Um algoritmo empírico regional para estimativa de clorofila-a na plataforma continental adjacente à Baixada Santista foi desenvolvido a partir de dados radiométricos e de concentração de clorofila-a, obtidos em 49 estações oceanográficas durante dois cruzeiros, em outubro de 2005 e março de 2006. Foram selecionadas aleatoriamente 32 estações para o desenvolvimento do algoritmo e 17 para avaliação do desempenho de modo a representar todos os intervalos de concentração de Cl-a nos dois subconjuntos de dados. O desempenho do algoritmo obtido foi superior (r2 = 0,8424 e EMQ= 0,0418) ao dos algoritmos globais dos sensores SeaWIFS, OC2v4 (r2=0,77; EMQ=0,07), OC4v4 (r2=0,78;EMQ=0,07) e MODIS, OC3 (r2=0,79;EMQ=0,09) para os dados radiométricos, e também superior (r2=0,68; EMQ = 0,028) ao algoritmo global OC3 (r2= 0,62; EMQ= 0,036) para os dados de refletância do sensor MODIS, e apresentou melhor desempenho quanto à influência dos demais componentes bio-ópticos da água nos desvios das estimativas. Com base em dados de dois outros cruzeiros (setembro de 2005 e março de 2006), foi feita uma caracterização oceanográfica da plataforma adjacente à Baixada Santista, que mostrou que a região apresenta acentuada variabilidade sazonal e pode ser caracterizada como oligotrófica em termos de disponibilidade de nutrientes e biomassa fitoplanctônica. / A regional empirical algorithm for chlorophyll-a estimative in the continental shelf adjacent to Baixada Santista was developed based on in situ data on spectral radiometric and chlorophyll-a concentration obtained in 49 oceanographic stations during two oceanographic cruisers, in October 2005 and March 2006. Data from 32 stations were randomly selected for algorithm development and the other 17 for algorithm evaluation, representing all intervals of chlorophyll-a concentration in the two data subset. The performance of the regional algorithm was superior (r2 = 0,8424; RMS = 0,0418) to the global algorithms of the SeaWiFS, OC2v4 (r2=0,77; RMS=0,07), OC4v4 (r2=0,78;RMS=0,07) and MODIS, OC3 (r2=0,79; RMS=0,09) for the radiometric data, and also superior (r2=0,68; RMS = 0,028) to the global algorithm OC3 (r2= 0,62; RMS= 0,036) for reflectance data acquired by MODIS sensor. Also, the regional algorithm presented better performance, while estimative errors, related to the influence of other biooptical components of seawater. Based on the data of two other cruisers (September 2005 and March 2006), the oceanographic characterization of the continental shelf adjacent to Baixada Santista was made, revealing the region presents accentuate seasonal variability and can be characterized as oligotrophic in terms of nutrient availability and phytoplankton biomass.

Um algoritmo empírico regional para estimativa de clorofila-a na plataforma continental adjacente à Baixada Santista foi desenvolvido a partir de dados radiométricos e de concentração de clorofila-a, obtidos em 49 estações oceanográficas durante dois cruzeiros, em outubro de 2005 e março de 2006. Foram selecionadas aleatoriamente 32 estações para o desenvolvimento do algoritmo e 17 para avaliação do desempenho de modo a representar todos os intervalos de concentração de Cl-a nos dois subconjuntos de dados. O desempenho do algoritmo obtido foi superior (r2 = 0,8424 e EMQ= 0,0418) ao dos algoritmos globais dos sensores SeaWIFS, OC2v4 (r2=0,77; EMQ=0,07), OC4v4 (r2=0,78;EMQ=0,07) e MODIS, OC3 (r2=0,79;EMQ=0,09) para os dados radiométricos, e também superior (r2=0,68; EMQ = 0,028) ao algoritmo global OC3 (r2= 0,62; EMQ= 0,036) para os dados de refletância do sensor MODIS, e apresentou melhor desempenho quanto à influência dos demais componentes bio-ópticos da água nos desvios das estimativas. Com base em dados de dois outros cruzeiros (setembro de 2005 e março de 2006), foi feita uma caracterização oceanográfica da plataforma adjacente à Baixada Santista, que mostrou que a região apresenta acentuada variabilidade sazonal e pode ser caracterizada como oligotrófica em termos de disponibilidade de nutrientes e biomassa fitoplanctônica. / A regional empirical algorithm for chlorophyll-a estimative in the continental shelf adjacent to Baixada Santista was developed based on in situ data on spectral radiometric and chlorophyll-a concentration obtained in 49 oceanographic stations during two oceanographic cruisers, in October 2005 and March 2006. Data from 32 stations were randomly selected for algorithm development and the other 17 for algorithm evaluation, representing all intervals of chlorophyll-a concentration in the two data subset. The performance of the regional algorithm was superior (r2 = 0,8424; RMS = 0,0418) to the global algorithms of the SeaWiFS, OC2v4 (r2=0,77; RMS=0,07), OC4v4 (r2=0,78;RMS=0,07) and MODIS, OC3 (r2=0,79; RMS=0,09) for the radiometric data, and also superior (r2=0,68; RMS = 0,028) to the global algorithm OC3 (r2= 0,62; RMS= 0,036) for reflectance data acquired by MODIS sensor. Also, the regional algorithm presented better performance, while estimative errors, related to the influence of other biooptical components of seawater. Based on the data of two other cruisers (September 2005 and March 2006), the oceanographic characterization of the continental shelf adjacent to Baixada Santista was made, revealing the region presents accentuate seasonal variability and can be characterized as oligotrophic in terms of nutrient availability and phytoplankton biomass.

A biomassa e a produtividade primária fitoplanctônica da costa sudeste foram estimadas através de sensoriamento remoto da cor do oceano e dados in situ. Foram realizados quatro cruzeiros hidrográficos sazonais de mesoescala nas regiões de plataforma e talude continental durante os verões e invernos de 2001 e 2002. Com a descrição das características hidrográficas e distribuições de nutrientes inorgânicos dissolvidos, complementada pela análise de imagens orbitais (AVHRR e SeaWiFS), foi possível determinar os padrões de circulação da Corrente do Brasil, monitorar ressurgências costeiras e de quebra de plataforma, meandramentos e vórtices de mesoescala, assim como, a intrusão de águas frias, menos salinas e ricas em nutrientes vindas de sul sobre a plataforma continental, no inverno. A área de estudo foi dividida nos domínios de plataforma, talude-verão e talude-inverno, baseados em análises estatísticas da biomassa e produção primária fitoplanctônica integradas na zona eufótica. O domínio de plataforma não apresentou diferença sazonal devido ao processo de intrusão da ACAS sobre a plataforma. Este foi apontado como o principal processo de fertilização da zona eufótica nas águas de plataforma e talude tanto no verão como no inverno. Imagens da produtividade primária oceânica foram geradas pela primeira vez para a costa brasileira a partir de imagens da cor do oceano (SeaWiFS), utilizando-se um algoritmo semi-analítico não espectral, verticalmente homogêneo e dados fotossintéticos in situ obtidos simultaneamente. O avanço científico decorrente do presente trabalho é significativo, pois as estimativas de biomassa e produtividade primária fitoplanctônica através de imagens da cor do oceano e dados in situ coletados simultaneamente, ainda não haviam sido realizados na Zona Econômica Exclusiva brasileira. Comparações entre temperaturas da superfície do mar obtidas pelo AVHRR e medidas in situ (CTD) mostraram diferenças menores que 0,5ºC. O algoritmo OC4 apresentou o melhor desempenho entre os algoritmos testados (OC2, GSM01 e NN) para estimar a concentração de clorofila a, a partir de dados SeaWiFS, em relação às medidas fluorimétricas in situ, subestimando as concentrações mais baixas e superestimando as mais altas. Os algoritmos semi-analíticos de produção primária por satélite testados concordaram com as estimativas in situ (14C) por um fator de 2, nos melhores casos. As análises de regressão múltipla mostraram uma relação linear entre a produção primária e a biomassa fitoplanctônica integradas na coluna d’água. Uma abordagem alternativa baseada em uma rede neural artificial multicamada perceptron (12-5-1) foi testada como um modelo não linear para estimar a produção primária integrada na coluna d’água. A produção primária média para o período 2001-2002 foi estimada a partir de dados SeaWiFS em 386 gC m-2 a-1 e a produção primária potencial para a plataforma continental sudeste brasileira (PCSE) foi estimada em 0,06 Gt C a-1. O limite superior da produção pesqueira foi estimado considerando-se uma cadeia trófica com 2,8 níveis e uma eficiência trófica média de 10%. O resultado obtido foi cerca de 90 vezes maior que a captura média entre 1991 e 2000. Porém, se a produção pesqueira estimada for um limite superior que será reduzido a 10% ou 20% devido à acessibilidade ambiental, os recursos pesqueiros estariam limitados por alimento na PCSE. / The phytoplankton biomass and primary production of the Southeastern Brazilian coast are estimated using ocean color remote sensing and in situ data. This study is based on four seasonal hydrographic cruises carried out during the summer and winter of 2001 and 2002, along the continental shelf and slope waters. The hydrographic and dissolved inorganic nutrients in situ measurements were complemented by the sea surface temperature from the Advanced Very High Resolution Radiometer (AVHRR) sensor and chlorophyll a estimates from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) sensor to identify relevant features of the Brazil Current (BC) circulation related to the biological dynamics of this oceanic region. Several meanders and vortices were observed throughout the period along the inshore frontal zone of the BC in association with break shelf upwelling. Coastal upwelling events were observed to encompass a region larger than normally indicated in the literature and anomalous upwelling events were observed during the winter. Cold, less saline, and nutrient rich waters were observed flowing northward over the shelf during the winter. Based on statistical analysis of water column integrated chlorophyll and primary production the study area was divided into 3 domains: shelf, summer-slope, and winter-slope. The shelf domain did not present a significant seasonal difference due to the intrusion of South Atlantic Central Water over the shelf. This intrusion is the main process for the euphotic zone productivity enhancement in the shelf and slope waters during the summer and winter. A non-spectral and vertically homogeneous semi-analytical algorithm was applied to the SeaWiFS ocean color data, which incorporate simultaneously measured in situ photosynthetic parameters. This is the first time that the phytoplankton primary production and biomass estimation over the Brazilian Economic Exclusive Zone were done through remote sensed ocean colour and simultaneously acquired in situ data. Comparisons between in situ measurements and AVHRR based estimates of sea surface temperature have shown differences lower than 0.5ºC. The OC4 algorithm performed better then other chlorophyll retrieval algorithms (OC2, GSM01 and NN) when compared with in situ fluorometric data. However, it overestimates chlorophyll a at higher concentrations and underestimates at lower concentration. The best performing ocean color remote sensing primary productivity algorithms tested agreed with the 14C-based estimates within a factor of 2. A multiple regression analysis showed linear relation between the water column integrated primary production and the integrated chlorophyll. An alternative approach based on a backpropagation multilayer perceptron artificial neural network (12-5-1) was tested to estimate the water column integrated primary production for non-linear phytoplankton production modeling. The mean primary production for the 2 year period in the South Brazilian Bight (SBB) estimated from SeaWiFS is 386 gC m-2 yr-1, and the potential primary production is 0.06 Gt C yr-1. The upper bound for sustainable fish yield was estimated using a food chain of 2.8 links and an average trophic efficiency of 10%. The result was ~90 times larger than the observed fish catch from 1991 through 2000. If this fish yield is an upper bound that will be decreased to 10% or 20% by environmental accessibility, the fishery resources in the SBB are likely to be food-limited.

A biomassa e a produtividade primária fitoplanctônica da costa sudeste foram estimadas através de sensoriamento remoto da cor do oceano e dados in situ. Foram realizados quatro cruzeiros hidrográficos sazonais de mesoescala nas regiões de plataforma e talude continental durante os verões e invernos de 2001 e 2002. Com a descrição das características hidrográficas e distribuições de nutrientes inorgânicos dissolvidos, complementada pela análise de imagens orbitais (AVHRR e SeaWiFS), foi possível determinar os padrões de circulação da Corrente do Brasil, monitorar ressurgências costeiras e de quebra de plataforma, meandramentos e vórtices de mesoescala, assim como, a intrusão de águas frias, menos salinas e ricas em nutrientes vindas de sul sobre a plataforma continental, no inverno. A área de estudo foi dividida nos domínios de plataforma, talude-verão e talude-inverno, baseados em análises estatísticas da biomassa e produção primária fitoplanctônica integradas na zona eufótica. O domínio de plataforma não apresentou diferença sazonal devido ao processo de intrusão da ACAS sobre a plataforma. Este foi apontado como o principal processo de fertilização da zona eufótica nas águas de plataforma e talude tanto no verão como no inverno. Imagens da produtividade primária oceânica foram geradas pela primeira vez para a costa brasileira a partir de imagens da cor do oceano (SeaWiFS), utilizando-se um algoritmo semi-analítico não espectral, verticalmente homogêneo e dados fotossintéticos in situ obtidos simultaneamente. O avanço científico decorrente do presente trabalho é significativo, pois as estimativas de biomassa e produtividade primária fitoplanctônica através de imagens da cor do oceano e dados in situ coletados simultaneamente, ainda não haviam sido realizados na Zona Econômica Exclusiva brasileira. Comparações entre temperaturas da superfície do mar obtidas pelo AVHRR e medidas in situ (CTD) mostraram diferenças menores que 0,5ºC. O algoritmo OC4 apresentou o melhor desempenho entre os algoritmos testados (OC2, GSM01 e NN) para estimar a concentração de clorofila a, a partir de dados SeaWiFS, em relação às medidas fluorimétricas in situ, subestimando as concentrações mais baixas e superestimando as mais altas. Os algoritmos semi-analíticos de produção primária por satélite testados concordaram com as estimativas in situ (14C) por um fator de 2, nos melhores casos. As análises de regressão múltipla mostraram uma relação linear entre a produção primária e a biomassa fitoplanctônica integradas na coluna d’água. Uma abordagem alternativa baseada em uma rede neural artificial multicamada perceptron (12-5-1) foi testada como um modelo não linear para estimar a produção primária integrada na coluna d’água. A produção primária média para o período 2001-2002 foi estimada a partir de dados SeaWiFS em 386 gC m-2 a-1 e a produção primária potencial para a plataforma continental sudeste brasileira (PCSE) foi estimada em 0,06 Gt C a-1. O limite superior da produção pesqueira foi estimado considerando-se uma cadeia trófica com 2,8 níveis e uma eficiência trófica média de 10%. O resultado obtido foi cerca de 90 vezes maior que a captura média entre 1991 e 2000. Porém, se a produção pesqueira estimada for um limite superior que será reduzido a 10% ou 20% devido à acessibilidade ambiental, os recursos pesqueiros estariam limitados por alimento na PCSE. / The phytoplankton biomass and primary production of the Southeastern Brazilian coast are estimated using ocean color remote sensing and in situ data. This study is based on four seasonal hydrographic cruises carried out during the summer and winter of 2001 and 2002, along the continental shelf and slope waters. The hydrographic and dissolved inorganic nutrients in situ measurements were complemented by the sea surface temperature from the Advanced Very High Resolution Radiometer (AVHRR) sensor and chlorophyll a estimates from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) sensor to identify relevant features of the Brazil Current (BC) circulation related to the biological dynamics of this oceanic region. Several meanders and vortices were observed throughout the period along the inshore frontal zone of the BC in association with break shelf upwelling. Coastal upwelling events were observed to encompass a region larger than normally indicated in the literature and anomalous upwelling events were observed during the winter. Cold, less saline, and nutrient rich waters were observed flowing northward over the shelf during the winter. Based on statistical analysis of water column integrated chlorophyll and primary production the study area was divided into 3 domains: shelf, summer-slope, and winter-slope. The shelf domain did not present a significant seasonal difference due to the intrusion of South Atlantic Central Water over the shelf. This intrusion is the main process for the euphotic zone productivity enhancement in the shelf and slope waters during the summer and winter. A non-spectral and vertically homogeneous semi-analytical algorithm was applied to the SeaWiFS ocean color data, which incorporate simultaneously measured in situ photosynthetic parameters. This is the first time that the phytoplankton primary production and biomass estimation over the Brazilian Economic Exclusive Zone were done through remote sensed ocean colour and simultaneously acquired in situ data. Comparisons between in situ measurements and AVHRR based estimates of sea surface temperature have shown differences lower than 0.5ºC. The OC4 algorithm performed better then other chlorophyll retrieval algorithms (OC2, GSM01 and NN) when compared with in situ fluorometric data. However, it overestimates chlorophyll a at higher concentrations and underestimates at lower concentration. The best performing ocean color remote sensing primary productivity algorithms tested agreed with the 14C-based estimates within a factor of 2. A multiple regression analysis showed linear relation between the water column integrated primary production and the integrated chlorophyll. An alternative approach based on a backpropagation multilayer perceptron artificial neural network (12-5-1) was tested to estimate the water column integrated primary production for non-linear phytoplankton production modeling. The mean primary production for the 2 year period in the South Brazilian Bight (SBB) estimated from SeaWiFS is 386 gC m-2 yr-1, and the potential primary production is 0.06 Gt C yr-1. The upper bound for sustainable fish yield was estimated using a food chain of 2.8 links and an average trophic efficiency of 10%. The result was ~90 times larger than the observed fish catch from 1991 through 2000. If this fish yield is an upper bound that will be decreased to 10% or 20% by environmental accessibility, the fishery resources in the SBB are likely to be food-limited.

Climatic variations, together with large-scale environmental forces and human development affect the quality of coastal recreational waters, creating potential risks to human health. These environmental forces, including increased temperature and precipitation, often promote specific vector-borne diseases in the Caribbean and Gulf of Mexico. Human activities affect water quality through discharges from urban areas, including nutrient and other pollutants derived from wastewater systems. Both water quality of recreational beaches and vector-borne diseases can be better managed by understanding their relationship with local environmental forces. I evaluated how changes in vector-borne diseases and poor recreational water quality were related to specific environmental factors through the application of satellite-derived observations, field observations, and public health records. Variability in dengue fever incidence rates in coastal towns of the Yucatan Peninsula (Mexico) was evaluated with respect to environmental factors in Chapter Two. Correlations between fecal indicator bacteria concentrations (i.e., culturable enterococci) at Escambron Beach (San Juan, Puerto Rico, USA) and regional environmental factors are discussed in Chapter Three. Predictions of dengue fever occurrences in the Yucatan Peninsula were tested using a nonlinear approach (i.e., Artificial Neural Networks) and are presented in Chapter Four. The Artificial Neural Network (ANN) model was also used to predict culturable enterococci concentration exceeding safe recreational water quality standards in Escambron Beach and results are presented in Chapter Five. Environmental factors assessed to understand their influence on dengue fever occurrences and culturable enterococci concentrations included precipitation, mean sea level (MSL), air temperatures (e.g., maximum, minimum, and average), humidity, and satellite-derived sea surface temperature (SST), dew point, direct normal irradiance (DNI), and turbidity. These factors were combined with demographic data (e.g., population size) and compared with dengue fever incidence rates and culturable enterococci concentration using linear and nonlinear statistical approaches. Dengue incidence rates in Yucatan (Mexico) generally increased in July/August and decreased during November/December. A linear regression model showed that previous dengue incidence rates explained 89% of dengue fever variability (p < 0.05). Dengue incidence two weeks prior (previous incidence) influences future outbreaks by allowing the virus to continue propagating. Yet dengue incidence was best explained by precipitation, minimum air temperature, humidity, and SST (p < 0.05). Dengue incidence variability was best explained by SST and minimum air temperature in our study region (r = 0.50 and 0.48, respectively). Increases in SST preceded increased dengue incidence rate by eight weeks. Dengue incidence time series were positively correlated to SST and minimum air temperature anomalies. This is related to the virus and mosquito behavior. Including oceanographic variables among environmental factors in the model improved modelling skill of dengue fever in Mexico. Chapter Three shows that precipitation, MSL, DNI, SST, and turbidity explained some of the enterococci variation in Escambron Beach surface waters (AIC = 26.76; r = 0.20). Variation in these parameters preceded increased culturable enterococci concentrations, with lags spanning from 24 h up to 11 days. The highest influence on culturable enterococci was precipitation between 480 mm–900 mm. Rainy events often result in overflows of sewage systems and other non-point sources near Escambron Beach in Puerto Rico. A significant decrease in culturable enterococci concentrations was observed during increased irradiance (r = -0.24). This may be due to bacterial inactivation. Increased culturable enterococci concentrations were significantly associated with higher turbidity daily anomalies (r = 0.25), in part because bacteria were protected from light inactivation. Increased culturable enterococci concentrations were related to warmer SST anomalies (r = 0.12); this is likely due to increased bacterial activity and reproduction. Higher culturable enterococci concentrations were also significantly correlated to medium to high values of dew point daily anomalies (r = 0.19). A significant decrease in culturable enterococci during higher daily MSL anomalies (r = -0.19) is possibly due to dilution of bacteria in beach waters, whereas during lower MSL anomalies the back-washing promotes increased bacteria concentrations through mixing from sediments. These environmental variables improve our understanding of the ecology of these bacteria over time. The predictive capability increases by including more than one environmental variable. Chapter Four explains a predictive model of dengue fever occurrences in San Juan, Puerto Rico (1994–2012), and Yucatan (2007–2012). The model was modified to predict dengue fever outbreak occurrences for two population segments: population at risk of infection (i.e., < 24 years old) and vulnerable population (i.e., < 5 years old and > 65 years old). There were a total of four predictive models, two sets for each location using the specified population segments. Model predictions showed previous dengue cases, minimum air temperature, date, and population size as the factors with the most influence to predict dengue fever outbreak occurrences in Mexico. Previous dengue cases, maximum air temperature, date, and population size were the most influential factors for San Juan, Puerto Rico. The models showed an accuracy around 50% and a predictive capability of 70%. These environmental and demographic variables are important primary predictors for dengue fever outbreaks in Puerto Rico and Mexico. Chapter Five shows the application of the ANNs model to predict culturable enterococci exceedance based on the U.S. Environmental Protection Agency (U.S. EPA) Recreational Water Quality Criteria (RWQC) at Escambron Beach, San Juan, Puerto Rico. The model identified DNI, turbidity, 48 h cumulative precipitation, MSL, and SST as the most influential factors to predict enterococci concentration exceedance, based on the U.S. EPA RWQC at Escambron Beach from 2005–2014. The model showed an accuracy of 76%, with a predictive capability greater than 60%, which is higher than linear models. Results showed the applicability of remote sensing data and ANNs to predict recreational water quality and help improve early warning system and public health. This work helps to better understand complex relationships between climatic variations and public health issues in tropical coastal areas and provides information that can be used by public health practitioners.

I examined the hypothesis that high variability in Sea Surface Temperature (SST) and ocean color are associated with higher coral cover and slower rates of decline of coral cover within the Florida Keys National Marine Sanctuary (FKNMS). Synoptic SST time series maps, covering the period 1994-2005, were constructed for the FKNMS with data collected using the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite sensors. The SST data were compared with coral cover time series assessments at 36 sites conducted by the Coral Reef and Evaluation Monitoring Program (CREMP; 1996-2005), sponsored by the Environmental Protection Agency and the State of Florida. Out of the 36 stations, Smith Shoals routinely experienced very different and extreme environmental conditions relative to the rest of the stations, including extreme salinity, suspended sediments, and "black water" events that led to the death of coral reef organisms such as in 2002. Among the other 35 stations, sites that experienced moderately higher SST variability (mean variance > 6) relative to other sites showed a trend toward higher percentage coral cover (r=0.62, p=6.33x10-5, N=35) and relatively slower rates of decline (r=0.41, p=0.02, N=35) over the 12-year study period. The results suggest that coral reefs sites that are continuously exposed to high but not extreme variability in temperature may develop resilience against episodes of extreme cold or elevated SST. Variability of suspended sediments and water clarity were estimated using satellite-derived, normalized water-leaving radiance products. Ocean color data were obtained from the Sea-viewing Wide-Field-of View Sensor (Sea WiFS) from 1998 to 2005. Normalized water-leaving radiance at 443 (Lwn443) was used as a proxy to examine variability in water clarity, and normalized water-leaving radiance at 670 (Lwn670) was used as a proxy to study variability in suspended sediments. A weak relationship was identified between variability of Lwn443 and Lwn670 and coral cover as estimated by CREMP assessments in 2005 (r=0.43, p = 0.01, N=35 and r = 0.47, p = 0.005, N=35, respectively). There was a weak relationship between coral cover change and Lwn670 from 1988 to 2005 (r = 0.46, p = 0.05, N=35), but there no relationship was observed between variability of Lwn443 and change in coral cover (r =0.27, p =0.11, N=35). Further research is required to understand the origin, concentration and composition of dissolved or suspended materials that change the turbidity of waters around reefs of the FKNMS, and whether these changes can be adequately interpreted by examining concurrent satellite imagery. Ultimately, such remote sensing and field research is required to understand how water quality affects the health of coral reefs, and how coral ecosystems adapt to environmental variability.

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L’anticipation et l’adaptation de nos sociétés aux bouleversements résultants du changement climatique sont aujourd’hui des questions majeures guidant les activités humaines et l’action publique. Néanmoins, la prévision reste un défi essentiel en raison des fortes incertitudes existantes et il est primordial de continuer à progresser dans la compréhension des mécanismes à l’origine de ces bouleversements. Au sein du cycle hydrologique, le réservoir de surface (incluant les lacs, les rivières et les plaines d’inondation) occupe une place importante car il est l’une des principales ressources en eau des écosystèmes et des populations. Or, la dynamique des stocks d’eau de surface est toujours mal connue aux échelles régionale et globale, du fait de l’absence de mesures pluriannuelles d’extension et de hauteur d’eau des zones inondées, et de la prise en compte limitée de ces variables dans les modèles hydrologiques et hydrodynamiques. La télédétection spatiale offre désormais la possibilité d’effectuer un suivi des stocks d’eau de surface en utilisant la complémentarité entre l’imagerie multi-spectrale, permettant de cartographier les étendues inondées, et l’altimétrie radar fournissant des séries temporelles de hauteur d’eau des hydro-systèmes continentaux. L’objectif de ma thèse est de tirer le meilleur parti de la complémentarité entre les différents types d’observations spatiales pour évaluer les ressources en eau du réservoir de surface et mesurer la dynamique des transferts d’eau des continents aux océans, et son impact sur la zone côtière en utilisant les concentrations de matières en suspension comme traceur des masses d’eau. Depuis le milieu des années 1990, la multiplication des missions multi-spectrales à moyenne résolution (< 1 km de résolution spatiale) et des altimètres radars à haute précision (comprise entre 10 et 30 cm) permet de réaliser un suivi hebdomadaire à mensuel des volumes d’eau de surface dans les grands bassins fluviaux. / The anticipation and adaptation of our societies to the upheavals resulting from climate change are today major issues guiding human activities and public action. Nevertheless, the forecast remains a key challenge because of the strong uncertainties that exist and it is essential to continue to progress in understanding the mechanisms behind these upheavals. Within the hydrological cycle, the surface reservoir (including lakes, rivers and floodplains) occupies an important place as it is one of the main water resources of ecosystems and populations. However, the dynamics of surface water stocks are still poorly known at the regional and global scales, due to the absence of multi-year measures of extension and water depth of the flooded areas, and the limited consideration of these variables in hydrological and hydrodynamic models. Satellite remote sensing now offers the possibility of monitoring surface water stocks by using the complementarity between multispectral imagery, allowing to map flooded areas, and the radar altimetry providing time series of water depths of continental hydro systems. The aim of my thesis is to make the most of the complementarity between the different types of spatial observations to evaluate the water resources of the surface reservoir and to measure the dynamics of water transfers between land and ocean, and its impact on the coastal zone using suspended particulate matter as tracer of water bodies. Since the mid-1990s, the multiplication of multispectral missions with medium resolution (<1 km of spatial resolution) and high-precision radar altimeters (between 10 and 30 cm) makes it possible to carry out weekly-to-monthly monitoring of volumes surface water in large river basins.

Les contaminants, dissouts ou adsorbés sur les particules, sont principalement délivrés au milieu marin par les fleuves. La dynamique sédimentaire constitue alors un proxy de la dynamique de ces contaminants. Cette thèse s'inscrit dans le projet ANR AMORAD, et se focalise sur la dynamique du matériel particulaire délivré par le Rhône au Golfe du Lion (Méditerranée nord-occidentale), principal contributeur d'apports solides au Golfe (80 % des sédiments). Alors que des études antérieures ont permis de bien représenter les processus au niveau du fond, les processus régissant les comportements des matières en supension (MES), majoritairement rencontrées dans le panache turbide du Rhône, sont encore mal apréhendés. En vue de mieux décrire la dynamique de ces MES et d'améliorer les modèles hydrosédimentaires existants, l'objectif est de mieux caractériser ces particules. À cette fin, un vaste jeu de données issu de capteurs déployés in situ (données collectées pour 12 campagnes en mer, réalisées de 2011 à 2016) a été exploité, permettant d’obtenir une vision 2D verticale mais seulement ponctuelle (spatialement et temporellement). De façon complémentaire, une base de données d'images satellitaires (donnée couleur de l'eau du capteur MERIS-300m acquise entre 2002 et 2012), offrant une vue plus synoptique et long terme mais uniquement en surface, a été exploitée. Le jeu de données d'images satellitaire (plus de 800 images) a été traité de façon innovante par l'application d'un traitement semi-automatique permettant l'extraction de différentes métriques du panache turbide du Rhône (e.g. aire, limites d'extension, forme, centres géométriques, concentrations). La distribution spatiale et les caractéristiques physiques des MES telles que leur concentration dans l'eau, leur diamètre médian ou encore leur vitesse de chute ont été étudiées et estimées en fonction des différents forçages hydrométéorologiques actifs sur la zone d'étude (e.g. débit du Rhône, vents dominants). Un nouveau modèle hydrosédimentaire reposant sur le couplage du modèle hydrodynamique MARS-3D et du module sédimentaire multiclasse MIXSED a été configuré et les données in situ et satellitaires ont pu être mobilisées afin de contraindre la vitesse de chute des sédiments, paramètre clef de la modélisation de la dynamique hydrosédimentaire. / Contaminants, which can be dissolved in water or adsorbed on particles, are mainly delivered to the coastal environment by rivers. Thus, sediment dynamics reperesent a relevant proxy of contaminants dynamics. ThisPhD thesis is part of the ANR AMORAD project, of which one workpackage focuses on the fate of sediments in the coastal environment. This work focuses on the dynamics of Rhône River sediments in the Gulf of Lions (north-western mediterranean), this river delivering 80 % of the sediments of the Gulf. While previous studies over the area allowed a better understanding of physical processes at the water-sediment interface, processes driving suspended particulate matter (SPM) dynamics are still poorly understood. To better describe this SPM dynamics and improve hydrosedimentary models, the aim is to better characterize these particles. To this end, a large dataset collected from in situ deployed sensors (data collected for 12 field campaigns, conducted from 2011 to 2016) was analyzed to get a 2D vertical but ponctual view (both spatially and temporally). Complementary, a satellite images dataset (MERIS-300m ocean colour archive from 2002 to 2012) was built in order to get a long term and more synoptic view (but limited to surface).This dataset (more than 800 images) was originaly studied, applying a semi-empirical process to extract various Rhône River turbid plume metrics (e.g. area of extension, south-east-westernmost points, shape, centroids, SPM concentrations). Plume metrics and physical properties of SPM such as their concentration in water, their median diameter or their settling velocity were investigated regarding the different hydrometeorological forcings (e.g. Rhône River discharge, prevailing winds). A new hydrosedimentary model, based on the coupling of the 3D hydrodynamical model MARS-3D and the sedimentary module MIXSED, was set and ocean color and in situ data were used to constrain the settling velocity of particles, key parameter of hydrosedimentary modelling.