Temporal linearization can bias root water uptake estimates

What the study found: The authors report that a temporal linearization used to estimate the spatial gradient of soil-water flux can introduce substantial error into root water uptake estimates. They argue that this approximation is only supported under steady-state conditions, not under dynamically changing field conditions.
Why the authors say this matters: The authors conclude that because this approximation feeds into estimates of root water uptake, root water potential, and radial permeability, errors in the gradient estimate may bias the broader hydraulic inference framework. They suggest that clarifying the mathematical foundations of the method is important for robust root water uptake estimation.
What the researchers tested: The paper is a correspondence article that reviews the derivation in Rickard et al. (2025) and uses numerical simulations to examine the effect of the approximation. It focuses on the soil-water mass balance, the temporal interpolation of the vertical water flux profile, and the resulting estimates of root water uptake.
What worked and what didn't: The simulations showed low mean absolute relative error (MARE) for the approximation during steady-state evaporation, but much larger error during early non-steady evaporation and under dynamic precipitation conditions. The authors also report that published transpiration estimates from Rickard et al. (2025) often fell outside the stated physically plausible bounds, especially after rainfall events.
What to keep in mind: The critique applies to the temporal linearization assumption discussed in the paper and does not describe new field measurements. The authors note that nonparametric and Bayesian representations may be preferable in some settings, but the abstract does not provide a full comparative test of those approaches.

Key points

• The authors say linearizing soil-water flux gradients over time can create large errors in root water uptake estimates.
• They argue the approximation is only defensible under steady-state conditions.
• Numerical simulations showed much higher error when soil-water conditions changed rapidly, including during precipitation events.
• Published transpiration estimates discussed by the authors often fell outside their stated plausible range after rainfall.
• The paper is a correspondence that critiques a prior method rather than reporting new field data.