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High-resolution surface faulting from the 1983 Idaho Lost River Fault M(w) 6.9 earthquake and previous events

We present high-resolution mapping and surface faulting measurements along the Lost River fault (Idaho-USA), a normal fault activated in the 1983 (M(w) 6.9) earthquake. The earthquake ruptured ~35 km of the fault with a maximum throw of ~3 m. From new 5 to 30 cm-pixel resolution topography collected...

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Detalles Bibliográficos
Autores principales: Bello, Simone, Scott, Chelsea P., Ferrarini, Federica, Brozzetti, Francesco, Scott, Tyler, Cirillo, Daniele, de Nardis, Rita, Arrowsmith, J Ramón, Lavecchia, Giusy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910603/
https://www.ncbi.nlm.nih.gov/pubmed/33637767
http://dx.doi.org/10.1038/s41597-021-00838-6
Descripción
Sumario:We present high-resolution mapping and surface faulting measurements along the Lost River fault (Idaho-USA), a normal fault activated in the 1983 (M(w) 6.9) earthquake. The earthquake ruptured ~35 km of the fault with a maximum throw of ~3 m. From new 5 to 30 cm-pixel resolution topography collected by an Unmanned Aerial Vehicle, we produce the most comprehensive dataset of systematically measured vertical separations from ~37 km of fault length activated by the 1983 and prehistoric earthquakes. We provide Digital Elevation Models, orthophotographs, and three tables of: (i) 757 surface rupture traces, (ii) 1295 serial topographic profiles spaced 25 m apart that indicate rupture zone width and (iii) 2053 vertical separation measurements, each with additional textual and numerical fields. Our novel dataset supports advancing scientific knowledge about this fault system, refining scaling laws of intra-continental faults, comparing to other earthquakes to better understand faulting processes, and contributing to global probabilistic hazard approaches. Our methodology can be applied to other fault zones with high-resolution topographic data.