The paper is concerned with the construction of maps of climatic indicators using a multivariate neural network. The application of the k-means clustering method for processing input data entering a neural network is described. An alternative neural model is considered within the framework of the multivariate neural network evolution.

The article discusses the practical application of the neural network for hydropower and water management systems. Various models of neural networks are understood, their advantages and disadvantages for a particular subject area. Method and operation of multiparametric neural network are described using practical examples, in particular, formation of interval estimates in reservoir of hydroelectric power station.