ANALYSIS AND TESTING OF METHODS FOR FORECASTING MAXIMUM MOUNTAIN RIVERS FLOW (Proceedings of the YSU C: Geological and Geographical Sciences, 2023)
The article discusses various methods for predicting the maximum flow of mountain rivers. Analysis and testing of techniques based on multivariate regression analysis and mathematical modeling were carried out, and a graphic-analytical approach was also used. For multivariate regression analysis, various predictors taken for the period of spring flood and for the previous winter period were considered. Some of the considered predictors were further selected as potential ones. The mathematical modeling method is based on modeling the processes of formation of snow reserves and water yield, as well as the formation of maximum flow. The graphic-analytical approach includes the construction of complex graphs that make it possible to visualize the patterns and trends of the characteristics under study. The basins of River Samur and River Andi Koysu were selected as objects for testing the approaches under study. Weather stations with a representative series of observations of meteorological characteristics were selected in the catchments of the listed rivers. The results of the study were mixed: the method of multivariate regression analysis made it possible to select predictors that give a satisfactory forecast only on dependent material; as a result of using a dynamic model of runoff formation, model parameters for flood months were obtained and optimized – testing for the feasibility of a separate forecast and the reliability of the methodology showed that both methods are more than 60% effective.
Keywords: mountain rivers; prediction; maximum flow; mathematical modeling; regression analysis