Classifying the sedimentary environments of the Xincun Lagoon, Hainan Island, by system cluster and principal component analyses

YANG Yang; GAO Shu; ZHOU Liang; WANG Yunwei; LI Gaocong; WANG Yaping; HAN Zhuochen; JIA Peihong

doi:10.1007/s13131-016-0939-1

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Article Navigation > Acta Oceanologica Sinica > 2017 > 36(4): 64-71

YANG Yang, GAO Shu, ZHOU Liang, WANG Yunwei, LI Gaocong, WANG Yaping, HAN Zhuochen, JIA Peihong. Classifying the sedimentary environments of the Xincun Lagoon, Hainan Island, by system cluster and principal component analyses[J]. Acta Oceanologica Sinica, 2017, 36(4): 64-71. doi: 10.1007/s13131-016-0939-1

Citation:

YANG Yang, GAO Shu, ZHOU Liang, WANG Yunwei, LI Gaocong, WANG Yaping, HAN Zhuochen, JIA Peihong. Classifying the sedimentary environments of the Xincun Lagoon, Hainan Island, by system cluster and principal component analyses[J]. Acta Oceanologica Sinica, 2017, 36(4): 64-71. doi: 10.1007/s13131-016-0939-1

Citation:

YANG Yang, GAO Shu, ZHOU Liang, WANG Yunwei, LI Gaocong, WANG Yaping, HAN Zhuochen, JIA Peihong. Classifying the sedimentary environments of the Xincun Lagoon, Hainan Island, by system cluster and principal component analyses[J]. Acta Oceanologica Sinica, 2017, 36(4): 64-71. doi: 10.1007/s13131-016-0939-1

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Classifying the sedimentary environments of the Xincun Lagoon, Hainan Island, by system cluster and principal component analyses

doi: 10.1007/s13131-016-0939-1

1.
State Key Laboratory for Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China;Ministry of Education Key Laboratory for Coast and Island Development, Nanjing University, Nanjing 210093, China
2.
College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
3.
Ministry of Education Key Laboratory for Coast and Island Development, Nanjing University, Nanjing 210093, China

Received Date: 2015-12-19
Rev Recd Date: 2016-06-22

Abstract

Abstract

An understanding of the sedimentary environment in relation to its controlling factors is of great importance in coastal geomorphology, ecology, tourism and aquaculture studies. We attempt to deal with this issue, using a case study from the Xincun Lagoon, Hainan Island in southern China. For the study, surficial sediment samples were collected, together with hydrodynamic and bathymetric surveys, during August 2013. Numerical simulation was carried out to obtain high-spatial resolution tidal current data. The sediment samples were analyzed to derive mean grain size, sorting coefficient, skewness and kurtosis, together with the sand, silt and clay contents. The modern sedimentary environments were classified using system cluster and principal component analyses. Grain size analysis reveals that the sediments are characterized by extremely slightly sandy silty mud (ESSSM) and slightly silty sand (SSS), which are distributed in the central lagoon and near-shore shallow water areas, respectively. Mean grain size varies from 0 to 8.0Ф, with an average of 4.6Ф. The silt content is the highest, i.e., 52% on average, with the average contents of sand and clay being 43% and 5%, respectively. There exists a significant correlation between mean size and water depth, suggesting that the surficial sediments become finer with increasing water depth. Cluster analyses reveals two groups of samples. The first group is characterized by mean grain size of more than 5.5Ф, whilst the second group has mean grain size of below 3.5Ф. Further, these groups also have different correlations between mean grain size and the other grain size parameters. In terms of the tidal current, the average values of the root mean square velocity (RMSV) are 7.5 cm/s and 6.9 cm/s on springs and neaps, respectively. For the RMSVs that are higher than 4 cm/s, a significant positive correlation is found between the content of the 63-125 μm fraction and the RMSV, suggesting that the RMSV determines the variability of the very fine sand fraction. Based on system cluster and principal component analyses (PCA), the modern sedimentary environments are classified into three types according to the grain size parameters, RMSVs and water depth data. The results suggest the importance of grain size parameters and high-spatial resolution hydrodynamic data in differentiating the coastal sedimentary environments.
- surficial sediment,
- grain size,
- lagoon sedimentary environment,
- statistical analysis,
- numerical simulation,
- Hainan Island

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References(53)

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