2.4. Data analysis
The Bayesian mixing model Mix SIAR (version 3.6.3) was used to identify the source of water absorbed by plant. The Mix SIAR model is a method to identify the proportional contributions of each water source (Stock and Semmens, 2013) according to the mean isotopic values (δ2H and δ18O), which were considered as the mixture data of the potential water sources (Dawson&Ehleringer, 1993; Beyer et al., 2018). The inputs of original data (for example, the 0-20 cm soil layer data was input as 0-10 cm and 10-20 cm isotope data), the discrimination data (the TDF data in the model), the running time of Markov chain Monte Carlo (MCMC), and the diagnosis method of the model results were according to (Zhou et al., 2021). The average value was output from the model. Three potential soil water sources were identified to facilitate subsequent analysis (i.e., shallow soil water (0–20 cm), middle soil water (20–60 cm), and deep soil water (60-100 cm)), according to the variability in the soil water content and the impacts of precipitation pulse.
One-way analysis of variance (ANOVA) followed by the post hoc Turkey’s test at p = 0.05 was used to assess hydrometeorological parameters of sampling date and sites. Two-way ANOVA was performed to examine the significant effects of hydrometeorological parameters and their interactions. Pearson’s correlations were tested at the p = 0.05 level. All statistical analyses were conducted using R software version 4.0.3, and all figures were plotted using Origin 9.1.
3. Results