Comprehensive assessment of eutrophication status based on Monte Carlo–triangular fuzzy numbers model: site study of Dongting Lake, Mid-South China

For the assessment of lake’s eutrophication status, a great deal of data uncertainties exists under the circumstances that monitoring data often are scarce and inaccuracy or the variation intervals are wide. In order to process these uncertainties of data and provide more valuable information for the decision makers, a methodology for assessing the eutrophication status was established by coupling Monte Carlo and triangular fuzzy numbers approaches and further combining it with the trophic level index method. This developed methodology was illustrated by a case study of evaluating the eutrophication status of Dongting Lake in Mid-South China (Hunan Province). The results indicated that the quantitative information of possible intervals of trophic level index, their corresponding probabilities and the comprehensive eutrophication statuses can be obtained. The eutrophication status of the East Dongting Lake was more serious than the southern and western parts. Portions of both East and South Dongting Lake showed a greater probability to light-eutrophic status, but with a worsening tendency, i.e., becoming mid-eutrophic in the 2010 year. By processing the data fuzzily and simulating their distribution characteristics stochastically, the presented methodology can be employed to process the uncertainties of the data evaluation and obtain a better early detection/warning of eutrophication levels with less requirement of time. Therefore, more reliable/valuable information can be provided to the decision makers, e.g., lake management authorities.