A semianalytical algorithm to retrieve the suspended particulate matter in a cascade reservoir system with widely differing optical properties
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Data
2019-09-03
Autores
Bernardo, Nariane Marselhe Ribeiro
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Universidade Estadual Paulista (Unesp)
Resumo
O Material Particulado em Suspensão (MPS) é o principal componente em sistemas aquáticos. Elevadas concentrações de MPS implicam na atenuação da luz, e ocasionam alterações das taxas fotossintéticas. Além disso, a presença de MPS no sistema aquático pode aumentar os níveis de turbidez, absorver poluentes e podem ser considerados como um indicativo de descargas de escoamento superficial. Portanto, monitorar as concentrações de MPS é essencial para a gerar informações técnicas que subsidiem o correto manejo dos recursos aquáticos, prevenindo colapsos hidrológicos. O sensoriamento remoto se mostra como uma eficiente ferramenta para monitorar e mapear MPS quando comparada às técnicas tradicionais de monitoramento, como as medidas in situ. Entretanto, diante de uma grande e complexa variabilidade de componentes óticos, desenvolver modelos de MPS por meio do sinal registrado em sensores remotos é um desafio. Diversos modelos foram desenvolvidos para reservatórios, lagos e lagoas específicos. Atualmente, não há um único modelo capaz de estimar MPS em reservatórios brasileiros em cascata. Com o objetivo de estimar as concentrações de MPS de forma acurada, o objetivo desta tese foi desenvolver um modelo semi-analítico capaz de estimar valores de coeficiente de atenuação, Kd, por meio do uso dos coeficientes de absorção e espalhamento e, consequentemente, utilizar os valores de Kd para estimar as concentrações de MPS. A adoção desta estratégica se baseou na atenuação da luz ao longo da coluna da água, causada pela presença de MPS. Inicialmente, as características óticas dos reservatórios foram investigadas. Foi observado que cada reservatório apresenta um componente oticamente ativo (COA) dominante, como em Barra Bonita, o primeiro reservatório da cascata, dominado pela fração orgânica do MPS, enquanto que Nova Avanhandava, o ultimo reservatório da cascata, a fração inorgânica de MPS é dominante. Além disso, Bariri e Ibitinga, reservatórios localizados próximos à Barra Bonita, apresentaram elevadas contribuições de material orgânico dissolvido colorido (CDOM). Todas estas características implicam em diferentes propriedades bio-ópticas. Sequencialmente, a qualidade da reflectância de sensoriamento remoto (Rsr) foi avaliada por meio da comparação de quatro métodos, publicados na literatura, para remoção do efeito especular. Para validação dos resultados, o resultado das simulações obtidas via Hydrolight® foi utilizado como dado de referência. Os resultados demonstraram que o uso de um fator hiperespectral que compense a componente especular foi a melhor abordagem para calcular os dados de Rsr, reduzindo aproximadamente 30% dos erros quando comparados às outras abordagens, as quais consideraram apenas a velocidade do vento como causa do efeito especular. Por fim, modelos empíricos e semi-analíticos foram desenvolvidos, sendo que os modelos semi-analíticos apresentaram um resultado mais satisfatório para as estimativas das concentrações de MPS do que os modelos empíricos. O modelo desenvolvido na presente tese, QAATRCS, resultou em erros médios menores que 30%, enquanto que os modelos empíricos retornaram erros de até 80%. Em vista do grande intervalo de concentrações de COAs e da variabilidade ótica observada no reservatórios em cascata, o QAATRCS foi capaz de estimar de forma acurada as concentrações de MPS.
Suspended particulate matter (SPM) is the main component presented within aquatic system. High levels of SPM concentration attenuate the light affecting the photosynthesis rates. Besides, can increase turbidity levels, absorb pollutions and is an indicative of runoff discharges. Therefore, monitoring SPM concentrations is essential to provide reliable information for a correct water management to prevent hydrological collapse. Remote sensing emerges as an efficient tool to map and monitor SPM when compared to traditional techniques, such as in situ measurements. Nevertheless, considering a widely range of optical components, modeling the remote sensing signal in terms of SPM is a challenge. Several models were developed for specific reservoirs, lakes or ponds. Up to our knowledge, there is not a single model capable to retrieve SPM in Brazilian linked reservoirs in a cascade system. In order to accurately estimate SPM, the aim of the thesis was developed a semianalytical model capable to estimate Kd via absorption and backscattering coefficients, and then, use Kd to derive SPM. This approach was adopted because SPM directly contributes to the light attenuation within the water column. Firstly, optical features were investigated. It was found that each reservoir presented a specific optical active component (OAC) dominance, such as Barra Bonita, the first reservoir in cascade is dominated by organic SPM, while Nova Avanhandava, the last reservoir in cascade is dominated by inorganic SPM. Besides, Bariri and Ibitinga reservoirs located nearest Barra Bonita, demonstrated high levels of CDOM contribution. All these characteristics imply in changes of bio-optical properties. In sequence, the quality of remote sensing reflectance (Rrs) was calculated by comparing four methods published in literature, and using as reference for validation, the simulated dataset via Hydrolight®. The results demonstrated that use a hyperspectral factor to compensate the specular component is the best approach to compute suitable Rrs, reducing 30% of errors when compared to approaches that use wind speed as the only factor of glint effect. Then, empirical and semianalytical models were developed, and the semianalytical model provided more satisfactory results of SPM estimations than empirical model. Our developed semianalytical model, called QAATRCS, retrieved errors for SPM estimates lower than 30% on average, while the empirical model reaches errors near 80%. Considering the widely range OACs concentration and the optical properties variability, QAATRCS was capable to provide reliable SPM estimates.
Suspended particulate matter (SPM) is the main component presented within aquatic system. High levels of SPM concentration attenuate the light affecting the photosynthesis rates. Besides, can increase turbidity levels, absorb pollutions and is an indicative of runoff discharges. Therefore, monitoring SPM concentrations is essential to provide reliable information for a correct water management to prevent hydrological collapse. Remote sensing emerges as an efficient tool to map and monitor SPM when compared to traditional techniques, such as in situ measurements. Nevertheless, considering a widely range of optical components, modeling the remote sensing signal in terms of SPM is a challenge. Several models were developed for specific reservoirs, lakes or ponds. Up to our knowledge, there is not a single model capable to retrieve SPM in Brazilian linked reservoirs in a cascade system. In order to accurately estimate SPM, the aim of the thesis was developed a semianalytical model capable to estimate Kd via absorption and backscattering coefficients, and then, use Kd to derive SPM. This approach was adopted because SPM directly contributes to the light attenuation within the water column. Firstly, optical features were investigated. It was found that each reservoir presented a specific optical active component (OAC) dominance, such as Barra Bonita, the first reservoir in cascade is dominated by organic SPM, while Nova Avanhandava, the last reservoir in cascade is dominated by inorganic SPM. Besides, Bariri and Ibitinga reservoirs located nearest Barra Bonita, demonstrated high levels of CDOM contribution. All these characteristics imply in changes of bio-optical properties. In sequence, the quality of remote sensing reflectance (Rrs) was calculated by comparing four methods published in literature, and using as reference for validation, the simulated dataset via Hydrolight®. The results demonstrated that use a hyperspectral factor to compensate the specular component is the best approach to compute suitable Rrs, reducing 30% of errors when compared to approaches that use wind speed as the only factor of glint effect. Then, empirical and semianalytical models were developed, and the semianalytical model provided more satisfactory results of SPM estimations than empirical model. Our developed semianalytical model, called QAATRCS, retrieved errors for SPM estimates lower than 30% on average, while the empirical model reaches errors near 80%. Considering the widely range OACs concentration and the optical properties variability, QAATRCS was capable to provide reliable SPM estimates.
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Palavras-chave
Bio-ótica, Águas interiores, Qualidade da água, OLI/Landsat-8, Sensoriamento remoto, Bio-optics, Inland water, Water quality, OLI/Landsat-8, Proximal remote sensing