The intensifying effects of climate change have led to increased flooding, even in desert regions, resulting in significant socio-economic and ecological impacts. This study analyzes the causes and consequences of flooding in the Zhem River basin using data from ground stations, including Kazhydromet, and satellite platforms such as USGS FEWS NET and Copernicus. Spatial analyses conducted in ArcGIS utilized classified raster data to map the dynamics of flooding, snow cover, vegetation, and soil conditions. This enabled a geoecological analysis of flood damage on the vital components of the local landscape. Results show that flooding in the Zhem River basin was driven by heavy winter precipitation, rapid snowmelt, and a sharp rise in spring temperatures. The flood damaged Kulsary city and also harmed the region’s soil, vegetation, and wildlife. In July 2024, the flooded sail area tripled compared to the same period in 2023. Additionally, the area of barren land or temporary water bodies (pools) formed three months after the water receded also tripled, increasing from 84.9 km² to 275.7 km². This study highlights the critical need for continued research on the long-term environmental effects of flooding and the development of adaptive management strategies for sustainable regional development.

Alakol Lake is one of the largest hydrologically closed lake located in Balkash-Alakol River Basin in southeast Kazakhstan. Having a coastline approximately at 490 km, Alakol Lake has faced multiple threats due to both natural and anthropogenic factors as a result of tectonic movements, geology, wind-wave conditions, growing tourism activities, fishing, and transport, etc. The present study aims to investigate the historical trends in coastline changes along Alakol Lake in Kazakhstan and estimate its change rate by using remote sensing data in particular scale-space images Landsat-5 TM, 7 ETM+, 8 OLI, and Sentinel-2A. Based on Landsat and Sentinel data, the modified normalized difference water index was calculated to demonstrate the coastline changes along Alakol Lake between 1990 and 2018. Moreover, the monitoring and analysis of coastline dynamics is based on the main morphometric characteristics of Alakol Lake including water surface area, coastline length, geomorphology of the coast, etc. Our results reveal that there is a continuous coastline retreat, depending on the coast types. For example, in the case of the denudation coasts, a land inundation was from 120 to 270 m between 1990 and 2018. In the case of the accumulative coast (mainly northeast, north, and northwest coasts) a land inundation was from 200 to 900 m. A vast area of agricultural land around Alakol Lake become flooded and lost. This study demonstrates the importance of monitoring coastline dynamics because it provides essential information for understanding the coastal response to contemporary nature and anthropogenic impacts.

The purpose of this study is to develop a methodology for automated determination of water surfaces and identification of small lakes in Kazakhstan using cartographic methods and an array of multi-time remote sensing (RS) data. The methodology involved automated surface water classification using multi-temporal Sentinel-2 satellite imagery (spanning the period 2016?2021, focusing on the warm months from May to September), Python-based processing on the Google Earth Engine platform, geographic information system (GIS) based morphometric analysis, and field validation to accurately identify and characterize small lakes in Kazakhstan. The study applied the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Vegetation Index (NDVI) to enhance surface water detection, reduce noise from vegetation, and improve the accuracy of lake boundary delineation from multi-temporal Sentinel-2 imagery. A technique for automated extraction of morphometric characteristics of small lakes has been developed, data on lake morphometry have been obtained. Verification against field measurements demonstrated a high degree of accuracy, with relative error rates of 12% for lake lengths and 13% for the widths. However, challenges such as dense vegetation, high salinity, and the color of shallow lake bottoms led to some classification errors, highlighting the need for further refinement of automated algorithms. As a result, a list of small lakes in Kazakhstan with a surface area from 1 to 10 km2 was identified.

Soil salinization poses a persistent threat to irrigated agroecosystems, yet remote sensing-based salinity assessment remains predominantly calibrated against bulk electrical conductivity without fully integrating crop physiological variability. This review examines the evolution of remote sensing approaches for soil salinity mapping (1994–2024), with particular emphasis on the role of crop salt tolerance in shaping spectral interpretation and mapping accuracy. A systematic synthesis of 58 peer-reviewed studies retrieved from the Scopus database was conducted using bibliometric analysis and structured full-text thematic classification to evaluate methodological trends and conceptual integration across soil, crops, and spectral domains. The results reveal substantial technological advancement, including multispectral and hyperspectral sensing, machine learning frameworks, and multi-source data integration. However, most approaches remain surface-oriented and statistically calibrated, with limited operationalization of crop-specific tolerance thresholds, root-zone salinity dynamics, and hydrochemical variability. The findings indicate that crop salt tolerance functions as a mediating factor within the soil–plant–spectral continuum, influencing the stability and transferability of spectral–salinity relationships. Integrating physiological tolerance parameters and subsurface processes into modeling frameworks is essential for improving agronomic interpretability and supporting more reliable salinity management in irrigated systems.

В статье исследуются современные процессы рельефообразование Северного Приаралья в период регрессии моря и факторы их образования. Целью исследования является определить преобладающие типы процессов рельефообразования Северного Приаралья в условиях регрессии моря и воздействия аридного климата. Методика исследования объединяет полевые наблюдения, интерпретацию данных ДЗЗ, цифровой фотограмметрический анализ аэрофотоснимков и обработку данных в ГИС. Была использована комбинация инструментальных геоморфологических полевых исследований, с использованием беспилотного летательного аппарата, тахеометра, дальномера и GPS координирование. В результате исследования создана карта современного земельного покрова исследуемого участка Северного Приаралья. Выделены 13 типов покрова: пустоши (неиспользуемые земли), земли занятые населенными пунктами, пашни, водно-болотные угодья, травы, степь с редкой растительностью, водная поверхность, осушенное дно Аральского моря, закрепленные пески, подвижные пески, соры и такыры. Отсутствие растительности на делювиально-пролювиальных выносах, склонах денудационного уступа, свидетельствуют об активных гравитационных процессах и ветровой эрозии. В Северном Приаралье выявлены несколько сел, подверженных неблагоприятному воздействию подвижных песков, это Косаман, Акеспе, Акбасты, Боген и др. В селах Акеспе и Акбасты подвижными песками засыпаются жилые дома и хозяйственные помещения местных жителей. Относительные высоты между основанием и гребнем бархана, в среднем составляет 2 метра. Площадь развития подвижных песков в с. Акеспе составляет 1,68 км², в с. Акбасты около 1,62 км². Высчитаны величины коэффициента нагрузки условного скота на пастбища на территории исследования, где высокий коэффициент отмечается в с. Акбасты. Характер происходящих рельефообразующих процессов указывает на усиление в регионе воздействия аридности климата и антропогенного влияния в результате регрессии моря. На первый план выходят эколого-геоморфологические проблемы, влияющие на здоровье человека и качество жизни местных жителей, возникшие в результате нерационального землепользования, хрупких пустынных экосистем вблизи населенных пунктов. С учетом полученных результатов становиться актуальным разработка и внедрение мероприятий рационального природопользования в условиях адаптации окружающей среды и жизнедеятельности человека к усиливающимся процессам аридизации климата и его последствий.

This paper presents an integrated approach to the mapping and structural-tectonic interpretation of lineaments in the Mangystau region using multispectral Landsat-8 OLI data and the medium-resolution Airbus WorldDEM4Ortho digital elevation model. Automatic extraction of linear structures has enabled the identification of over 35,000 lineaments of varying length and orientation, forming a network of intersecting zones that influence the distribution of sedimentary thicknesses, drainage directions, and the location of karst-suffosion depressions. The most prominent are the north-western and sub-latitudinal systems, closely correlated with zones of fracturing and faults, which confirms their tectonic origin. The spatial concentration of lineaments coincides with areas of increased permeability in carbonate and gypsum-bearing rocks and localizes the pathways of groundwater circulation, contributing to the development of karst-suffosion processes. The obtained results demonstrate the significance of structural influences on the region’s current geomorphological and hydrogeological conditions and also have practical importance for engineering-geological surveys, the assessment of geological risks, and the planning of sustainable land use.