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Seismicity Clustering and Statistical Modeling of the Intermediate-Depth Earthquakes in the Weber Deep, Banda Arc

  • Andrean Vesalius Hasiholan Simanjuntak*
  • , Kutubuddin Ansari
  • , Maria Kagda
  • , Lindung Zalbuin Mase
  • , Adi Susilo
  • , Anne Meylani Magdalena Sirait
  • , Yusran Asnawi
  • , Muhammad Zainuddin Lubis
  • , Ratri Andinisari
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We analyzed seismicity clustering and source mechanisms of intermediate-depth earthquakes in the Weber Deep, Banda Arc, with a focus on the 2023 Mw 7.6 Tanimbar event. Using joint Bayesian moment tensor inversion and nearest-neighbor clustering in the space-time-depth-magnitude (STDM) domain, we identified a thrust faulting source mechanism-oriented NW-SE at a depth of 108 ± 3 km, dominated by a double-couple component (92%). Centroid position was shifted 6 km south and 8 km east, with uncertainties estimated at ± 3 km. Seismicity from 2019 to 2023 exhibited a unimodal clustering pattern, indicating a single dominant seismogenic process, consistent with the uniform geometry of the Indo-Australian slab subducting beneath the Banda Arc. The time interval between events contributed most to clustering (45.83%), highlighting temporal controls on seismicity. The findings refine understanding of slab deformation beneath the Banda Arc and provide implications for seismic hazard, supporting infrastructure resilience and disaster planning in eastern Indonesia. The STDM framework, combined with full-waveform inversion, demonstrates robust applicability for tectonic and hazard studies in complex subduction environments.

Original languageEnglish
Article number214
JournalTransportation Infrastructure Geotechnology
Volume12
Issue number6
DOIs
Publication statusPublished - Aug 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Bayesian inversion
  • Earthquake clustering
  • Molucca
  • Seismicity
  • Spatial multivariate

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