Remote sensing of chlorophyll-a concentration based on absorption coefficients in Ibitinga reservoir
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2018-03-23
Autores
Andrade, Caroline Piffer de
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Universidade Estadual Paulista (Unesp)
Resumo
O presente estudo objetivou estimar as concentrações de clorofila-a (Chl-a) no reservatório da usina hidroelétrica de Ibitinga (RHI), localizado no Rio Tietê, estado de São Paulo, Brasil, por meio de coeficientes de absorção obtidos via algoritmos quase-analíticos (QAAs). Para isso, realizou-se uma caracterização bio-ótica e biogeoquímica do RHI, por meio de dados espectrais e de qualidade da água coletados em dois trabalhos de campo, conduzidos em Julho de 2016 e Junho de 2017. Os desempenhos das versões originais QAAV5 e QAAV6 em estimar as propriedades óticas inerentes (POIs) no RHI foram avaliados. Versões re-parametrizadas para dois reservatórios localizados no sistema em cascata do Rio Tietê, QAABBHR e QAAOMW, foram também testadas para a área de estudo. Além disso, foram avaliadas as performances de esquemas compostos pelas versões do QAA já mencionadas, seguidas por quatro modelos para estimativa de Chl-a, os quais utilizam coeficientes de absorção como dados de entrada. A distribuição espacial das concentrações de Chl-a foi analisada por meio da aplicação desses esquemas em uma imagem do sensor Ocean and Land Colour Instrument (OLCI) instalado a bordo do satélite Sentinel-3A, com aquisição coincidente com o segundo trabalho de campo realizado na área de estudo. A caracterização bio-ótica demonstrou variabilidade espacial e temporal dos constituintes oticamente significativos (COSs) no RHI, com predominância da absorção pelo material orgânico colorido dissolvido (CDOM). As versões do QAA testadas para o primeiro conjunto de dados não se mostraram completamente adequadas na obtenção de coeficientes de absorção em todos os comprimentos de onda. Com relação aos esquemas para estimativa de concentração de Chl-a, apenas aqueles baseados no QAAV5 foram capazes de obter resultados razoáveis - Raiz do Erro Médio Quadrático Normalizado (REMQN) < 47.50 % - para os dados da imagem OLCI. Todos os quatro modelos para estimativa de Chl-a testados apresentaram resultados similares para os dados de saída do QAAV5. Esses resultados enfatizam o desafio gerado pela grande variabilidade ótica dos sistemas em cascata, com relação à modelagem bio-óptica. Os resultados obtidos dão suporte a futuros trabalhos, os quais podem resultar em aplicações como o monitoramento do estado trófico na área de estudo a partir de dados de satélite, com maior acurácia proveniente do uso de modelos que possam estimar consistentemente suas POIs.
This research was aimed at retrieving chlorophyll-a (Chl-a) concentrations in Ibitinga Hydroelectric Reservoir (IHR), located at Tietê River, São Paulo State, Brazil, using absorption coefficients obtained via Quasi-analytical algorithms (QAAs). For this purpose, a bio-optical and bio-geochemical characterization of IHR was carried out, through spectral and water quality data collected in two field campaigns conducted in July, 2016 and June, 2017. The suitability of two QAA native forms (QAAV5 and QAAV6) in retrieving inherent optical properties (IOPs) in IHR was assessed. Versions re-parameterized for two reservoirs also located in the Tietê River cascading system, QAABBHR and QAAOMW, were also tested for the study area. Besides that, the performances of schemes composed by the QAA versions already mentioned followed by four models that use absorption coefficients as inputs for estimating Chl-a concentration in Ibitinga Reservoir were evaluated. Spatial distribution of Chl-a in the reservoir was analyzed, since these schemes were applied in an image of the Ocean and Land Colour Instrument (OLCI) sensor onboard Sentinel-3A satellite, with acquisition date coincident with the second field campaign. The bio-optical characterization showed spatial and temporal variability of optically significant constituent (OSC) in IHR and colored dissolved organic matter (CDOM) predominance in its absorption budget. None of the QAA versions tested for the first dataset was completely satisfactory in retrieving absorption coefficients for IHR in all wavelengths. Regarding the schemes for Chl-a concentration estimates, only the ones based on QAAV5 were able to obtain reasonable results - Normalized Root Mean Square Error (nRMSE) < 47.50 % - for the OLCI image data. All four models for Chl-a estimation tested presented similar results for QAAV5 outputs. These results highlight the challenge of copying with high optical variability in cascading systems. The results obtained support further works, which can, prospectively, lead to many practical applications, as monitoring of trophic state in the study area from satellite data, with higher accuracy provided by the use of models that can consistently retrieve the IOPs for this specific water system.
This research was aimed at retrieving chlorophyll-a (Chl-a) concentrations in Ibitinga Hydroelectric Reservoir (IHR), located at Tietê River, São Paulo State, Brazil, using absorption coefficients obtained via Quasi-analytical algorithms (QAAs). For this purpose, a bio-optical and bio-geochemical characterization of IHR was carried out, through spectral and water quality data collected in two field campaigns conducted in July, 2016 and June, 2017. The suitability of two QAA native forms (QAAV5 and QAAV6) in retrieving inherent optical properties (IOPs) in IHR was assessed. Versions re-parameterized for two reservoirs also located in the Tietê River cascading system, QAABBHR and QAAOMW, were also tested for the study area. Besides that, the performances of schemes composed by the QAA versions already mentioned followed by four models that use absorption coefficients as inputs for estimating Chl-a concentration in Ibitinga Reservoir were evaluated. Spatial distribution of Chl-a in the reservoir was analyzed, since these schemes were applied in an image of the Ocean and Land Colour Instrument (OLCI) sensor onboard Sentinel-3A satellite, with acquisition date coincident with the second field campaign. The bio-optical characterization showed spatial and temporal variability of optically significant constituent (OSC) in IHR and colored dissolved organic matter (CDOM) predominance in its absorption budget. None of the QAA versions tested for the first dataset was completely satisfactory in retrieving absorption coefficients for IHR in all wavelengths. Regarding the schemes for Chl-a concentration estimates, only the ones based on QAAV5 were able to obtain reasonable results - Normalized Root Mean Square Error (nRMSE) < 47.50 % - for the OLCI image data. All four models for Chl-a estimation tested presented similar results for QAAV5 outputs. These results highlight the challenge of copying with high optical variability in cascading systems. The results obtained support further works, which can, prospectively, lead to many practical applications, as monitoring of trophic state in the study area from satellite data, with higher accuracy provided by the use of models that can consistently retrieve the IOPs for this specific water system.
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Qualidade de águas interiores, Algoritmo Quase-Analítico, Propriedades óticas inerentes, Fitoplâncton, OLCI/Sentinel-3A, Inland water quality, Quasi-Analytical Algorithm, Inherent optical properties, Phytoplankton