Dissertations / Theses on the topic 'Bio-optical model'

Previous research in the US Virgin Islands (USVI) has demonstrated that land-based sources of pollution associated with watershed development and climate change are local and global factors causing coral reef degradation. A good indicator that can be used to assess stress on these environments is the water quality. Conventional assessment methods based on in situ measurements are timely and costly. Satellite remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic nature of water quality parameters by applying bio-optical models. Chlorophyll-a, suspended sediments (TSM), and colored-dissolved organic matter are color-producing agents (CPAs) that define the water quality and can be measured remotely. However, the interference of multiple optically active constituents that characterize the water column as well as reflectance from the bottom poses a challenge in shallow coastal environments in USVI. In this study, field and laboratory based data were collected from sites on St. Thomas and St. John to characterize the CPAs and bottom reflectance of substrates. Results indicate that the optical properties of these waters are a function of multiple CPAs with chlorophyll-a values ranging from 0.10 to 2.35 ?g/L and TSM values from 8.97 to 15.7 mg/L. These data were combined with in situ hyperspectral radiometric and Landsat OLI satellite data to develop a regionally tiered model that can predict CPA concentrations using traditional band ratio and multivariate approaches. Band ratio models for the hyperspectral dataset (R² = 0.35; RMSE = 0.10 ?g/L) and Landsat OLI dataset (R² = 0.35; RMSE = 0.12 ?g/L) indicated promising accuracy. However, a stronger model was developed using a multivariate, partial least squares regression to identify wavelengths that are more sensitive to chlorophyll-a (R² = 0.62, RMSE = 0.08 ?g/L) and TSM (R² = 0.55). This approach takes advantage of the full spectrum of hyperspectral data, thus providing a more robust predictive model. Models developed in this study will significantly improve near-real time and long-term water quality monitoring in USVI and will provide insight to factors contributing to coral reef decline.

Orientador: Nilton Nobuhiro Imai
Abstract: The acquisition of data using Remote Sensing and in-situ sampling allows several data sources to be integrated for the analysis and observations of environmental characteristics and may require computational methods to support the data processing, exploration and analysis. The need to integrate data from different sources is highlighted in studies of dynamic and complex environments that frequently change, such as hydroelectric reservoirs. Reservoirs are artificial ecosystems, which influence directly the regional characteristics, mainly because of their multipurpose use. The interactions of the electromagnetic energy with the optically active components occur along the entire water column, so that the behavior of the light field reflects the changes applied along the entire euphotic zone. However, the values taken from images are used accordingly to a plane and associated with the respective point or area of surface. The calibration of bio-optical models considering only the surface sampling data can not deliver fully effective results because the electromagnetic radiation interacts with the components located along the water column and the response captured by the sensors does not only represent the value associated with the surface. Considering this scenario, this work proposes an investigation on the influence of the vertical distribution of the optical properties along the water column, in order to contemplate records about the interaction in different levels of depth, b... (Complete abstract click electronic access below)
Resumo: A aquisição de dados por meio da combinação de Sensoriamento Remoto e amostragens in-situ permite que várias fontes de dados sejam integradas para a análise e observação de características do alvo de interesse e pode exigir métodos computacionais para apoiar o processamento, exploração e análise de dados. A necessidade de integrar dados de diferentes fontes é destacada em estudos de ambientes dinâmicos e complexos que se alteram frequentemente, como os reservatórios hidrelétricos. Os reservatórios são ecossistemas artificiais, que influenciam diretamente nas características regionais, principalmente devido ao seu uso múltiplo uso. As interações da energia eletromagnética com os componentes opticamente ativos ocorrem ao longo de toda a coluna d’água, de modo que o comportamento do campo de luz reflete as mudanças aplicadas ao longo da zona eufótica. No entanto, as grandezas registradas nas imagens são usados de acordo com o plano e limitadas ao respectivo ponto ou área da superfície. A calibração de modelos bio-ópticos, considerando apenas os dados de amostragem da superfície, pode não fornecer resultados totalmente eficazes, porque a radiação eletromagnética interage com os componentes localizados ao longo da coluna de água e, consequentemente, a resposta capturada pelos sensores não representa apenas o valor associado à superfície. Este trabalho propõe uma investigação sobre a influência da distribuição vertical das propriedades ópticas ao longo da coluna d’água, a fim de co... (Resumo completo, clicar acesso eletrônico abaixo)
Doutor

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.

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 Fernanda Sayuri Yoshino Watanabe null (fernandasyw@yahoo.com.br) on 2016-04-28T12:54:41Z No. of bitstreams: 1 Watanabe_tese.pdf: 3879331 bytes, checksum: f393ffe1bbc36d214f1bed6945d9dedd (MD5)
Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-05-02T12:36:43Z (GMT) No. of bitstreams: 1 watanabe_fsy_dr_prud.pdf: 3879331 bytes, checksum: f393ffe1bbc36d214f1bed6945d9dedd (MD5)
Made available in DSpace on 2016-05-02T12:36:43Z (GMT). No. of bitstreams: 1 watanabe_fsy_dr_prud.pdf: 3879331 bytes, checksum: f393ffe1bbc36d214f1bed6945d9dedd (MD5) Previous issue date: 2016-03-15
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
The aim of this research was to parameterize and calibrate models based on remote sensing data in order to estimate accurately the chlorophyll-a concentration, [Chl-a], in a tropical eutrophic reservoir. Firstly, a bio-optical characterization was conducted to identify particularities in the study area. Thus, existing empirical models and quasi-analytical algorithms (QAA) were tested and, after, parameterized and calibrated for the investigated environment. Such models derive [Chl-a] and inherent optical properties (IOPs), respectively, from remote sensing reflectance (Rrs). This research was developed in the Barra Bonita hydroelectric reservoir (BBHR), lies in Tietê River (Brazil). Reservoirs are artificial environments which change severely the hydrodynamic of rivers and the biogeochemical balance of aquatic systems. Such alterations can lead to unique bio-optical status and, consequently, models developed for rivers and lakes are not suitable to explain the processes which happen in reservoirs. The trophic state is an important water quality parameter and can be determined based on Chl-a concentration, photosynthetically active pigment present in all the phytoplankton species and detected by remote sensors. Therefore, the use of orbital and aerial images is a viable alternative to monitoring of trophic state in these environments. Results showed that bio-optical status in BBHR is remarkable different compared to other aquatic systems found in literature, corroborated by inaccurate performance of models proposed to other areas. The parameterization and calibration proposed in this research estimated accurately Chl-a concentration, mainly, adopting absorption coefficients derived by QAA. The fitted models can be used in mapping trophic state and frequent monitoring of water quality in BBHR by environmental agency and hydroelectric plant managers. In addition, it is likely that the parameters proposed in this research are suitable for other inland waters.
O objetivo do presente trabalho foi parametrizar e calibrar modelos baseado em dados de sensoriamento remoto para estimar acuradamente a concentração da clorofila-a, [Chl-a], em um reservatório tropical e eutrofizado. Primeiramente, uma caracterização bio-óptica da área estudo foi realizada para identificar particularidades do ambiente. Então, modelos empíricos e algoritmos quase-analíticos (QAA) existentes foram testados e, posteriormente parametrizados e calibrados para o ambiente investigado. Tais modelos derivam a [Chl-a] e propriedades ópticas inerentes (POIs), respectivamente, a partir da reflectância de sensoriamento remoto (Rrs). Esta pesquisa foi desenvolvida no reservatório da hidroelétrica de Barra Bonita (RHBB), localizado no Rio Tietê (Brasil). Reservatórios são ambientes artificiais que modificam severamente a hidrodinâmica de rios e o equilíbrio biogeoquímico do ecossistema aquático. Tais alterações podem proporcionar características bio-ópticas únicas ao ambiente e modelos para rios e lagos podem não ser adequados para explicar os processos que ocorrem em reservatórios. O grau de eutrofização é um importante parâmetro de qualidade da água e pode ser determinado com base na [Chl-a], pigmento fotossiteticamente ativo presente em todas as espécies de fitoplâncton, detectado por sensores remotos. Portanto, o uso de imagens orbitais e aerotransportadas é uma alternativa viável para o monitoramento do estado trófico desses ambientes. Resultados mostram que as características bio-ópticas em RHBB são consideravelmente diferentes de outros ambientes pesquisados na literatura, corroborado com desempenho não acurado de modelos propostos para outros ambientes. A parametrização e calibração propostas nesta pesquisa estimaram acuradamente a [Chl-a], principalmente, adotando os coeficientes de absorção derivados do QAA. Os modelos ajustados podem ser utilizados no mapeamento do estado trófico e monitoramento periódico da qualidade da água em RHBB por agências ambientes e gestores de usinas hidroelétricas. Além disso, é provável que os parâmetros propostos nesta pesquisa sejam adequados para outras águas continentais.
CNPq: 200157/2015-9

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.

Electronic noses combine an array of cross-selective gas sensors with a pattern recognition engine to identify odors. Pattern recognition of multivariate gas sensor response is usually performed using existing statistical and chemometric techniques. An alternative solution involves developing novel algorithms inspired by information processing in the biological olfactory system. The objective of this dissertation is to develop a neuromorphic architecture for pattern recognition for a chemosensor array inspired by key signal processing mechanisms in the olfactory system. Our approach can be summarized as follows. First, a high-dimensional odor signal is generated from a chemical sensor array. Three approaches have been proposed to generate this combinatorial and high dimensional odor signal: temperature-modulation of a metal-oxide chemoresistor, a large population of optical microbead sensors, and infrared spectroscopy. The resulting high-dimensional odor signals are subject to dimensionality reduction using a self-organizing model of chemotopic convergence. This convergence transforms the initial combinatorial high-dimensional code into an organized spatial pattern (i.e., an odor image), which decouples odor identity from intensity. Two lateral inhibitory circuits subsequently process the highly overlapping odor images obtained after convergence. The first shunting lateral inhibition circuits perform gain control enabling identification of the odorant across a wide range of concentration. This shunting lateral inhibition is followed by an additive lateral inhibition circuit with center-surround connections. These circuits improve contrast between odor images leading to more sparse and orthogonal patterns than the one available at the input. The sharpened odor image is stored in a neurodynamic model of a cortex. Finally, anti-Hebbian/ Hebbian inhibitory feedback from the cortical circuits to the contrast enhancement circuits performs mixture segmentation and weaker odor/background suppression, respectively. We validate the models using experimental datasets and show our results are consistent with recent neurobiological findings.

Afin d’améliorer l’efficacité des traitements des pathologies articulaires, en tenant compte de leur complexité et de leur ampleur, des études récentes ont mis en évidence le rôle des assemblages lipidiques associés à la structure discontinue du fluide synovial dans le contrôle du fonctionnement tribologique articulaire. Ceci à conduit à la mise au point d’un modèle tribologique ex vivo (thèse AM Sfarghiu, 2006), proposant un « motif élémentaire » de la biolubrification articulaire, constitué de l’empilement d’interfaces phospholipidiques et de couches aqueuses. En utilisant ce modèle, l’objectif de ce travail a été d’étudier l’évolution des interfaces phospholipidiques du fluide synovial en présence de pathologies. Pour ce faire, une méthodologie nano-bio-tribologique alliant des analyses biochimiques, physicochimiques, nano-mécaniques et tribologiques a été utilisée. Les résultats de ces analyses montrent : l’influence de la faible rugosité des surfaces frottantes caractérisant les stades précoces des pathologies et celle des propriétés des interfaces phospholipidiques (liées à la variation de leur composition) sur la résistance mécanique, l’évolution au cours du frottement et la dégradation in situ des assemblages lipidiques des fluides synoviaux pathologiques. Le comportement des assemblages lipidiques est accentué par l’action des enzymes associées aux pathologies. Par conséquent, le fonctionnement articulaire dépend de la résistance mécanique des interfaces phospholipidiques et pour obtenir des coefficients de frottement très bas, l’accommodation de vitesse doit s’effectuer au niveau des couches d’hydratation qui entourent les ions présents dans la couche aqueuse. Ces résultats permettront de comprendre à court terme l’évolution des interfaces phospholipidiques dans les pathologies articulaires et, à plus long terme le bon enchaînement cause/conséquence responsable d’une pathologie articulaire afin de développer des traitements plus efficaces, ciblés et non prothétiques
In order to improve the effectiveness of joint diseases’ treatments, given their complexity and magnitude, recent studies have highlighted the role of lipid assemblies associated with the discontinuous structure of the synovial fluid (SF) in the tribological performance of joint operation. Thus, an ex vivo tribological model (AM Sfarghiu, PhD thesis, 2006) providing a "basic pattern" for joint biolubrification was developed. It consists of the stack of phospholipidic interfaces and aqueous layers. Using this model, the objective of this work was to study the evolution of phospholipidic interfaces of SF within pathological state. Therefore, a nano-bio-tribological methodology combining biochemical, physicochemical, nano-mechanical and tribological analysis was used. The results of these analyses show: the influence of even small rubbing surfaces’ roughness characteristics of early stage illness and that of phospholipidic interfaces’ properties (related to their composition change) on the mechanical strength, changes in friction and in situ degradation of lipidic assemblies of pathological SF. The tribological operation is highlighted by enzymes’ associated with diseases. Thus, joint operation depends on the mechanical strength of phospholipidic interfaces and to obtain very low friction coefficients, velocity accommodation must be done at the level of hydration layers surrounding ions in the aqueous solution. These results would therefore allow better understanding of the evolution of phospholipidic interfaces in joint diseases and of the proper cause/consequence sequence responsible for a joint disease in order to develop more effective, targeted and non prosthetic treatments

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

L'objectif était d'utiliser le cytomètre en flux (Cytosense, CytoBuoy b.v., NL) afin de comprendre l'influence des paramètres structurels et morphologiques des cellules phytoplanctoniques sur la rétrodiffusion. Nous avons analysé les propriétés optiques des cellules sur différentes phases de croissance. Une expérience en microcosme a été réalisée sur deux espèces (Thalassiosira pseudonana et Chlamydomonas Concordia) durant 20 jours. Les efficacités de diffusion avant et de côté de Thalassiosira pseudonana étaient respectivement 2,2 et 1,6 fois plus importantes que celles de Chlamydomonas Concordia. Les variations intra- et inter-espèces ont été expliquées par des simulations théoriques et des mesures in situ (biogéochimiques et observations au microscope à balayage électronique). Les mesures in situ ont permis d'obtenur des informations sur la structure des cellules (e.g. épaisseur de la frustule). L'efficacité de diffusion avant est impactée par l'agrégation et la taille des cellules. L'indice de réfraction réel du chloroplaste est un paramètre clé pouvant expliquer les variations de l'efficacité de côté. À l'avenir, nous recommandons d'utiliser un modèle à deux couches (cytoplasmes-chloroplaste) pour simuler les propriétés optiques des cellules phytoplanctoniques. Une analyse de la relation entre la concentration en carbone organique particulaire (POC) et le coefficient de rétrodiffusion a été effectuée. Des relations linéaires fortes ont été observées uniquement durant la phase exponentielle. Une reconstruction du coefficient de rétrodiffusion a permis de mettre en évidence que le POC était d'origine phytoplanctonique pour une espèce et d'origine bactérienne pour l'autre
The objective was to use the flow cytometer (Cytosense, CityBuoy B.V., NL) to understand the influence of structural and morphological parameters of phytoplankton cells on the backscattering. We have analyzed the optical properties of the cells over different growth phases. A microcosm experiment was performed on two species (Thalassiosira pseudonana and Chlamydomonas Concordia) during 20 days. The forward and sideward efficiencies of Thalassiosira pseudonana were, respectively, 2.2 and 1.6 times higher than the efficiencies Chlamydomonas Concordia. The inter- and intra-species variations were explained by theoretical simulations and in situ measurements (biogeochemical and observations from scanning electron microscope). In situ measurements were used to obtain informations about the cell structure (e.g. thickness of the frustule). The forward efficiency was impacted by the aggregation and the cell size. The real refractive index of the chloroplast is a key parameter that could explain variations of the sideward efficiency. In the future, we recommend to use a two-layered sphere model (cytoplasm-chloroplast) to simulate the optical properties of phytoplankton cells. An analysis of the relationship between the particulate organic carbon concentration (POC) and the backscattering coefficient was performed. Strong linear relationships were observed only during the exponential phase. A reconstruction of the backscattering coefficient permitted to highlight that the POC was from phytoplankton cells origin for a species and bacterial origin for the other one

Submitted by SARAH CRISTINA ARAUJO MARTINS null (sarahca.martins@gmail.com) on 2017-08-27T12:54:53Z No. of bitstreams: 1 Dissertacao_MartinsSarah.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5)
Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-08-29T17:18:44Z (GMT) No. of bitstreams: 1 martins_sca_me_prud.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5)
Made available in DSpace on 2017-08-29T17:18:44Z (GMT). No. of bitstreams: 1 martins_sca_me_prud.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5) Previous issue date: 2017-08-03
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
A matéria orgânica dissolvida (DOM) é a componente da água que pode ser usada como indicativo de sua qualidade, pois possui duas fontes: uma alóctone, relacionada com descargas de material terrestre, estando vinculada aos ácidos húmicos, e outra autóctone, associada às descargas fluviais ou produção própria do corpo hídrico estudado, estando relacionada aos ácidos fúlvicos. A matéria orgânica dissolvida colorida (CDOM) é a fração colorida da DOM, que pode ser usada como proxy para a observação desta última em águas interiores. O reservatório hidrelétrico de Funil (FHR) foi o corpo hídrico escolhido como área de estudo deste trabalho. Neste contexto, o objetivo geral desta pesquisa foi identificar e avaliar as mudanças no coeficiente de absorção da CDOM (aCDOM) na superfície da água ao longo do tempo (1995 – 2010), bem como entender a sua relação com mudanças no uso e cobertura da terra (LULC) na bacia de contribuição do FHR. Para alcançar tal objetivo foram realizados: (i) o mapeamento histórico de LULC (1995 – 2010, com 5 anos de intervalo) para detecção de mudanças; (ii) o estudo de um conjunto de modelos bio-ópticos baseados na literatura, bem como de um novo modelo empírico desenvolvido para estimar aCDOM via reflectância simulada (Rrs_simulated) para o sensor Thematic Mapper (TM); (iii) a distribuição espaço-temporal do aCDOM por meio da aplicação de um modelo bio-óptico em imagens TM/Landsat-5 de 1995 a 2010, e (iv) a análise das fontes possíveis de CDOM/DOM , assim como do comportamento/distribuição do aCDOM no FHR ao longo do tempo. Assim, o primeiro estudo desenvolvido nesta pesquisa foi o da parametrização do algoritmo maquinas de vetores de suporte (SVM) de acordo com as características da área de estudo para classificação supervisionada de LULC na bacia de contribuição do FHR. A detecção de mudança da classificação obtida para LULC demonstrou que a parametrização proposta para o SVM tornou o algoritmo capaz de diferenciar classes grandes e contínuas, classes estreitas e alongadas, além de áreas não contínuas e pequenas localizadas dentro de outra classe maior. A classificação obtida para o SVM apresentou boa avaliação estatística, com acurácia geral entre 86% e 96% para toda a série temporal, acurácia do produtor de 90%, acurácia do usuário maior do que 86% e índice Kappa entre 86% e 91%. Ainda, foi observado que o LULC desenvolvido na área de estudo se manteve relativamente estável ao longo da série histórica analisada. O segundo estudo realizado proporcionou o desenvolvimento de um modelo empírico em um comprimento de onda (485 nm) e uma razão de bandas (B4/B1) alternativos para estimativa de aCDOM via Rra_simulated para o TM/Landsat-5 (RMSE = 7%, Nash = 0.91). Este modelo também pôde identificar mesmo pequenas variações nos valores de reflectância via dados orbitais, assim como pode diferenciar variações sutis no aCDOM. Ainda, foram identificados dois padrões de comportamento da CDOM para o FHR: um associado ao LULC e à ocorrência de chuva/lixiviação, bem como outro relacionado à Clorofila-a (Chl-a) em situações de floração de algas. Os referidos estudos que compõe esta pesquisa foram padronizados como artigos científicos para a confecção deste documento. O primeiro estudo, sobre a parametrização do SVM, foi publicado na revista Modelling Earth Systems Environment – Springer (DOI 10.1007/s40808-016-0190-y). O segundo estudo, sobre a distribuição histórica do aCDOM está na etapa de revisão para futura submissão.
The dissolved organic matter (DOM) is a water compound related to water quality, since it has two sources: one allochthonous, related to terrestrial discharges that can be linked to humic acids, and another autochthonous, associated with river input and itself production, so related to or fulvic acids. The colored dissolved organic carbon (CDOM) is the colored fraction of DOM that could be used as a proxy for its occurrence in inland waters. The Funil hydroelectric reservoir (FHR) was chosen as the study site for this work. In this context, the general aim of this research was to identify and to evaluate the changes in CDOM absorption coefficient (aCDOM) at the water surface over time (1995 – 2010), and to understand its relationship with land cover land use (LULC) changes in FHR watershed. For match this goal, (i) a LULC historical mapping (1995 – 2010, with 5 years of interval) was made to change detection, (ii) a bio-optical model set and a new model were studied in order to estimate aCDOM from simulated reflectance (Rrs_simulated) for Thematic Mapper (TM) sensor, (iii) a aCDOM spatial and temporal distribution was obtained by applying a bio-optical model in TM/Landsat-5 imagery from 1995 to 2010, and (iv) the possible CDOM/DOM sources in FHR were found, as well aCDOM historical behavior/distribution over time was analysed. Thus, the first study was the support vector machine algorithm (SVM) parameterization according to study area characteristics to LULC supervised classification in FHR watershed. The obtained LULC change detection analysis demonstrates that the proposed SVM parameterization made the algorithm able to differentiate large and continuous classes, lengthy and thin areas, and non-continuous small areas located inside wide classes. The obtained classification had great statistics with overall accuracy among 86% and 98% over the time series, the producer accuracy of 90%, the user accuracy higher than 86%, and the Kappa statistics ranged from 86% to 91%. In addition, no significant changes in LULC were identified in the study site over all time series. The second study provides a bio-optical model at alternatives wavelength (485 nm) and a band ratio (B4/B1) for aCDOM estimation using simulated Rrs for TM/Landsat-5 (RMSE = 7%, Nash = 0.91). This model could identify even small variations in reflectance values from orbital data, as well as differentiate even slight alterations in aCDOM. Two significantly different aCDOM behaviors were also identified for FHR: one associated with LULC and rainfall/runoff occurrence, and other correlated to Chlorophyll-a high concentrations (Chl-a) in algal blooms situations. The referred studies that compose this research ware standardized as academic articles in this document. The first study, about SVM parameterization, was published yet in Modeling Earth Systems Environment – Springer (DOI 10.1007/s40808-016-0190-y). The second study, about aCDOM historical distribution is in the revision step to future submission.

Indiana University-Purdue University Indianapolis (IUPUI)
Cyanobacterial blooms are currently one of the most important issues faced by environmental agencies, water authorities and public health organizations. Remote sensing provides an advanced approach to monitor cyanobacteria by detecting and quantifying chlorophyll-a (Chl-a) and phycocaynin (PC). In this thesis, an analytical bio-optical model, more typically applied to ocean waters, was modified to accommodate the complexity of inland waters. The newly developed models work well to estimate inherent optical properties, including absorption and backscattering coefficients, in eight different study sites distributed around the globe. Based on derived absorption coefficients, Chl-a and PC concentrations were accurately retrieved for data sets collected annually from 2006 to 2010, and the estimation accuracy exceeded that of currently used algorithms. An important advantage of the model is that low concentrations of Chl-a and PC can be predicted more accurately, enabling early warning of cyanobacterial blooms. In addition, the results also indicated good spatial and temporal transferability of the algorithms, since no specific calibration procedures were required for data sets collected in a different sites and seasons. The compatibility of the newly developed algorithm with MERIS spectra provides the possibility for routine surveillance of cyanobacterial growth in inland waters.

博士
國立成功大學
環境工程學系碩博士班
96
Nutrient overenrichment (eutrophication) is the major cause of decline in overall water qualities of lakes and reservoirs. Since the watershed nonpoint sources (NPS) pollution is the primary source of nutrient and sediment loads, the study of the linkage between NPS pollution and lake/reservoir water quality is essential and of importance. With an intention to perform better assessments of the linkage, this study was divided into two parts: for a better estimation of NPS loads, collecting representative data and using appropriate models; and for a better evaluation of the water status, mapping the water quality parameters using remote sensing (RS) techniques. This new approach was carried out at Tsengwen Reservoir (TWR), the largest artificial freshwater source in Taiwan. In the first part of this study, two sampling site in the TWR watershed, Tapu Dam and Takubuyan Dam, were selected to estimate the NPS loads, which represents the NPS loads from the entire TWR watershed and an undistributed forest watershed, respectively. The flow rates were measured with weirs and samples taken for water quality analysis in both non-rainy and rainy days for 2 years (2002 and 2003). The subroutine of the Hydrological Simulation Program - FORTRAN (HSPF) was used to simulate runoff for additional 3 years (2000, 2001 and 2004). Total annual loads of various water quality parameters were then estimated by a regression model. The results indicate that most of the parameter concentrations in both sites are higher during the rainy days. In Takubuyan Dam, the values of parameter concentrations and loads are typically higher as compared to data from other undisturbed forest areas. The fluctuation of annual load from TWR watershed is significant. For example, in Takubuyan Dam, six major events of the entire year, for which the total duration is merely 6.4 days, contribute 42% of the annual precipitation and at least 40% of the annual NPS loads. In the second part of this study, two approaches had been developed for mapping water qualities from remotely sensed imagery. Whenever the hyperspectral image is available, e.g., images taken by MODerate resolution Imaging Spectroradiometer (MODIS) onboard AQUA satellite or the hyperspectral imager-ISIS from an airborne platform, a novel approach that integrates a semi-analytical (SA) model and a genetic algorithm (GA) to retrieve the constituents of water bodies from remote sensing of ocean color (GA-SA) was suggested. Following the same procedures the International Ocean-Color Coordinating Group (IOCCG) employed in evaluating various algorithms, this GA-SA approach is validated against a synthetic dataset (N=500) and an in-situ dataset (N=656) compiled by the IOCCG. The results of validation indicate that the GA-SA technique is accurate and robust, easy to use, and sufficiently fast to process satellite imagery on a regional scale. This novel approach is applied in processing the images taken by MODIS and generates maps of water constituents and IOPs, including concentrations of chlorophyll-a (Chl-a), non-algal particle (NAP), and the absorption coefficient of color dissolved organic matter (CDOM) at 443nm. On the other hand, an empirical approach (FORTW-EM) that transform the ratio of Green to Blue band and Red to Blue band of the imagery to respective retrieve the concentration of Chl-a and suspended solids (SS) was suggested, whenever there are only multispectral images available, e.g., images taken by FORMOSAT-2. During the development of FORTW-EM, both the in-situ measurement of spectral reflectance in TWR and the techniques of image processing are applied to the time series of imagery collected by FORMOSAT-2. The result of FORTW-EM shows that the relative percentage differences (RPD) for retrieving Chl-a and SS from the FORMOSAT-2 imagery are 51% and 33%, respectively. The error might be caused by the different level of atmospheric effect on different date. Another possibility is that the FORMOSAT-2 imagery and the in-situ measurement were not collected on the same time. Because the most appropriate hyperspectral image for mapping reservoir water quality is not available at present. Therefore, based on fifteen FORMOSAT-2 images in TWR taken in 2006, we apply the FORTW-EM approach to derive maps of Chl-a and SS. With the daily runoff loads derived by the NPS regression model and the ancillary information of averaged precipitation and effective storage volume of TWR, the imagery revealed surface dispersal patterns can be reasonably categorized as low-level, stormwater, full-level and water level decreasing periods. The results demonstrated that the different characteristics of Chl-a and SS make them ideal tracers for observing large-scale dispersal patterns. Mapping the water constituents from remotely sensed data enables a better understanding of the linkage of river-borne substances in TWR.

碩士
國立成功大學
環境工程學系
106
Eutrophication is a common water quality problem of reservoirs in south Taiwan, and most of reservoirs which was identified as the eutrophic reservoir because of low transparency instead of chlorophyll-a. The cause of low transparency are mainly high concentration of suspended solids instead of chlorophyll-a. The strategy of restoring eutrophic reservoirs must be based on science as integrating watershed and bio-optical models for liking catchment loading to the depth of Secchi disk to simulate different load reduction scenarios. Therefore, this study was integrating watershed model, receiving water model and Secchi disk depth physical model to develop an integrating model. The result of HSPF watershed hydrological modeling is acceptable. The simulated total inflow rate is close to observed inflow rate. The R2 value of calibration and validation are 0.5929 and 0.7574 respectively. According to loading estimation result, the loading constituents includes SS, NH4-N, NO3-N, NO2-N, TP, TOC, and BOD¬. The sources of pollutant loading in Agongdian Reservoir are point source from residents, nonpoint source, and cross-watershed diversion. Nonpoint source and cross-watershed diversion are the main resources with more than 95% proportion, and point source with less than 5% proportion. The variation trend of total loading is similar to precipitation change. There are three loading reduction scenarios are simulated in this study. (1) Point source control: SS is reduced from 200mg/L to 20mg/L. TOC is reduced from 3.93 to 0.8 mg/L. PO43- is reduced from 1.33 mg/L to 0.16 mg/L. BOD is reduced from 5.92 to 2 mg/L (2) Nonpoint source control: TP and TN emission are reduced to 70% in fruit land. (3) Cross-watershed diversion control: SS is reduced to 60% and TP is reduced to 80%. In the result, the cross–watershed diversion control is the most effective one. Agongdian Reservoir is identified as eutrophic due to overloading of SS loading which leads to low transparency.

碩士
國立成功大學
環境工程學系碩博士班
95
Monitoring the water quality is an essential work for evaluating the reservoir condition, monitoring the drinking water safety, analyzing the contaminant source, and indicating the eutrophicated status. The data collected by the traditional approach of sampling at a few stations on certain dates, however, is limited both in time and space. As a result, such data is not able to provide the temporal and spatial information for the entire water reservoir.. In this study, both the in-situ measurement of spectral reflectance and the technique of image processing are applied to the time series of remote-sensing imagery collected by FORMOSAT-2, with the intention to monitor the temporal and spatial distribution of chlorophyll-a (Chl-a) and suspended sediment (SS). The result shows that a close correlation exists between various parameters of water quality and the in-situ measurement of the hyper-spectral reflectance. The R2 value of the empirical regression model for Chl-a and SS is 0.79 and 0.87, respectively. Therefore, firstly, this research applies the empirical model to analyze the FORMOSAT-2 imagery. The result shows that the relative percentage differences (RPD) of Chl-a and SS are as low as 51% and 33%, respectively. Secondly, based on the technique of non-linear optimization using the inverse matrix method, this research employs a set of bio-optical models to derive the semi-empirical relationship between various parameters of water quality and the surface reflectance derived from FORMOSAT-2 images. In spite of the much longer time required for image processing, the semi-empirical method gives an even lower value of RPD for Chl-a (48%). However, the RPD for SS is run up to 112% in this case. This might be caused by the different level of atmospheric effect on different date. Another possibility is that the FORMOSAT-2 imagery and the in-situ measurement were not collected on the same time. Nevertheless, this research demonstrated that the time series of FORMOSAT-2 images is an ideal source of data for studying the temporal and spatial distribution of the phytoplankton and suspended sediment. This study concludes that the errors in estimating the water quality of a reservoir from the imagery of FORMOSAT-2 are much larger than the one obtained from the laboratory analysis. Therefore, it is not appropriate to simply use the satellite-derived parameters to infer the water quality or to indicate the status of eutrophication. However, the satellite is still an ideal platform for monitoring the water quality over the entire reservoir. The remote sensing imagery is able to show the spatial and temporal variation of the phytoplankton concentration and the distribution of the turbidity in the reservoir after the inflows from different branches.