Characterization of Environmental Seismic Signals in a Post-Wildfire
Environment: Examples from the Museum Fire, AZ
Abstract
The 2019 Museum Fire burned in a mountainous region near the city of
Flagstaff, AZ, USA. Due to the high risk of post-wildfire debris flows
and flooding entering the city, we deployed a network of seismometers
within the burn area and downstream drainages to examine the efficacy of
seismic monitoring for post-fire flows. Seismic instruments were
deployed during the 2019, 2020, and 2021 monsoon seasons following the
fire and recorded several debris flow and flood events, as well as
signals associated with rainfall, lighting and wind. Signal power,
frequency content, and wave polarization were measured for multiple
events and compared to rain gauge records and images recorded by cameras
installed in the study area. We use these data to demonstrate the
efficacy of seismic recordings to (1) detect and differentiate between
different energy sources, (2) estimate the timing of lightning strikes,
(3) calculate rainfall intensities, and (4) determine debris flow
timing, size, velocity, and location. This work confirms the validity of
theoretical models for interpreting seismic signals associated with
debris flows and rainfall in post-wildfire settings and demonstrates the
efficacy of seismic data for identifying and characterizing debris
flows.