Inter-annual and decadal variation in the pelagic marine ecosystem of the Yellow and East China seas

The water-leaving radiance measurements and chlorophyll concentrations of the Coastal Zone Color Scanner (CZCS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were compared to investigate decadal trends in the Yellow and East China Seas (YECS). A unified bio-optical algorithm was derived to convert CZCS pigments to SeaWiFS chlorophyll concentrations. The conversion is applied to level-2 CZCS data. We established monthly variations in the stratified and well-mixed areas using a coupled ocean wave-circulation model and the ocean color satellite data for estimating primary productivity in the Yellow Sea using satellite observations. The model results were compared with remotely sensed sea surface temperature and water-leaving radiance at 667nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) to develop a method to differentiate stratified and well-mixed waters using remote sensing data. We used and modified an existing primary productivity algorithm to estimate phytoplankton primary production using satellite data in the Yellow Sea. The Yellow Sea was first partitioned into three subregions based on the bathymetry and physical features to parameterize the algorithm. A local empirical chlorophyll algorithm was applied to derive more accurate chlorophyll concentration in the Yellow Sea and an approach was presented for estimating the diffuse attenuation coefficient. We investigated whether it was necessary to model the vertical biomass profile. Finally, the algorithm was applied to derive the primary production in the Yellow Sea. The primary production derived using the local algorithm was higher in the middle of the Yellow Sea in May and September than in the shallower (\u3c50 m) coastal areas. The low primary production in the coastal areas is caused by high turbidity due to strong tides and shallow depths. Lower turbidity in the middle of the Yellow Sea allows the light energy for primary production to penetrate to a deeper depth. Our computation of daily total primary production for the entire the Yellow Sea is 19.7 x 104 tonC d-1 in May and 15.8 x 10 4 tonC d-1 in September, and the annual total primary production in the Yellow Sea was 50.1 x 106 tonC yr-1. The resulting maps of primary production calculated from the remotely sensed data provide the first synoptic views of primary production in the Yellow Sea. (Abstract shortened by UMI.)

MODIS STANDARD (OC3) CHLOROPHYLL-A ALGORITHM EVALUATION IN INDONESIAN SEAS

The MODIS-estimated chlorophyll-a information was widely used in some operational application in Indonesia. However, there is no information about the performance of MODIS chlorophyll-a in Indonesian seas and there is no data used in development of algorithm was taken in Indonesian seas. Even the algorithm was validated in other area, it is important to know the performance of the algorithm work in Indonesian seas. Performance of MODIS Standard (OC3) algorithm at Indonesian seas was analyzed in this paper. The in-situ chlorophyll-a concentration data was collected during MOMSEI (Monsoon Offset Monitoring and Its Social and Ecosystem Impact) 2012 Cruise 25th April – 12th   May 2012 and also from archived data of the Research and Development Center for Marine Coastal Resources, Agency of Marine and Fisheries Research and Development, Indonesian Ministry of  Marine Affairs and Fisheries. The in-situ data used in this research is located in Indian Ocean the west of Sumatera part and Pacific Ocean the north of Papua Province part. Satellite data which is used is Ocean Color MODIS Level-2 Product that downloaded from NASA and MODIS L-0 from LAPAN Ground Station. MODIS Level 0 from LAPAN then processed to Level-2  using latest SeaDAS Software. The match-up resulted the MNB(%) is -4.8% that means satellite-estimated was underestimate in 4.8 % and RMSE is 0.058. When the data was separated following to the data source, the correlation and trend line equation became better. From MOMSEI Cruise data, the MNB(%) was -18.8% and RMSE 0.05. From Pacific Ocean Data, MNB (%) was -27 % and RMSE 0.049. From SONNE Cruise 2005, MNB (%) was -27 % and RMSE 0.049. MODIS standard algorithm is work well in Indonesia case-1 seawaters, which contain chlorophyll-a only, and derived that influence to the electromagnetic wave

A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors' data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters

Dissolved organic carbon fluxes in the Middle Atlantic Bight: An integrated approach based on satellite data and ocean model products

Continental margins play an important role in global carbon cycle, accounting for 15-21% of the global marine primary production. Since carbon fluxes across continental margins from land to the open ocean are not well constrained, we undertook a study to develop satellite algorithms to retrieve dissolved organic carbon (DOC) and combined these satellite data with physical circulation model products to quantify the shelf boundary fluxes of DOC for the U.S. Middle Atlantic Bight (MAB). Satellite DOC was computed through seasonal relationships of DOC with colored dissolved organic matter absorption coefficients, which were derived from an extensive set of in situ measurements. The multiyear time series of satellite-derived DOC stocks (4.9TeragramsC; Tg) shows that freshwater discharge influences the magnitude and seasonal variability of DOC on the continental shelf. For the 2010-2012 period studied, the average total estuarine export of DOC into the MAB shelf is 0.77TgCyr(-1) (year). The integrated DOC tracer fluxes across the shelf boundaries are 12.1TgCyr(-1) entering the MAB from the southwest alongshore boundary, 18.5TgCyr(-1) entering the MAB from the northeast alongshore boundary, and 29.0TgCyr(-1) flowing out of the MAB across the entire length of the 100m isobath. The magnitude of the cross-shelf DOC flux is quite variable in time (monthly) and space (north to south). The highly dynamic exchange of water along the shelf boundaries regulates the DOC budget of the MAB at subseasonal time scales

Investigation of Colored Dissolved Organic Matter and Dissolved Organic Carbon Using Combination of Ocean Color Data and Numerical Model in the Northern Gulf of Mexico

The first part of this thesis includes evaluating and developing empirical band ratio algorithms for the estimation of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) for SeaWiFS, MODIS and MERIS ocean color sensors for the northern Gulf of Mexico. For CDOM, matchup comparison between SeaWiFS-derived CDOM absorption coefficients and in situ absorption measurements at 412 nm (aCDOM(412)) were examined using the D’Sa et al. (2006) and the Mannino et al. (2008) algorithms. These reflectance band ratio algorithms were also assessed to retrieve aCDOM(412) from MODIS and MERIS data using the Rrs(488)/Rrs(555) and Rrs(510)/Rrs(560) band ratios, respectively. Since DOC cannot be measured directly by remote sensors, CDOM as the colored component of DOC is utilized as a proxy to estimate DOC remotely. A seasonal relationship between CDOM and DOC was established for the summer and spring-winter with high correlation for both periods. Seasonal band ratio empirical algorithms to estimate DOC were thus developed. In the second part of this study, a numerical model to study CDOM dynamics in the northern Gulf of Mexico was examined. To derive surface CDOM concentration maps from simulated salinity output from the Navy Coastal Ocean Model (NCOM), a highly correlated linear inverse relationship between CDOM and salinity is required which was examined for both inner-shelf and outer-shelf areas for the spring-winter and the summer periods. Applying these relationships on NCOM simulated salinity resulted in hourly maps of CDOM exhibiting high consistency with CDOM patterns derived from SeaWiFS sensor. Overlaying the NCOM-derived CDOM maps on the simulated currents showed the profound effect of currents on CDOM advection. Cold fronts strongly impact CDOM advection in both the inner and outer shelves by flushing CDOM-laden waters out of the coastal bays

Revisiting the Ocean Color Algorithms for Particulate Organic Carbon and Chlorophyll-a Concentrations in the Ross Sea

The Ross Sea is the most productive marginal sea in the Southern Ocean and plays an important role in carbon cycling. However, limited sampling of Chlorophyll-a (Chl) and particulate organic carbon (POC) concentrations from research expeditions constrains our understanding of the biogeochemical processes there. Satellites provide a useful tool for synoptic mapping of surface water properties on regional and global scales, yet the general applicability of the published algorithms in the Ross Sea is poorly known. Based on the data collected from 18 cruises in the past 20 years, we analyzed both the NASA standard and locally developed Chl and POC algorithms applicable to the Ross Sea. Our results show that Chl and POC are markedly underestimated using the NASA standard algorithms, with root mean square difference (RMSD) of 4.72 mg m−3 and 218.0 mg m−3, and mean bias of −3.48 mg m−3 and −159.1 mg m−3, for a wide range of Chl (0.42–16.3 mg m−3) and POC (46.8–812 mg m−3). Similar poor performances were also found for other algorithms applicable in the Ross Sea. We locally tuned both Chl and POC algorithms, and found that the Rrs667-based approach showed the most robust performances in retrieving both Chl and POC, with improved RMSD of 2.86 mg m−3 and 129.7 mg m−3, and limited biases. Our results show that the algal bloom signals in the Ross Sea in terms of Chl and POC are significantly greater than previously determined. More field observations will further constrain the locally tuned algorithms

Phytoplankton functional types from Space.

The concept of phytoplankton functional types has emerged as a useful approach to classifying phytoplankton. It finds many applications in addressing some serious contemporary issues facing science and society. Its use is not without challenges, however. As noted earlier, there is no universally-accepted set of functional types, and the types used have to be carefully selected to suit the particular problem being addressed. It is important that the sum total of all functional types matches all phytoplankton under consideration. For example, if in a biogeochemical study, we classify phytoplankton as silicifiers, calcifiers, DMS-producers and nitrogen fix- ers, then there is danger that the study may neglect phytoplankton that do not contribute in any significant way to those functions, but may nevertheless be a significant contributor to, say primary production. Such considerations often lead to the adoption of a category of “other phytoplankton” in models, with no clear defining traits assigned them, but that are nevertheless necessary to close budgets on phytoplankton processes. Since this group is a collection of all phytoplankton that defy classification according to a set of traits, it is difficult to model their physi- ological processes. Our understanding of the diverse functions of phytoplankton is still growing, and as we recognize more functions, there will be a need to balance the desire to incorporate the increasing number of functional types in models against observational challenges of identifying and mapping them adequately. Modelling approaches to dealing with increasing functional diversity have been proposed, for example, using the complex adaptive systems theory and system of infinite diversity, as in the work of Bruggemann and Kooijman (2007). But it is unlikely that remote-sensing approaches might be able to deal with anything but a few prominent functional types. As long as these challenges are explicitly addressed, the functional- type concept should continue to fill a real need to capture, in an economic fashion, the diversity in phytoplankton, and remote sensing should continue to be a useful tool to map them. Remote sensing of phytoplankton functional types is an emerging field, whose potential is not fully realised, nor its limitations clearly established. In this report, we provide an overview of progress to date, examine the advantages and limitations of various methods, and outline suggestions for further development. The overview provided in this chapter is intended to set the stage for detailed considerations of remote-sensing applications in later chapters. In the next chapter, we examine various in situ methods that exist for observing phytoplankton functional types, and how they relate to remote-sensing techniques. In the subsequent chapters, we review the theoretical and empirical bases for the existing and emerging remote-sensing approaches; assess knowledge about the limitations, assumptions, and likely accuracy or predictive skill of the approaches; provide some preliminary comparative analyses; and look towards future prospects with respect to algorithm development, validation studies, and new satellite mis- sions

Remote sensing of spatio-temporal relationships between the partitioned absorption coefficients of phytoplankton cells and mineral particles and euphotic zone depths in a partially mixed shelf sea

AbstractAbsorption coefficients for mineral particles and phytoplankton cells in the 488nm waveband, aMSS(488) and aCHL(488), and euphotic zone depths, z1%PAR, were determined for the Irish Sea and St. George's Channel from 8years of MODIS remote sensing reflectance observations. The results are presented as composite maps of the entire region for the months of January, April, July and October and as time series averaged over 2week intervals for three selected locations representing different mixing regimes. Annual cycles in aMSS(488) were observed in most areas, with maximum values occurring in winter when increased vertical mixing brought fine sediments to the surface. Euphotic depths were strongly influenced by aMSS(488) cycles, but sharp reductions were superimposed wherever phytoplankton blooms occurred. A key hydrographic feature of this region is the formation of a front in St. George's Channel between mixed and seasonally stratified water bodies. On the mixed side of the front, single peaks in aCHL(488) were observed in summer when the euphotic zone was at its deepest. On the stratified side, double peaks in aCHL(488) occurred in spring and autumn while low summer values of aCHL(488) coincided with high values of z1%PAR. The remote sensing evidence indicates, therefore, that phytoplankton growth (as reflected by net accumulation at the surface) in summer was limited by light availability in mixed waters, and nutrient availability in the stratified region. We conclude that observations of spatio-temporal patterns in phytoplankton and mineral particle absorption coefficients and euphotic depths derived from ocean colour sensors can provide insights into the processes determining the depth of penetration of solar radiation, and also the factors limiting near-surface primary production, in optically complex and spatially heterogeneous shelf seas

Water quality assessment and characterisation of chlorophyll-a variability related to river discharges, within the southeastern Bay of Biscay : evaluation and development of chlorophyll-a algorithms for MODIS and MERIS imagery

222 p. : il.[ES]La implementación de las directivas europeas Marco del Agua (Water FrameworkDirective) y la Estrategia Marina (Marine Strategy Framework Directive), implican un incremento del monitoreo de la calidad del agua, dentro de los límites de las aguas costeras y de la zona económica exclusiva europea. La teledetección es el único método que permite obtener observaciones frecuentes y sinópticas de áreas extensas. Por ello, los datos del "color del agua" son utilizados cada vez más, como una herramienta para evaluar la calidad del agua, estimando la concentración de diferentes constituyentes del agua, como por ejemplo la concentración de clorofila-a, considerada como un indicador de la biomasa del fitoplancton y de la eutrofización del agua. Los dos sensores elegidos para este estudio, MODIS y MERIS, proporcionan información satelital diaria y global, a una resolución media, además de mapas de clorofila-a derivados de dicha información. Sin embargo, los algoritmos utilizados a nivel global en aguas oceánicas (o de caso 1), se muestran imprecisos para determinar la concentración de clorofila en aguas ópticamente más complejas, debido a la presencia de material en suspensión y/o materia orgánica disuelta, como es el caso de las aguas costeras o también llamadas aguas de caso 2. Los constituyentes del agua en estas zonas son afectados por fenómenos locales y presentan, en general, características regionales. Por ello, una de los métodos utilizados para determinar la concentración de clorofila en aguas de caso2 con mayor exactitud, es la parametrización de algoritmos empíricos locales. Otras aproximaciones emplean, por ejemplo, algoritmos analíticos, semi-analíticos o de redes neuronales, pero los algoritmos empíricos, los cuales han sido elegidos para este estudio, tienen la ventaja de ser matemáticamente más simples que los anteriores. Son fáciles y rápidos de aplicar y se desarrollan a partir de medidas realizadas en el campo,siendo por ello, de alcance regional o local.Los principales objetivos de esta tesis son: 1) seleccionar el algoritmo de clorofila-a, aplicado a imágenes de MODIS y MERIS, más adecuado para evaluar la calidad del agua en la plataforma continental del País Vasco; y 2) estudiar la variabilidad de la clorofila-a entre 2005 y 2010 con respecto a las descargas de los ríos en la misma área de estudio, utilizando mapas de clorofila-a producidos con el algoritmo que proporcione la mayor precisión.En primer lugar, se ha evaluado la precisión con la que los distintos algoritmos más empleados en la literatura, determinan la concentración de clorofila-a. Por lo tanto, ha sido necesario realizar medidas de campo y, para ello, desarrollar un protocolo y adaptar unas plataformas para la medida en alta mar de la radiancia solar y la radiancia emergente del agua, para calcular así la reflectancia de teledetección. El capítulo I del apartado de los resultados, describe los experimentos realizados en el laboratorio y en el campo para poner a punto el protocolo y poder obtener medidas de campo con el espectroradiómentro Ocean Optics HR4000CG.En el capítulo II, se describe como dicho protocolo se puso a prueba durante una campaña de 20 días en el golfo de Vizcaya, entre el 5 y el 25 de mayo del 2008. Se muestrearon un total de 68 estaciones, donde se realizaron medidas espectrales, y se tomaron muestras de agua para posteriormente determinar en el laboratorio las concentraciones de clorofila-a, sólidos en suspensión y materia orgánica disuelta. Las plataformas desarrolladas permitieron realizar medidas espectrales en la superficie del agua, de una forma rápida y consistente, puesto que el sensor se ajusta en la posición correcta y su estabilidad está garantizada por su diseño. En general, las signaturas espectrales obtenidas durante la campaña corresponden con las que se encuentran en la literatura científica y su similitud con los espectros proporcionados por el espectroradiometro TriOS permiten concluir que el protocolo y las plataformas desarrolladas para el HR4000CG, son apropiados para realizar mediadas espectrales en alta mar.Sin embargo, en el capítulo III se utilizaron las medidas realizadas con el espectroradiometro TriOS, debido, en primer lugar, a la disponibilidad de este aparato en la campaña realizada en aguas costeras del País Vasco, y en segundo lugar, debido a su mayor precisión en este tipo de aguas. La mayor variabilidad encontrada en estas aguas, en lo referente a su composición y a la hidrodinámica de las plumas de los ríos, hace que una mayor precisión sea necesaria en este medio, la cual es aportada por el TriOS. Esto se debe a que este aparato mide la radiancia solar y la radiancia emergente del agua simultáneamente, y no con un intervalo máximo de 10 minutos como en el caso del HR4000CG. Estas medidas se han utilizado para desarrollar un algoritmo específico para las aguas costeras del país vasco, aplicado a imágenes de MERIS y MODIS. Además, una clasificación de las masas con análisis discriminante de los datos hidrológicos es comparada con la clasificación realizada con un "cluster" de los datos espectrales, resultando en una correspondencia del 80%. Se concluye que este algoritmo funciona mejor que los demás algoritmos evaluados (Gitelson, MERIS OC5, OC4Ev6) para los productos de MERIS. Se confirma también que el algoritmo no se ve afectado por los 23 pigmentos auxiliares identificados (correspondientes a 56 especies de fitoplancton) en las concentraciones medidas durante la campaña, ni por sólidos en suspensión hasta una concentración de 6.6 g.m-3. Así, este algoritmo se puede aplicar en aguas costeras con concentraciones de clorofila entre 0.1 y 9.57 mg.m-3. Por otro lado, la exactitud con la que el algoritmo local, aplicado a las imágenes de MODIS, determina la clorofila-a, es ligeramente menor a la del algoritmo OC5, como se muestra en elcapitulo IV.En el capítulo IV, el algoritmo local desarrollado, el algoritmo OC5 aplicado a MODIS y el algoritmo global OC3M, son validados con datos in situ de clorofila estimada por fluorimetría. Estos datos fueron obtenidos durante las campañas de la red de calidad llevadas a cabo entre 2005 y 2010 en las aguas costeras y continentales del País Vasco. Se compararon los algoritmos entre sí y se validaron de dos formas diferentes: 1) haciendo coincidir las mediadas in situ de clorofila con las medidas tomadas por el satélite en las mismas localizaciones con un intervalo máximo de 3 horas; y 2) calculando el percentil 90 de cada mes del año para las imágenes obtenidas durante el periodo 2005-2010 y comparándolo con la misma medida calculada durante el mismo periodo, con las medidas cuatrimestrales de clorofila-a tomadas in situ. Se compararon los ciclos anuales de la clorofila para las 4 masas de agua en las cuales se dividen las aguas del País Vasco, utilizando los valores del percentil 90. En general, el OC5 proporcionó un mejor resultado. Un mapa de clorofila realizado con los valores de percentil 90 con el OC5 de todas las imágenes existentes entre 2005 y 2010, fue utilizado para evaluar el estado de la calidad del agua. Según la directiva Marco, la calidad del agua se puede dividir en 5 categorías o estados: bueno", "Bueno", "Aceptable", "Deficiente", "Malo" correspondientes a los siguientes rangos de concentración de clorofila-a para las aguas del país vasco (percentil 90): ¿ 3.5 mg.m-3, 3.5- 7 mg.m-3, 7-10 mg.m-3, 10-14 mg.m-3 y ¿ 14 mg.m-3. Por lo tanto, se le otorgó a cada pixel del mapa de percentil 90, su correspondiente estado según su concentración de clorofila-a. Así, se obtuvo un mapa con el estado de la calidad del agua por cada píxel. El estado final de cada masa de agua se obtuvo al promediar el valor de todos los píxeles dentro de la masa del agua. Se obtuvo el mismo estado de la calidad del agua con los datos in situ que con los datos satelitales para todas las masas de agua, es decir "Muy bueno". Esto sugiere que un uso complementario de ambas metodologías, sería una buena solución para obtener una evaluación eficiente de la calidad de las aguas costeras utilizando la clorofila-a, sin un muestreo exhaustivo de la zona, reduciendo así el esfuerzo y el coste del monitoreo de campo. En el capítulo V, se describe la variabilidad espacial y temporal de la clorofila-a en relación con las descargas de los ríos del País Vasco. En general, se observa un aumento de la concentración de clorofila-a uno o dos días después de un episodio de lluvias en las zonas costeras del país vasco, cerca de las desembocaduras del Nervión y del Adour. Sin embargo, no hay un registro anterior que permita decir que este incremento tan rápido de la clorofila-a después del aporte de nutrientes al ecosistema marino, se deba a floraciones algales causadas por nutrientes fluviales. Por lo tanto, la clorofila-a medida por el satélite podría ser debida a origen terrestre, estuárico o bentónico, o que se trate de una sobre-estimación de los productos satelitales, debido a la presencia de material disuelto o en suspensión. Por otra parte, los patrones de variabilidad estacional de la clorofila-a son diferentes en las desembocaduras del Adour y del Nervión, y se distinguen a su vez de los patrones observados en aguas oceánicas. En el caso del Adour, las concentraciones de clorofila-a más altas se registran a finales de otoño y principios de primavera, principalmente entre abril y junio, los meses con los niveles de descargas fluviales más altos. En el caso del Nervión, el ciclo es similar al de las aguas oceánicas, en las que se observan floraciones de fitoplancton en primavera y a finales de otoño. Sin embargo, se observa un pico de clorofila-a en aguas de la desembocadura del Nervión, que no se advierte en aguas oceánicas. Finalmente, el análisis de la variabilidad inter-anual muestra una leve disminución de la concentración de clorofila-a (determinada a partir de datos de satélite) en el 2005 y el 2010 en las desembocaduras del Nervión y del Adour, y un ligero aumento en aguas oceánicas.En conclusión, los resultados presentados en esta tesis, aportan un conocimiento científico importante con respecto al uso de la teledetección como herramienta para determinar la concentración de clorofila-a con los sensores MERIS y MODIS, en aguas del País Vasco y del golfo de Vizcaya. El método desarrollado, por el cual se combinan las medidas in situ y de satélite de la clorofila-a, es un método eficaz para la evaluación de la calidad del agua en las áreas protegidas por las directivas europeas Marco del Agua y Estrategia Marina. Además, esta tesis aporta información sustancial acerca de la variabilidad espacial y temporal de la clorofila-a en la zona de estudio durante el periodo 2005 y 2010, a partir de datos satelitales. Sin embargo, se registran inexactitudes en la determinación de clorofila-a en los casos de altas descargas fluviales. Por lo tanto, la siguiente etapa de este trabajo consistiría en analizar en mayor profundidad los procesos y los factores que afectan la variabilidad de la clorofila-a en áreas costeras, así como la mejora de la estimación mediante satélite de este pigmento en dichas áreas.[EN]The implementation of water quality European Water Framework (WFD) and Marine Strategy Directives (MSFD) requires an intensification of water quality monitoring, within the limits of the Exclusive Economic Zone. Remote sensing technologies can provide a valuable tool for frequent, synoptic, water-quality observations, over large areas. Hence, ocean colour data is used increasingly as a tool to assess water quality, by estimating the concentration of the water constituents, such as chlorophyll-a (a proxy of the eutrophication risk). Both MODIS and MERIS, the satellite sensors selected for this study, provide global and daily ocean information and satellite-derived chlorophyll-a maps at a medium resolution (1 km x 1 km). However, algorithms designed for assessments at global scales for these sensors are less accurate locally, due to the variability of optically-active in-water constituents. Hence, regionally parameterized empirical algorithms are useful to cope with the inaccuracies produced. Additionally, to improve the water quality assessment in Basque coastal waters, the effect of river discharges needs to be studied, as it is one of the major factors affecting phytoplankton growth in this region. The main objectives of this thesis are: 1) to select the most suitable chlorophyll-a algorithms applied to MERIS and MODIS satellite images to assess the water quality in the Basque coastal and offshore waters (southeastern corner of the Bay of Biscay); and 2) to study the variability of chlorophyll-a with respect to river discharges into the same area, between 2005 and 2010. To address these objectives, four regional empirical algorithms for MERIS and MODIS were developed with spectral and biogeochemical data acquired in situ. Two were developed for the entire Bay of Biscay with spectral measurements acquired with the OceanOptics spectrometer and biogeochemical data. A protocol and a specific platform were developed in this study especially for this spectrometer. Another two algorithms were developed with spectral data obtained with the TriOS spectrometer, as it provided improved results for the coastal waters than the OceanOptics spectrometer. The optical data was acquired during oceanographic surveys in the area of study. The influence of suspended matter, phytoplankton species and pigment content, on the algorithms developed was explored. These algorithms were validated with in situ data and were compared to well-established global and regional chlorophyll-a algorithms. The algorithms developed in this study generally improved the estimation of chlorophyll-a in Basque coastal waters. However, the OC5 algorithm was considered more suitable for the ecological water quality assessment of the study area, as it corresponded most accurately with in situ measurements. A 90th percentile chlorophyll-a map was generated with this algorithm to apply the classification scheme required by the Directives. The water quality status assessment obtained using both, in situ and satellite data, resulted in high quality status for all the water bodies. Hence, remote sensing is suited for the quality assessment and water body classification, when a densification of the monitoring network is needed to comply with European marine policies. A complementary use of both methodologies provides an efficient assessment of the water quality, within European Directives. Finally, daily MODIS imagery permitted the characterisation of the variability of chlorophyll-a in the Basque coast and the Bay of Biscay at a daily, seasonal and inter-annual scale. The seasonal chlorophyll-a cycle differs slightly in coastal waters, compared to the offshore waters, especially those areas affected by high river discharges (such as the Adour). The spring chlorophyll-a peak in March, in the offshore waters, is shifted to May in the nearby area influenced by the Adour. The unsupervised classification performed confirms that, at present, phytoplankton is at good status and eutrophication risk is low in the Basque coastal waters. This thesis is the first study that provides scientific knowledge on the assessment of water quality, using remote sensing and chlorophyll-a, in Basque coastal and offshore water bodies. It provides also important spectral and biogeochemical information on the water bodies of the area, which will be valuable in future studies.I gratefully acknowledge the funding sources that made my PhD possible. I was funded by Fundación de Centros Tecnológicos Iñaki Goenag