Journal of Coastal Conservation

, Volume 21, Issue 1, pp 197–207 | Cite as

Evaluation of spatiotemporal differences in suspended sediment concentration derived from remote sensing and numerical simulation for coastal waters

  • Jianzhong Lu
  • Xiaoling Chen
  • Pang Zhang
  • Jue Huang


Remote sensing and numerical models are often used to monitor the suspended sediment concentration (SSC) in coastal waters; however, the derived SSC varies between the two methods in both space and time. In this study, a method was proposed to assess the spatiotemporal differences in SSC derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images and numerical simulation for coastal waters, using the Bohai Sea in China as an example. An empirical model for SSC retrieval from remote sensed images was initially established. A comparison of the temporal synchronicity over a single day period was performed between the observed data and the numerically simulated results. The range in the SSC at different observation sites was significantly different. Both the SSC values and their daily variation ranges were larger near the estuary of the Yellow River compared with the open area due to the concurrence of tidal flow and the introduction of fresh river water with high turbidity near the estuary. The areas that exhibited spatial differences were defined according to their differences in remotely sensed and numerically simulated SSC distribution patterns. Finally, the reasons for these spatiotemporal differences were discussed. The results provided understanding into the spatiotemporal differences that were introduced when multi-source data were used, thus improving the accuracy of the results when monitoring coastal environments for the management of coastal conservation.


Remote sensing Numerical simulation Suspended sediment Spatiotemporal difference Bohai Sea 



This work was funded by the National Natural Science Funding of China (NSFC) (Grant No. 41331174), Natural Science Foundation of Hubei Province of China (2015CFB331); the Special Fund by Surveying & Mapping and Geoinformation Research in the Public Interest (201512026), the Collaborative Innovation Center for Major Ecological Security Issues of Jiangxi Province and Monitoring Implementation (Grant No. JXS-EW-08), the Open Foundation of Jiangxi Engineering Research Center of Water Engineering Safety and Resources Efficient Utilization, and the LIESMARS special research funding.


  1. Bakhtyar R, Barry DA, Yeganeh-Bakhtiary A, Li L, Parlange JY, Sander GC (2010) Numerical simulation of two-phase flow for sediment transport in the inner-surf and swash zones. Adv Water Resour 33(3):277–290CrossRefGoogle Scholar
  2. Barale V, Zin I (2000) Impact of continental margins in the Mediterranean Sea: hints from the surface colour and temperature historical record. J Coast Conserv 6(1):5–14CrossRefGoogle Scholar
  3. Bi N, Yang Z, Wang H, Fan D, Sun X, Lei K (2011) Seasonal variation of suspended-sediment transport through the southern Bohai Strait. Estuar Coast Shelf Sci 93:239–247CrossRefGoogle Scholar
  4. Booth JG, Miller RL, McKee BA, Leathers RA (2000) Wind-induced bottom sediment resuspension in a microtidal coastal environment. Cont Shelf Res 20:785–806CrossRefGoogle Scholar
  5. Chavez PS (1996) Image-based atmospheric corrections – revisited and improved. Photogramm Eng Remote Sens 62(9):1 025–1 036Google Scholar
  6. Chen X, Lu J, Cui T, Jiang W, Tian L, Chen L, Zhao W (2010) Coupling remote sensing retrieval with numerical simulation for SPM study – taking Bohai Sea in China as a case. Int J Appl Earth Obs Geoinf 12(S2):203–211CrossRefGoogle Scholar
  7. Cruz-Garcia LM, Arreola-Lizarraga JA, Ceseña-Beltran GE, Mendoza-Salgado RA, Galina-Tessaro P, Beltran-Morales LF, Ortega-Rubio A (2015) An examination of coastal conservation by remote sensing in Baja California Sur, México. J Coast Conserv 19(4):609–619CrossRefGoogle Scholar
  8. Ferreira MA, Andrade F, Mendes RN, Paula J (2012) Use of satellite remote sensing for coastal conservation in the eastern African coast: advantages and shortcomings. Eur J Remote Sens 45(2):293–304CrossRefGoogle Scholar
  9. Gailani J, Ziegler CK, Lick W (1991) The transport of sediments in the Fox River. J Great Lakes Res 17:479–494CrossRefGoogle Scholar
  10. HydroQual I (2002) A primer for ECOMSED, user manual version 1.3. HydroQual, Inc., Mahwah, pp 33–35Google Scholar
  11. Jiang WS, Pohlmann T, Sundermann J, Feng SZ (2000) A modeling study of SPM transport in the Bohai Sea. J Mar Syst 24:175–200CrossRefGoogle Scholar
  12. Jiang WS, Pohlmann T, Sun J, Starke A (2004) SPM transport in the Bohai Sea: field experiments and numerical modeling. J Mar Syst 44:175–188CrossRefGoogle Scholar
  13. Jorgensen PV, Edelvang K (2000) CASI data utilized for mapping suspended matter concentrations in sediment plumes and verification of 2-D hydrodynamic modelling. Int J Remote Sens 21(11):2247–2258CrossRefGoogle Scholar
  14. Kouts T, Sipelgas L, Savinits N, Raudsepp U (2007) Environmental monitoring of water quality in coastal sea area using remote sensing and modeling. Environ Res, Eng Manag 1(39):8–13Google Scholar
  15. Li GS, Dong C, Wang HL (2006) Numerical simulation of transportation of SPM from the Yellow River to the Bohai Sea. China Ocean Eng 20(1):133–146Google Scholar
  16. Lu X, Zhang J (2006) Numerical study on spatially varying bottom friction coefficient of a 2D tidal model with adjoint method. Cont Shelf Res 26(16):1905–1923CrossRefGoogle Scholar
  17. Lu J, Wai WHO, Chen X, Zhang P (2014a) Flow prediction using ENVISAT RA-2 SSH validated model: a case study for Hong Kong-Zhuhai-Macau bridge in Pearl River estuary, China. Aquat Ecosyst Health Manag 7(3):305–315Google Scholar
  18. Lu J, Chen X, Tian L, Zhang W (2014b) Numerical simulation aided MODIS capture of sediment transport for the Bohai Sea in China. Int J Remote Sens 35(11–12):4225–4238CrossRefGoogle Scholar
  19. Miller RL, Mckee BA, D’Sa EJ (2005) Monitoring bottom sediment resuspension and suspended sediments in shallow coastal waters. In: Remote Sensing of Coastal Aquatic Environments, Springer, pp. 259–276Google Scholar
  20. Mobley CD (1994) Light and water: radiative transfer in natural waters. San Diego, Academic Press, Inc., California, p 592Google Scholar
  21. Ouillon S, Durand N, Forget P, Fiandrino A, Fraunie P, (1998) Remote sensing as a tool for suspended sediment transport modeling in coastal areas. In: Proceeding of Third International Conference on Multiphase Flow, ICMF’98, 8–12 June, Lyon, FranceGoogle Scholar
  22. Ouillon S, Douillet P, Andrefouet S (2004) Coupling satellite data with in situ measurements and numerical modeling to study fine suspended-sediment transport: a study for the lagoon of New Caledonia. Coral Reefs 23:109–122CrossRefGoogle Scholar
  23. Pleskachevsky A, Gayer G, Horstmann J, Rosenthal W (2005) Synergy of satellite remote sensing and numerical modeling for monitoring of suspended particulate matter. Ocean Dyn 55:2–9CrossRefGoogle Scholar
  24. Qin Y, Li F (1982) The study of the SPM in the Bohai Sea. Acta Oceanol Sin 4(2):191–200 (in Chinese)Google Scholar
  25. Rasyif TM, Syamsidik A’a M, Fahmi M (2016) Numerical simulation of the impacts of reflected tsunami waves on Pulo Raya Island during the 2004 Indian Ocean tsunami. J Coast Conserv 20(6):489–499CrossRefGoogle Scholar
  26. Ren ME, Shi YL (1986) Sediment discharge of Yellow River China and its effect on the sedimentation of the Bohai and Yellow Sea. Cont Shelf Res 6(6):785–810CrossRefGoogle Scholar
  27. Sipelgas L, Raudsepp U, Kouts T (2006) Operational monitoring of suspended matter distribution using MODIS images and numerical modeling. Adv Space Res 38:2182–2188CrossRefGoogle Scholar
  28. The Bohai Sea Geology (1985) Science Press, Beijing, pp232 (in Chinese)Google Scholar
  29. Van Rijn LC (1984) Sediment transport, part II: suspended load transport. ASCE J Hydraul Eng 110(11):1 613–1 641Google Scholar
  30. Wang L, Zhao D, Yang J, Chen Y (2012) Retrieval of total suspended matter from MODIS 250 m imagery in the Bohai Sea of China. J Oceanogr 68:719–725CrossRefGoogle Scholar
  31. Wang D, Liu Q, Lv X, (2014) A study on bottom friction coefficient in the Bohai, Yellow, and East China Sea. Mathematical Problems in Engineering, 1–7, Article ID 432529, 7 pages, DOI:  10.1155/2014/432529
  32. Zhang P, Wai WHO, Chen X, Lu J, Tian L (2014a) Improving sediment transport prediction by assimilating satellite images in a Tidal Bay model of Hong Kong. Water 6(3):642–660CrossRefGoogle Scholar
  33. Zhang P, Wai WHO, Lu J, Chen X (2014b) Numerical modeling of cohesive sediment transport in a tidal bay with current velocity assimilation. J Oceanogr 70(6):505–519CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Jianzhong Lu
    • 1
    • 2
  • Xiaoling Chen
    • 1
  • Pang Zhang
    • 3
  • Jue Huang
    • 4
  1. 1.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina
  2. 2.Jiangxi Engineering Research Center of Water Engineering Safety and Resources Efficient UtilizationNanchangChina
  3. 3.Ministry of Water Resource and Chinese Academy of SciencesInstitute of HydroecologyWuhanChina
  4. 4.College of GeomaticsShandong University of Science and TechnologyQingdaoChina

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