Abstract
Evaluating the eutrophication level of lakes with a single method alone is challenging since uncertain, fuzzy, and complex processes exist in eutrophication evaluations. The parameters selected for assessing eutrophication include chlorophyII-a, chemical oxygen demand, total phosphorus, total nitrogen, and clarity. Firstly, to deal with the uncertainties and fuzziness of data, triangular fuzzy numbers (TFN) were applied to describe the fuzziness of parameters. Secondly, to assess the eutrophication grade of lakes comprehensively, an improved fuzzy matter element (FME) approach was incorporated with TFNs with weights determined by combination of entropy method and analytic hierarchy process (AHP). In addition, the Monte Carlo (MC) approach was applied to easily simulate the arithmetic operations of eutrophication evaluation. The hybrid model of TFN, FME, and MC method is termed as the TFN–MC–FME model, which can provide more valuable information for decision makers. The developed model was applied to assess the eutrophication levels of 24 typical lakes in China. The evaluation indicators were expressed by TFNs input into the FME model to evaluate eutrophication grade. The results of MC simulation supplied quantitative information of possible intervals, the corresponding probabilities, as well as the comprehensive eutrophication levels. The eutrophication grades obtained for most lakes were identical to the results of the other three methods, which proved the correctness of the model. The presented methodology can be employed to process the data uncertainties and fuzziness by stochastically simulating their distribution characteristics, and obtain a better understanding of eutrophication levels. Moreover, the proposed model can also describe the trend of eutrophication development in lakes, and provide more valuable information for lake management authorities.
Highlights
Water resources of desirable quantity and suitable quality are a prerequisite for sustainable development of the economy, society and ecology [1]
The Monte Carlo (MC) method was performed by theCrystal Ball software, which is applied as an analytical tool to help execute, analyze, and make decisions by performing simulations and forecasting of data on spreadsheet models [18]
Eutrophication Grade Evaluated by Hybrid triangular fuzzy numbers (TFN)–MC–fuzzy matter element (FME) Model
Summary
Water resources of desirable quantity and suitable quality are a prerequisite for sustainable development of the economy, society and ecology [1]. In China, most lakes have serious water environmental problems, such as shrinkage of water surface area, eutrophication of lakes, organic pollution, etc. Eutrophication due to natural process (e.g., weathering, precipitation, soil erosion, etc.) and anthropogenic activities (industrial pollution, domestic drainage, etc.), has become a serious and common concern which threatens the public health and the ecological environment, even inducing water-borne diseases [2,3,4,5,6]. Res. Public Health 2019, 16, 1769; doi:10.3390/ijerph16101769 www.mdpi.com/journal/ijerph
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