Complex Assessment and Forecasting of Chemical Pollution of Small Rivers by Economic and Mathematical Modelling Methods

Abstract

The purpose of this work is to determine the hydrochemical parameters of the water of the river Seret and the features of the accumulation of heavy metals by bivalve molluscs Unio pictorum L. to predict the chemical contamination of the reservoir in the near future. Water samples for the study were taken in spring (April) and summer (July) from the Seret River at two points: above and below Ternopil. It is established that the chemical composition of the water of the river Seret is formed under the influence of a number of factors, but seasonal and anthropogenic factors play a dominant role. In the spring season, a number of hydrochemical indicators (pH, water hardness, concentration of ΝΟ 2 - , ΝН4 + , Сl- ions and metals) have lower values than in the summer. In addition, there is an increase in the amount of organic matter, ammonium cations, nitrite ions, chloride ions, phosphate ions and a decrease in oxygen concentration below Ternopil, especially in the summer season. This is evidence that the Seret River is under significant anthropogenic impact. An increase in the concentration of metals (Mn, Cu and Pb) in summer below Ternopil was revealed, which may be due to the discharge of insufficiently treated wastewater. The series of metal concentrations in the water of the Seret River looks as follows Mn → Zn → Pb → Cd → Cu, and the series of accumulation of metals in the tissues of molluscs Unio pictorum L. has the form Zn → Mn → Cu → Pb → Cd. On the basis of bioaccumulation coefficients of heavy metals by molluscs, a prediction of the situation on their content in water for the short term based on the theory of Markov chains was made. This theory allows us to make forecasts of a factor, taking into account the possibility of accidental influences on the environment, and to investigate the highest probability of finding a factor in a certain numerical parameter. The possibility of using economic and mathematical modelling tools and statistical methods based on correlation-regression analysis using modern Matlab information systems to identify correlations between chemical indicators of water quality and biological molluscs for modelling the environmental situation of the river Seret and assessing the contribution of the studied indicators in pollution of small rivers is shown.