Abstract: In order to correctly evaluate the trophic state of a lake and then to establish scientific basis for the prevention of lake eutrophication, a lake eutrophication stochastic assessment method (LESAM) by using Bayes formula is proposed. In this method, according to the maximum likelihood ordering principle, the assessment order of each water quality index of an actual lake was firstly derived through calculating the probability of each of those water quality indices belonging to the assessment order used in the lake eutrophication assessment criteria. Secondly, the assessment order of lake eutrophication is derived by using the weighting average method. The characteristics of LESAM are that the method is simple, and the computation work is moderate. LESAM, together with other two methods, i.e. the lake eutrophication fuzzy assessment method (LEFAM) and the lake eutrophication gray assessment method (LEGAM), has been tested against the measured data of 30 lakes all over the country. It is found that the difference of assessment results among those three methods is not greater than 1 order in 29 lakes, i.e. 96.6％ of the total lakes. It is concluded that all these three methods (LESAM, LEFAM, and LEGAM) have comparable computation precision. Though in lake eutrophication assessment we can calculate the weight of each water quality index according to the correlation coefficient between each water quality index and chlorophyll, this method only suits the lakes of phytoplankton type. As to the equally weighting average method, it can be used for any kind of lakes. For there is a lot of uncertainty involved both in determining the number and type of water quality index in lake eutrophication assessment and in determining the assessment order and its corresponding standard water quality concentration, the lake eutrophication assessment methods also have uncertainty. It is suggested that the lake eutrophication assessment should be studied with various approaches in order to overcome the weakness of one particular method and to make assessment results more reasonable.

Key words: lake eutrophication, Bayes formula, stochastic assessment method, fuzzy assessment method, grey assessment method, uncertainty