Using receiver functions, Rayleigh wave phase velocity dispersion determined from ambient noise and teleseismic earthquakes, and Rayleigh wave horizontal to vertical ground motion amplitude ratios from earthquakes observed across the PLUTONS seismic array, we construct a one-dimensional (1-D) S-wave velocity (Vs) seismic model with uncertainties for Uturuncu volcano, Bolivia, located in the central Andes and overlying the eastward-subducting Nazca plate. We find a fast upper crustal lid placed upon a low-velocity zone (LVZ) in the mid-crust. By incorporating all three types of measurements with complimentary sensitivity, we also explore the average density and Vp/Vs (ratio of P-wave to S-wave velocity) structures beneath the young silicic volcanic field. We observe slightly higher Vp/Vs and a decrease in density near the LVZ, which implies a dacitic source of the partially molten magma body. We exploit the impact of the 1-D model on full moment tensor inversion for the two largest local earthquakes recorded (both magnitude ∼3), demonstrating that the 1-D model influences the waveform fits and the estimated source type for the full moment tensor. Our 1-D model can serve as a robust starting point for future efforts to determine a three-dimensional velocity model for Uturuncu volcano.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OCRF-2014-CRG3-2300
Acknowledgements: The authors are grateful to George Zandt and an anonymous reviewer for insightful comments that improved this paper. The facilities of the Incorporated Research Institutions for Seismology (IRIS) Data Management System (DMS) and specifically the IRIS Data Management Center were used to access the waveform and metadata required in this study. The IRIS DMS is funded through the National Science Foundation and specifically the GEO Directorate through the Instrumentation and Facilities Program of the National Science Foundation (NSF) under Cooperative Agreement EAR-0552316. This research was supported by NSF grants EAR-1215959 and EAR-0909254 at the University of Alaska, NSF grant CyberSEES-1442665 (to F.-C.L.) and the King Abdullah University of Science and Technology (KAUST) under award OCRF-2014-CRG3-2300 (to F.-C.L.), and NSF grant EAR-0952154 (to W.S.) at Washington University in St. Louis.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.