Snowmelt from the Tianshan Mountains (TS) is a major contributor to the water resources of the Central Asian region. Thus, changes in snow phenology over the TS have significant implications for regional water supplies and ecosystem services. However, the characteristics of changes in snow phenology and their influences on the climate are poorly understood throughout the entire TS due to the lack of in situ observations, limitations of optical remote sensing due to clouds, and decentralized political landscapes. Using passive microwave remote sensing snow data from 1979 to 2016 across the TS, this study investigates the spatiotemporal variations of snow phenology and their attributes and implications. The results show that the mean snow onset day (D_o), snow end day (D_e), snow cover duration days (D_d), and maximum snow depth (SD_max) from 1979 to 2016 were the 78.2nd day of hydrological year (DOY), 222.4th DOY, 146.2 days, and 16.1 cm over the TS, respectively. D_d exhibited a spatial distribution of days with a temperature of <0 °C derived from meteorological station observations. Anomalies of snow phenology displayed the regional diversities over the TS, with shortened D_d in high-altitude regions and the Fergana Valley but increased D_d in the Ili Valley and upper reaches of the Chu and Aksu Rivers. Increased SD_max was exhibited in the central part of the TS, and decreased SD_max was observed in the western and eastern parts of the TS. Changes in D_d were dominated by earlier D_e, which was caused by increased melt-season temperatures (T_m). Earlier D_e with increased accumulation of seasonal precipitation (P_a) influenced the hydrological processes in the snowmelt recharge basin, increasing runoff and earlier peak runoff in the spring, which intensified the regional water crisis.

The Great Lakes Depression region basin is among the most sensitive regions to vegetation change due to climate change. This study estimated spatial-temporal changes and relationships in hydro-climate and vegetation dynamics in the basin. Studying the spatial-temporal variation between vegetation dynamics and hydro-climate in this basin is essential for assessing climate change and sustainability. This research involved an examination of the mean yearly air temperature, overall annual rainfall, fluctuations in river discharge, vegetation cover, and alterations in vegetation types within the selected basin stations. This was accomplished through the utilization of hydro-meteorological analysis, satellite assessment, land cover determination, and statistical analysis. Over the course of the study, it was observed that the average annual air temperature increased at all stations (with a positive change of Z = +1.16). The amount of precipitation decreased (Z = −0.79), especially from 2000 to 2014, and its statistical significance decreased. During the study period, average river discharge significantly decreased (Z = −3.51). Due to these combined factors, the lake’s water level also decreased (Z = −2.03). Vegetation cover change varied in high mountains, near river and lake water surfaces, and in arid regions. Changes in air temperature and precipitation in the current year determine vegetation cover. Because of the large amount of precipitation in the summer months from 2000 to 2010 and 2020, the growth of vegetation cover during that period was relatively good. This study was conducted in arid and semi-arid regions of Central Asia and demonstrates the impact of climate change on changes in vegetation cover.

The western region of Mongolia is characterized by an arid climate and a fragile ecological environment. It is a sensitive zone in response to global climate change and one of the major sources of dust globally. This region is home to numerous lakes, and their dynamic changes not only reflect global climate variations but also have implications for the global ecological environment quality. In this study, Landsat images were used as the data source, and Google Earth Engine (GEE) was employed to extract lakes with an area larger than 1 km² from 1992 to 2021. The spatiotemporal characteristics of lake water area (LWA) changes were analyzed, and a structural equation model was applied to attribute the lake changes. The results indicate an overall trend of increasing lake area followed by a decrease in the study area. Specifically, lakes in the provinces of Khovd and Gobi-Altai exhibited a decreasing trend followed by an increasing trend, while lakes in the provinces of Uvs and Zavkhan showed an increasing trend followed by a decreasing trend. Three typical types of lakes, namely, alpine lakes, throughflow lakes, and terminal lakes, all exhibited a trend of increasing area followed by a decrease. The analysis of driving forces behind lake area changes reveals that climate change and human activities primarily exert indirect influences on the lake area changes in each province. Specifically, climate change and human activities lead to changes in soil moisture, which have a significant explanatory power for lake area changes. Regarding the typical types of lakes, climate change serves as the primary driving force for alpine lakes, while human activities are the main driving forces for throughflow lakes and terminal lakes.