Soil salinity and waterlogging are significant challenges in agricultural regions worldwide, including Kazakhstan. Understanding the characteristics and distribution of saline and waterlogged soils is crucial for developing effective strategies to mitigate their negative impact on crop productivity and environmental sustainability. This study aims to provide a comprehensive assessment of saline and waterlogged soils in various zones of the Republic of Kazakhstan, including the desert, foothill semi-desert (vertical), semi-desert (latitudinal), and dry-steppe areas. By examining the genetic horizons, chemical composition, ionic composition, salt content, and granulometric composition of these soils, this research contributes to the knowledge base necessary for implementing targeted soil management practices and restoration techniques. Fieldwork was conducted at 66 designated base points, where detailed descriptions of the genetic horizons of these soils were made. The data collected from these surveys were utilized to create an extensive information database, encompassing various indicators such as nomenclature, profile structure morphology, chemical composition, ionic composition of water extracts, salt content, absorbed cations, and granulometric composition. The findings reveal that saline soils cover a significant area of 16.7% (35,817.4 thousand hectares) of the agricultural land, while waterlogged soils occupy 0.5% (1,083.4 thousand hectares). The study highlights the poor fertility of saline soils due to high concentrations of water-soluble salts, predominantly sodium chlorides and sulfates, throughout the soil profile. Conversely, waterlogged soils exhibit distinct features such as gleyed horizons and a greenish-grayish color, with variations in fertility. The information presented in this study contributes to the understanding of the characteristics and distribution of saline and waterlogged soils in Kazakhstan, facilitating the development of strategies to restore soil fertility and implement appropriate management practices.

This article studies the morphological and physicochemical properties of soils in the natural habitat of dandelion kok-saghyz (Taraxacum kok-saghyz L.E. Rodin) (TKS)—a source of high-quality rubber. The purpose of the work is to study the natural soil habitat of dandelion TKS in comparison with the nearby area where TKS is absent. The methods of soil research are comparative, geographical, morphological, and analytical. Soil sections were laid down and georeferenced, and relief, vegetation, and morphological structures of soil profiles by genetic horizons were described. A database of the physical and chemical properties of soils by horizon was created. Landscapes and soil conditions of in situ populations have been studied in the Kegen District of the Almaty region in the territory of the Kegen River floodplain, in the areas of the Jalauly and Kegen villages, and in the zone of groundwater inclination north of Saryzhas village. The natural soil habitat of TKS was studied. It was found that TKS grows in conditions of moisture floodplains of intermountain valleys on saline floodplain meadowy soils of a sulfate–sodium composition with a high content of total humus and nutrient elements in an alkaline environment.

Soil degradation in arid ecosystems is a major threat to sustainable development and food security, especially under accelerating climate change. Kazakhstan, where more than 70% of agricultural land suffers from salinisation, erosion, and humus loss, offers a representative case for studying climate-driven degradation. This study quantitatively assessed the influence of air temperature, precipitation, aridity index, and extreme climatic events on soil properties in the arid regions of western Kazakhstan (Atyrau and Mangystau). The analysis integrated long-term meteorological time series (1941–2023) with field and laboratory data (1967–2024) into a harmonised dataset of 1330 records. Principal component analysis (PCA) identified four degradation gradients explaining 73.6% of total variance, while Random Forest and SHAP algorithms quantified variable importance. Mean annual temperature, frequency of arid years, and aridity index were the strongest predictors of humus, salinity, pH, and CO₂ parameters, with climate factors accounting for up to 30% of soil variability. The findings demonstrate that climatic stressors are the main drivers of soil degradation in arid zones, with climate factors explaining up to 30% of the variability in key soil properties (humus, salinity, pH, and CO₂)—a substantial proportion that underscores their dominant role relative to local geochemical and anthropogenic influences. The proposed hybrid PCA—Random Forest/SHAP framework provides a robust tool for analysing climate–soil interactions and supports the design of adaptive land-use strategies to achieve Land Degradation Neutrality (LDN) in Kazakhstan and other arid regions.