Cyanobacterial algal bloom is a major water quality issue in inland lakes, reservoirs, and estuarine environments because of its scum and bad odor forming and toxin producing abilities. Health risks from cyanobacterial toxin can vary from skin irritations to fever, intestinal problems, and neurological disorders. Terminations of blooms also cause oxygen depletion leading to hypoxia and widespread fish kills. Adding to the problem, many species of cyanobacteria produce odorous compounds such as geosmin and 2-methylisoborneol (MIB) that cause “earthy-muddy” and “musty” odor in drinking water, which is also a serious issue in aquaculture and drinking water industry. Therefore continuous monitoring of cyanobacterial presence in recreational water bodies, surface drinking water sources, and water bodies dedicated for aquaculture is highly required for their early detection and subsequent issuance of a health warning and reducing the economic loss. Remote sensing techniques offers the capability of identifying and monitoring cyanobacterial blooms in a synoptic scale. Over the years, the scientific community has focused on developing methods to quantify cyanobacterial biomass using phycocyanin,an accessory photosynthetic pigment, as a marker pigment. However, because of the confounding influence of chlorophyll-a and other photo pigments, remote retrieval of phycocyanin signal from turbid productive water has been a difficult task. This dissertation analyzes the potential of remote sensing techniques and develops empirical and quasi-analytical algorithms to isolate the phycocyanin signal from the remote sensing reflectance data using a set of radiative transfer equations and retrieves phycocyanin concentration in the water bodies. An extensive dataset, consisting of in situ radiometric measurements, absorption measurements of phytoplankton, colored dissolved organic matter, detritus, and pigment concentration, was used to optimize the algorithms. Validations of all algorithms were also performed using an independent dataset and errors and uncertainties from the algorithms were discussed. Despite the simplicity, an empirical model produced highest accuracy of phycocyanin retrieval, whereas, the newly developed quasi-analytical phycocyanin algorithm performed better than the existing semi-analytical algorithm. Results show that remote sensing techniques can be used to quantify cyanobacterial phycocyanin abundance in turbid and hypereutrophic waters.

In situ measurements were used to study the bio-optical properties of marine waters within the Gulf of Paria (GOP, Venezuela) and in the Southeastern Caribbean Sea (SEC) as they are affected by the seasonal discharge of the Orinoco River plume. The main purpose of this study was to determine the impact of colored dissolved organic matter (CDOM) (also known as Gelbstoff), phytoplankton, and total suspended matter (TSM) in the color of the Orinoco River plume. This information is essential for regional ocean color algorithms development. Salinity and silica values indicate that the GOP and SEC waters were under the influence of the Orinoco River plume during both seasons. This riverine influence resulted in high values of Gelbstoff absorption, αg(λ), which contributed to up to 90% of the total absorption at 440 nm in both the GOP and SEC regardless of the season. Phytoplankton absorption contributions were normally around 5%, but during the dry season these values reached 20% in the SEC. Ratios of αg(440) to αph(440) were extremely large, with most of the values ranging from 10 to 50. Due to the strong absorption by Gelbstoff, light at the blue wavelengths (412 nm, 440 nm and 490 nm) was attenuated to 1% of the subsurface irradiance in the first 5 m of the water column within the GOP, and in the first 10 m of the water column in the SEC. Furthermore, the absorption by Gelbstoff significantly decreased the water leaving radiance (Lw(λ)) in the blue wavelengths along the Orinoco River plume. As αg(λ) relatively decreased from the GOP to the SEC (X≈1.6 m-1 and X≈ 0.9 m-1, respectively), a shift in the maximum peak of Rrs(λ) spectra (Rrsmax(λ)), towards shorter wavelengths (from ~ 580 nm to ~500 nm) was observed. Similar to Gelbstoff, concentrations of TSM normally decreased from the stations near the Delta to the stations in the SEC. The impact of TSM on the color of the Orinoco plume was represented by a reduction in the magnitude of Rrsmax(λ) of ~50% going from the waters near the Orinoco delta to the SEC, indistinctively of the season.

The objective of the research reported in this thesis was to develop a technique to monitor the dynamics of sediments and nutrients entering the coastal ocean with river plumes associated with high intensity low frequency events (e.g. floods), using ocean colour remote sensing. To achieve this objective, an inverse bio-optical model was developed, based on analytical and empirical relationships between concentrations of optically significant substances and remote sensing of water-leaving radiance. The model determines concentrations of water-colouring substances such as chlorophyll, suspended sediments, and coloured dissolved organic matter, as well as the values of optical parameters using water-leaving radiances derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). To solve atmospheric correction in coastal waters, the aerosol type over clear waters is transferred to adjacent turbid water pixels. The vicinity of the Herbert River, central Great Barrier Reef zone, Australia, was used as a case study for the application of the algorithm developed. The satellite ocean colour technique was successfully validated using sea-truth measurements of water-colouring constituents acquired in the area during various seasons throughout 2002-2004. A high correlation between chlorophyll and dissolved organic matter was found in the coastal waters of the region, and when the bio-optical model was constrained to make chlorophyll a function of dissolved organic matter, the relationship between in situ and satellite-derived data was substantially improved. With reliable retrieval of the major water-colouring constituents, the technique was subsequently applied to study fluxes of particulate and dissolved organic and inorganic matter following a flood event in the Herbert River during the austral summer of 1999. Extensive field observations covering a seasonal flood in the Herbert River in February 2004 revealed high sediment and nutrient exports from the river to the adjacent coastal waters during the flood event. Due to rapid settling, the bulk of the sediment-rich influx was deposited close inshore, while the majority of nutrients exported from the river were consumed by phytoplankton in a relatively small area of the coastal ocean. With the help of ocean colour remote sensing, it was demonstrated that river-borne sediments and nutrients discharged by a typical flood in the Herbert River are mostly precipitated or consumed within the first 20 km from the coast and therefore are unlikely to reach and possibly affect the midshelf coral reefs of this section of the Great Barrier Reef lagoon.

<p>Semi-analytical models for remote sensing of water quality parameters need to be parameterized with specific inherent optical properties. In this thesis, data on specific inherent optical properties of Swedish lakes and coastal waters is presented. Also, the problems of measuring in situ spectral backscattering are addressed. It is shown how measured specific inherent optical properties are used to parameterize semi-analytical bio-optical models. The models are then used to produce large synthetic data sets based on the distribution of water quality parameters, and from these data sets, band ratio or single band ratio algorithms for remote estimation of water quality parameters are constructed. A similar model was also used to calculate under water PAR from measured water quality parameters.</p><p>The specific inherent optical properties of Swedish lakes and coastal waters are very similar to earlier reported data from the oceanic environment. However, different relations of the water quality parameters will affect the inherent optical properties absorption and backscattering. The absorption spectra are dominated by yellow substance with terrestrial origin. Phytoplankton absorption is low, and account in general only for about 10 % of the total absorption in regions where phytoplankton pigments are active. The spectral backscattering is dominated by suspended particulate inorganic matter. Phytoplankton backscattering is almost negligible, except in cases where the phytoplankton community is dominated by highly scattering cyanobacteria. Experiences from remote sensing campaigns and modeling shows that remote chlorophyll estimation is most effective at longer wavelengths, where the absorption of yellow substance is low. However, modeling also predicts that large uncertainties have to be expected in the estimation of chlorophyll, both from variation in the specific phytoplankton absorption and from influences of other optically active water quality parameters.</p>

Semi-analytical models for remote sensing of water quality parameters need to be parameterized with specific inherent optical properties. In this thesis, data on specific inherent optical properties of Swedish lakes and coastal waters is presented. Also, the problems of measuring in situ spectral backscattering are addressed. It is shown how measured specific inherent optical properties are used to parameterize semi-analytical bio-optical models. The models are then used to produce large synthetic data sets based on the distribution of water quality parameters, and from these data sets, band ratio or single band ratio algorithms for remote estimation of water quality parameters are constructed. A similar model was also used to calculate under water PAR from measured water quality parameters. The specific inherent optical properties of Swedish lakes and coastal waters are very similar to earlier reported data from the oceanic environment. However, different relations of the water quality parameters will affect the inherent optical properties absorption and backscattering. The absorption spectra are dominated by yellow substance with terrestrial origin. Phytoplankton absorption is low, and account in general only for about 10 % of the total absorption in regions where phytoplankton pigments are active. The spectral backscattering is dominated by suspended particulate inorganic matter. Phytoplankton backscattering is almost negligible, except in cases where the phytoplankton community is dominated by highly scattering cyanobacteria. Experiences from remote sensing campaigns and modeling shows that remote chlorophyll estimation is most effective at longer wavelengths, where the absorption of yellow substance is low. However, modeling also predicts that large uncertainties have to be expected in the estimation of chlorophyll, both from variation in the specific phytoplankton absorption and from influences of other optically active water quality parameters.

Water quality in Tampa Bay was examined using concurrent in situ and satellite remote sensing observations. Chlorophyll and suspended sediment concentrations showed large short-term variability, primarily driven by tide and wind forcing. Superimposed on these high frequency variations were recurrent phytoplankton blooms stimulated by decreases in turbidity 1-2 days after wind-induced bottom sediment resuspension events; the blooms were particularly strong if neap tides occurred after the wind events. The in situ data show that observations once per month are inadequate to sample short-term variability and that therefore the current monthly water quality surveys may have uncertainties of -50 to 200% if they are used to represent the monthly mean concentrations of chlorophyll or suspended sediment. Such uncertainties make it difficult to identify trends and interannual variability based on the in situ monitoring program. Colored dissolved organic matter (CDOM) generally showed good relationship with salinity and primarily delivered by riverine inputs but showed conservative and non-conservative mixing behaviors for the dry and wet seasons, respectively. CDOM in Old Tampa Bay (OTB), however, showed properties that were different from those in other Bay segments, and the non-conservative CDOM mixing behavior may be simply due to a three-end-member mixing scenario in which Hillsborough Bay and Middle Tampa Bay also receive water from Old Tampa Bay. A turbidity algorithm was successfully developed for application of MODIS/Aqua 250 m imagery. The MODIS turbidity images showed distinct spatial and temporal patterns related to river runoff in the upper bay and wind-induced sediment resuspension events in the middle and lower portions of the Bay. Similarly, light attenuation from SeaWiFS estimated using a new semi-analytical algorithm confirmed that water clarity was related to river runoff and to wind-induced sediment resuspension events. Wind is shown repeatedly to be another important factor controlling water quality in the Bay. The study shows that remote sensing products have the potential to be an important tool to help resource managers assess conditions in a large estuary like Tampa Bay synoptically, frequently and repeatedly.

The objective of the research reported in this thesis was to develop a technique to monitor the dynamics of sediments and nutrients entering the coastal ocean with river plumes associated with high intensity low frequency events (e.g. floods), using ocean colour remote sensing. To achieve this objective, an inverse bio-optical model was developed, based on analytical and empirical relationships between concentrations of optically significant substances and remote sensing of water-leaving radiance. The model determines concentrations of water-colouring substances such as chlorophyll, suspended sediments, and coloured dissolved organic matter, as well as the values of optical parameters using water-leaving radiances derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). To solve atmospheric correction in coastal waters, the aerosol type over clear waters is transferred to adjacent turbid water pixels. The vicinity of the Herbert River, central Great Barrier Reef zone, Australia, was used as a case study for the application of the algorithm developed. The satellite ocean colour technique was successfully validated using sea-truth measurements of water-colouring constituents acquired in the area during various seasons throughout 2002-2004. A high correlation between chlorophyll and dissolved organic matter was found in the coastal waters of the region, and when the bio-optical model was constrained to make chlorophyll a function of dissolved organic matter, the relationship between in situ and satellite-derived data was substantially improved. With reliable retrieval of the major water-colouring constituents, the technique was subsequently applied to study fluxes of particulate and dissolved organic and inorganic matter following a flood event in the Herbert River during the austral summer of 1999. Extensive field observations covering a seasonal flood in the Herbert River in February 2004 revealed high sediment and nutrient exports from the river to the adjacent coastal waters during the flood event. Due to rapid settling, the bulk of the sediment-rich influx was deposited close inshore, while the majority of nutrients exported from the river were consumed by phytoplankton in a relatively small area of the coastal ocean. With the help of ocean colour remote sensing, it was demonstrated that river-borne sediments and nutrients discharged by a typical flood in the Herbert River are mostly precipitated or consumed within the first 20 km from the coast and therefore are unlikely to reach and possibly affect the midshelf coral reefs of this section of the Great Barrier Reef lagoon.

A importância de estudos sobre a produção primária (PP) marinha é consenso devido ao seu papel no ciclo do carbono global. Técnicas rápidas e não invasivas para medição de taxas de PP foram desenvolvidas nas últimas décadas para melhorar a resolução espacial e temporal das aquisições de dados, além de suprir as desvantagens e lacunas deixadas pelos métodos clássicos que envolvem a incubação de amostras. Os objetivos deste trabalho são: (1) comparar duas técnicas mais novas, a Bio-óptica (PPabs) e a Fluorescência Ativa Variável (PPFire), com o método clássico de evolução de oxigênio pelo metabolismo da comunidade planctônica que estima a PP bruta (PPB), (2) e determinar a influência de variáveis oceanográficas e como elas podem predizer a PP no canal de São Sebastião ao longo de diferentes períodos amostrais (verões de 2014, 2016 e 2018, inverno de 2014 e primavera de 2015). A PPB variou entre 47,55 e 341,94 mg C m-3 d-1, a PPabs entre 73,7 &#177; 6,9 e 454,9 &#177; 25,8 mg C m-3 d-1 e a PPFire entre 9,0 e 57,8 mg C m-3 d-1 no verão de 2018. As relações entre os métodos foram significativas (PPB vs PPabs, p = 0,007, PPB vs PPFire, p = 0,01 e PPabs vs PPFire, p = 0,01). A partir de uma regressão linear múltipla, vimos que a PPB (p = 0,003) e PPFire (p < 0,001) foram previstas pela temperatura e pela concentração da clorofila-a, já a PPabs (p = 0,007) pelas duas variáveis adicionadas a salinidade. Esses resultados indicam que apesar dos métodos apresentarem magnitudes diferentes, informações adicionais sobre o ambiente são incorporadas por cada técnica. A PPB acrescenta informações quanto a comunidade planctônica como um todo, a PPabs sobre a composição pigmentar e de tamanhos de espécies e a PPFire sobre a fotofisiologia das células fitoplanctônicas. Quanto às condições oceanográficas, as relações com a temperatura e a salinidade indicam que os métodos são sensíveis a alteração de massas d\'água, como a Água Central do Atlântico Sul (ACAS), bem como a entrada de aporte continental por plumas de rios, que são responsáveis pela disponibilidade de luz e nutrientes que afetam a PP no canal. Concluindo, os métodos são complementares e podem variar de diferentes formas conforme a dinâmica local, no entanto, são significativamente proporcionais uns aos outros, o que indica a robustez entre as medidas das duas técnicas mais novas aqui comparadas. / There is a consensus of the importance of primary production (PP) studies due to its role on the global carbon cycle. Fast and non-invasive techniques to measure rates of PP were developed in the last few decades to improve temporal and spatial data acquisition, and to overcome disadvantages and gaps associated with classical methods using incubation of samples. The aim of this work are: (1) compare two newer techniques, Bio-optical (PPabs) and Active Variable Fluorescence (PPFire), to the classical method involving oxygen evolution by the planktonic community metabolism (PPB), and (2) determine the influence of oceanographic variables and investigate how they could predict PP in the São Sebastião channel. PPB varied between 47.55 and 341.94 mg C m-3 d-1, PPabs between 73.7 &#177; 6.9 and 454.9 &#177; 25.8 mg C m-3 d-1 and PPFire between 9.0 and 57.8 mg C m-3 d-1 in the summer of 2018. The relationships between methods were significant (PPB vs PPabs, p = 0.007, PPB vs PPFire, p = 0.01 and PPabs vs PPFire, p = 0.01). After a multiple linear regression test, we found that PPB (p = 0.003) and PPFire (p < 0.001) were predicted by temperature and chlorophyll-a concentration, however, PPabs (p = 0.007) was also predicted by salinity. These results indicate that despite the methods show different magnitudes, each one includes different information about the environment. The PPB adds overall information about the planktonic community, while the PPabs adds pigment composition and species size and the PPFire adds phytoplankton cell photophysiology. We found correlations with the different PPs and temperature and salinity indicating that the three methods are sensitive to water mass changes, as the South Atlantic Central Water (SACW) and the intrusion of river plumes in the channel, both responsible for light and nutrients availability. In conclusion, the three methods are complementary and could vary in different ways due to local dynamics. However, they are proportional to each other, showing strength to the use of the two newest techniques (PPabs and PPFire).

Submitted by STELA ROSA AMARAL GONÇALVES (stelinhaamaral@hotmail.com) on 2016-08-12T03:20:24Z No. of bitstreams: 1 Dissertação_final_imai_v3.pdf: 3555316 bytes, checksum: b4386413378a1a29e513286831a880a2 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-08-15T14:30:47Z (GMT) No. of bitstreams: 1 goncalves_sra_me_prud.pdf: 3555316 bytes, checksum: b4386413378a1a29e513286831a880a2 (MD5) / Made available in DSpace on 2016-08-15T14:30:47Z (GMT). No. of bitstreams: 1 goncalves_sra_me_prud.pdf: 3555316 bytes, checksum: b4386413378a1a29e513286831a880a2 (MD5) Previous issue date: 2016-07-08 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Informações quantitativas e qualitativas de sistemas aquáticos podem ser obtidas por meio de dados de sensoriamento remoto. Nesses sistemas, a porção fotoativa do carbono orgânico dissolvido (COD), pode apresentar correlação com o Carbono Orgânico Dissolvido Colorido (CDOM) que é responsável pela alteração da cor da água e consequentemente pode alterar processos de fotossíntese e fotodegradação. Sendo assim o presente trabalho teve como objetivo avaliar a variabilidade espacial das concentrações de CDOM de uma série temporal, de imagens do sensor Operational Land Imager OLI a bordo do satélite Landsat 8, ao longo de um ano no reservatório de Barra Bonita/SP, sendo este o primeiro de uma série de reservatórios em cascata do Rio Tietê, no estado de São Paulo. Foram encontradas correlações entre a concentração laboratorial do COD e o CDOM para o campo de maio o que motivou a modelagem. Foram ajustados modelos inversos, de banda simples e de razão de bandas, para predição de CDOM com dados de dois trabalhos de campo realizados no ano de 2014, sendo o primeiro no mês de maio e o segundo no mês de outubro. Além disso, foram testados modelos encontrados na literatura, também com os dados levantados em campo, para estimativa de CDOM. Os resultados obtidos mostraram que, para os modelos bio-ópticos, de banda simples e razão de bandas, não há diferenças estatistica. O melhor modelo foi selecionado baseado em análise de erro, depois da aplicação dos modelos na imagem OLI coincidente com o trabalho de campo. Uma série de imagens do sensor OLI no período de um ano foi adotada tendo em vista da disponibilidade dos dados gratuitos e resolução radiométrica de 12 bits. A série temporal de imagens do sensor OLI, após ser processada para minimizar os efeitos atmosféricos, permitiu mostrar a dinâmica de CDOM no reservatório em conjunto com dados de precipitação e temperatura do Instituto Nacional de Meteorologia (INMET). Foi possível observar que o reservatório apresenta uma tendência de valores maiores de CDOM após aportes de nutrientes causados por eventos de precipitação. A temperatura apesar de influenciar na velocidade da reação de degradação não foi o fator principal para a variação da concentração de CDOM. O ajuste e avaliação de modelos foi essencial para escolha do modelo mais adequado a realidade local e sazonal do escopo do trabalho. Além disso o modelo aplicado pode contribuir para o cálculo do balanço de carbono, como também em outros estudos que necessitem dessa informação. / Quantitative and qualitative information about aquatic systems can be obtained by using the Remote Sensing techniques. In these aquatic systems, the photoactive portion of Dissolved Organic Carbon (DOC) can be correlated with the Colored Dissolved Organic Matter (CDOM), responsible for the water color alteration and can modify the photosynthesis and photodegradation process. In this sense, this project aimed to evaluate the spatial variability of CDOM concentrations in a one-year temporal analysis from images acquired by the Operational Land Imager OLI sensor onboard the satellite Landsat 8. The study site is the reservoir located in Barra Bonita, State of São Paulo, which is the first in a series of cascading reservoirs from Tietê River in State of São Paulo. The results showed correlations between the COD and CDOM concentrations for the data acquired in May 2014, motivating the CDOM modeling. Inverse models were adjusted, by using simple spectral band and band ratio, for CDOM prediction using data acquired from two field works carried out in 2014, the first in May and the second in October. Moreover, the models found in related literature were tested, also with the data collected in field, for the CDOM estimative. The obtained results showed that for the bio-optical models, from simple spectral band and band ratio, there is no statistic differences. The model who best fitted to the CDOM estimation was selected based on error analysis after their application in OLI images, which coincided with the field work. One year OLI images were used considering their availability, without fees, and their radiometric resolution of 12 bits. This temporal series, after being processed to attenuate the atmospheric effects, allowed showing the CDOM dynamics in the Barra Bonita reservoir combined with temperature and precipitation data from the Instituto Nacional de Metereologia (INMET). It was possible observe that the reservoir shows a bias of higher values of CDOM after nutrients intakes caused by precipitation. The temperature, despite of its influence on degradation reaction velocity, was not the principal factor for the CDOM concentration variation. Finally, the adjustment and models validation was essential for the correct choice of the model which better represents the local and season reality. In addition, the applied model can contribute for the carbon balance calculation, as well for other researches, which use this information.

Submitted by Ana Carolina Campos Gomes (carol.campos01@hotmail.com) on 2018-04-20T17:35:54Z No. of bitstreams: 1 AnaCarolina.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) / Approved for entry into archive by Claudia Adriana Spindola null (claudia@fct.unesp.br) on 2018-04-20T19:06:20Z (GMT) No. of bitstreams: 1 gomes_acc_me_prud.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) / Made available in DSpace on 2018-04-20T19:06:20Z (GMT). No. of bitstreams: 1 gomes_acc_me_prud.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) Previous issue date: 2018-03-23 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / O presente trabalho teve como objetivo estimar as profundidades da zona eufótica (Zeu) e do disco de Secchi (ZSD) a partir do coeficiente de atenuação da luz (kd) utilizando dados do sensor Operational Land Imager (OLI)/Landsat-8 no reservatório de Bariri. Como importantes parâmetros de medida da claridade da água, kd, Zeu e ZSD são afetados pelas substâncias opticamente significativas (SOS). A caracterização óptica do reservatório foi realizada a partir de duas campanhas de campo realizadas no período seco, aqui nomeadas como BAR1 (agosto/2016) e BAR2 (junho/2017), que contaram com análises das propriedades ópticas inerentes (POIs), das SOS e da coleta de dados radiométricos para o cálculo da reflectância de sensoriamento remoto (Rsr). A localização do reservatório de Bariri como o segundo do Sistema de Reservatórios em Cascata (SRC) do Rio Tietê promove a heterogeneidade dos seus níveis de eutrofização na direção montante-jusante além de caracterizá-lo como altamente produtivo. As campanhas de campo foram marcadas por uma significativa diferença nos valores de concentração de clorofila-a ([Chl-a]) que apresentou variação média entre 7,99 e 119,76 μg L-1 com os maiores valores em BAR1, com decréscimo das SOS em BAR2 em relação a BAR1 e predomínio de material particulado orgânico (MPO) nas duas campanhas de campo; a turbidez variou entre 5,72 e 16,60 NTU. A absorção por matéria orgânica colorida dissolvida (aCDOM) foi predominante nas duas campanhas de campo, sendo mais expressiva em BAR2. Para as estimativas de kd, nove modelos empíricos e três modelos semi-analíticos baseados em dados radiométricos como razões entre as bandas azul/verde e azul/vermelho do sensor OLI/Landsat-8 e baseados em [Chl-a] foram avaliados. Considerando a propriedade óptica aparente (POA) do kd, um modelo semi-analítico baseado em POIs e na distribuição angular da luz apresentou os menores erros (erro médio percentual absoluto – MAPE) de 40% em relação aos modelos empíricos de [Chl-a] com 60% e de 80% para os modelos empíricos baseados em razões de bandas. A partir das estimativas de kd, modelos de estimativa de Zeu e ZSD foram avaliados. Para as estimativas de Zeu, cinco modelos empíricos, baseados na relação entre o coeficiente de atenuação da luz da radiação fotossinteticamente ativa [kd(PAR)] e de kd em 490 nm [kd(490)], e um modelo semi-analítico, baseado na equação de transferência radiativa, foram considerados; para as estimativas de ZSD, um modelo semi-analítico foi testado. Os resultados obtidos foram melhores para um modelo empírico (erro percentual absoluto – ε) de Zeu com 16% em relação ao modelo semi-analítico (ε 30%) e os erros nas estimativas de ZSD foram de 57%. Os erros nas estimativas de kd revelaram que a acurácia dos modelos empíricos foi comprometida devido à influência por CDOM e que o modelo semi-analítico, por considerar a natureza óptica de kd como uma POA, apresentou os melhores resultados. As estimativas de ZSD também foram afetadas pelas características ópticas de Bariri, não apresentando correlação com a matéria orgânica em BAR2, marcado pelo decréscimo de [Chl-a] e aumento dos valores de aCDOM. Zeu mostrou melhores resultados a partir de um modelo empírico calibrado com dados ópticos semelhantes aos do reservatório de Bariri em comparação ao modelo semi-analítico, desenvolvido para abranger as variações bio-ópticas sazonais e regionais. kd, Zeu e ZSD foram espacializados a partir de imagens do sensor OLI/Landsat-8 permitindo a avaliação espaçotemporal desses parâmetros que apresentaram um padrão sazonal quando analisados em relação aos dados de precipitação. kd apresentou variação entre 0,89 e 5,60 m-1 para o período analisado (2016) e Zeu e ZSD apresentaram variação entre 0,30 e 7,60 m e entre 0,32 e 2,95 m, respectivamente, para o período de 2014-2016. Pode-se concluir então, que apesar das estimativas de kd, Zeu e ZSD terem sido afetadas pela influência de CDOM no reservatório de Bariri, o esquema semi-analítico foi capaz de estimar kd com menor erro e permitiu as estimativas de Zeu e ZSD. / The objective of this present work was estimate the euphotic zone (Zeu) and Secchi disk (ZSD) depths from the light attenuation coefficient (kd) using the Operational Land Imager (OLI)/Landsat-8 data in Bariri reservoir. The kd, Zeu and ZSD are important water clarity parameters and are influenced by the optically significant substances (OSS). The optical characterization was carried out with data collected in two field campaigns in the dry period, here called BAR1 (august/2016) and BAR2 (june/2017), that included analysis of the inherent optical properties (IOPs), of the OSS and radiometric data to calculate the remote sensing reflectance (Rrs). The location of Bariri reservoir as the second of the Cascading Reservoir System (CRS) of Tietê River promotes the heterogeneity of the eutrophication levels from upstream to downstream besides characterizes the reservoir as highly productive. The field campaigns presented a significant difference in chlorophyll-a concentrations ([Chl-a]) with mean variation between 7.99 and 119.76 μg L-1 with the highest values in BAR1, with reduce of the OSS in BAR2 in relation to BAR1 and predominance of organic particulate matter (OPM) in both field campaigns and variation in turbidity from 5.72 to 16.60 NTU. The absorption of chromophoric dissolved organic matter (CDOM) was dominant in both field campaigns and more expressive in BAR2. For the kd estimates, nine empirical models and three semi-analytical models based on radiometric data such as ratios of blue-green and blue-red bands of (OLI)/Landsat 8 sensor and based on [Chl-a] were evaluated. Considering the apparent optical property (AOP) of kd, a semi-analytical model based on IOPs and the light angular distribution presented the lowest errors (mean absolute percentage error – MAPE) of 40% in relation to the empirical models of [Chl-a] with 60% and of 80% for the empirical models based on the band ratios. Through the kd estimates, models to derive Zeu and ZSD were evaluated. For the Zeu estimates, five empirical models were considered based on the relation between the attenuation coefficient of the photosynthetically active radiation [kd(PAR)] and the kd at 490 nm [kd(490)], and one semi-analytical model, based on the radiative transfer equation; for the ZSD estimates, one semi-analytical model was tested. The empirical model of Zeu showed the better results with the (unbiased absolute percentage error – ε) 16% in relation to the semi-analytical model (ε 30%) and the estimates errors of ZSD were 57%. The errors in kd estimates revealed that the accuracy of the empirical models was affected by the CDOM influence in Bariri reservoir and the semi-analytical model presented a better performance when considering the optical nature of kd as an AOP. The ZSD estimates were also affected by the optical characteristics of Bariri with no correlation to the SPM in BAR2, where the [Chl-a] decreased and the aCDOM increased. Zeu showed better results from an empirical model calibrated with similar optical data to Bariri reservoir in relation to the semi-analytical model developed to be applied in a wide range of bio-optical seasonal and regional variations. The kd, Zeu and ZSD were spatially distributed through OLI/Landsat-8 images allowing the temporal-spatial assessment of theses parameters, which presented a seasonal pattern when analyzed in relation to rainfall data. kd presented variation from 0.89 to 5.60 m-1 to the analyzed period (2016) and Zeu and ZSD presented variations between 0.30 and 7.60 m and between 0.32 and 2.95 m, respectively, for 2014-2016 period. It can be concluded, therefore, that despite of the CDOM have affected the kd, Zeu and ZSD retrievals in Bariri reservoir, the semi-analytical scheme was able to estimate kd with lowest error and enable the Zeu and ZSD estimates. / CNPq: 131737/2016-3 / FAPESP: 2012/19821-1 e 2015/21586-9