Numerical Simulation About Water Eutrophication And Research On The Risk Probability In Small Artificial Lake

Eutrophication of lakes is a major problem for the lake water ecological environment, most of the lakes in our country are in a state of eutrophication at present. In order to improve the urban ecological environment and improve the quality of urban residents’ life, the construction of the small artificial lakes has been a rapid development with the rapid development of urbanization and the improvement of people’s living standard. And the small artificial lakes are the important part of the urban ecosystem and landscape diversity. While the small artificial lakes have the following characteristics, such as small water area and vulnerable to outside influence of strong interference, small water storage, easy to pollution, low self-purification ability, fragile water ecological system and water quality of rapid conversion. The research foundation of the small artificial lakes is relatively weak compared with large water eutrophication lakes. In order to study water eutrophication mechanism, simulation model and united risk probability of the small artificial lakes, we took the small artificial Meihu Lake of Zhengzhou University New Campus as the experimental field, and launched a series of research work.(1) The change rules of pollutants in the water quality and sediment of the each monitoring section in the Meihu Lake were analyzed, and the correlations between the monitoring indicators were analyzed on the basis of field monitoring and laboratory tests. The limiting factors affecting water eutrophication of Meihu Lake were identified on the basis of the monitoring data, and the degree of water eutrophication was evaluated using the comprehensive nutrition state index and point method.(2) According to the measured data of Meihu Lake, the interaction relationships between the algae, chlorophyll a and other water quality impact factors were analyzed, and the nonlinear simulations of algae and chlorophyll a were also analyzed using artificial neural network method. On the basis of the main affecting factors of water transparency in Meihu Lake were identified, a multiple regression model was established between water water transparency and the main affecting factors; and the quantitative relation was setted between water transparency and attenuation coefficient of illumination according to Beer-Lambert Law, the eutrophication model was constructed on the basis of water transparency and combined with eutrophication basic model and hydrodynamic model. Then the parameters of the model were calibrated and validated, and analyzed the effects for the algal growth in Meihu Lake according to the different situations, such as the changes of illumination, and nutrient concentration and water transparency.(3) On the basis of the simulation results of the water eutrophication model, the marginal distribution functions of water eutrophication index were established. Then the degree of fitting was tested and the goodness of fitting was evaluated for the joint distribution of two dimensional and three dimensional Copula function under different combinations, and the more suitable joint distribution of Copula function was selected for each combination. The two dimensional and three dimensional portfolio risk probability of water eutrophication index was quantitative analyzed.