Abstract: Accurately identifying and quantifying variation trends in hydro-meteorological variables in alpine and high-cold regions is of great scientific and practical significance for addressing the multifaceted challenges posed by climate change, optimizing regional water resource allocation, and promoting sustainable watershed management. As one of China’s most important hydropower bases, the hydrological evolution of the upper and middle reaches of the Yalong River directly affects downstream hydropower development, operational scheduling, and long-term energy security. In this study, based on a comprehensive analysis of long-term observations from 1960 to 2020, we employed the Pettitt non-parametric change-point detection method and linear trend analysis to investigate the temporal variation characteristics of annual streamflow, precipitation, air temperature, and potential evapotranspiration (PET). The study further incorporated snow dynamics and examined the runoff–precipitation relationship at a monthly time scale to explore the hydrological response of the regional water cycle under a warming climate. The results indicate several key findings. (1) The change-points of different hydro-meteorological variables occurred at different times, reflecting the asynchronous nature of climate-related shifts in the basin. Precipitation exhibited the earliest abrupt change in 1978, followed by air temperature and PET, which shifted significantly in 1997 and 2005, respectively. After these change-points, the warming rate accelerated markedly (0.50  ℃ per decade), accompanied by a substantial increase in PET (42.2 mm per decade), indicating a pronounced intensification of atmospheric evaporative demand. (2) From 1979 to 2018, mean snow depth exhibited a persistent decreasing trend, while the date of maximum snow depth was delayed by approximately 1.9 days per decade. This delay suggests a prolonged snowmelt season, which may have important implications for spring runoff timing, reservoir refill cycles, and water availability. (3) Monthly runoff generally increased, with a notable enhancement in cold-season runoff contributions and a decline in runoff concentration during the warm season. Such changes are likely linked to shifts in precipitation phase (from snow to rain) and earlier snowmelt under a warmer climate, which together lead to altered intra-annual runoff distribution patterns. (4) The region exhibited an overall wetting trend, as evidenced by a decreasing aridity index and an increasing runoff coefficient. In particular, the increase in precipitation emerged as the dominant driver of water cycle intensification, while the occurrence and magnitude of extreme precipitation events further enhanced the efficiency of rainfall-to-runoff conversion, amplifying short-term hydrological responses. These findings provide new evidence of the complex interplay between climatic forcing, cryospheric processes, and hydrological responses in alpine basins. The observed wetting tendency and altered runoff seasonality underscore the necessity for adaptive water resource management strategies. For example, the shift toward increased cold-season runoff may challenge existing reservoir operation rules, which are often optimized for historical seasonal flow patterns. Moreover, the intensification of extreme precipitation events poses greater risks for flood management and infrastructure resilience in the Yalong River Basin. From a broader perspective, this study highlights the importance of integrating snow and glacier monitoring, precipitation phase discrimination, and high-resolution hydrological modeling to better predict future changes under continued warming scenarios. Overall, our results not only deepen the understanding of hydrological response processes in high-altitude cold regions but also provide scientific insights for sustainable hydropower development, flood control, and climate adaptation in the Yalong River Basin and similar alpine watersheds worldwide. The multi-decadal dataset used in this work offers a valuable reference for detecting long-term climate signals and developing robust regional adaptation policies. By linking statistical change-point detection with physical interpretations of snow–runoff processes, the study demonstrates that climate-induced changes in temperature, precipitation, and snow dynamics are reshaping the seasonal and inter-annual water cycle in ways that will require proactive and flexible water management approaches in the coming decades.