Nitrogen (N) deposition tends to accompany precipitation in temperate forests, and vegetation productivity is mostly controlled by water and N availability. Many studies showed that tree species response to precipitation or N deposition alone influences, while the N deposition and precipitation interactive effects on the traits of tree physiology, especially in non-structural carbohydrates (NSCs) and long-term water use efficiency (WUE), are still unclear. In this study, we measured carbon stable isotope (δ13C), total soluble sugar and starch content, total phenols, and other physiological traits (e.g., leaf C:N:P stoichiometry, lignin, and cellulose content) of two dominant tree species (Quercus variabilis Blume and Liquidambar formosana Hance) under canopy-simulated N deposition and precipitation addition to analyze the changes of long-term WUE and NSC contents and to explain the response strategies of dominant trees to abiotic environmental changes. This study showed that N deposition decreased the root NSC concentrations of L. formosana and the leaf lignin content of Q. variabilis. The increased precipitation showed a negative effect on specific leaf area (SLA) and a positive effect on leaf WUE of Q. variabilis, while it increased the leaf C and N content and decreased the leaf cellulose content of L. formosana. The nitrogen–water interaction reduced the leaf lignin and total phenol content of Q. variabilis and decreased the leaf total phenol content of L. formosana, but it increased the leaf C and N content of L. formosana. Moreover, the response of L. formosana to the nitrogen–water interaction was greater than that of Q. variabilis, highlighting the differences between the two dominant tree species. The results showed that N deposition and precipitation obviously affected the tree growth strategies by affecting the NSC contents and long-term WUE. Canopy-simulated N deposition and precipitation provide a new insight into the effect of the nitrogen–water interaction on tree growth traits in a temperate forest ecosystem, enabling a better prediction of the response of dominant tree species to global change.