Three Bayesian tracer models: Which is better for determining sources of root water uptake based on stable isotopes under various soil water conditions?

Abstract Background and aims Stable isotope methods provide a powerful technique to quantify the sources of plant root water uptake (RWU). Although many models coupled with stable isotopes have been developed to estimate RWU, little is known about their pros and cons, especially their performance under different soil water content (SWC) conditions. Methods In this study, three Bayesian mixing models, including MixSIAR, MixSIR and SIAR, were tested their merit and demerit in determining RWU of winter wheat with six sampling events under various SWC conditions (normal, dry and wet) in the North China Plain. Results The proportions of RWU in different soil layers showed significant differences among the three Bayesian models, for example, the proportion of 0-20 cm soil layer calculated by MixSIR, MixSIAR and SIAR were 69.7%, 50.1% and 48.3% for the 3rd sampling under the dry condition, respectively. Furthermore, the average proportion of 0-20 cm layer under dry condition was lower than that under normal and wet conditions, taken MixSIR as an example, being 51.4%, 82.5% and 65.4%, respectively. The performance of three models in determining plant water source appointment varied with SWC conditions: the performance indicators such as coefficient of determination, Nash-Sutcliffe efficiency coefficient in MixSIAR were higher than that in MixSIR and SIAR, showing that MixSIAR performed well under the normal and wet condition. While the rank of performance under the dry condition was MixSIR, MixSIAR and SIAR, respectively. Conclusions Overall, MixSIAR performed relatively better than other models in predicting RWU under various soil moisture conditions.