METHODS OF FORECASTING FLOOD SITUATIONS ON THE RIVERS OF KAZAKHSTAN AND THE ROLE OF LANDSCAPES ON THIS PROCESS

Abstract

The authors provide a pioneering assessment of the impact of agricultural landscapes on snow cover accumulation. The study aims to demonstrate their role in runoff accumulation during the spring period. The methodological approach involves calculating the probability of flood events based on the total autumn-spring snow water equivalent in correlation with atmospheric temperature values.

This article highlights high precipitation variability from September to March relative to long-term average data, which complicates situational forecasting. The work presents original, informational, and literature-based data on the causes of floods in the rivers of Northern and Western Kazakhstan. It is shown that the flow directions of rivers, categorized into northern and southern landscapes, possess distinct characteristics. These include weather and soil features that, in some cases, hinder the movement of floodwaters, while in others, accelerate the formation of meltwater that moves rapidly within the riverbed.

To illustrate this, data on maximum precipitation (mm) from September to March and during the autumn-winter periods are provided based on the Arkalyk Agricultural Experimental Station (the southernmost part of the basin). This is compared with maximum precipitation (mm) from September to May and during the autumn-winter and spring periods according to the Shagalaly meteorological station (the northernmost part of the basin), alongside air temperature data for these periods at both stations.

The originality of this work lies in the observation that the further south the part of the river basin is located, the greater the volume of generated water, which further increases the runoff volume in the northern part of the basin. Data from meteorological stations located from south to north along the river can simultaneously provide information on both air temperature and river water levels.