A dynamic sediment model based on satellite-measured concentration of the surface suspended matter in the East China Sea

The concentration of total suspended matter (TSM) at the sea surface is derived from satellite data using a complex proxy TSM model in East China Sea from 1997 to 2008. The structure of the mean TSM image is similar to that of the topography, indicating that the distribution of the surface concentration is strongly related to the water depth. A dynamic sediment model (DSM) is constructed to relate the TSM concentration at the sea surface with suspended sediment at the benthic boundary layer, the Rouse number, and the water depth. The DSM model is improved through iteration with a convergence identified by the mean relative difference between two adjacent bottom TSM images which becomes smaller with the more iterations and the value is less than 1% after 50 iterations. The performance of the DSM model is validated by satellite-measured concentration with a mean relative error of 5.2% for the monthly mean images. The DSM model is used to deduce the bottom TSM concentration at the benthic boundary layer and the distribution of the Rouse number. The spatial distribution of the sea surface TSM concentration is determined predominately by both the bottom suspended sediment concentration and water depth. The temporal variation of the sea surface concentration mainly depends upon the Rouse number in the water column. Our result shows that the discharge of the Changjiang River can change the distribution of the Rouse number to form a band-shaped region in the Changjiang Estuary. The DSM model provides a framework for understanding some of the mechanisms of the formation and variation of the primary TSM plume and the secondary plume in the ECS. The primary TSM plume corresponds approximately to the region with depth shallower than 20 m and the secondary plume corresponds to the region with depths between 20 and 50 m.

[1]  M. Chami,et al.  Analysis of riverine suspended particulate matter fluxes (Gulf of Lion, Mediterranean Sea) using a synergy of ocean color observations with a 3-D hydrodynamic sediment transport model , 2015 .

[2]  Zengzhou Hao,et al.  A potentially universal algorithm for estimating aerosol scattering reflectance from satellite remote sensing data , 2014 .

[3]  Zengzhou Hao,et al.  A new approach to estimate the aerosol scattering ratios for the atmospheric correction of satellite remote sensing data in coastal regions , 2013 .

[4]  Delu Pan,et al.  A regional remote sensing algorithm for total suspended matter in the East China Sea , 2012 .

[5]  Guangxue Li,et al.  Distribution of suspended particulate matter in the northern Bohai Bay in summer and its relation with thermocline , 2011 .

[6]  W. Guan,et al.  Sediment transport in the Yellow Sea and East China Sea , 2011 .

[7]  Shu Gao,et al.  Delineating suspended sediment concentration patterns in surface waters of the Changjiang Estuary by remote sensing analysis , 2010 .

[8]  Menghua Wang,et al.  Satellite observations of the seasonal sediment plume in central East China Sea , 2010 .

[9]  N. Guillou,et al.  Three‐dimensional modeling of tide‐induced suspended transport of seabed multicomponent sediments in the eastern English Channel , 2009 .

[10]  Wensheng Jiang,et al.  Study on the seasonal variation of the suspended sediment distribution and transportation in the East China Seas based on SeaWiFS data , 2008 .

[11]  Chunyan Li,et al.  Cross-shelf circulation in the Yellow and East China Seas indicated by MODIS satellite observations , 2008 .

[12]  J. Winterwerp.  Stratification effects by fine suspended sediment at low, medium, and very high concentrations , 2006 .

[13]  Menghua Wang,et al.  Estimation of ocean contribution at the MODIS near‐infrared wavelengths along the east coast of the U.S.: Two case studies , 2005 .

[14]  J. Hölemann,et al.  Suspended particulate matter on the Laptev Sea shelf (Siberian Arctic) during ice-free conditions , 2003 .

[15]  Alex E. Hay,et al.  Coherent Doppler Profiler measurements of near-bed suspended sediment fluxes and the influence of bed forms , 2002 .

[16]  J. Winterwerp,et al.  Turbulent exchange of fine sediments in a tidal channel in the Ems/Dollard estuary. Part II. Analysis with a 1DV numerical model , 2001 .

[17]  Xinyu Guo,et al.  Three-dimensional structure of tidal current in the East China Sea and the Yellow Sea , 1998 .

[18]  S. Tassan.  Local algorithms using SeaWiFS data for the retrieval of phytoplankton, pigments, suspended sediment, and yellow substance in coastal waters. , 1994, Applied optics.

[19]  R. Sternberg,et al.  The effect of particle settling velocity on computed suspended sediment concentration profiles , 1989 .

[20]  R. H. Meade,et al.  World-Wide Delivery of River Sediment to the Oceans , 1983, The Journal of Geology.

[21]  Morrough P. O'Brien,et al.  Review of the theory of turbulent flow and its relation to sediment‐transportation , 1933 .

[22]  P. Chong.  DISTRIBUTION FEATURES OF SUSPENDED MATTER AND AMOUNT OF SEDIMENT AT THE CHANGJIANG ESTUARY AND ADJACENT AREA , 2003 .

[23]  K. Iseki,et al.  Variation of turbidity and particle transport in the bottom layer of the East China Sea , 2003 .

[24]  C. Harris,et al.  Across‐shelf sediment transport: Interactions between suspended sediment and bed sediment , 2002 .

[25]  Jiang Kun.  On Secondary Plume in the Southern Waters of the Changjiang River Estuary , 2002 .

[26]  程鹏,et al.  Characteristics of Suspended Sediment Concentrations over the Areas Adjacent to Changjiang River Estuary, the Summer of 1998 , 2000 .

[27]  Su Jilan,et al.  Changjiang river plume and suspended sediment transport in Hangzhou Bay , 1989 .