Joint Inversion of Gravity Anomaly and Seismic Data for Improved Crustal Imaging in the Guangdong–Hong Kong–Macao Greater Bay Area

Abstract

Satellite-derived gravity observations provide important constraints on subsurface structure variations, but are limited by poor depth resolution and strong nonuniqueness. Integrating gravity data with seismic data offers an effective approach for improving crustal imaging in tectonically complex regions. Compared with single dataset inversions, the joint inversion greatly improves model resolution and reduces inversion nonuniqueness. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA), located in southern China, is a highly urbanized region with a dense population and strong economic activity. In this study, we built a crustal S-wave velocity and density model of the GBA by joint inversion of gravity anomaly and seismic data. The results show that the crustal structure is very complex. In the shallow crust, the crustal model correlates well with major geological units, and the Pearl River Delta exhibits a prominent low-velocity anomaly associated with thick sedimentary layers, reflecting mechanically weak crust. The seismic events are preferentially located in the transition zone between high-velocity and low-velocity anomalies in the upper crust. At 30 km depth, there is a prominent north-south trending high-velocity anomaly, which may be related to the uplift of the Moho interface. These results show that joint inversion of gravity and seismic data provides an effective strategy for crustal imaging in tectonically complex regions and offers improved constraints for seismic hazard assessment.