3D-SCS: Three-dimensional lithospheric-scale structural and density model of the South China Sea

DOI

We present a comprehensive 3D lithospheric-scale model of the South China Sea region (SCS), which reveals the structural configuration of the area. This model delineates seven distinct geological units: (1) seawater, (2) sedimentary cover, (3) continental crystalline crust, (4) oceanic crust, (5) upper lithospheric mantle, (6) lower lithospheric mantle, and (7) sub-lithospheric mantle. The model covers an area of 960 km × 1260 km and reach down to a depth of 250 km. It is provided as uniformly spaced grids with 10 km intervals for each unit. The geometries and density distributions within the crust have been compiled and interpolated from a variety of datasets, predominantly seismic data (see section 6). To eliminate boundary effects, the model boundaries have been extended by more than 500 km in all horizontal directions, incorporating additional constraining data from the extended region. Additionally, we provide gridded gravity field data, a density voxel cube for the sub-lithospheric mantle, and relevant tomography data. Notably, the density of the lower lithospheric mantle was derived from 3D gravity inversion modeling.

Topography and bathymetry data were obtained from the ETOPO_2022 dataset (NOAA National Centers for Environmental Information, 2022). Then, we integrated reflection and refraction seismic profiles (Table 1 and 2) to constrain the sediment base and the Moho interface, and where seismic profiles were lacking, we used a global crustal model-ECM1 (Mooney et al., 2023) to fill gaps.

To derive sediment thickness from Multi-Channel Seismic (MCS) reflection data (as listed in Table 1, section 6), the two-way travel time (TWT) was converted to depth below the seafloor using specific time-depth conversion formulas (Table 3). For the Moho interface, the TWT within the crystalline crust layer is converted to depth below sediment basement by using the time-depth relationship established by Huang et al. (2023) (Table 3), which is based on velocity-depth profiles from seismic refraction data in the SCS. Additionally, the Ocean Bottom Seismometer (OBS) refraction data (Table 2), presented in depth terms, were extracted directly through digitization. For the upper mantle, we converted the Vs tomography data of Tang & Zheng (2013) into mantle temperature using the method of Priestley & McKenzie (2006) and defined the depth of the 1300°C isotherm as the Lithosphere-Asthenosphere Boundary (LAB).

To enhance the gravity response of our 3D density models, we referenced the free-air gravity disturbance at an altitude of 6 km above sea level, as derived from the EIGEN-6C4 model (Förste et al., 2014; Ince et al., 2019), a global gravity model that combines satellite and terrestrial data sources. We selected a height of 6 km that is above the highest topographical point of the model in order to ensure that all gravity observations are outside the subsurface space of relevant mass variations.

Identifier
DOI https://doi.org/10.5880/fidgeo.2024.031
Related Identifier Cites https://doi.org/10.6038/cjg20140215
Related Identifier Cites https://doi.org/10.1016/j.margeo.2017.07.022
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2021.105450
Related Identifier Cites https://doi.org/10.1029/2021TC007127
Related Identifier Cites https://doi.org/10.1016/j.jog.2021.101877
Related Identifier Cites https://doi.org/10.1038/s41467-020-18448-y
Related Identifier Cites https://doi.org/10.1007/s11001-013-9173-9
Related Identifier Cites https://doi.org/10.1016/j.tecto.2012.09.026
Related Identifier Cites https://doi.org/10.1260/0144-5987.32.1.243
Related Identifier Cites https://doi.org/10.1007/s11001-014-9237-5
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2015.09.013
Related Identifier Cites https://doi.org/10.1016/j.epsl.2018.02.011
Related Identifier Cites https://doi.org/10.1016/j.epsl.2019.115932
Related Identifier Cites https://doi.org/10.1360/csb2008-53-19-2342
Related Identifier Cites https://doi.org/10.1002/2013JB010395
Related Identifier Cites https://doi.org/10.1016/j.margeo.2018.12.007
Related Identifier Cites https://doi.org/10.5880/ICGEM.2015.1
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2011.01.004
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2007.11.004
Related Identifier Cites https://doi.org/10.1016/j.tecto.2015.03.003
Related Identifier Cites https://doi.org/10.1002/2016GC006247
Related Identifier Cites https://doi.org/10.1016/j.gr.2022.09.005
Related Identifier Cites https://doi.org/10.1002/gj.2842
Related Identifier Cites https://doi.org/10.1002/cjg2.20234
Related Identifier Cites https://doi.org/10.1007/s12583-009-0003-6
Related Identifier Cites https://doi.org/10.1093/gji/ggz219
Related Identifier Cites https://doi.org/10.1029/2020TC006260
Related Identifier Cites https://doi.org/10.1016/j.pepi.2022.106966
Related Identifier Cites https://doi.org/10.1016/j.margeo.2010.01.007
Related Identifier Cites https://doi.org/10.5194/essd-11-647-2019
Related Identifier Cites https://doi.org/10.1016/j.tecto.2007.11.012
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2016.07.022
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2018.02.020
Related Identifier Cites https://doi.org/10.1130/B35001.1
Related Identifier Cites https://doi.org/10.1007/s11001-019-09381-x
Related Identifier Cites https://doi.org/10.1029/2019JB018610
Related Identifier Cites https://doi.org/10.1016/j.epsl.2013.06.007
Related Identifier Cites https://doi.org/10.1002/2013JB010639
Related Identifier Cites https://doi.org/10.1007/s12583-015-0588-x
Related Identifier Cites https://doi.org/10.1007/s11001-007-9014-9
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2007.09.004
Related Identifier Cites https://doi.org/10.1007/s11001-008-9059-4
Related Identifier Cites http://publications.iodp.org/proceedings/349/349title.html
Related Identifier Cites https://doi.org/10.1016/j.earscirev.2022.103917
Related Identifier Cites https://doi.org/10.1016/j.gr.2021.06.015
Related Identifier Cites https://www.jto.ac.cn/EN/10.11978/2016122
Related Identifier Cites https://doi.org/10.1016/j.tecto.2018.06.002
Related Identifier Cites https://doi.org/10.1093/gji/ggab006
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2021.105079
Related Identifier Cites https://doi.org/10.1080/00206814.2018.1553114
Related Identifier Cites https://doi.org/10.1007/s11001-015-9248-x
Related Identifier Cites https://doi.org/10.1130/G34402.1
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2014.03.012
Related Identifier Cites https://doi.org/10.1016/j.earscirev.2023.104493
Related Identifier Cites https://doi.org/10.1029/95JB01866
Related Identifier Cites https://doi.org/10.1007/s11001-018-9353-8
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2020.104711
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2013.10.008
Related Identifier Cites https://doi.org/10.1016/j.epsl.2006.01.008
Related Identifier Cites https://doi.org/10.6038/cjg20141008
Related Identifier Cites https://doi.org/10.1016/S0040-1951(01)00222-0
Related Identifier Cites https://doi.org/10.3969/j.issn.0001-5733.2011.12.012
Related Identifier Cites https://doi.org/10.1002/cjg2.1682
Related Identifier Cites https://doi.org/10.1016/j.tecto.2016.09.022
Related Identifier Cites https://doi.org/10.1016/j.tecto.2013.07.010
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2019.03.008
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2013.12.010
Related Identifier Cites https://doi.org/10.1007/s11430-014-4835-2
Related Identifier Cites https://doi.org/10.3969/j.issn.0001-5733.2011.12.019
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2014.02.018
Related Identifier Cites https://doi.org/10.14379/iodp.proc.367368.2018
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2012.10.037
Related Identifier Cites https://doi.org/10.1007/s11001-018-09376-0
Related Identifier Cites https://doi.org/10.1002/2016JB013481
Related Identifier Cites https://doi.org/10.1029/2019JB017785
Related Identifier Cites https://doi.org/10.1080/00206814.2019.1695002
Related Identifier Cites https://doi.org/10.1007/s11430-020-9654-4
Related Identifier Cites https://doi.org/10.1016/j.tecto.2005.10.039
Related Identifier Cites https://doi.org/10.3969/j.issn.1001-909X.2021.03.004
Related Identifier Cites https://doi.org/10.1007/s12583-020-1064-9
Related Identifier Cites https://doi.org/10.1002/cjg2.1691
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2020.104557
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2021.105255
Related Identifier Cites https://doi.org/10.1016/j.tecto.2013.12.013
Related Identifier Cites https://doi.org/10.1002/gj.3145
Related Identifier Cites https://doi.org/10.1080/00206814.2019.1597392
Related Identifier Cites https://doi.org/10.1007/s11430-011-4324-9
Related Identifier Cites https://doi.org/10.1007/s11430-021-9894-7
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2021.105140
Related Identifier Cites https://doi.org/10.1007/s11001-019-09378-6
Related Identifier Cites https://doi.org/10.1007/s11001-019-09384-8
Related Identifier Cites https://doi.org/10.1016/S0040-1951(01)00062-2
Related Identifier Cites https://doi.org/10.1007/s11001-005-0732-6
Related Identifier Cites https://doi.org/10.1007/s11001-012-9154-4
Related Identifier Cites https://doi.org/10.1016/j.gr.2020.11.012
Related Identifier Cites https://doi.org/10.1016/j.jseaes.2020.104536
Related Identifier Cites https://doi.org/10.1029/2020JB019827
Related Identifier Cites https://doi.org/10.1007/s11001-016-9266-3
Related Identifier Cites https://doi.org/10.1016/j.marpetgeo.2020.104396
Related Identifier Cites https://doi.org/10.16539/j.ddgzyckx.2022.03.018
Related Identifier Cites https://doi.org/10.1016/j.epsl.2019.115862
Related Identifier Cites https://doi.org/10.1002/2017GC007034
Related Identifier Cites https://doi.org/10.1029/2020TC006547
Related Identifier Cites https://doi.org/10.1111/bre.12220
Related Identifier Cites https://doi.org/10.1016/j.epsl.2018.08.048
Related Identifier Cites https://www.researchgate.net/publication/285770114
Related Identifier Cites https://doi.org/10.1016/j.tecto.2012.05.027
Related Identifier Cites https://doi.org/10.1002/gj.3034
Metadata Access http://doidb.wdc-terra.org/oaip/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:doidb.wdc-terra.org:8541
Provenance
Creator Li, Yan ORCID logo; Bott, Judith ORCID logo; Liu, Shaowen ORCID logo; Tan, Pingchuan ORCID logo; Anikiev, Denis ORCID logo; Scheck-Wenderoth, Magdalena ORCID logo
Publisher GFZ Data Services
Contributor Li, Yan
Publication Year 2024
Rights CC BY 4.0; http://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact Li, Yan (MOE Key Laboratory of Coast and Island Development, School of Geography and Ocean Science, Nanjing University, Nanjing, China)
Representation
Resource Type Dataset
Version 1.2
Discipline Geospheric Sciences
Spatial Coverage (111.100W, 9.500S, 120.300E, 20.900N); Study area in the South China Sea