FORECASTING OF THE STATE OF THE SMALL ARAL SEA BASED ON OPEN DATA SOURCES
Ключевые слова:
Small Aral Sea, sea level, machine learning, river discharge, basins, Syrdarya, hydrodynamic modeling.Аннотация
The study of the dynamics of the level and volume of water in the Aral Sea is an urgent scientific task
due to the need to understand the mechanisms of natural and anthropogenic processes that have induced a radical
change in its water and salt balance over the past 60 years. In particular, the study of the dynamics of water balance
components in the basin of the Small Aral Sea is the most important task when planning scenarios for water use in
the region. In the proposed work, based on the methods of machine learning (for the implementation of
computational functions in the program), two statistical models were developed: a forecast model for the monthly
values of river flow in the Syrdarya river and the forecast of variability of the water volume of the Small Aral Sea.
Based on the simulation results, forecasts were made for the values of the Syrdarya drainage and the water volume of
the Small Aral Sea. In conditions of low availability of field observations data, the operational estimates of the water
balance component are the most important source of information on the changes occurring in the basin under
investigation. The proposed technique can also be used to obtain initial conditions in experiments on hydrodynamic
modeling, as well as to calculate climatic scenarios for the development of the hydrological system of the Aral Sea.
