The study of the hydrological regimes of rivers in different regions of the globe has revealed the need to include the soil moisture content in flood prediction models. This paper investigates the nature of the dependence of soil moisture content on soil texture in the East Kazakhstan region. Data from ERA-5-land reanalysis, soil maps, hydrogeological maps, and the meteorological data of Kazhydromet were used. The years for analysis were selected due to their different moisture conditions. This study analyzed soil moisture within the root zone (0–28 cm depth). A JavaScript-based algorithm was developed in Google Earth Engine to analyze soil moisture and total precipitation across five Soil Texture Index categories during the growing seasons (April–September) of 2013, 2022, and 2023. Final cartographic processing and spatial distribution analysis were conducted using ESRI ArcGIS Pro 3.3. The study of soil moisture’s relationship with different soil textures in the East Kazakhstan region has revealed several key trends. The maximum values of soil moisture for each texture class change very slightly from year to year. The minimum soil moisture values fluctuate more strongly from year to year. The regression analysis demonstrates a statistically significant relationship between precipitation and soil moisture. The best performance is achieved when using a 1-day lag for 2013 and varying optimal lags for 2022 and 2023 (ranging from 1 to 3 days) during the high-precipitation period (months 6–9), with filtering applied to remove days with negligible rainfall.

This article presents the results of crop yield in areas with different technologies of cultivation based on the network of automatic stations that provide data on climatic and soil-hydrological monitoring in the dry steppe during the vegetation period of May–September 2013–2016 . These data on regional ecological and climatic parameters are of great interest to the ecologists, plant physiologists, and farmers working in the Kulunda Plain (Altai Territory). We compared the following options for cropping technologies: the modern system, which is the "no-till", technology without autumn tillage;the intensive technology of deep autumn tillage by plough PG-3-5 at a depth of 22–24 cm. Cultivation of crops was carried out using the following scheme of crop rotation: the modern system: 1–2–3–4 (wheat – peas – wheat – rape); the intensive system: 5/6 – 7/8 – 9/10 (fallow – wheat – wheat). We believe that the use of modern technology in these conditions is better due to exchange between the different layers of soil. When the ordinary Soviet system , the so-called "plow sole" , was used , at a depth of 24 cm , we observed that this creates a water conductivity barrier that seems to preclude the possibility of lifting water from the lower horizons. Results of the study of infiltration of soil moisture at the depth of 30 and 60 cm have shown in some years the advantages of the modern technology over the ordinary Soviet system: in the version with the use of modern technology we can trace better exchange between the various horizons and , probably, moisture replenishment from the lower horizons. Differences in individual observation periods are comparatively large due to the redistribution of soil moisture, depending on the weather conditions, the crops used in the crop rotations, and cultivation techniques. Moreover, the average moisture reserves within the one meter layer did not show any significant differences during the growing seasons of 2013–2016 . In terms of soil moisture usage and productive grain yield according to the four year experiment, the application of the modern technology with crop rotation "wheat – rape – wheat – peas" was more effective than the ordinary Soviet system with crop rotation "wheat – fallow – wheat – wheat". The four-year observation period is clearly insufficient to identify the advantages of the modern system, as during this time it is impossible to significantly improve soil quality indicators, which will continue to determine its water-retaining properties and moisture accumulation.

The assessment of the hydrological functions of landscapes and the landscape–hydrological background is an important instrument for minimizing damage from rivers and preventing water conflicts under conditions of data scarcity for hydrological modeling. To assess the climate–hydrological background of the East Kazakhstan region, the Selyaninov Hydro-thermal Coefficient and the Vysotsky–Ivanov Moisture Coefficient were used. The East Kazakhstan region is a typical continental arid and semi-arid region. The presence of mountain ranges, such as the Altai, makes the climate and environment in the region highly varied. A dataset from 30 weather stations for the period 1961–2023 was used for calculations. Three interpolation methods and landscape extrapolation were used to construct maps of the coefficients. Over the observation period, the values of the moisture indices at the weather stations in the region fluctuated within a wide range. Both coefficients are in the range from extra arid to extra humid climates.