Intelligent distribution characteristic analysis of heavy metals in reservoir sediments

  • Wang Min
  • Cheng Wen
  • Ren Jie-Hui
  • Meng Ting
  • Wan Tian
Article
  • 20 Downloads

Abstract

Heavy metals in reservoir sediments have a potential and concealed hazard influence on the environment. Benthos are sensitive to the quality of water environment. A research was conducted on the distribution characteristic of heavy metals and benthos in sediments of a reservoir used as water source, and discussions were made on the mutual relations between heavy metals and benthos in sediments. Samples were taken from the sediments of Tangpu Reservoir—a water source reservoir—to analyze the contents of heavy metals and the number of species of benthos. The results showed that significant sedimentation of Fe and Mn in the reservoir sediments, long-term enrichment of Cu and Zn and insignificant accumulation of Cr, Cd and Pb in the reservoir area. The distribution characteristic of benthos was decided by water quality of the reservoir, hydrology, the sedimentary environment, etc., showing much less number of species, biological density and biomass in the reservoir area than the upstream area. The contents of heavy metals such as Mn and Cr had great influence on the distribution of benthos.

Keywords

Water-source reservoir Sediments Heavy metals Benthos 

References

  1. 1.
    Mayer, L.M., Chen, Z., Findlay, R.H.: Bioavailability of sedimentary contaminates subject to deposit-feeder digestion. Environ. Sci. Technol. 30(8), 2641–2645 (1996)CrossRefGoogle Scholar
  2. 2.
    Van Dolah, R.F., Hyland, J.L., Holland, A.F.: A benthic index of biological integrity for assessing habitat quality in estuaries of the southeastern USA. Mar. Environ. Res. 48(4–5), 269–283 (1999)CrossRefGoogle Scholar
  3. 3.
    Berg, P., Rysgaard, S., Funch, P.: Effects of bioturbation on solutes and solids in marine sediments. Aquat. Microbial. Ecol. 26(1), 81–94 (2001)CrossRefGoogle Scholar
  4. 4.
    Thompson, B., Lowe, S.: Assessment of macrobenthos response to sediment contamination in the San Francisco Estuary, California, USA. Environ. Toxicol. Chem. 23(9), 2178–2187 (2004)CrossRefGoogle Scholar
  5. 5.
    Peeters, E.T., Gylstra, R., Vos, J.H.: Benthic macroinvertebrate community structure in relation to food and environmental variables. Hydrobiologia 519(1–3), 103–115 (2004)CrossRefGoogle Scholar
  6. 6.
    Zhu, G.W., Wang, F., Zhang, Y.L.: Hypoxia and its environmental influences in large, shallow, and eutrophic Lake Taihu, China. Int. Assoc. Theor. Appl. Limnol. 30(3), 361–365 (2008)Google Scholar
  7. 7.
    Barry, J.P., Dayton, P.K.: Physical heterogeneity and the organization of marine communities. Ecol. Heterog. 86, 270–320 (1991)CrossRefGoogle Scholar
  8. 8.
    Dauvin, J.C., Ruellet, T., Borja, A.: The estuarine quality paradox: is it possible to define an ecological quality status for specific modified and naturally stressed estuarine ecosystems. Mar. Pollut. Bull. 59(1), 38–47 (2009)CrossRefGoogle Scholar
  9. 9.
    Underwood, A.J., Chapman, M.G.: Scales of spatial patterns of distribution of intertidal invertebrates. Oecologia 107(2), 212–224 (1996)CrossRefGoogle Scholar
  10. 10.
    Du, Y., Xu, K., Warren, A., Lei, Y., Dai, R.: Benthic ciliate and meiofaunal communities in two contrasting habitats of an intertidal estuarine wetland. J. Sea Res. 70(3), 50–63 (2012)CrossRefGoogle Scholar
  11. 11.
    Vardhana, M., Arunkumar, N., Abdulhay, E., Ramirez-Gonzalez, G.: Convolutional neural network for bio-medical image segmentation with hardware acceleration. Cogn. Syst. Res. 50, 10–14 (2018)CrossRefGoogle Scholar
  12. 12.
    Abdulhay, E., Elamaran, V., Arunkumar, N., Venkatraman, V.: Fault-tolerant medical imaging system with quintuple modular redundancy (QMR) configurations. J Ambient Intell Human Comput (2018).  https://doi.org/10.1007/s12652-018-0748-9 Google Scholar
  13. 13.
    Abdulhay, E., Arunkumar, N., Narasimhan, K., Vellaiappan, E., Venkatraman, V.: Gait and tremor investigation using machine learning techniques for the diagnosis of Parkinson disease. Fut. Gener. Comput. Syst. (2018).  https://doi.org/10.1016/j.future.2018.02.009 Google Scholar
  14. 14.
    Abdulhay, E., Mohammed, M.A., Ibrahim, D.A., Arunkumar, N., Venkatraman, V.: Computer aided solution for automatic segmenting and measurements of blood leucocytes using static microscope images. J. Med. Syst. 10, 1–10 (2018)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Wang Min
    • 1
  • Cheng Wen
    • 1
  • Ren Jie-Hui
    • 1
  • Meng Ting
    • 1
  • Wan Tian
    • 1
  1. 1.State Key Laboratory of Eco-hydraulics in Northwest Arid RegionXi’an University of TechnologyXi’anChina

Personalised recommendations