Characterization of Environmental Seismic Signals in a Post‐Wildfire Environment: Examples From the Museum Fire, AZ

Abstract

AbstractThe 2019 Museum Fire burned in a mountainous region near the city of Flagstaff, AZ, USA. Due to the high risk of post‐fire 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, lightning 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 test the efficacy of seismic recordings to (a) detect and differentiate between different energy sources, (b) estimate the timing of lightning strikes, (c) calculate rainfall intensities, and (d) determine debris flow timing, size, velocity, and location. We then calculate forward models of seismic signals associated with debris flows and rainfall to better interpret our results and characterize these events. Our observations and modeling show that we can differentiate between these sources and that seismic data can provide insight into post‐fire debris flow characteristics, including relative particle sizes and velocity.