Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog

• Published in: Geophysical research letters 2022-06, Vol.49 (12), p.n/a
• Main Authors: Chen, Han, Yang, Hongfeng, Zhu, Gaohua, Xu, Min, Lin, Jian, You, Qingyu
• Format: Article
• Language: English
• Subjects: Clustering; Deformation; Depth; Earthquakes; EQTransformer; Fault lines; Faults; Geological faults; Hydration; Learning algorithms; Machine learning; Mariana Subduction Zone; Ocean bottom; ocean bottom seismometer; Ocean bottom seismometers; Ocean floor; Oceanic trenches; Oceans; outer‐rise fault; Phase detectors; Plates; Resolution; Seismic activity; Seismographs; Seismometers; Subduction; Subduction (geology); Subduction zones; Water depth; Waveforms
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2022GL097779

Outer‐rise faults are predominantly concentrated near ocean trenches due to subducted plate bending. These faults play crucial roles in the hydration of subducted plates and the consequent subducting processes. However, it has not yet been possible to develop high‐resolution structures of outer‐rise faults due to the lack of near‐field observations. In this study we deployed an ocean bottom seismometer (OBS) network near the Challenger Deep in the Southernmost Mariana Trench, between December 2016 and June 2017, covering both the overriding and subducting plates. We applied a machine‐learning phase detector (EQTransformer) to the OBS data and found more than 1,975 earthquakes. An identified outer‐rise event cluster revealed an outer‐rise fault penetrating to depths of 50 km, which was inferred as a normal fault based on the extensional depth from tomographic images in the region, shedding new lights on water input at the southmost Mariana subduction zone. Plain Language Summary Estimating water input at subduction zones plays a crucial role in understanding the material cycles of the Earth and subduction zone dynamics. As outer‐rise faults provide the primary channel for water to penetrate into the incoming plate, investigating the generation and extent of outer‐rise faults is thus an effective way to understand the hydration degree. However, high‐resolution structure of outer‐rise faults is not common due to the lack of near‐field observations. In this study, we apply a machine‐learning phase detector (EQTransformer) to a new ocean bottom seismometer data set at the southernmost Mariana Subduction Zone. After careful analysis of earthquake location and clustering, we find a deep outer‐rise fault extending to 50 km in depth. We interpret the fault as a normal fault based on the depth range of a cluster of events with high waveform similarity. Such a deep outer‐rise fault implies much higher water input at southern most Mariana than had been previously estimated. Key Points A machine‐learning phase detector (EQTransformer) was applied to nearfield ocean bottom seismometer data at the southernmost Mariana trench The outer‐rise seismicity at the southernmost Marina trench varied along the trench, with one identified cluster We identified an outer‐rise fault that penetrates to depths of 50 km