Temporal variation of major nutrients and probabilistic eutrophication evaluation based on stochastic-fuzzy method in Honghu Lake, Middle China

Honghu Lake, which is listed in the Ramsar Convention, was found to be contaminated with elevated nutrients to a certain extent. This study investigated the seasonal variation of major nutrients and probabilistic eutrophic state in surface water from Honghu Lake. Average concentrations of total nitrogen (TN), total phosphorus (TP), chlorophyll- a (Chl- a ), chemical oxygen demand (COD Mn ) and transparency (SD) in summer and winter generally exceeded Grade III of the Chinese environmental quality standards for surface water (GB 3838-2002), with the exception of COD Mn in winter. Mean concentrations of Chl- a and COD Mn in summer were higher than that in winter, while mean concentrations of TN, TP and SD were slightly higher in winter. The improved probabilistic comprehensive trophic level index (PTLI) method based on stochastic-fuzzy theory was established to evaluate the eutrophic state in Honghu Lake. Compared with the Monte-Carlo sampling method, the Latin Hypercube sampling (LH-TFN) method was selected for the evaluation simulation due to its efficiency and stability. Evaluation results indicated that mean PTLI in summer (69.70) and winter (61.96) were both subordinated to Grade IV (Medium eutrophication). The corresponding reliability of eutrophication level subordinating to Grade IV in summer was of relatively low reliability (51.27%), which might mislead decision makers to some extent and suggest recheck. The probabilistic eutrophication level in summer developed with a trend from medium to severe eutrophication. Sensitivity analysis illustrated that COD Mn and Chl- a were the priority pollutants in summer, with the contributions to PTLI of 43.3% and 22.5% respectively. Chl- a was the priority pollutant in winter, with the contribution to PTLI up to 51.3%.