The Qinling Mountains, the so-called “central water tower,” are extremely important water resource hubs in China. The influence of the forest ecological environment on water quality is complicated. Therefore, to investigate the spatiotemporal variations in water quality, we employed a random forest model to integrate multiple key water quality indicators into one overall ranking value. Monthly monitoring data of surface runoff and atmospheric precipitation events (2003–2022) for the Huodigou stream in the Qinling Mountains were used. The results revealed that after atmospheric precipitation entered the forest ecosystem, the coefficients of variation of surface runoff for most of the selected indicators decreased, but there were significant differences among the six indicators (NO3−, Mg2+, Na+, pH, K+, Ca2+). Most of the indicators within surface runoff were positively correlated, such as those in atmospheric precipitation. However, some indices of surface runoff were negatively correlated with those of atmospheric precipitation, and there was a significant negative correlation between Ca2+ in atmospheric precipitation and Ca2+ in surface runoff and between NO3−in atmospheric precipitation and K+ and Na+ in surface runoff (p < 0.01). The water quality grade of the surface runoff generated by atmospheric precipitation through forest ecosystems was significantly improved (p < 0.001), among which the average water quality grade of surface runoff was approximately 3.6, that is, between Grade I-3 and Grade I-4, whereas the average water quality grade of atmospheric precipitation was approximately 4.5, that is, between Grade I-4 and Grade I-5. The order of improved water quality was NO3− > Mg2+ > Na+ > pH > K+ > Ca2+. Overall, our assessment revealed that from 2003 to 2022, the water quality grade in the Huodigou stream improved and was more stable. In summary, the forest ecosystem in the Huodigou stream has a significant water quality purification effect on the atmospheric precipitation it receives. Our novel criterion-based approach for categorizing the water quality of atmospheric precipitation and surface runoff offers a new tool for examining spatiotemporal stream water quality variations in the Qinling region and other mountainous areas.
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