статья в журнале

En

PHYSICAL OCEANOGRAPHY

ISSN:0928-5105
eSSN:1573-160X

2019

10.22449/1573-160X-2019-1-63-76

Introduction. Scenarios of development of the processes in the complex marine ecosystems are forecasted by the models developed for marine ecosystems. At that the method for formalizing the scheme of the cause-effect relations (impacts) is required. In other words, it is necessary to construct the equation system for the model variables connecting the functions representing the modeled processes. Data and Methods. Proposed are the methods for modeling the processes in the marine ecosystems based on the system principles of the adaptive balance of causes and informational unity of the processes' models and the corresponding observational data. Analysis of Results. It is shown that application of these principles permits to construct the adaptive models with negative feedbacks of the 1st and the 2nd orders between the model variables and the speed of their variation. These models provide automatic fitting of the model variables to each other and to the external effects; at the same time they preserve the matter balances in the substance transformation reactions in the marine environment. The simulation results reveal that the 2nd order adaptive models are more sensitive to the external effects influencing the ecosystem and adapt to them quicker. Application of the adaptive modeling principles is illustrated by the data of hydrochemical observations in the Sevastopol Bay. Two methods of reconstructing dynamics of the nitrite concentration are comparatively analyzed using the time series of the ammonium and nitrate observations. Discussion and Conclusions. It is shown that the dynamic-stochastic equation provides much higher accuracy of reconstruction of the unobserved process of the nitrite concentration as compared to the method of the normalized relations of the mean values. Besides, the reconstruction accuracy increases with growth of length of the observation time series applied at constructing their covariance matrix.

ADAPTIVE MODELING, ADAPTIVE BALANCE OF CAUSES, MARINE ECOSYSTEM, RECONSTRUCTION OF THE UNOBSERVED PROCESSES, INFLUENCE COEFFICIENTS, COVARIANCE MATRIX, DYNAMIC-STOCHASTIC EQUATION, NITRIFICATION, SEVASTOPOL BAY

2019-12-12 15:49:00