Spatiotemporal Variations in Snow/Ice Cover, Climate Responses and Future Trends in the Headwaters of the Keriya River on the Northern Slope of the Kunlun Mountains

Against the backdrop of global warming and the ‘warming and wetting’ trend in north-western China, changes in seasonal snowpack and glacial ice in high-altitude cold regions directly impact water security in inland river basins. At present, there is a paucity of systematic research concerning the long-term evolution of snow and ice cover, multi-scale climate responses and future trends in the source region of the Keriya River on the northern slope of the Kunlun Mountains. To address this, this study utilised Landsat remote sensing imagery and meteorological station data from 2005 to 2024. Employing a multi-model fusion framework that integrates various machine learning and time-series models—including random forests, gradient boosting trees and ARIMA—the research incorporated trend factors, climate cycle identification and probabilistic modelling of extreme events to systematically analyse the spatiotemporal variability of snow/ice coverage and its multiscale coupling relationships with air temperature and precipitation. Given the inherent limitations of optical remote sensing methods in distinguishing between seasonal snow and glacial ice, this study defines the extracted coverage type as snow/ice coverage. Given the inherent limitations of optical remote sensing methods in distinguishing between seasonal snow and glacial ice, this study defines the extracted coverage type as snow/ice coverage. The results indicate that: (1) the annual average snow/ice cover percentage in the study area shows a non-significant decreasing trend (−0.69%/year, p > 0.1); within the year, it exhibits a pattern of accumulation in winter and melting in summer, with a peak in January (average 63.2%) and a trough in August (average 11.6%); (2) snow/ice cover percentage increases significantly with altitude; the annual average SICP in the <2000 m elevation zone is 5.2%; in the 2000–3000 m and 3000–4000 m altitude ranges, this rises to 5.7% and 8.3%, respectively, representing the primary seasonal snow/ice distribution zones; in areas above 6000 m, the annual average reaches 70.3%, constituting a zone of perennial stable snow/ice cover; (3) the relationship between snow/ice and temperature and precipitation exhibits significant time-scale dependence: correlations are weak on an annual scale (temperature R = −0.25, precipitation R = −0.14), but significantly strengthen on a monthly scale and exhibit seasonal differentiation; during the melting season, temperature exerts a dominant negative influence (August R = −0.35), whilst during the accumulation season, solid precipitation provides a positive supplement (February R = 0.34), with the strongest correlation with temperature occurring in September (R = −0.50); (4) it is projected that between 2025 and 2044, snow and ice cover will follow a fluctuating downward trend (averaging an annual decrease of roughly −0.12%), falling to approximately 29% by 2044; at the same time, temperatures are expected to continue rising (+0.035 °C per year), whilst precipitation will increase slightly (+0.4% per year). The results of this study provide a sound scientific basis for formulating sustainable water resource management strategies for the northern flank of the Kunlun Mountains and optimising measures to regulate snowmelt runoff. They are of great importance for safeguarding the stability of the oasis ecological systems in the Keriya River basin and ensuring the sustainable development and utilisation of water resources.