Contribution to the classification of small catchments according to the drainage area

Abstract

ABSTRACT The adoption of an area value to define large, medium or small river basins should take into account the hydrological processes involved in the basin. Changes in runoff are identified with greater sensitivity in small catchments, as in large catchments it is not possible to disregard factors such as infiltration and evaporation, which directly interfere with the rainfall-runoff conversion phenomenon. Thus, the objective of this study is to classify the small catchments of the Amazon Region by drainage area using a simple linear model (SLM). The SLM is based on a linear and time-invariant system that establishes a cause-and-effect relationship between the data. The model was applied to rainfall and runoff data from test catchments to verify the linearity between these variables. The performance of the model was evaluated through the Root Mean Square Error (RMS) and metric distance . The results indicated that in the catchments with drainage areas less than to 500 km², the adjustment between the observed and simulated flow was good, presenting RMS and metric distance values less than 3 m³/s and 2000, respectively. In basins of the dimensions above 500 km², the RMS and results began to show nonlinearity from 4 m³/s and 3000, respectively, showing that SLM should not be applied to medium and large river basins. Thus, the small catchments of the Amazon were classified as drainage areas less than 500 km².