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Formation and Evolution of the Anaerobic Zone in the Black Sea from the Most Recent Salinization to the Present State: Retrospective Estimation Based on Mathematical Modeling

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Abstract

It is established that the formation and evolution of the anaerobic zone of the Black Sea are associated with the beginning and development of the most recent salinization of the sea and the formation of pycnocline at intermediate depths; a deterioration of deep-water aeration and the formation of anaerobic conditions in deeper layers; the rate of sulfate-reduction first in the near-bed layer and later, as oxygen is depleted, in the water mass. Formalization of these processes based on refined present-day data on water balance enabled the reproduction of profiles of water salinity and vertical-exchange coefficient for different formation stages of salinity regime in the Black Sea. The vertical distribution of oxygen and hydrogen sulfide is reconstructed, and the rates of oxygen consumption in water column and sulfate reduction in the near-bed layer and at the upper boundary of the anaerobic zone are evaluated in numerical experiments. The obtained data show the transformation of the vertical distribution of oxygen and hydrogen sulfide in the Black Sea from the beginning of its most recent salinization to the present-day state. It is shown that the anaerobic zone rises from 2000 to 200 m within 500–600 years (in the period 3.9–4.5 Ka from the beginning of water exchange through the Bosphorus), and next the upper boundary of the anaerobic zone slowly ascends up to its present-day position (130–180 m). Mathematical modeling was used to evaluate the fluxes of oxygen and hydrogen sulfide at different formation stages of the anaerobic zone in the sea.

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Translated from Vodnye Resursy, Vol. 32, No. 3, 2005, pp. 307–321.

Original Russian Text Copyright © 2005 by Leonov, Shaporenko.

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Leonov, A.V., Shaporenko, S.I. Formation and Evolution of the Anaerobic Zone in the Black Sea from the Most Recent Salinization to the Present State: Retrospective Estimation Based on Mathematical Modeling. Water Resour 32, 276–290 (2005). https://doi.org/10.1007/s11268-005-0037-9

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