Padrões espaço-temporais do transporte de sedimentos suspensos dos rios amazônicos de águas brancas : relações com o clima e mudanças na cobertura do solo

• Autor(a) principal: Montanher, Otávio Cristiano
• Data de Publicação: 2016
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Estadual de Maringá (RI-UEM)
• Texto Completo: http://repositorio.uem.br:8080/jspui/handle/1/2905
• topic: Transporte de sedimentos, Rios Amazônicos, Bacias Hidrográficas, Amazônia, Sensoriamento remoto, Imagens Landsat, Séries Temporais, Sedimentos suspensos - Brasil; Amazon drainage basin; Sediment yield; Time series; Landsat 5 images. Regression analysis; El niño - Brazil; Ciências Humanas; Geografia

This study involves a research about the suspended sediment transport (SST) of large Amazonian white water rivers: Içá, Japurá, Juruá, Purus, Madeira, Solimões and Amazonas. Despite the environmental importance of the suspended sediment concentration (SSC) for those rivers, there are spatial and temporal restrictions in the in situ collected data series. As the amount of suspended sediment in the rivers might indicate the frequency and intensity of climatic processes and soil coverage changes, important research issues in the Amazon, an adequate database may support some hypothesis about the environmental dynamic of this region. Therefore, this research adopted empirical models, which use orbital images as input data, for estimating the SSC in the main Amazonian rivers that promote the sediment transport. Such models have not yet been applied, so this database is inedited, which is accessible in this document. This database supported some hypothesis tests, and some results are contradictory when compared to the consulted bibliography. In relation to the main results obtained here: (i) 5643 images were processed: 5511 from TM sensor and 132 from ETM+ sensor. Of that total, 5409 were applied for retrieving temporal series, while 234 were used in an experiment to investigate the applicability of the TM models in ETM+ data; (ii) the SSC estimates were grouped with in situ collected data, provided by the Brazilian National Water Agency and by the ORE HYBAM (from the last were also obtained estimates from MODIS images). With discharge data, the SSC series generated daily SST series, which have an average extension of 30,05 years. The mean periodicity of SSC data for all stations is one value every 11,46 days; (iii) it is possible to estimate the SST by using discharge data for three stations: Óbidos, Manacapuru and Fazenda Vista Alegre (rivers: Amazonas, Solimões and Madeira). For other stations, the described method should be applied only for certain periods of the year; (iv) the transport and sediment yield were mapped, as well as its temporal variabilities, for both monthly and annual scales. Also, were discussed some spatial relations between the sediment yield and latitude, longitude and distance from the source region; (v) trend analysis were performed for all the stations, taking into account series of approximately 30 years, and were not founded significant trends of SST increase or decrease along time. Another trend analysis was applied using extended temporal series (between 43 and 67 years) for the rivers: Amazonas, Madeira and Solimões, and once again significant trends were not founded; (vi) were performed analysis of the relationship between the SST and climate variables, as precipitation and sea surface temperature anomalies (SSTA) of both Atlantic and Pacific oceans. In annual scale, taking into account the series seasonality, correlations between the precipitation and the SST were observed for almost all the stations. However, when the trend-cycle series were used, significant correlations were not observed. In relation to the climate indexes, those with the highest correlations with the SST were associated to the North Tropical Atlantic. Some tests were performed using indexes linked to the El Niño episodes, which seems to have little influence over the SST estimated in the handled stations; (vii) the relation between the estimated SST and the deforestation at the hydrographic basin level was evaluated. Taking into consideration the PRODES and Terra-i databases, it was not possible to conclude that the deforestation is triggering an increase in the SST of the Amazon river. Finally, it is expected that these results collaborate for a better description and understating of some great Amazonian rivers