The Water Framework Directive (WFD) requires a level of "confidence" and "precision" in the established freshwater monitoring system, as several sources of variability can contribute significantly to the mis-classification of water body ecological status. Diatoms and macrophytes are required by the Directive as biological quality element (BQE) and are routinely used in France to monitor the health of rivers. The present study evaluated uncertainties related to the application of the data acquisition protocol for the two vegetation-based assessment methods in France (Biological Diatoms index, IBD 2007 and Biological River Macrophyte index, IBMR). We aimed to estimate the overall impact of inter-operator variability on IBD 2007 and IBMR results, and on river ecological status classification, at the French national scale. A systemic approach was designed and sampling surveys were conducted at the same sites by three different operators belonging to different French bodies involved in monitoring. Results showed significant inter-operator variability regarding the species lists obtained, but also in terms of richness and abundance metrics. However, statistical analyses did not reveal any significant difference in the distribution of IBD 2007 and IBMR scores between the three operators, among all sites considered together. The mean deviation at a site was ± 0.85 for the diatom index (differences ranged between 0 and 6.6 IBD 2007 points) and ± 0.57 for the macrophyte index (the effective range was 0 and 3 IBMR points). In general, inter-operator variability was higher for moderate and poor ecological status classes. The distribution of such variability observed along the entire quality gradient of our data set, for both diatoms and macrophytes, was used to fit a model able to define the probability for a site to belong to a given status class according to its index score. Identifying and quantifying the key factors that contribute to the potential misclassification of the ecological status finally allowed us to propose future recommendations in order to minimise the main sources of error.