Abstract
An effective measure to cope with eutrophication of lakes is to remove nutrients that can cause algal blooming by taking advantage of natural water purification processes. Here, the term “purification” is defined, in a wide sense, as the potential role of a water body to contribute to the reduction of pollutants and thus controlling eutrophication. Also regarded as a kind of ecological regulating services, biological purification involves various processes concerning seasonal nutrient fixation, such as uptake by aquatic macrophyte, biofouling onto foliage substrates, feeding by organisms in higher trophic level, and eternal loss or removal of substance from the water. In order to evaluate the water purification ability, a numerical lake ecosystem model (EcoTaihu) was developed and applied to Lakes Taihu. The model includes the biological interactions between pelagic compartments (phytoplankton and zooplankton, detritus, dissolved organic matter, fish, and nutrients). Under dynamic forcing of meteorological and hydrological parameters, the model was run over years to evaluate the annual nutrient cycles and purification functions. The reproducibility of the model was validated for water body by comparison with the field data from the water quality monitoring campaign. Numerical results revealed that self-purification capacity of nitrogen of Lake Taihu in years 2006, 2008, and 2010 is 4.00 × 104, 4.27 × 104, and 4.11 × 104 ton, respectively, whereas self-purification capacity of phosphorus of Lake Taihu in years 2006, 2008, and 2010 is 1.56 × 103, 1.80 × 103, and 1.71 × 103 ton, respectively.
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Acknowledgments
This work was jointly supported by the research project “Study on the influence of water level control on submerged vegetation in a lake and the mechanism” (NSFC41230853), State Major Project of Water Pollution Control and Management (Grant No. 2014ZX07101-011), and “Accurate evaluation technology of cyanobacteria bloom stock in the lake”(NIGLAS2012135010). We would like to thank the Taihu Basin Authority of Ministry of Water Resources, Shanghai, China, and Taihu Laboratory for Lake Ecosystem Research, Chinese Academy of Sciences, for providing monitoring data.
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Han, T., Zhang, H., Hu, W. et al. Research on self-purification capacity of Lake Taihu. Environ Sci Pollut Res 22, 8201–8215 (2015). https://doi.org/10.1007/s11356-014-3920-6
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DOI: https://doi.org/10.1007/s11356-014-3920-6