METHOD OF LONG-TERM FORECAST OF WATER INFLOW TO THE CASCADE OF RESERVOIRS ON THE KOLYME RIVER FOR THE SECOND QUARTER OF THE YEAR
On the Kolyma River (North-East of Russia) operates a cascade of two hydropower plants. For more efficient use of water resources, the Kolyma hydropower industry needs to forecast the total of water inflow into the reservoirs for the second quarter of the year. The need for predictions of water inflow for the second quarter to the cascade of hydroelectric stations is due to the following reasons. Firstly, in April, in front of the Kolyma hydropower industry, there is a dilemma: to pass a spring flood wave, to discharge unused water from the reservoirs or not, and if so, to what extent. So, if the year turns out to be low-water, as a result of idle discharges of water, when oriented to the norm, reservoirs can "go off into the winter" with insufficient water, which will cause a decrease in the generation of electricity in the winter. Secondly, almost every year during the summer-autumn low water hydroelectric power stations perform idle discharges of water to ensure navigational levels on the river. Kolyma, and in this case, the hydropower industry also faces the problem of the permissible value of idle discharges of water from reservoirs. In this paper, the goal is to develop a methodology for the long-term forecast of the total inflow of water into the Kolyma and Ust-Srednekanskoye reservoirs for the second quarter. This technique is being developed for the first time. A characteristic feature of the territory under consideration is the cold climate. Permafrost is widespread everywhere. The water discharge in the second quarter is 40-50% of the annual volume. It is formed mainly by meltwater. Spring flood begins in the first half of May and ends in the second half of June, early July. The initial data on the flow of water to the cascade of reservoirs on the Kolyma River, the maximum water reserves in the snow cover in the reservoir basin were obtained from the Kolyma Department of Hydrometeorology and Environmental Monitoring. Information on air temperature is taken from the website of the Russian Institute of Hydrometeorological Information - the World Data Center. In the multi-year course of water inflow in the second quarter, there is no statistically significant trend, but there are non-linear trends in long-term fluctuations in mean air temperature in the second quarter and maximum snow reserves in the reservoir cascade basin. The presence of positive trends, obviously, is connected with the modern global warming of the climate. The increase in precipitation is apparently compensated by the increase in evaporation from the surface of the catchment area due to the increase in air temperature, so the rate of water inflow does not change. Spectral analysis of a series of water inflows revealed cycles of 3 and 6 years, that is, it can be assumed that the series under investigation represents the realization of a random process of large space-time scale, to which the statistical model of a complex Markov chain corresponds. The series of predictors has trends, therefore it is expedient to make the construction of the forecast model using a sliding training sample. A satisfactory method of forecasting of the water inflow to the cascade of reservoirs for the second quarter was obtained by the method of a sliding training sample, and the justification of the verification forecasts was 76,2 %. Predictors were the maximum water reserves in the snow cover and the Polar-Eurasian index of atmospheric circulation. It is shown that the method of sliding regression is more effective than the traditional approach, in which the regression coefficients in the prognostic equation are constant.