The analysis of bubbly two-phase flows is challenging due to their turbulent nature and the need for intrusive
phase-detection probes. However, accurately characterizing these flows is crucial for safely designing critical
infrastructure such as dams and their appurtenant structures. The combination of dual-tip intrusive phase detection probes with advanced signal processing algorithms enables the assessment of pseudo-instantaneous
1-D velocity time series; for which the limitations are not fully fathomed. In this investigation, we theoretically
define four major sources of error, which we quantify using synthetically generated turbulent time series,
coupled with the simulated response of a phase-detection probe. Based on the analysis of 1010 simulated
bubble trajectories, our findings show that typical high-velocity flows in hydraulic structures hold up to 15%
error in the mean velocity estimations and up to 35% error in the turbulence intensity estimations for the
most critical conditions, typically occurring in the proximity of the wall. Based on thousands of simulations,
our study provides a novel data-driven tool for the estimation of these baseline errors (bias and uncertainties)
in real-word phase-detection probe measurements of bubbly flows (air concentrations 𝑐 < 40%).