In the Deepwater Horizon oil spill, optical plume velocimetry (OPV), a flow measurement technique for use in seafloor hydrothermal systems, was found to have the least uncertainty in estimating the rate at which oil was escaping from the well in the deep sea. However, OPV still had a high uncertainty of 21, partly due to the limited accuracy of the temporal cross-correlation algorithm used. In this work, the accuracy of several in-situ optical velocimetries, namely wavelet-based optical velocimetry (WOV), OPV, and two classical correlation-based algorithms, namely fast Fourier transform (FFT) and normalized cross-correlation (NCC), for a plume flow with Reynolds numbers varying from 1847 to 11,656 was investigated. WOV, FFT, and NCC resulted in flow rates closer to the expected turbulent plume flow rate as compared to OPV. Moreover, a noisy velocity field was found using OPV. The accuracy of wavelet-based algorithm outperformed all cross-correlation based algorithms. The flow rate was measured with an error of 8.5 using WOV, whereas errors of 18.2, 19.7, to 21.1 were obtained when applying FFT, OPV, and NCC, respectively. There was a statistically significant difference between wavelet-based and correlation-based algorithms, but no statistically significant difference between the estimation of the three cross-correlation based velocimetries. WOV outperformed the other velocimetries and estimated flow rates with an error of 8.5, whereas the OPV, FFT, and NCC were estimated with errors of 19.7, 18.2, and 50.8, respectively. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.