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Abstract

Remote measurements of different environmental parameters received during last 30 years are used for the synthesis of a Complex Simulation Model (CSM) describing the combined water regimes of the Aral-Caspian System (ACS) including the consideration of aquatic and climatic natural processes. The problem of stabilizing the sea levels of these two water bodies is modelled and a solution obtained through implementation of a modeling system, including the CSM, remote measurements database, data processing sub-block, surface cover recognition sub-block, and user interface. A set of scenarios to control the ACS water regime is investigated. The role of remote sensing methods for the estimation of water balance components and synoptic situations is also evaluated. The main purpose of the computer experiments is in the search of a scenario for control of the water regime in the ACS under the realization of which the Aral Sea level will increase and the Caspian Sea level will decrease. The results of this research indicate that there is a regime for ACS water control under which it is possible to stabilize the Aral and Caspian Sea levels at their 1960 level within twelve to fifteen years. This would be implemented by the transport of water from the open portion of the Caspian Sea into saline lowlands and the Kara-Bogaz-Gol Gulf, located on its eastern shore, thus facilitating rapid evaporation followed by the movement of atmospheric moisture into the Aral Sea basin. The scenario “evaporation/precipitation” when the Caspian Sea level is lowered by increasing the flow of its waters to other reservoirs/evaporators is evaluated. Such reservoirs are the area of saline lands and depressions situated in the East Caspian Sea coast. Their absolute levels are below the recent Caspian Sea level. The results of this investigation show that the formation of an adaptive measurements system with the interchange of remote measurements and mathematical modeling provides a reliable evaluation of the ACS. This will lead to the creation of a system capable of predicting the dynamics of natural processes and assessing long-term consequences of large-scale global-change effects on the ACS.

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