|FDSN code||X3 (2018-2018)||Network name||Seismic Characterization and Tracking of Flash Floods in a Post-Fire Arid Canyon System (Seismic Study of Post-Fire Flash Floods)|
|Start year||2018||Operated by||
|End year||2018||Deployment region||United States of America|
We plan to record and characterize seismic signals that are generated by monsoon-season flash floods within an arid canyon system, downslope of a recent burn area in Arizona. Our goal is to identify the frequency bands most affected by the passage of nearby flash floods in a particular canyon system, then use the amplitude variations of seismic noise to trace the floods’ spatiotemporal paths. To this end, we will deploy a dense local network of mainly short-period seismometers - instruments loaned from IRIS PASSCAL augmented by one broadband sensor from USF - plus two trail cameras to document daytime flooding events and a weather station to measure meteorological data in the field area. The exact field site will be selected from among several recent burn areas - probably from last year's fire season - which are upslope of flash flood-prone canyons, depending on permission from the relevant National Forest offices. We are currently requesting permission to install instruments around several likely post-fire flood channels, particularly Kellner Canyon in the Tonto National Forest; for the safety of the instruments, we will install on high ground and at a sufficient distance from the flood channel(s). We plan to deploy the network in late spring 2018 (~May), record during the monsoon season, and retrieve the instruments at the end of the monsoon season (September-October). Due to the proximity of the field area to PASSCAL, we plan to use U-Haul trucks to transport instruments from Socorro to the field and back. We request 12 sensors (three-component L22-3D short-period but a few could be medium- or broadband sensors if available) and 12 RT130 digitizers plus ancillary equipment (solar panels, power boxes, GPS units, 36 CF cards, and quick-deploy boxes).
|Digital Object Identifier (DOI)||https://doi.org/10.7914/SN/X3_2018|
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