On the basis of the specified starting points and guidelines, the thesis presents in detail a development of a multi-criteria method (the MCA method) for analysing and determining the suitability of the examined areas or catchments for economic use of water. The emphasis is on hydropower use of water, which is one of the most topical uses, but also one which conflicts the most with the objectives of achieving good water status. As a novelty in this field, the MCA method comprises the process of calibrating the values of the searched model parameters (model variables) of the MCA method. The calibration is based on the selection of calibration data representing sections or areas that are suitable and unsuitable for the analysed type of economic water use, as well as on the selection of the objective function which is used to evaluate the performance of a particular set of selected values for the searched model parameters. Due to a large solution space, the method also foresees the use of tools for searching optimal or near-optimal solutions, such as genetic algorithms. The developed MCA method was applied to three watercourses, where it appeared that for efficient determination of watercourse sections regarding their suitability for hydropower use fewer relevant indicators were required than initially assumed. To evaluate the method performance, a comparative analysis is further carried out, which includes examples with different starting points, such as a different method of determining the values of model variables, different selection of calibration data and a different method for evaluating and scoring of variants by a given indicator. In addition a comparative analysis was also performed on other watercourse where results got by application of calibrated values of model variables were compared with results got by application of values of model variables which were previously defined by expert judgement and stakeholders’ involvement. The conclusion comprises a discussion on main findings and performance of developed MCA method, confirmation of working hypotheses and establishes the need for additional confirmation and further work.