Elsevier

Ocean Engineering

Volume 235, 1 September 2021, 109334
Ocean Engineering

Large-scale seismic seafloor stability analysis in the South China Sea

https://doi.org/10.1016/j.oceaneng.2021.109334Get rights and content

Highlights

  • Large-scale seismic seafloor stability map in the South China Sea.

  • Earthquake probability, seismicity and seafloor soil properties distribution.

  • Large-scale Peak Ground Acceleration maps for the South China Sea.

  • 3D continuous model for seafloor soil properties within the South China Sea.

Abstract

Earthquakes are considered as the major trigger of submarine landslides. This study analyzes the large-scale seismic seafloor stability in the South China Sea (SCS), taking into consideration the earthquake probability and spatial distribution of seismicity and seafloor soil properties. For this cause, the geographical, seismic, and seafloor soil characteristics are first determined. The digital elevation model (DEM) of the study area is established using the geographic information system (GIS). Large-scale Peak Ground Acceleration (PGA) maps under different exceedance probabilities (EPs) are derived using the Chinese Probability Seismic Hazard Analysis (CPSHA) method. Three-dimension continuous models for seafloor soil properties are obtained using a proposed best-fit distribution-based Kriging method. With this information, the large-scale seafloor stability under different EPs is evaluated with an infinite slope model in the study area of the SCS. The proposed large-scale seismic seafloor stability is validated against recorded earthquake-induced submarine landslides. The analysis shows that the seafloor stability is found to be highly nonuniform, and the study area can be divided into three main parts based on their distinct seafloor stabilities. This study sheds new light on the large-scale seafloor stability, and can assist the development of ocean engineering projects in the SCS.

Introduction

Most ocean engineering facilities are connected to the seafloor in some form (Randolph et al., 2011). The stability of seafloor plays a critical role in ocean engineering facilities’ safety. Submarine landslides, which often occur in sloping seafloor (Prior et al., 1989; Yalçiner et al., 2003), can cause destructive damage to ocean engineering facilities (Roesner et al., 2019; Locat and Mienert, 2012; Locat and Lee, 2005). Therefore, it is of great significance to investigate the triggering of submarine landslides and seafloor stability. Evidence suggests that earthquake is one of the main triggers of submarine landslides (Hance, 2003; Brink et al., 2009; Wu et al., 2018). Such submarine landslides are often very large in area coverage and enormous in volume (Zhu et al., 2019; Haflidason et al., 2004; Bryn et al., 2005; Prior and Suhayda, 1979). These characteristics place demand on large-scale seismic seafloor stability analysis (Nian et al., 2019; Guo et al., 2019; Li et al., 2017).

The South China Sea (SCS) is an oil and gas productive area (Chen et al., 2018b; Li et al., 2018; Zhu et al., 2010) with high and significantly nonuniform seismicity (Guo et al., 2019; Liu and Wang, 2014), which brings risks to ocean engineering facilities. Zhu et al. (2018) analyzed the submarine landslide susceptibility in the SCS through a probability process, based on a hypothetical slope model representing the typical seafloor morphology in the SCS, under uniform seismicity. Li et al. (2014) assessed the seafloor stability of the Baiyun Sag (a large-scale sag in the SCS) using the gray clustering method, and seismic force was one of the five factors considered, which was later expanded to the northern slope of the SCS (Guo et al., 2019). Liu and Wang (2014) considered the nonuniform distribution of seismicity and evaluated the stability of the Zhujiang River Mouth Basin based on limited seismic data. Further assessment of large-scale seismic seafloor stability within the SCS, taking into consideration earthquake probability and spatial distribution based on comprehensive data, is needed.

To achieve this goal, the seafloor soil properties data, including physical and mechanical properties, are required. However, due to the limited amount of seafloor soil properties data in the SCS, estimation of the seafloor soil properties in the unsampled area is needed. Zhou et al. (2019) characterized the stability of an area along the continental shelf of the SCS with seafloor soil properties data from a single nearby borehole. Data from multi-sources were utilized in the analysis by Zhang and Luan (2013) and Nian et al. (2019), but the spatial variability of seafloor soil properties was not considered. Li et al. (2017) estimated the shear strength of seafloor soil in the Liwan gas field within the SCS using 3D seismic data, but such data are unavailable for other regions of the SCS. A model for the characterization of seafloor soil properties considering the scarce seafloor soil properties data and the spatial variability of actual seafloor soil properties within the SCS is needed for large-scale seafloor stability analysis.

This study aims to analyze the large-scale seismic seafloor stability within the SCS taking into consideration earthquake probability and spatial distribution of seismicity and seafloor soil properties. The framework of this study is illustrated in Fig. 1: (1) High-resolution digital elevation model (DEM) for the study area in the SCS is constructed; (2) PGA maps of the study area in the SCS under different EPs are derived using the Chinese Probabilistic Seismic Hazard Analysis (CPSHA) method; (3) A best-fit distribution-based Kriging method for seafloor soil properties is developed, and continuous 3D models for seafloor soil parameters in the SCS study area are established; (4) An infinite slope model is adopted for large-scale seismic seafloor stability analysis. Validation of the proposed method is conducted using reported seismic induced submarine landslides in the SCS.

Section snippets

Topography

The intense tectonic activity in the SCS shaped its topography (Zhu and Lei, 2013; Zhao et al., 2019). The SCS is composed of three parts, the continental shelf, the continental slope, and the deep basin (Liu and Wang, 2014; Zhang and Luan, 2013). The continental shelf extends from NE to SW, with elevation contours mostly parallel to the coastline of China. The water depth of the continental shelf is within 0–200m (Feng and Bao, 1982; Li and Jin, 1989). Developing from the outer shelf, the

Basic theory

The probabilistic seismic hazards analysis (PSHA) method is often used to characterize the random nature of earthquakes. This method, proposed by Cornell in 1968, studies the relationship between the ground motion parameters (such as PGA) and the average return period. The potential source and corresponding seismicity levels are taken into account (Cornell, 1968). This method has become a basic theory for seismic engineering design (McGuire, 1995, 2008; Budnitz et al., 1997). The procedures of

A best-fit distribution-based Kriging method

There are various sources of uncertainties in geotechnical engineering practice (Li et al., 2011; Cao and Wang, 2014; Jiang et al., 2015). Therefore, the soil properties parameters can be treated as random variables to reflect the uncertainties (Tang et al., 2012, 2013). The Gaussian distribution has often been thought to be the best-fit distribution of soil properties parameters. However, evidence suggests that the Gaussian distribution, usually adopted empirically without validation, is

Infinite seafloor slope model

The limit equilibrium method-based infinite slope model is utilized to quantify the stability of the seafloor in this study. The Mohr-Coulomb criterion is adopted for the strength of the seafloor soil. Although the infinite slope model is simple, many researchers have suggested that it is appropriate for the analysis of submarine landslides considering submarine slopes are generally mild but large in scale (Prior and Suhayda, 1979; Ikari et al., 2011; Baeten et al., 2014). The stability of

Conclusions

Large-scale seismic seafloor stability within the South China Sea is analyzed in this study, taking into consideration earthquake probability and spatial distribution of seismicity and seafloor soil properties. To achieve this, a high-resolution digital elevation model (DEM) for the study region in the SCS is constructed, PGA maps of the study region in the SCS under different EPs are obtained, and continuous 3D models for seafloor soil parameters in the SCS study region are established. The

CRediT authorship contribution statement

Yuxi Wang: Writing – original draft, Methodology. Rui Wang: Conceptualization, Writing – review & editing. Jian-Min Zhang: Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors would like to thank the National Natural Science Foundation of China (No. 52022046 and No. 52038005) for funding this study. The bathymetry data for this study were obtained from the GEBCO (https://www.gebco.net). The earthquake data for this study were obtained from the International Seismological Centre (http://www.isc.ac.uk).

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