Seasonal and Annual Probabilistic Forecasting of Water Levels in Large Lakes (Case Study of the Ladoga Lake)
| Autor: | Natalia V. Myakisheva, Sergei V. Shanochkin, Anna A. Batmazova, Ekaterina Gaidukova |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Hydrology
Water resources 0208 environmental biotechnology Environmental science 02 engineering and technology Autoregressive integrated moving average Probabilistic forecasting 010501 environmental sciences 01 natural sciences 020801 environmental engineering 0105 earth and related environmental sciences Water level |
| Zdroj: | International Letters of Natural Sciences. 82:13-19 |
| ISSN: | 2300-9675 |
| Popis: | The production functions of water-dependent sectors of the economy can include the water level in the lake as a natural resource. This characteristic must be able to reliably predict for the effective functioning of sectors of the economy. In the article the main attention is paid to the methods of forecasting based on the extrapolation of natural variations of the large lakes water level. As an example, is considered. In this paper, it is assumed that the level varies accordingly to a stochastic multi-cycle process with principal energy-containing zones in frequency bands associated with seasonal and multi-annual variations. Hence, the multi-year monthly and yearly averaged time series are represented by the ARIMA (auto-regression integrated moving average) processes. Forecasts are generated by using of the seasonal ARIMA-models, which take into account not only the seasonal but also the evolution non-stationarity. To compare the forecasts and the actual values, the relative errors are computed. It is shown that implementation of the models mainly allows receiving good and excellent forecasts. Subject Classification Numbers: UDC 556.555.2.06(4) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|