The classification of rivers based on geomorphological criteria played, in the past, a secondary role for management decision making, although in the last years they have experienced a shift from the scientific field to that of the technical. Currently, managers require the most simplified form of classifications in order to use them in plans and planning projects, management and restoration. On the one hand, this means that classifications should be directed toward simplifying the diversity of fluvial environments in a number of manageable types, and on the other hand, to apply to each geomorphic type a management model. In this study, we have developed a method of “Geomorphic Classification of Rivers” according to specific stream power variables and median grain size. The new method is dynamic (ability to readjust and gain robustness with the incorporation of new data) and predictive. We obtained six types directly from the method, although we added a seventh type (bedrock rivers) for its special singularity. Each geomorphic type presents concrete values of specific stream power and median grain size, which additionally involves a hydraulic geometry adjusted to terms of balance. The change from a geomorphic type to another would reflect a geomorphologic imbalance in the form of greater power and sediment size. Our results have been compared with six commonly used classifications (e.g., Rosgen Classification System or River Styles Framework). “Geomorphic Classification of Rivers” stands as a flexible tool that allows the development of a “personalized” geomorphic classification for rivers of the same geomorphological province. Through the temporary revision of various sites that act as control points, we can learn, should the case arise, the intensity and geomorphic change of the site. “Geomorphic Classification of Rivers” acts as an alert system for any geomorphologic disturbance. Its simple application and interpretation facilitate the implementation in the administrative environment, or its attachment to other commonly used classifications.
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