A statistical-based reach scale classification for the lower Tapajós river channel, eastern Amazonia

• Autor(a) principal: De Cortes, João Paulo S
• Data de Publicação: 2021
• Outros Autores: de Fraga, Rafael, Pupim, Fabiano N, Luvizotto, George L [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1177/0309133320981550; http://hdl.handle.net/11449/205768
• topic: Amazon; Fluvial rias; geomorphometry; statistical classification

The Tapajós river is among the largest rivers in the world and has been credited as the main affluent of the lower Amazon River. Geomorphological studies in the Tapajós commonly deal with evolutionary, hydrological, and sedimentological issues. Recently, important advances have been made in understanding the morphology and dynamics in the Tapajós, especially in the confluence zone near Santarém, eastern Amazonian Brazil. However, the lack of an independent channel classification system makes it difficult to integrate data obtained from different sources. This work presents a classification system for the lower Tapajós based on morphometric variables extracted from transversal profiles coupled with radar and optical remote sensing data. We used discriminant analysis of principal components for the first time in fluvial geomorphology to provide a clustering-based geomorphological classification, which is statistically supported. We propose a segmentation of the channel into three distinct sections referred to as narrower channel reach, higher ria reach, and lower ria reach. The results showed that the channel has a distinct morphological pattern in each of these reaches, which can also be observed by the variation along the longitudinal profile. Our findings showed that the most variable hydrological and sedimentological patterns are found in the lower ria reach, while the higher ria reach comprises a canyon-shaped, more stable part of the channel. We discuss the implications of this pattern on the ria’s evolution. The method developed here could be applied to other areas of the Amazon basin, where the lack of data and logistical difficulties carrying out fieldwork are common obstacles to large-scale investigations. The identified reaches are indended to be considered in the sample design of future works and in the formulation of water resources management strategies.