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@PhDThesis{Valerio:2018:AsSpVa,
               author = "Valerio, Aline de Matos",
                title = "Assessment of the spatiotemporal variability of optical and 
                         biogeochemical parameters in the Lower Amazon region and of the 
                         carbon content in the Amazon River continuum using in situ and 
                         Remote Sensing data",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2018",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2018-06-04",
             keywords = "continuum do rio amazonas, par{\^a}metros 
                         biogeoqu{\'{\i}}micos, propriedades bio-{\'o}pticas, CDOM, 
                         balan{\c{c}}o de carbono, sensoriamento remoto da cor da 
                         {\'a}gua, amazon river continuum, biogeochemical parameters, 
                         bio-optical properties, CDOM, carbon budget, water colour remote 
                         sensing.",
             abstract = "O continuum do Rio Amazonas {\'e} uma regi{\~a}o determinante no 
                         balan{\c{c}}o de carbono global, mas sua extens{\~a}o 
                         geogr{\'a}fica dificulta sua observa{\c{c}}{\~a}o in situ. 
                         Considerando as caracter{\'{\i}}sticas de alta 
                         resolu{\c{c}}{\~a}o temporal e cobertura sin{\'o}ptica, o 
                         sensoriamento remoto da cor da {\'a}gua (SRCA) representa uma 
                         ferramenta importante para monitorar a distribui{\c{c}}{\~a}o e 
                         variabilidade das fra{\c{c}}{\~o}es de carbono e outros 
                         par{\^a}metros biogeoqu{\'{\i}}micos nas {\'a}guas 
                         amaz{\^o}nicas. Entretanto, a efic{\'a}cia dos produtos gerados 
                         por SRCA para estudar a din{\^a}mica biogeoqu{\'{\i}}mica de um 
                         sistema aqu{\'a}tico, depende da acur{\'a}cia e precis{\~a}o 
                         para representar as propriedades bio-{\'o}pticas da {\'a}rea 
                         investigada. Este trabalho foi desenvolvido no continuum do Baixo 
                         Rio Amazonas, onde uma descri{\c{c}}{\~a}o abrangente da 
                         variabilidade espa{\c{c}}o-temporal de dados radiom{\'e}tricos, 
                         bio-{\'o}pticos e biogeoqu{\'{\i}}micos foi realizada com o 
                         objetivo de mapear as fra{\c{c}}{\~o}es de carbono por SRCA. Na 
                         regi{\~a}o do Baixo Amazonas (RBA), foram feitas amostragens in 
                         situ de reflect{\^a}ncia de sensoriamento remoto, par{\^a}metros 
                         bio{\'o}pticos como os coeficientes de absor{\c{c}}{\~a}o pela 
                         mat{\'e}ria org{\^a}nica colorida dissolvida (aCDOM), material 
                         particulado total (ap), fitopl{\^a}ncton (aphy) e 
                         part{\'{\i}}culas n{\~a}o-algais (anap), e par{\^a}metros 
                         biogeoqu{\'{\i}}micos como o material particulado em 
                         suspens{\~a}o (SPM), concentra{\c{c}}{\~a}o de clorofila-a, 
                         concentra{\c{c}}{\~a}o de carbono org{\^a}nico dissolvido 
                         (DOC), e press{\~a}o parcial do di{\'o}xido de carbono (pCO2) 
                         para todas as esta{\c{c}}{\~o}es hidrol{\'o}gicas - enchente, 
                         cheia, vazante e baixa, durante o per{\'{\i}}odo de 2014-2017. 
                         Na pluma do Rio Amazonas (PRA), dados in situ de pCO2, salinidade 
                         da superf{\'{\i}}cie do mar (SSS) e temperatura da 
                         superf{\'{\i}}cie do mar (SST) foram adquiridos durante as 
                         esta{\c{c}}{\~o}es de cheia, vazante e baixa durante os anos de 
                         2010-2012. As caracter{\'{\i}}sticas bio-{\'o}pticas descritas 
                         neste trabalho permitiram uma clara distin{\c{c}}{\~a}o entre o 
                         corpo de {\'a}gua principal do Rio Amazonas, dominado por NAP e 
                         CDOM, e os tribut{\'a}rios de {\'a}guas claras e dominados por 
                         CDOM. A an{\'a}lise da variabilidade espa{\c{c}}o-temporal das 
                         propriedades bio-{\'o}pticas evidenciou: 1) o impacto da 
                         dilui{\c{c}}{\~a}o dos par{\^a}metros biogeoqu{\'{\i}}micos 
                         causados pela contribui{\c{c}}{\~a}o dos tribut{\'a}rios assim 
                         como os processos de degrada{\c{c}}{\~a}o do DOM no curso do Rio 
                         Amazonas; 2) a homogeneidade das caracter{\'{\i}}sticas 
                         bio-{\'o}pticas durante as esta{\c{c}}{\~o}es hidrol{\'o}gicas 
                         de cheia, vazante e baixa, em contraste com a esta{\c{c}}{\~a}o 
                         da enchente (caracter{\'{\i}}stica predominante do SPM); 3) a 
                         vulnerabilidade das {\'a}guas amaz{\^o}nicas {\`a}s 
                         condi{\c{c}}{\~o}es hidrol{\'o}gicas excepcionais; 4) a pouca 
                         influ{\^e}ncia de processos de menor escala (por exemplo, xiv 
                         efeito de mar{\'e}) nas caracter{\'{\i}}sticas bio-{\'o}pticas 
                         regionais. Foram desenvolvidos algoritmos de invers{\~a}o 
                         regionais de CDOM, (aCDOM(412) e da inclina{\c{c}}{\~a}o da 
                         curva no intervalo do UV, S275-295), DOC e pCO2. Primeiro foram 
                         desenvolvidas formula{\c{c}}{\~o}es emp{\'{\i}}ricas de 
                         aCDOM(412) (N = 100, R2 = 0.67, p<0.05) e S275-295 (N = 100, R2 = 
                         0.83, p<0.05), baseados em modelo linear multivariado e n{\~a}o 
                         linear, respectivamente. Devido a diferentes padr{\~o}es sazonais 
                         de DOC (clara distin{\c{c}}{\~a}o da enchente em 
                         rela{\c{c}}{\~a}o {\`a}s demais), sua estimativa foi 
                         particularmente complexa. A pCO2 foi estimada satisfatoriamente a 
                         partir de uma rela{\c{c}}{\~a}o multivariada usando CDOM e 
                         temperatura (N = 69, R2 = 0.80, p<0.05). Os modelos desenvolvidos 
                         para estimar aCDOM(412), S275-295, DOC e pCO2, foram aplicados em 
                         imagens sazonais do sensor orbital Medium Resolution Imaging 
                         Spectrometer (MERIS) para os anos de 2010- 2011 para demonstrar a 
                         din{\^a}mica das fra{\c{c}}{\~o}es de carbono nas {\'a}guas 
                         amaz{\^o}nicas. O Rio Amazonas foi fonte de carbono durante todas 
                         as esta{\c{c}}{\~o}es com a maior (menor) emiss{\~a}o de 
                         carbono durante a cheia (baixa). A variabilidade intra-sazonal 
                         destaca a forte din{\^a}mica em {\'a}reas de 
                         transi{\c{c}}{\~a}o entre {\'a}guas de rio e oceano. Na PRA, a 
                         pCO2 foi satisfatoriamente estimada a partir de uma 
                         rela{\c{c}}{\~a}o multivariada usando SSS e SST (N = 76, R2= 
                         0.74, p<0.05) e o modelo foi aplicado em dados do sensor Soil 
                         Moisture and Ocean Salinity (SMOS) para os anos de 2010-2014. A 
                         an{\'a}lise dos mapas da pCO2-SMOS evidenciou o impacto do 
                         padr{\~a}o hidrol{\'o}gico na variabilidade inter e intra-anual 
                         na pCO2. Em geral, a PRA durante as esta{\c{c}}{\~o}es de 
                         enchente e cheia atuou como uma fonte de CO2, enquanto que durante 
                         as esta{\c{c}}{\~o}es de vazante e baixa se comportou como um 
                         sumidouro de CO2. Os resultados aqui apresentados demonstram que a 
                         PRA sequestra menos carbono do que se presume atualmente e que 
                         inclusive, pode tamb{\'e}m agir como emissor de CO2 durante 
                         alguns per{\'{\i}}odos do ano. Este estudo enfatiza a 
                         necessidade de se obter informa{\c{c}}{\~o}es adicionais in situ 
                         (principalmente na {\'a}rea de transi{\c{c}}{\~a}o entre o rio 
                         e o oceano) para refinar e melhorar a valida{\c{c}}{\~a}o dos 
                         modelos aqui desenvolvidos e assim obter uma melhor 
                         compreens{\~a}o do papel do continuum do Rio Amazonas no 
                         balan{\c{c}}o global de carbono. Os m{\'e}todos propostos por 
                         este estudo para estimar as fra{\c{c}}{\~o}es de carbono no 
                         continuum do Rio Amazonas tem potencial para aplica{\c{c}}{\~a}o 
                         em outros grandes rios globais, especialmente em regi{\~o}es 
                         tropicais. ABSTRACT: The Amazon River continuum plays a crucial 
                         role to the global carbon budget but its geographic extension 
                         challenges in situ observations. Due to its high temporal and 
                         synoptic coverage, the water colour remote sensing (WCRS) 
                         represents a relevant observation tool to monitor the distribution 
                         and variability of carbon content and other biogeochemical 
                         parameters on the Amazon waters. However, the optimal exploitation 
                         of the information provided by WCRS for investigating 
                         biogeochemical dynamics of a water system relies on accurate 
                         retrieval of bio-optical properties of the area investigated. This 
                         work focused on the Lower Amazon River continuum where a 
                         comprehensive description of the spatiotemporal variability of 
                         radiometric, bio-optical and biogeochemical parameters was 
                         performed with the aim of mapping carbon content from remote 
                         sensing observation. In the Lower Amazon River region (LAR), in 
                         situ sampling of remote sensing reflectance, bio-optical 
                         parameters (absorption properties of the coloured dissolved 
                         organic matter (aCDOM), total particulate matter (ap), 
                         phytoplankton (aphy) and non-algal particles (anap)) and 
                         biogeochemical parameters (suspended particulate matter (SPM), 
                         chlorophyll-a, dissolved organic carbon (DOC) concentration, and 
                         partial pressure of dioxide carbon (pCO2)) were acquired for all 
                         regional hydrological seasons (i.e. rising water (RW), high water 
                         (HW), falling water (FW) and low water (LW)), over the 2014-2017 
                         time period. In the Amazon River plume (ARP), in situ pCO2, sea 
                         surface salinity (SSS) and water surface temperature (SST) were 
                         acquired during HW, FW and LW seasons during 2010-2012. The 
                         general description of the bio-optical characteristics of the 
                         Lower Amazon River performed from this original data set has 
                         allowed a clear optical distinction between waters from the Amazon 
                         mainstream (NAP and CDOM dominated) and those corresponding to the 
                         Amazon tributaries (clear waters and CDOM dominated). The analysis 
                         of the spatiotemporal variability of the Lower Amazon bio-optical 
                         properties emphasized: 1) the predominant impact of Amazon 
                         tributaries dilution on biogeochemical parameters and degradation 
                         processes of the DOM along the Amazon course; 2) the homogeneity 
                         in the Amazon bio-optical characteristics during the HW, FW, LW 
                         seasons the latter contrasting with the RW season (SPM major 
                         characteristics); 3) the sensitivity of the Amazon water to 
                         exceptional hydrological conditions; 4) the restricted influence 
                         of small scale processes (e.g. tidal effects) on the regional 
                         biooptical characteristics. Regional CDOM (aCDOM(412) and CDOM 
                         spectral slope in the UV, S275-295), DOC and pCO2 inversion 
                         algorithms were developed. aCDOM(412) and S275-295 empirical 
                         formulations based on a multiband linear relationship (N = 100, R2 
                         = 0.67, p<0.05) and a nonlinear relationship (N = 100, R2 = 0.83, 
                         p<0.05), respectively, were first developed. The DOC retrieval 
                         from aCDOM(412) in the LAR has been shown to be relatively complex 
                         relying on the specific consideration of the seasonal pattern in 
                         the algorithm definition (distinction between RW and the other 
                         seasons). pCO2 was satisfactorily retrieved from a unique 
                         algorithm using CDOM and temperature as input parameters (N = 69, 
                         R2 = 0.80, p<0.05). The models developed here for estimating 
                         aCDOM(412), S275-295, DOC and pCO2 were applied on Medium 
                         Resolution Imaging xii Spectrometer (MERIS) seasonal composite 
                         images for the years of 2010-2011 to illustrate the spatiotemporal 
                         dynamics of the carbon contents in the Amazon waters. Amazon River 
                         was found to represent a source of carbon during all seasons, with 
                         the highest (lowest) carbon export during the RW (LW). The 
                         intra-seasonal variability underlines the strong dynamics of the 
                         transition areas between the river and oceanic waters. In the ARP, 
                         pCO2 was satisfactorily retrieved using SSS and SST as proxies (N 
                         = 76, R2= 0.74, p<0.05) and the model was applied on Soil Moisture 
                         and Ocean Salinity (SMOS) images for the years of 2010-2014. The 
                         analysis of SMOS-based pCO2 maps has illustrated the impact of the 
                         hydrological pattern on inter and intra-annual pCO2 variability. 
                         The ARP during the RW and HW seasons was generally representing a 
                         net source of CO2. Conversely, during the FW and LW seasons, the 
                         ARP was a net sink of CO2. The latter results restricted carbon 
                         sink area when compared to previous observations and net source of 
                         CO2 (during some periods of the year) are particularly original. 
                         This study emphasized the crucial need of additional in situ 
                         information (especially in the river to ocean transition area) for 
                         refining and better validating the models developed in this study 
                         and thus obtain a better insight into the understanding of the 
                         role of the Amazon River Continuum on the global carbon budget. 
                         The methods here proposed to assess the carbon content in the 
                         Amazon River continuum might be potentially applied to other large 
                         river systems, especially over tropical areas.",
            committee = "Novo, Evlyn Marcia Le{\~a}o de Moraes (presidente) and Kampel, 
                         Milton (orientador) and Vantrepotte, Vincent (orientador) and 
                         Rudorff, Nat{\'a}lia de Moraes and Alc{\^a}ntara, Enner Herenio 
                         de and Loisel, Hubert",
         englishtitle = "Avalia{\c{c}}{\~a}o da variabilidade espa{\c{c}}o-temporal dos 
                         par{\^a}metros {\'o}pticos e biogeoqu{\'{\i}}micos na 
                         regi{\~a}o do Baixo Amazonas e das fra{\c{c}}{\~o}es de carbono 
                         no continuum do Rio Amazonas utilizando dados in situ e de 
                         sensoriamento remoto",
             language = "en",
                pages = "237",
                  ibi = "8JMKD3MGP3W34R/3R677US",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/3R677US",
           targetfile = "publicacao.pdf",
        urlaccessdate = "04 dez. 2020"
}


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