author = "Montanher, Ot{\'a}vio Cristiano and Novo, Evlyn M{\'a}rcia 
                         Le{\~a}o de Moraes and Souza Filho, Edvard Elias de",
          affiliation = "{Universidade Estadual de Maring{\'a} (UEM)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Estadual 
                         de Maring{\'a} (UEM)}",
                title = "Temporal trend of the suspended sediment transport of the Amazon 
                         River (19842016)",
              journal = "Hidrological Sciences Journal",
                 year = "2018",
               volume = "63",
               number = "13/14",
                pages = "1901--1912",
             keywords = "suspended sediment concentration, Amazon Basin, sediment flux 
                         changes, time series analysis, remote sensing, Landsat 5.",
             abstract = "We discuss the claim that the Amazon River has been subjected to a 
                         noticeable increase in suspended sediment transport (SST) in 
                         response to both climate and land-use changes. To study this, both 
                         satellite imagery and in situ data were compiled to produce a 
                         32-year time series (1984 2016) of suspended sediment 
                         concentration. Both parametric and nonparametric statistics were 
                         applied to examine the SST time trend. The results indicate that 
                         there has been no statistically significant increase in SST in the 
                         last 32 years, independent of the statistical approach. The 
                         results indicate that, over the last 32 years at the {\'O}bidos 
                         station, in Brazil, a recurring pattern of increase and decrease 
                         in SST has occurred, rather than a unidirectional systematic 
                         trend. This further explains the increasing trend reported in the 
                         literature and indicates that short time series are not 
                         recommended for time trend analyses due to the large inter-annual 
                  doi = "10.1080/02626667.2018.1546387",
                  url = "http://dx.doi.org/10.1080/02626667.2018.1546387",
                 issn = "0262-6667",
             language = "en",
           targetfile = "montanher_temporal.pdf",
        urlaccessdate = "26 nov. 2020"