Three Bayesian Tracer Models: Which Is Better for Determining Sources of Root Water Uptake Based on Stable Isotopes under Various Soil Water Conditions?

Abstract

Stable hydrogen and oxygen isotopes provide a powerful technique for quantifying the proportion of root water uptake (RWU) from different potential water sources. Although many models coupled with stable isotopes have been developed to estimate plant water source apportionment, inter-comparisons of different methods are still limited, especially their performance under different soil water content (SWC) conditions. In this study, three Bayesian tracer mixing models, which included MixSIAR, MixSIR and SIAR, were tested to evaluate their performances in determining the RWU of winter wheat under various SWC conditions (normal, dry and wet) in the North China Plain (NCP). The proportions of RWU in different soil layers showed significant differences (p p p > 0.05) was found in the main RWU depth (i.e., 0–20 cm) among the three models, except for individual sampling periods. The performance of three models in determining plant water source allocation varied with SWC conditions: the performance indicators such as coefficient of determination (R2) and Nash-Sutcliffe efficiency coefficient (NS) in MixSIAR were higher than that in MixSIR and SIAR, showing that MixSIAR performed well under normal and wet conditions. The rank of performance under the dry condition was MixSIR, MixSIAR, and then SIAR. Overall, MixSIAR performed relatively better than other models in predicting RWU under the three different soil moisture conditions.

Keywords

• stable isotope
• root water uptake
• soil water content
• winter wheat
• Bayesian model