The adoption of an area value to define large, medium or small river basins should take into account the various processes involved in the basin behavior. In small basins, rainfall-flow conversion phenomena are described using simpler techniques. In order to classify small river basins according to their drainage areas, the main objective of this study was to identify and classify the small basins of the Amazon using a simple linear model (MLS). The model is applied to the rainfall and flow data from selected test basins in order to verify the linearity between these variables. The MLS used in this study is based on a linear and time invariant system that establishes a cause and effect relationship between rainfall and flow data. The performance of the model was evaluated through the RMS (square root of the mean square error), and from the results, small hydrographic basins were classified as a function of the drainage area. The method of Otto Pfafstetter is applied searching to identify at what level of codification are found only small river basins. The results indicated that in the basins with drainage areas less than or equal to 620 km², the adjustment between the observed and simulated flow duration curves was higher, presenting RMS values below 3 m³ / s. In the basins with dimensions over 620 km ², the RMS results exceeded 4 m³ / s, and the flow duration curves did not present a good fit, demonstrating that the MLS fails when applied to the hydrological data of these basins. Thus, the small hydrographic basins of the Amazon were classified with areas of drainage less or equal to 620 km ². The Ottocoding method was applied until level 9, where 51,319 ottobacias were delimited, all classified as small basins.
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