Identification of the Power of a Series of Impurity Sources Based on a Variational Algorithm for Assimilation of Measurement Data

The aim of the work is to construct, test, and use a variation algorithm for identifying the capacities of a series of pollution sources in a passive admixture transfer model. The calculation results are considered depending on the amount of information and the location of the measurement points. The paper implements an example of variation assimilation of data on the concentration of suspended matter in the upper layer of the Sea of Azov in the area of the Dolgaya Spit, which is of great importance for navigation in this area. In the numerical implementation of the linear model of passive impurity transfer, the results of calculations based on the model of water circulation in the Sea of Azov, iterative methods for minimizing functionals, and solving the conjugate problem for constructing their gradients in the parameter space were used. When implementing the algorithm, the integration of the main and related tasks is carried out. The solution of the problem in variations is used when searching for a parameter for iteration. As a result of the implemented numerical experiments, the operability of the procedure is shown, which made it possible, under certain conditions, to accurately find the specified source capacities. The implemented variation procedure for assimilating measurement data and identifying the capacities of pollution sources can be used to solve similar environmental problems.