Abstract: Artificial neural network was developed to evaluate the nutrient states of South Lake water in Changchun in this paper. Taking Chemical Oxygen Demand, Tolal Nitrogen and Total Phosphorus as evaluation parameters and after repeating attempts, the four-layer structural Error Back Propagation network was established to evaluate lake nutrient states.There are three neural units in input layer, four in both hidden layers, and one in output layer. Taking the evaluation criterion of lake nutrient states as sample pattern, the network was trained in the light of learning rule of Error Back Propagation network. After 39?925 tries, the network reached the convergence standard given in advance. The operation process of the network is simple and convenient, and the results indicate that South Lake water in Changchun is, on the whole, in the state of extreme eutrophication.