Preprints
https://doi.org/10.5194/egusphere-2026-4829
https://doi.org/10.5194/egusphere-2026-4829
27 Oct 2026
 | 27 Oct 2026
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

Technical note: An evaluation of error propagation in MixSIAR for root water uptake

Han Fu, Ruiqi Ren, Huijie Li, Jeffrey McDonnell, Adrià Barbeta, Wenxiu Zou, and Bingcheng Si

Abstract. Quantifying root water uptake (RWU) using hydrogen and oxygen stable isotopes and Bayesian mixing models is widely applied in ecohydrology. But its reliability remains unclear due to multiple uncertainties and the underdetermined nature of the problem. Here we systematically evaluate error propagation in MixSIAR-based RWU estimation using synthetic datasets with known RWU profiles. Through 2916 controlled simulations, we assess the contributions of eight factors, including observed soil and plant water isotopic compositions, RWU patterns, and model configuration (source grouping, prior information, and error structure) to the variance in accuracy and uncertainty of estimated root wate uptake proportions using MixSIAR. Results show that prior information and source grouping dominate RWU inference, explaining over 40% of the total variance. By contrast, when evaluated using posterior-predicted plant water isotopic compositions, their contribution falls below 10%, while soil and plant isotopic compositions and error structure together explain over 40%. This shift results in two things: (1) it masks the influence of prior information and source grouping for inferring RWU proportions using MixSIAR, and (2) it reveals a critical limitation in the approach: accurate isotope fits of observed plant water do not guarantee correct RWU inference, since multiple RWU solutions can produce identical isotopic compositions. These findings demonstrate that prior information and source grouping should be explicitly specified and carefully justified in future applications of MixSIAR in studies of quantifying RWU using Bayesian mixing models. Also, the multi-criteria evaluation frameworks beyond posterior predicted plant water isotopic composition are needed to assess the performance of MixSIAR in isotope-based RWU estimation.

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Han Fu, Ruiqi Ren, Huijie Li, Jeffrey McDonnell, Adrià Barbeta, Wenxiu Zou, and Bingcheng Si

Status: open (until 08 Dec 2026)

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Han Fu, Ruiqi Ren, Huijie Li, Jeffrey McDonnell, Adrià Barbeta, Wenxiu Zou, and Bingcheng Si
Han Fu, Ruiqi Ren, Huijie Li, Jeffrey McDonnell, Adrià Barbeta, Wenxiu Zou, and Bingcheng Si
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Short summary
Bayesian isotope mixing models are widely used to estimate root water uptake (RWU), but their uncertainty remains poorly understood. Using 2916 numerical experiments with known RWU profiles, we show that prior information and source grouping dominate RWU estimation, while commonly used posterior predictive checks can mask these effects. Our findings highlight the need for explicit prior justification and multi-criteria model evaluation to improve the reliability of isotope-based RWU estimation.
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