Understanding Long‐Term Streamflow Response to Snowfall Change: Insights From a Multivariate Analysis

Abstract Ongoing climate change is modifying snow dynamics, further altering streamflow ( Q ) in cold regions. Despite extensive research over the past decades, the impact of changes in snow on mean annual Q remains debated, and the underlying mechanisms driving these responses are still unclear. In this study, we employ the Budyko framework to establish multivariate relationships between a Budyko model parameter and several variables, including snowfall fraction ( f s ), across 931 carefully selected snow‐influenced catchments in the Northern Hemisphere. Our results show that the average elasticity of Q to f s across all catchments is 0.13. However, mean annual Q responses vary among catchments, with 78% of catchments experiencing decreased Q and others exhibiting increased Q with declining f s . These variations are manifested in decreased warm‐season Q and increased cold‐season Q , respectively. Additionally, attribution analysis of Q change highlights a critical role of f s changes as a second‐order control on Q after precipitation. Examining possible mechanisms behind the varying Q responses reveal that the influence of f s on snowmelt intensity and snow season available energy is more pronounced in catchments exhibiting positive Q feedback to f s . In contrast, its impact on rainfall intensity and the asynchrony between available energy and liquid water input is greater in catchments displaying negative Q feedback to f s . Our findings enhance the understanding of Q responses to changing f s and provide valuable insights for water resource management in snow‐influenced regions in a warming climate.