A Sediment Diagenesis Model of Seasonal Nitrate and Ammonium Flux Spatial Variation Contributing to Eutrophication at Taihu, China

Int J Environ Res Public Health. 2020 Jun 11;17(11):4158. doi: 10.3390/ijerph17114158.


Algal blooms have thrived on the third-largest shallow lake in China, Taihu over the past decade. Due to the recycling of nutrients such as nitrate and ammonium, this problem has been difficult to eradicate. Sediment flux, a product of diagenesis, explains the recycling of nutrients. The objective was to simulate the seasonal spatial variations of nitrate and ammonium flux. In this paper, sediment diagenesis modeling was applied to Taihu with Environmental Fluid Dynamics Code (EFDC). Latin hypercube sampling was used to create an input file from twelve (12) nitrogen related parameters of sediment diagenesis and incorporated into the EFDC. The results were analyzed under four seasons: summer, autumn, winter, and spring. The concentration of NH4-N in the sediment-water column increased from 2.744903 to 22.38613 (g/m3). In summer, there was an accumulation of ammonium in the water column. In autumn and winter, the sediment was progressively oxidized. In spring, low-oxygen conditions intensify denitrification. This allows algal blooms to continue to thrive, creating a threat to water quality sustainability. The sediment diagenesis model, coupled with water quality measured data, showed an average relative error for Total Nitrogen (TN) of 38.137%, making the model suitable. Future studies should simulate phosphate flux and measure sediment fluxes on the lake.

Keywords: algae; ammonium; diagenesis; nitrate; sediment flux; sustainability; water quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ammonium Compounds*
  • China
  • Environmental Monitoring*
  • Eutrophication*
  • Geologic Sediments*
  • Lakes
  • Models, Theoretical*
  • Nitrogen
  • Phosphorus
  • Seasons
  • Water Pollution / statistics & numerical data*


  • Ammonium Compounds
  • Phosphorus
  • Nitrogen