The stable carbon isotope composition (δ13C) has been demonstrated to be a useful indicator of environmental conditions occurring during plant growth. Previous studies suggest that tree leaf δ13C is correlated with mean annual precipitation (MAP) over a broad range of climates with precipitation between 100 and 2000 mm/year. However, this relationship confirmed at the large scale may not be present at the local scale with complex terrain where factors other than precipitation may lead to additional variability in plant water stress. In this study, we investigated δ13C of tree leaves in a native vegetation catchment over a local gradient of hydro-climatic conditions induced by two hillslopes with opposite aspects. Significant seasonal variations, calculated as a difference between the maximum and minimum δ13C values for each tree, were observed for two species, up to 1.9‰ for Eucalyptus (E.) paniculata, and up to 2.7‰ for Acacia (A.) pycnantha on the north-facing slope (NFS). Also the mean δ13C values calculated from all investigated trees of each hillslope were significantly different and leaf δ13C on the NFS was higher by 1.4 ± 0.5‰ than that on the south-facing slope (SFS). These results cannot be explained by the negligible difference in precipitation between the two hillslopes located just 200 m apart. The correlation coefficients between the δ13C of E. tree leaves and the integrated aridity index (AI) were statistically significant for temporal observations on the NFS (R2 0.18–0.44, p-value 0.00–0.06), and spatial observations (R2 = 0.35, p-value 0.05) at the end of the dry season. These results suggest that AI as a measure of plant water stress is better associated with leaf δ13C than precipitation. Therefore, leaf δ13C value can be used as a valuable proxy for plant water stress across the landscape in both time and space.