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Providing early warning for flooding in the Yellowstone National Park using ambient seismic noise
  • Bingxu Luo,
  • Hejun Zhu,
  • David Lumley
Bingxu Luo
Department of Sustainable Earth Systems Sciences, The University of Texas at Dallas

Corresponding Author:[email protected]

Author Profile
Hejun Zhu
Department of Sustainable Earth Systems Sciences, The University of Texas at Dallas, Department of Physics, The University of Texas at Dallas
David Lumley
Department of Sustainable Earth Systems Sciences, The University of Texas at Dallas, Department of Physics, The University of Texas at Dallas

Abstract

We utilize twelve-year ambient seismic noise (ASN) recordings to measure near-surface seismic velocity variations (dv/v) within the YNP flooding watersheds. We have observed that the annual peaks of dv/v variations have two to three months lead-time in comparison to anomalous water discharges. Our analysis indicates that the annual cycle of dv/v is highly correlated with the effective precipitation, which takes into account the snowpack loading and melting water infiltration processes. The annual peaks of dv/v are likely caused by abnormal melt water, which exceed the water storage capacity of the land. Furthermore, the best-fit poroelastic model provides further evidence that precipitation factors primarily influence the variations of the seismic field. Our analysis successfully explains the indicative changes in dv/v prior to the 2014 and 2022 YNP floods. This study demonstrates the potential of using seismic observables to monitor and assess the risk of devastating floods in the YNP.  
21 Mar 2024Submitted to ESS Open Archive
21 Mar 2024Published in ESS Open Archive