Abstract Li and Pawlowicz (2025), https://doi.org/10.1029/2024jc021432 proposed that a baseline relationship between river discharge ( Q ) and plume area ( A ) could be established using a simple linear regression model (Equation 2 in their paper) to remove seasonal effects for an analysis of tidal influence. However, this method overlooks a fundamental problem: due to the aliasing effect between the fixed ∼24hr observation period of the MODIS satellite and the period of the major diurnal tidal constituents (K1 and P1, with periods of 23.9345 and 24.0659 hr, respectively), the key explanatory variables in their observational dataset—river discharge (Q) and tidal elevation ( η )—are not independent and are significantly negatively correlated. Here, we use the 2018 hydrological data cited in their paper to conduct a series of numerical experiments based on a multiplicative effect model. Our Monte Carlo sensitivity analysis reveals that the baseline regression model systematically overestimates the discharge‐area slope by approximately 7.8%. Consequently, the magnitude of tidal modulation is underestimated by approximately 23.6%. We therefore argue that the baseline model used in the original study is methodologically flawed, and consequently, the core quantitative conclusion of the original paper—that the tidal modulation of the plume area is approximately 20%—is likely a significant underestimation.
Cao et al. (Wed,) studied this question.