The efficiency assessment of short-term maximum flood level forecast methodology in the upper and middle course of the Tsna river

Abstract

A significant rise in water levels in the rivers during the spring flood and the release of rivers to the floodplain is the main danger in this period for nearby territories and people living there. This phenomenon can lead to flooding of large areas, significant economic losses, environmental damage, and threaten the health and life of local residents. Such negative consequences of high floods are typical for the Tambov region rivers, which indicates the need to develop an effective system for forecasting and preventing maximum flood levels. The climatic changes that have taken place over the past few decades, which are also reflected in the rivers’ water regime, show the need to modernize existing forecasting methodologies. In this paper, the authors have demonstrated the results of the effectiveness assessment of the existing methodology for short-term forecasting of the maximum flood level on the Tsna River at two gauging stations (“Kuzmino-Gat” and “Tambov”). Calculations were made using modern data in accordance with this methodology and a comparative analysis was carried out with the calculations of previous years. Based on this analysis, an assessment of the flood levels forecast methodology accuracy was given. According to the study results, it was found that the existing methodology for short-term forecasting of the maximum flood level on the Tsna River is largely ineffective nowadays with regard to modern conditions of spring flood runoff formation. In the analysis of the Kuzmino-Gat gauging station, the values of the maximum flood levels obtained by the reanalysis method according to the tested methodology using modern data showed significant deviations from the actual observed values. At the same time, for the operational forecast of maximum water levels at the Tambov gauging station, it is possible to use the correlation dependence with the observed water levels at the Kuzmino-Gat gauging station, as before. The correlation coefficient with modern data was 0.96. The authors have highlighted the main drawbacks of the existing methodology and made suggestions for improvement, in particular, what factors need to be analyzed in order to clarify the forecast.