2018 №4 (61) Article 10

V.S. Valiev, D.V. Ivanov, D.Ye. Shamaev, I.I. Ziganshin, L.K. Mustafina, N.V. Shurmina, O.A. Bogdanova, F.M. Abdulina

THE ANALYSIS OF THE STRUCTURE OF HYDROCHEMICAL INDICES OF RIVER SYSTEMS. P.P. 89-99.

UDC 551.482.2:[551.48:54]

 

The article describes an attempt to test a dynamic stochastic model of the qualitative assessment of water resources taking into consideration temporal and spatial variations of the hydrochemical background at the example of the Kazanka River. The article singles out three orthogonal factors essential for modeling a hydrochemical situation and being formative for the assessment of local changes of hydrochemical indices in certain riverbed areas. The first factor is constituted by variables forming the major structure of hydrochemical processes: conductivity, dry residue, hardness, calcium, magnesium, sulfates, river flow volume, seasonal flexibility of major ions flow. The second factor unites variables reflecting the intensity of water processes associated with organic compounds entering a water system to be transformed: permanent and dichromate oxidizability, biochemical oxygen consumption. There is a correlation between the aforementioned indices and water color, which can be used to assess the organic contamination of surface waters. The third factor of this hydrochemical model is the concentration of suspended forms of heavy metals. Water turbidity determines the amount of metals (cadmium, copper, zinc, manganese, iron) migrating in their solid phase. The conducted research enables the author to assess the potential exceedance of maximum permissible concentrations of pollutants.  The article shows that their percentage accounted for by anthropogenic impact is distributed stochastically. Hence, an assessment should rely on probabilistic methods. Probabilistic characterization of a stochastic system enables a researcher to adequately and efficiently assess environmental situation at any particular water source.

 

Water quality; hydrochemical processes; factor analysis; dynamic and stochastic models; the Kazanka River

 

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