Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Research Area and Measured Data
2.2. Satellite Data Acquisition and Processing
2.3. Remote Sensing Retrieval Algorithm
3. Results
3.1. Formation of a Remote Sensing Retrieval Model
3.2. Results and Error Analysis of TSM in the Pearl River Estuary
4. Discussion
4.1. The Differences and Reasons for the TSM between the Flood Season and Dry Season
4.2. Differences and Reasons Analysis for TSM between 2013 and 2020
4.2.1. Influence of Precipitation
4.2.2. Influence of Runoff Volume
4.2.3. The Impact of Water Consumption
4.3. The Impacts of the Hong Kong–Zhuhai–Macao Bridge on the Pearl River TSM
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Webster, T.; Lemckert, C. Sediment resuspension within a microtidal estuary/embayment and the implication to channel management. J. Coast. Res. 2002, 36, 753–756. [Google Scholar] [CrossRef]
- Lv, J.W.; Liu, X.N.; Wang, J.; Cheng, J.B. Remote sensing retrieval of the suspended solid concentration in coast of South China based on PSO_RBF. Mar. Environ. Sci. 2013, 32, 669–673. [Google Scholar]
- Chen, S.; Zhang, G.; Yang, S.; Yu, Z. Temporal and Spatial Changes of Suspended Sediment Concentration and Resuspension in the Yangtze River Estuary and Its Adjacent Waters. Acta Geogr. Sin. 2004, 59, 260–266. [Google Scholar]
- Chen, J.Y.; Chen, S.L. Estuarine and coastal challenges in China. Mar. Geol. Lett. 2002, 18, 1–5+3. [Google Scholar]
- Zhang, X.Y.; Pan, D.L. Study on Coastal Water Quality Evaluation Based on Ocean Color Remote Sensing Satellite. In Proceedings of the 6th Symposium on Imaging Spectroscopy Technology and Applications, Shanghai, China, 28 October 2006. [Google Scholar]
- Pan, D.L.; Gong, F. Progress in Application Technology of Satellite Ocean Remote Sensing in China. J. Hangzhou Norm. Univ. 2011, 10, 1–10. [Google Scholar]
- Barnes, B.B.; Hu, C.; Kovach, C.; Silverstein, R.N. Sediment plumes induced by the Port of Miami dredging: Analysis and interpretation using Landsat and MODIS data. Remote Sens. Environ. 2015, 170, 328–339. [Google Scholar] [CrossRef]
- Cai, L.; Tang, D.; Levy, G.; Liu, D. Remote sensing of the impacts of construction in coastal waters on suspended particulate matter concentration-the case of the Yangtze River delta, China. Int. J. Remote Sens. 2016, 37, 2132–2147. [Google Scholar] [CrossRef]
- Hunter, K.A.; Liss, P.S. The surface charge of suspended particles in estuarine and coastal waters. Nature 1979, 282, 823–825. [Google Scholar] [CrossRef]
- Ma, H.; Zhong, H.L.; Luo, Z.; Zhu, L.; Shi, F. Suspended sediment concentrations in the Yangtze Estuary based on Landsat 8 remote sensing retrieval. Shanghai Land Resour. 2018, 39, 80–84. [Google Scholar]
- Morel, A. In-water and remote measurements of ocean color. Bound.-Layer Meteorol. 1980, 18, 177–201. [Google Scholar] [CrossRef]
- Dekker, A.G.; Peters, S.W. The use of the Thematic appear for the analysis of eutrophic lakes: A case study in the Netherlands. Int. J. Remote Sens. 1993, 14, 799–822. [Google Scholar] [CrossRef]
- Zhang, Y.Z.; Nie, Y.P.; Lin, Q.Z.; Jing, L.-H.; Zhang, B. Surface Water Quality Monitoring Using Remote Sensing. Remote Sens. Technol. Appl. 2000, 4, 214–219. [Google Scholar]
- Kloiber, S.M.; Brezonik, P.L.; Olmanson, L.G.; Bauer, E.M. A procedure for regional lake water clarity assessment using Landsat multispectral data. Remote Sens. Environ. 2002, 82, 38–47. [Google Scholar] [CrossRef]
- Wang, Q. Spatial and temporal distribution of suspended sediment in offshore region of Haiyang city by remote sensing. Master’s degree, University of Chinese Academy of Sciences, Qingdao, China, June 2019. [Google Scholar]
- Williamson, A.N.; Grabau, W.E. Sediment concentration mapping in tidal estuaries. NASA Spec. Publ. 1974, 351, 13–47. [Google Scholar]
- Gordon, H.R. Remove of atmospheric effects from satellite imagery of the oceans. Appl. Opt. 1978, 17, 1631–1636. [Google Scholar] [CrossRef] [PubMed]
- Munday, J.C.; Alföldi, T.T. Landsat test of diffuse reflectance models for aquatic suspended solids measurement. Remote Sens. Environ. 1979, 8, 169–183. [Google Scholar] [CrossRef]
- Tassan, S. An improved in-water algorithm for the determination of chlorophyll and suspended sediment concentration from Thematic Mapper data in coastal waters. Int. J. Remote Sens. 1993, 14, 1221–1229. [Google Scholar] [CrossRef]
- Moore, K.A.; Wetzel, R.L.; Orth, R.J. Seasonal pulses of turbidity and their relations to eelgrass (Zostera marina L.) survival in an estuary. J. Exp. Mar. Biol. Ecol. 1997, 215, 115–134. [Google Scholar] [CrossRef]
- Ramaswamy, V.; Rao, P.S.; Rao, K.H.; Raiker, V. Tidal Influence on Suspended Sediment Distribution and Dispersal in the Northern Andaman Sea and Gulf of Martaban. Mar. Geol. 2004, 208, 33–42. [Google Scholar] [CrossRef]
- Li, Y.; Li, J. Suspended sediment remote sensing algorithm based on the phenomenon of spectral reflectance slope transfer between sea surface and remote sensor. Chin. Sci. Bull. 1999, 17, 1892–1897. [Google Scholar]
- Liu, D.Z.; Zhang, C.G.; Fu, D.Y.; Shen, C. Hyperspectral data-based remote- sensing inversion model for suspended sediment in surface waters at the Pearl River Estuary. Mar. Sci. 2010, 34, 77–80. [Google Scholar]
- Kazemzadeh, M.B.; Ayyoubzadeh, S.A.; Moridnezhad, A. Remote Sensing of Temporal and Spatial Variations of Suspended Sediment Concentration in Bahmanshir Estuary, Iran. Indian J. Sci. Technol. 2013, 6, 5036–5045. [Google Scholar] [CrossRef]
- Montanher, O.C.; Novo, E.M.; Barbosa, C.C.; Rennó, C.D.; Silva, T.S.F. Empirical models for estimating the suspended sediment concentration in Amazonian White water rivers using Landsat5/TM. Int. J. Appl. Earth Obs. Geo Inf. 2014, 29, 67–77. [Google Scholar]
- Ma, W.D.; Wu, C.Q.; Li, L.; Wang, Y.M. Remote Sensing Retrieval of Total Suspended Matter in Hangzhou Bay Based on HJ-CCD. In Proceedings of the 16th China Environmental Remote Sensing Application Technology Forum, Nanning, China, 28 March 2012. [Google Scholar]
- Li, X. An United Equation for Remote Sensing Quantitative Analysis of Suspended Sediment and Its Application at the Pearl River Estuary. Remote Sens. Environ. 1992, 7, 106–114. [Google Scholar]
- Han, B.; Loisel, H.; Vantrepotte, V.; Mériaux, X.; Bryère, P.; Ouillon, S.; Dessailly, D.; Xing, Q.; Zhu, J. Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters. Remote Sens. 2016, 8, 211. [Google Scholar] [CrossRef]
- Liu, X.P.; Deng, R.R.; Peng, X.J. An Integrated Model for Quantitative Remote Sensing Measurement of Suspended Sediment and Its Application in the Pearl River Estuary. Acta Sci. Nat. Univ. Sunyatseni 2005, 44, 109–113. [Google Scholar]
- Deng, R.R.; He, Z.J.; Cheng, X.X. Model for water pollution remote sensing based on double scattering and its application on the the Pearl River Estuary. Acta Oceanol. Sin. 2003, 25, 69–78. [Google Scholar]
- Liu, F.F.; Chen, C.Q.; Tang, S.L.; Liu, D.Z. A piecewise algorithm for retrieval of suspended sediment concentration based on in situ spectral data by MERIS in the Pearl River estuary. J. Trop. Oceanogr. 2009, 28, 9–14. [Google Scholar]
- Xi, H.X.; Zhang, Y.Z. Total suspended matter observation in the Pearl River Estuary from in situ and MERIS data. Environ. Monit. Assess. 2011, 177, 563–574. [Google Scholar] [CrossRef]
- Zhu, F.; Ou, S.Y.; Zhang, S.; Luo, K. MODIS images-based retrieval and analysis of spatial-temporal change of superficial suspended sediment concentration in the Pearl River Estuary. J. Sediment Res. 2015, 2, 67–73. [Google Scholar]
- Luan, H.; Fu, D.Y.; Li, M.J.; Zeng, J.S.; Chen, Q.D. Based on Landsat 8 suspended sediment concentration of the Pearl River on each season inversion and analysis. Mar. Environ. Sci. 2017, 36, 892–897. [Google Scholar]
- Liu, D.Z.; LI, Z.; Chen, Z.H.; Cheng, Y.C. Influence of Hong Kong-Zhuhai-Macao Bridge on the Distribution of Suspended Sediment in the Pearl River Estuary. Mar. Environ. Sci. 2020, 40, 90–96. [Google Scholar]
- Jia, G.; Xu, S.; Chen, W.; Lei, F.; Bai, Y.; Huh, C. 100-year ecosystem history elucidated from inner shelf sediments off the Pearl River Estuary, China. Mar. Chem. 2013, 151, 47–55. [Google Scholar] [CrossRef]
- Wei, X.; Wu, C.Y. The formation and development of the deposition bodies and main channel in the Zhujiang River Delta. Haiyang Xuebao 2018, 40, 66–78. [Google Scholar]
- Liu, C.J.; Xia, H.Y.; Wang, D.Y. The observation and analysis of eastern Guangdong coastal downwelling in the winter of 2006. Acta Oceanol. Sin. 2010, 32, 1–9. [Google Scholar]
- Xiao, Z.J. Characteristics and transport trend of surface sediments in Pearl River Estuary and the adjacent sea area. Mar. Sci. Bull. 2012, 31, 481–488. [Google Scholar]
- Zhan, W.K.; Wu, J.; Wei, X.; Tang, S.; Zhan, H. Quantile trend analysis for suspended sediment concentration in the Pearl River Estuary based on remote sensing. J. Trop. Oceanogr. 2019, 38, 32–42. [Google Scholar]
- Gao, F.; Wang, Y.P.; Hu, X.Y. Experimental Research on the Selection of Coagulant for Slightly Polluted Cellar Rainwater Treatment. J. Green Sci. Technol. 2018, 6, 1–5. [Google Scholar]
- Pozdnyakov, D.; Grassl, H. Color of Inland and Coastal Water; Springer: Berlin/Heidelberg, Germany, 2003; pp. 81–120. [Google Scholar]
- Zhou, Y.; Zhou, W.Q.; Wang, S.X.; Zhang, P. Applications of remote sensing techniques to inland water quality monitoring. Adv. Water Sci. 2004, 15, 312–317. [Google Scholar]
- Zhang, K.; Zhang, K.; Niu, P.T.; Gao, L. Research Progress of Water Quality Monitoring Technique Based on Remote Sensing. Mod. Min. 2018, 34, 171–174+202. [Google Scholar]
- Gordon, H.R.; Clark, D.K. Clear water radiance for atmospheric correction of Coastal Zone Color Scanner imagery. Appl. Opt. 1981, 20, 4175–5180. [Google Scholar] [CrossRef] [PubMed]
- Shu, X.Z.; Yin, Q.; Kuang, D.B. Relationship between Algal Chlorophyll Concentration and Spectral Reflectance of Inland Water. J. Remote Sens. 2000, 4, 41–45. [Google Scholar]
- Härmä, P.; Vepsäläinen, J.; Hannonen, T.; Pyhälahti, T.; Kämäri, J.; Kallio, K.; Eloheimo, K.; Koponen, S. Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland. Sci. Total Environ. 2001, 268, 107–121. [Google Scholar] [CrossRef] [PubMed]
- Thiemann, S.; Kaufmann, H. Lake water quality monitoring using hyperspectral airborne data—A semiempirical multisensor and multitemporal approach for the Mecklenburg Lake District, Germany. Remote Sens. Environ. 2002, 81, 228–237. [Google Scholar] [CrossRef]
- Zhang, Y.; Xia, H.Y.; Qian, L.B.; Zhu, P.L. Analysis on hydrological characteristics off the Pearl River Estuary in summer and winter of 2006. J. Trop. Oceanogr. 2011, 30, 20–28. [Google Scholar]
- Han, W.Y.; Ma, K.M. A study on the Upwelling along the coast of eastern Guangdong. Acta Oceanol. Sin. 1988, 10, 52–59. [Google Scholar]
Time | Total Station | Effective Station | TSM (mg/L) | Average (mg/L) |
---|---|---|---|---|
January 2013 | 15 | 13 | 9.80–18.40 | 13.39 |
July 2013 | 15 | 12 | 5.49–64.19 | 47.94 |
May 2020 | 19 | 14 | 4.40–32.40 | 13.24 |
November 2020 | 20 | 15 | 3.20–24.10 | 9.14 |
Band | Wavelength (μm) | Spatial Resolution (m) |
---|---|---|
Band 1 Coastal | 0.433–0.453 | 30 |
Band 2 Blue | 0.450–0.515 | 30 |
Band 3 Green | 0.525–0.600 | 30 |
Band 4 Red | 0.630–0.680 | 30 |
Band 5 NIR | 0.845–0.885 | 30 |
Band 6 SWIR 1 | 1.560–1.660 | 30 |
Band 7 SWIR 2 | 2.100–2.300 | 30 |
Band 8 Pan | 0.500–0.680 | 15 |
Band 9 Cirrus | 1.360–1.390 | 30 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ma, Z.; Zhao, Y.; Zhao, W.; Feng, J.; Liu, Y.; Tsou, J.Y.; Zhang, Y. Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China). J. Mar. Sci. Eng. 2024, 12, 167. https://doi.org/10.3390/jmse12010167
Ma Z, Zhao Y, Zhao W, Feng J, Liu Y, Tsou JY, Zhang Y. Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China). Journal of Marine Science and Engineering. 2024; 12(1):167. https://doi.org/10.3390/jmse12010167
Chicago/Turabian StyleMa, Zhaoyue, Yong Zhao, Wenjing Zhao, Jiajun Feng, Yingying Liu, Jin Yeu Tsou, and Yuanzhi Zhang. 2024. "Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China)" Journal of Marine Science and Engineering 12, no. 1: 167. https://doi.org/10.3390/jmse12010167
APA StyleMa, Z., Zhao, Y., Zhao, W., Feng, J., Liu, Y., Tsou, J. Y., & Zhang, Y. (2024). Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China). Journal of Marine Science and Engineering, 12(1), 167. https://doi.org/10.3390/jmse12010167