Exploring the evolution of vegetation cover and its drivers in the Ferghana Basin helps to understand the current ecological status of the Ferghana Basin and to analyze the vegetation changes and drivers, with a view to providing a scientific basis for regional ecological and environmental management and planning. Based on GIMMS NDVI3g and meteorological data, the spatial and temporal evolution characteristics of NDVI were analyzed from multiple perspectives with the help of linear trend and Mann–Kendall (MK) test methods using arcgis and the R language spatial analysis module, combined with partial correlation coefficients and residual analysis methods to analyze the impacts of climate change and human activities on the regional vegetation cover of the Ferghana Basin from 1982 to 2015. NDVI driving forces. The results showed the following: (1) The growing season of vegetation NDVI in the Ferghana Basin showed an increasing trend in the 34-year period, with an increase rate of 0.0044/10a, and the spatial distribution was significantly different, which was high in the central part of the country and low in the northern and southern parts of the country. (2) Temperature and precipitation simultaneously co-influenced the vegetation NDVI growth season, with most of the temperature and precipitation contributing in the spring, most of the temperature in the summer being negatively phased and the precipitation positively correlated, and most of the temperature and precipitation in the fall inhibiting vegetation NDVI growth. (3) The combined effect of climate change and human activities was the main reason for the overall rapid increase and great spatial variations in vegetation NDVI in China, and the spatial distribution of drivers, namely human activities and climate change, contributed 44.6% to vegetation NDVI in the growing season. The contribution of climate change and human activities to vegetation NDVI in the Ferghana Basin was 62.32% and 93.29%, respectively. The study suggests that more attention should be paid to the role of human activities and climate change in vegetation restoration to inform ecosystem management and green development.

Central Asia (CA), a typical arid and semiarid region, has experienced worsening droughts, adversely impacting agricultural production and socioeconomic development. However, the evolution of hydrological droughts in CA remains unclear. Here, we used instrumental streamflow and reanalysis to demonstrate a decline in surface runoff in CA since the 1990s, with 44.6% and 33.2% of the area dominated by reductions in snowmelt and precipitation, respectively. We found that global warming contributes to the long‐term decrease in surface runoff, while short‐term fluctuations in surface runoff are caused by the El Niño‐Southern Oscillation, such as southern CA drying induced by decreasing precipitation during La Niña. We project the future hydrological drought characteristics based on state‐of‐the‐art global hydrological simulations and found increasing duration and severity of hydrological droughts in CA, especially in the Amu Darya basin, and the Caspian Sea East Coast basin. These increasing droughts are exacerbated by higher anthropogenic emissions, posing high‐level risks to 39.01% of land area and 35.9% of human population under an extremely high emissions scenario. These findings highlight the need for improved water conservation technologies and concerted development strategies should be considered by national policy makers in this water‐scarce and climatically sensitive region.

As the largest city in northern China and the capital of China, the rapid increases in Beijing’s water consumption in recent years have made water resources provision an increasing problem. To rationally allocate water resources, it is important to obtain long‐term runoff information in Beijing. In this study we develop a 236‐year chronology of tree‐ring widths based on cores from Pinus tabuliformis from four sampling sites. The resulting regression model reconstructs December–July runoff of the Yongding River in Beijing, with 49.5% of the variance explained, back to 1786 CE. Among the last 236 years, 1868, 1956, 1991, 1998, 2018, and 2021 were extremely high runoff years; and 1900, 1906, 1999, and 2000 were extremely low runoff years. Comparison of the runoff reconstruction results with climate grid data demonstrated a large magnitude of climate change in North China during the study period. Linkage analysis between the reconstructed runoff and large‐scale water vapor indicated that the high runoff years occurred during negative phases of the Pacific Decadal Oscillation, which may be influenced by the East Asian Summer Monsoon. Projections indicate that the flow of the Yongding River will increase in the future. Supported by policies such as the Ecological Water Supply and South‐to‐North Water Diversion, regional vegetation productivity and Yongding River runoff have increased substantially since 2000. Vegetation growth interacts with runoff volume. It is unclear how long these increases will continue.

Eastern Xinjiang, as a typical extremely arid area, exhibits a high sensitivity to climate change. Gaining a comprehensive understanding of the climatic changes in this region, along with their driving mechanisms, and comparing these with the broader trend of “warming and humidifying” in the Northwest can provide a scientific foundation for adapting to and addressing climate change. Based on a study of precipitation and temperature data from seven meteorological stations in Eastern Xinjiang from 1960 to 2022, the following findings were observed: (1) The climate of eastern Xinjiang is generally characterized by a warming and humidifying trend, with the rates of mean annual temperature and total annual precipitation being 0.39 °C/10 a and 3.32 mm/10 a. The eastern part of Xinjiang has less precipitation, with a lower growth rate than that of the neighboring regions, and higher temperatures, with a higher growth rate than that of the neighboring regions. (2) The first principal component of precipitation explains 47.85% of the variation in total precipitation, with a significant upward trend (p < 0.05) and an abrupt change in the late 1970s. It contains strong signals of regional precipitation, temperature, and dry and wet changes. (3) The increase in the first principal component of annual precipitation in eastern Xinjiang is mainly related to the warming of SSTs in the Indian Ocean and the central-eastern part of the tropical southern Pacific Ocean as well as the weakening of the Asian monsoon.

Anthropogenic climate change affects regional hydrological cycles and poses significant challenges to the sustainable supply of freshwater. The Central China water tower (CCWT) is the key source region feeding the Yangtze and Yellow Rivers, and its runoff is indispensable for the surrounding mega‐city clusters. Here we present a reconstruction of CCWT runoff depth (RD) back to 1595 CE, based on a new dendrochronological network including 100 tree‐ring sampling sites and an ensemble averaging approach that combines multiple regression models. Comparison of this reconstruction with similar records from six water tower regions along the Pacific Rim (Mongolian Plateau, Tibetan Plateau TP, Great Dividing Range, Southern and Northern Rocky Mountains, Andes Mountains) revealed that the CCWT provide the most stable water supply, while the TP to be most susceptible to extreme runoff events. Twenty‐first century projections indicate generally increasing runoff across most Pacific Rim water towers, whereas the Northern Rocky Mountains are projected to decline substantially. We attribute the differences in runoff variability and projected trends across Pacific Rim water towers to their distinct geographies and synoptic climatic conditions. The long‐term runoff reconstructions and projected changes highlighted in this study provide insights for adaptive management strategies in China and all other regions relying on supply from mountain water towers.