In the context of climate change, the southern slope of the Qilian Mountains stands as a pivotal region for China’s ecological security, holding immense significance for sustaining ecological sustainable development. This study aims to precisely monitor and predict the dynamic changes in vegetation cover within this region, along with their time-lagged effects on climate change, thereby providing a scientific basis for ecological management. By calculating the kNDVI from 2001 to 2020 on the Google Earth Engine (GEE) platform, and integrating the Sen’s trend analysis, Hurst exponent, and partial correlation analysis, we have conducted an in-depth exploration of the long-term spatiotemporal variations in kNDVI on the southern slope of the Qilian Mountains and its delayed responses to climate factors. The primary research findings can be summarized as follows: The kNDVI on the southern slope of the Qilian Mountains exhibits an overall positive trend, with notable geographical variations in its spatial distribution. The proportion of areas showing vegetation improvement is as high as 84%, while degraded areas account for only 17%. Furthermore, there is an average lag response of 1.6 months for kNDVI to precipitation and 0.6 months to temperature in this region. The response speed positively correlates with the time-lagged partial correlation coefficient between kNDVI and climate factors. Notably, kNDVI is more sensitive to temperature variations in the southern slope area of the Qilian Mountains. This study not only fills the gap in long-term kNDVI monitoring for the southern slope of the Qilian Mountains but also offers scientific support for ecological governance and green development initiatives in the region. Additionally, it showcases the innovative application of advanced remote sensing technologies and statistical analysis methods in ecological research, providing fresh perspectives for future ecological management strategies. These findings hold profound implications for promoting sustainable development and ecological conservation in the Qilian Mountains area.

Understanding vegetation phenology dynamics is essential for evaluating ecosystem responses to environmental changes. While previous studies have primarily focused on the correlation between vegetation phenology and climate variables, the integrated effects of meteorological factors, topography, and greenhouse gas (GHG) have often been overlooked. This study aims to analyze the spatiotemporal variations in grassland phenology on the southern slopes of the Qilian Mountains from 2002 to 2022, investigating the combined effects of these environmental factors. Our findings reveal significant spatial heterogeneity in vegetation phenology during the study period. Specifically, the start of the growing season (SOS), length of growing season (LOS), and end of the growing season (EOS) advanced, lengthened, and delayed by 0.35, 0.55, and 0.20 days per year, respectively. Climate factors were the primary drivers of phenological changes, with annual precipitation being the main determinant of SOS and LOS, while annual minimum temperature significantly influenced EOS. Topography and GHG had indirect effects on phenology, influencing both annual precipitation and temperature. Additionally, topography affected phenology through its impact on N₂O and CO₂ emissions. This study highlights the complex interactions between climate, topography, and GHG in shaping vegetation phenology, providing new insights into the driving mechanisms behind phenological changes in semi-arid grassland ecosystems.