triggered, between June and September 2024. We apply signal processing techniques to detect and characterise avalanche events on the recorded data. We analyse the spatio-temporal evolution of the waveforms and frequency content of different types of avalanche signals (e.g., wet slab, storm slabs). Weather data indicate that the natural avalanches examined here occurred during local peaks in precipitation.

Session: Fiber-Optic Sensing Applications in Seismology and Environmental Science [Poster]

Type: Poster

Room: Exhibit Hall A+B

Date: 4/17/2026

Presentation Time: 08:00 AM (local time)

Presenting Author: Meghan Miller

Student Presenter: No

Invited Presentation: 

Poster Number: 82

Additional Authors