The Eutrophication Evaluation Method Based On Multidimensional Normal Cloud Model

It is very important to evaluate water eutrophication. In view of the randomness and fuzziness in the process of evaluation, the eutrophication evaluation method based on multidimensional normal cloud model(Multidimensional Normal Cloud Model Method, MNCM) is proposed, which put each evaluation factor respectively as one-dimensional attribute of the multi-dimensional normal cloud model, choosing the reasonable parameters of the cloud model and the weights of the evaluation factors are determined by the entropy weight method. The multidimensional normal cloud models that all evaluation factors belonging to each eutrophication level are generated and water eutrophication level is determined by the certainty. MNCM method is used to evaluate twelve typical lakes and reservoirs in China and contrasted with the real water quality, the eutrophication valuation method based on one-dimensional normal cloud model, which is proposed recently, and other common methods (the related weighted nutrition state index method, scoring method, fuzzy comprehensive evaluation method) which are widely used.The results show that the results of MNCM method are consistent with the actual water barrier, which show that MNCM method is feasible. Without increasing the complexity of modeling, the MNCM method is further simplification and the parameters of the cloud model are improved than the eutrophication valuation method based on one-dimensional normal cloud model. Comparing with other common methods, the evaluation results of the MNCM method are in good agreement with that of the common methods, which show that MNCM method is effective and make up for the limitations of common methods. According to the certainty, the MNCM method can determine the eutrophication level directly, furthermore, this method can judge water eutrophication degree whose eutrophication level are in the same, so that it is more consistent with the complexity of water eutrophication evaluation.