[en] A method for predicting water quality by linear regression using aquatic bryophy te canonical variables as predictors is presented. An example of application in the Alsatian Rhine valley is developed. The /--squared obtained before and after cross-validation reached 0.68 and 0.58 for the standard deviation of temperatures, 0.55 and 0.46 for the logarithm of the mean concentrations of N-NH4+, 0.52 and 0.43 for the logarithm of the mean concentrations of N-NO3- and 0.38 and 0.31 for the logarithm of the mean concentrations of P-PO43-. Higher r-squared were not expected due to the broad physico-chemical ranges and the low diversity of genuine aquatic bryophytes. The predicted values of the mean concentrations of N-NH4+, P-PO43- and of the standard deviation of temperatures were often greater than the measured ones. The aquatic bryophytes integrate the sudden increase of the trophic level in oligotrophic streams during the floods of the main eutrophic river and testify to a higher trophic level than expected from regular physico-chemical analyses outside the flood period. Aquatic bryophytes are also affected by water quality in the long term and indicate pollutants other than those measured in current water quality. Other factors besides trophic level might influence the aquatic bryophyte assemblages and should be monitored in order to find the precise relationships between water quality and aquatic macrophytes and in order to create a more accurate model of the effects of the flooding of disconnected streams by the Rhine waters (currently in progress in the Upper Rhine) on the aquatic macrophyte assemblages.