The TOPEX/POSEIDON Project is a joint U.S. and French mission to develop and operate an Earth orbiting satellite capable of making accurate measurements of the mean sea level in a way that allows the study of ocean dynamics. The understanding of ocean dynamics is very important in order to study events such as El Nino. Soon after the launch of the TOPEX satellite, some unusually high, but localized, values of the ocean's radar cross section, sigma-0, were observed by scientists at the NASA Goddard Space Flight Center. These phenomena have been referred to as sigma-0 blooms, and are accompanied by an increase in noise in the significant wave height (SWH) and altitude measurements. Since approximately 5% of all data recorded by the satellite contains sigma-0 blooms, it is important to understand their causes so that corrective measures can be taken by NASA. This thesis investigates two possible origins of the sigma-0 blooms: a surface containing a step discontinuity in sigma-0, and a surface containing slick or calm areas. Models corresponding to the theoretical returns from these two types of surfaces are developed and studied. / Master of Science

Satellite altimetry has been traditionally used in the past few decades to measure elevation of land ice, quantify changes in ice topography and infer the mass balance of large and remote areas such as the Greenland and Antarctic ice sheets. Radar altimetry is particularly well suited to this task due to its all-weather year-round capability of observing the ice surface. However, monitoring of ice caps and ice fields - bodies of ice with areas typically smaller than ~ 10,000 km2 - has proven more challenging. The large footprint of a conventional radar altimeter and coarse ground track coverage are less suited to observing comparatively small regions with complex topography. Since 2010, the European Space Agency’s CryoSat-2 satellite has been collecting ice elevation measurements over ice caps and ice fields with its novel radar altimeter. CryoSat-2’s smaller inter-track spacing provides higher density of observations compared to previous satellite altimeters. Additionally, it generates more accurate measurements because (i) the footprint size is reduced in the along-track direction by means of synthetic aperture radar processing and (ii) interferometry allows to precisely locate the the across-track angle of arrival of a reflection from the surface. Furthermore, the interferometric capabilities of CryoSat-2 allow for the processing of the delayed surface reflections after the first echo. When applied over a sloping surface, this procedure generates a swath of elevations a few km wide compared to the conventional approach returning a single elevation. In this thesis, swath processing of CryoSat-2 interferometric data is exploited to generate topographic data over ice caps and ice fields. The dense elevation field is then used to compute maps of elevation change rates at sub-kilometer resolution with the aim of quantifying ice volume change and mass balance. A number of algorithms have been developed in this work, partly or entirely, to form a complete processing chain from generating the elevation field to calculating volume and mass change. These algorithms are discussed in detail before presenting the results obtained in two selected regions: Iceland and Patagonia. Over Icelandic ice caps, the high-resolution mapping reveals complex surface elevation changes, related to climate, ice dynamics and sub-glacial, geothermal and magmatic processes. The mass balance of each of the six largest ice caps (90% of Iceland’s permanent ice cover) is calculated independently for the first time using spaceborne radar altimetry data. Between October 2010 and September 2015 Icelandic ice caps have lost a total of 5.8± 0.7 Gt a ̄1, contributing 0.016± 0.002 mm a ̄1 to eustatic sea level rise. This estimate indicates that over this period the mass balance was 40% less negative than the preceding 15 years, a fact which partly reflects the anomalous positive balance year across the Vatnaj ̈okull ice cap (~ 70% of the glaciated area) in 2014/15. Furthermore, it is demonstrated how swath processing of CryoSat-2 interferometric data allows the monitoring of glaciological processes at the catchment scale. Comparison of the geodetic estimates of mass balance against those based on in situ data shows good agreement. The thesis then investigates surface elevation change on the Northern and Southern Patagonian Ice Fields to quantify their mass balance. This area is characterized by some of the fastest flowing glaciers in the world, displaying complex interactions with the proglacial environments (including marine fjords and freshwater lakes) they often drain into. Field observations are sparse due to the inaccessibility of these ice fields and even remotely sensed data are limited, often tied to comparisons to the topography in 2000 as measured by the Shuttle Radar Topography Mission. Despite gaps in the spatial coverage, in particular due to the complex topography, CryoSat-2 swath radar altimetry provides insight into the patterns of change on the ice fields in the most recent period (2011 to 2017) and allows to independently calculate the mass balance of glaciers or catchments as small as 300 km2. The northern part of the Southern Patagonian ice field displays the strongest losses due to a combination between ice dynamics and warming temperatures. In contrast Pio XI, the largest glacier on this ice field and in South America, is advancing and gaining mass. Between April 2011 and march 2017, the two ice fields combined have lost an average of 21.29± 1.98 Gt a ̄1 (equivalent to 0.059± 0.005 mm a ̄1 eustatic sea level rise), 24% and 42% more negative when compared to the periods 2000-2012/14 and 1975-2000. In particular the Northern Patagonian ice field, responsible for one third of the mass loss, is losing mass 70% faster compared to the first decade of the 21st century. These results confirm the overall strong mass loss of the Patagonian ice fields, second only to glaciers and ice caps in Alaska and the Canadian Arctic, and higher than High Mountain Asia, which all extend over areas ~ 5-8 times larger (excluding glaciers at the periphery of the Greenland and Antarctic ice sheets).

No description available.

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.

Le bassin Amazonien est connu comme le plus grand système hydrologique du monde et pour son rôle important sur le système terre, influençant le cycle du carbone et le climat global. Les pressions anthropiques récentes, telles que la déforestation, les changements climatiques, la construction de barrage hydro-électriques, ainsi que l’augmentation des crues et sécheresse extrêmes qui se produisent dans cette région, motivent l’étude de l’hydrologie du bassin Amazonien. Dans le même temps, des méthodes hydrologiques de modélisation et de surveillance par observation satellitaire ont été développées qui peuvent fournir les bases techniques à cette fin. Ce travail a eu pour objectif la compréhension et la prévision du régime hydrologique du bassin Amazonien. Nous avons développé et évaluer des techniques de modélisation hydrologique-hydrodynamique de grande échelle, d’assimilation de données in situ et spatiales et de prévision hydrologique. L’ensemble de ces techniques nous a permis d’explorer le fonctionnement du bassin Amazonien en terme de processus physiques et de prévisibilité hydrologique. Nous avons utilisé le modèle hydrologique-hydrodynamique de grande échelle MGB-IPH pour simuler le bassin, le forçage précipitation étant fourni par l’observation spatiale. Les résultats de la modélisation sont satisfaisants lorsque validés à partir de données in situ de débit et de hauteurs d’eau mais également de données dérivées de l’observation spatiale incluant les niveaux d’eau déduits de l’altimétrie radar, le contenu en eau total issu de la gravimétrie satellitaire, l’extension des zones inondées. Nous avons montré que les eaux superficielles sont responsables en grande partie de la variation du stock total d’eau, l’influence des grands plans d’eau sur la variabilité spatiale des précipitations et l’influence des plaines d’inondation et des effets de remous sur la propagation des ondes de crues. Nos analyses ont montré le rôle prépondérant des conditions initiales, en particulier des eaux superficielles, pour la prévisibilité des grands fleuves Amazoniens, la connaissance des précipitations futures n’ayant qu’une influence secondaire. Ainsi, pour améliorer l’estimation des variables d’état hydrologiques, nous avons développé, pour la première fois, un schéma d’assimilation de données pour un modèle hydrologique-hydrodynamique de grande échelle, pour l’assimilation de données de jaugeages in situ et dérivées de l’altimétrie radar (débit et hauteur d’eau), dont les résultats se sont montrés satisfaisants. Nous avons également développé un prototype de système de prévision des débits pour le bassin Amazonien, basé sur le modèle initialisé avec les conditions initiales optimales fournies par le schéma d’assimilation de données, et en utilisant la pluie estimée par satellite disponible en temps réel. Les résultats ont été prometteurs, le modèle étant capable de prévoir les débits dans les principaux fleuves Amazoniens avec une antécédence importante (entre 1 et 3 mois), permettant d’anticiper, par exemple, la sècheresse extrême de 2005. Ces résultats démontrent le potentiel de la modélisation hydrologique appuyé par l’observation spatiale pour la prévision des débits avec une grande antécédence dans les grands bassins versant mondiaux. / A bacia Amazônica se destaca como o principal sistema hidrológico do mundo e pelo seu importante papel no sistema terrestre, influenciando o ciclo de carbono e o clima global. Recentes pressões antrópicas, como o desflorestamento, mudanças climáticas e a construção de barragens hidroelétricas, somados às crescentes cheias e secas extremas ocorridas nesta região, motivam o estudo da hidrologia da bacia Amazônica. Ao mesmo tempo, têm se desenvolvido métodos hidrológicos de modelagem e monitoramento via sensoriamento remoto que podem fornecer as bases técnicas para este fim. Este trabalho objetivou a compreensão e previsão da hidrologia da bacia Amazônica. Foram desenvolvidas e avaliadas diversas técnicas, incluindo de modelagem hidrológica-hidrodinâmica de larga escala, de assimilação de dados in situ e de sensoriamento remoto, e de previsão hidrológica. Este conjunto de técnicas foi utilizado para compreender o funcionamento da bacia Amazônica em termos de seus processos hidrológicos e sua previsibilidade hidrológica. O modelo hidrológico-hidrodinâmico de larga escala MGB-IPH foi utilizado para simular a bacia, sendo forçado com dados de chuva estimados por satélite. O modelo mostrou bom desempenho em uma validação detalhada contra observações de vazões e cotas in situ além de dados oriundos de sensoriamento remoto, incluindo níveis d’água de altimetria por radar, armazenamento d’água de gravimetria espacial e extensão de áreas alagadas. Mostrou-se a dominância das águas superficiais nas variações do armazenamento de água, a influência dos grandes corpos d’água sobre a variabilidade espacial da precipitação, além da importância das várzeas da inundação e efeitos de remanso sobre a propagação das ondas de cheia Amazônicas. As condições hidrológicas iniciais, com destaque para as águas superficiais, mostraram dominar a previsibilidade hidrológica nos grandes rios amazônicos, tendo assim a precipitação no futuro um papel secundário. Portanto, afim de melhor estimar os estados hidrológicos, de forma pioneira, foi desenvolvido um esquema de assimilação de dados para um modelo hidrológicohidrodinâmico de larga escala para assimilar informações in situ e de altimetria por radar, cujo desempenho se mostrou satisfatório. Desenvolveu-se também um protótipo de sistema de previsão de vazões para a bacia Amazônica, baseado no modelo inicializado com condições iniciais ótimas do esquema de assimilação de dados e utilizando precipitação estimada por satélite disponível em tempo real. Os resultados foram promissores e o modelo foi capaz de prever vazões nos principais rios amazônicos com grande antecedência (~1 a 3 meses), antecipando, por exemplo, a grande seca de 2005. Estes resultados mostram o potencial da modelagem hidrológica de larga escala apoiada por informação de sensoriamento remoto na previsão de vazões com alta antecedência nas grandes bacias hidrográficas do mundo. / The Amazon basin is known as the world’s main hydrological system and by its important role in the earth system, carbon cycle and global climate. Recent anthropogenic pressure, such as deforestation, climate change and the construction of hydropower dams, together with increasing extreme floods and droughts, encourage the research on the hydrology of the Amazon basin. On the other hand, hydrological methods for modeling and remotely sensed observation are being developed, and can be used for this goal. This work aimed at understanding and forecasting the hydrology of the Amazon River basin. We developed and evaluated techniques for large scale hydrologic-hydrodynamic modeling, data assimilation of both in situ and remote sensing data and hydrological forecasting. By means of these techniques, we explored the functioning of the Amazon River basin, in terms of its physical processes and its hydrological predictability. We used the MGB-IPH large scale hydrologichydrodynamic model forced by satellite-based precipitation. The model had a good performance when extensively validated against in situ discharge and stage measurements and also remotely sensed data, including radar altimetry-based water levels, gravimetric-based terrestrial water storage and flood inundation extent. We showed that surface waters governs most of the terrestrial water storage changes, the influence of large water bodies on precipitation spatial variability and the importance of the floodplains and backwater effects on the routing of the Amazon floodwaves. Analyses showed the dominant role of hydrological initial conditions, mainly surface waters, on hydrological predictability on the main Amazon Rivers, while the knowledge of future precipitation may be secondary. Aiming at the optimal estimation of these hydrological states, we developed, for the first time, a data assimilation scheme for both gauged and satellite altimetry-based discharge and water levels into a large scale hydrologic-hydrodynamic model, and it showed a good performance. We also developed a forecast system prototype, where the model is based on initial conditions gathered by the data assimilation scheme and forced by satellite-based precipitation. Results are promising and the model was able to provide accurate discharge forecasts in the main Amazon rivers even for very large lead times (~1 to 3 months), predicting, for example, the historical 2005 drought. These results point to the potential of large scale hydrological models supported with remote sensing information for providing hydrological forecasts well in advance at world’s large rivers and poorly monitored regions.

Le bassin Amazonien est connu comme le plus grand système hydrologique du monde et pour son rôle important sur le système terre, influençant le cycle du carbone et le climat global. Les pressions anthropiques récentes, telles que la déforestation, les changements climatiques, la construction de barrage hydro-électriques, ainsi que l’augmentation des crues et sécheresse extrêmes qui se produisent dans cette région, motivent l’étude de l’hydrologie du bassin Amazonien. Dans le même temps, des méthodes hydrologiques de modélisation et de surveillance par observation satellitaire ont été développées qui peuvent fournir les bases techniques à cette fin. Ce travail a eu pour objectif la compréhension et la prévision du régime hydrologique du bassin Amazonien. Nous avons développé et évaluer des techniques de modélisation hydrologique-hydrodynamique de grande échelle, d’assimilation de données in situ et spatiales et de prévision hydrologique. L’ensemble de ces techniques nous a permis d’explorer le fonctionnement du bassin Amazonien en terme de processus physiques et de prévisibilité hydrologique. Nous avons utilisé le modèle hydrologique-hydrodynamique de grande échelle MGB-IPH pour simuler le bassin, le forçage précipitation étant fourni par l’observation spatiale. Les résultats de la modélisation sont satisfaisants lorsque validés à partir de données in situ de débit et de hauteurs d’eau mais également de données dérivées de l’observation spatiale incluant les niveaux d’eau déduits de l’altimétrie radar, le contenu en eau total issu de la gravimétrie satellitaire, l’extension des zones inondées. Nous avons montré que les eaux superficielles sont responsables en grande partie de la variation du stock total d’eau, l’influence des grands plans d’eau sur la variabilité spatiale des précipitations et l’influence des plaines d’inondation et des effets de remous sur la propagation des ondes de crues. Nos analyses ont montré le rôle prépondérant des conditions initiales, en particulier des eaux superficielles, pour la prévisibilité des grands fleuves Amazoniens, la connaissance des précipitations futures n’ayant qu’une influence secondaire. Ainsi, pour améliorer l’estimation des variables d’état hydrologiques, nous avons développé, pour la première fois, un schéma d’assimilation de données pour un modèle hydrologique-hydrodynamique de grande échelle, pour l’assimilation de données de jaugeages in situ et dérivées de l’altimétrie radar (débit et hauteur d’eau), dont les résultats se sont montrés satisfaisants. Nous avons également développé un prototype de système de prévision des débits pour le bassin Amazonien, basé sur le modèle initialisé avec les conditions initiales optimales fournies par le schéma d’assimilation de données, et en utilisant la pluie estimée par satellite disponible en temps réel. Les résultats ont été prometteurs, le modèle étant capable de prévoir les débits dans les principaux fleuves Amazoniens avec une antécédence importante (entre 1 et 3 mois), permettant d’anticiper, par exemple, la sècheresse extrême de 2005. Ces résultats démontrent le potentiel de la modélisation hydrologique appuyé par l’observation spatiale pour la prévision des débits avec une grande antécédence dans les grands bassins versant mondiaux. / A bacia Amazônica se destaca como o principal sistema hidrológico do mundo e pelo seu importante papel no sistema terrestre, influenciando o ciclo de carbono e o clima global. Recentes pressões antrópicas, como o desflorestamento, mudanças climáticas e a construção de barragens hidroelétricas, somados às crescentes cheias e secas extremas ocorridas nesta região, motivam o estudo da hidrologia da bacia Amazônica. Ao mesmo tempo, têm se desenvolvido métodos hidrológicos de modelagem e monitoramento via sensoriamento remoto que podem fornecer as bases técnicas para este fim. Este trabalho objetivou a compreensão e previsão da hidrologia da bacia Amazônica. Foram desenvolvidas e avaliadas diversas técnicas, incluindo de modelagem hidrológica-hidrodinâmica de larga escala, de assimilação de dados in situ e de sensoriamento remoto, e de previsão hidrológica. Este conjunto de técnicas foi utilizado para compreender o funcionamento da bacia Amazônica em termos de seus processos hidrológicos e sua previsibilidade hidrológica. O modelo hidrológico-hidrodinâmico de larga escala MGB-IPH foi utilizado para simular a bacia, sendo forçado com dados de chuva estimados por satélite. O modelo mostrou bom desempenho em uma validação detalhada contra observações de vazões e cotas in situ além de dados oriundos de sensoriamento remoto, incluindo níveis d’água de altimetria por radar, armazenamento d’água de gravimetria espacial e extensão de áreas alagadas. Mostrou-se a dominância das águas superficiais nas variações do armazenamento de água, a influência dos grandes corpos d’água sobre a variabilidade espacial da precipitação, além da importância das várzeas da inundação e efeitos de remanso sobre a propagação das ondas de cheia Amazônicas. As condições hidrológicas iniciais, com destaque para as águas superficiais, mostraram dominar a previsibilidade hidrológica nos grandes rios amazônicos, tendo assim a precipitação no futuro um papel secundário. Portanto, afim de melhor estimar os estados hidrológicos, de forma pioneira, foi desenvolvido um esquema de assimilação de dados para um modelo hidrológicohidrodinâmico de larga escala para assimilar informações in situ e de altimetria por radar, cujo desempenho se mostrou satisfatório. Desenvolveu-se também um protótipo de sistema de previsão de vazões para a bacia Amazônica, baseado no modelo inicializado com condições iniciais ótimas do esquema de assimilação de dados e utilizando precipitação estimada por satélite disponível em tempo real. Os resultados foram promissores e o modelo foi capaz de prever vazões nos principais rios amazônicos com grande antecedência (~1 a 3 meses), antecipando, por exemplo, a grande seca de 2005. Estes resultados mostram o potencial da modelagem hidrológica de larga escala apoiada por informação de sensoriamento remoto na previsão de vazões com alta antecedência nas grandes bacias hidrográficas do mundo. / The Amazon basin is known as the world’s main hydrological system and by its important role in the earth system, carbon cycle and global climate. Recent anthropogenic pressure, such as deforestation, climate change and the construction of hydropower dams, together with increasing extreme floods and droughts, encourage the research on the hydrology of the Amazon basin. On the other hand, hydrological methods for modeling and remotely sensed observation are being developed, and can be used for this goal. This work aimed at understanding and forecasting the hydrology of the Amazon River basin. We developed and evaluated techniques for large scale hydrologic-hydrodynamic modeling, data assimilation of both in situ and remote sensing data and hydrological forecasting. By means of these techniques, we explored the functioning of the Amazon River basin, in terms of its physical processes and its hydrological predictability. We used the MGB-IPH large scale hydrologichydrodynamic model forced by satellite-based precipitation. The model had a good performance when extensively validated against in situ discharge and stage measurements and also remotely sensed data, including radar altimetry-based water levels, gravimetric-based terrestrial water storage and flood inundation extent. We showed that surface waters governs most of the terrestrial water storage changes, the influence of large water bodies on precipitation spatial variability and the importance of the floodplains and backwater effects on the routing of the Amazon floodwaves. Analyses showed the dominant role of hydrological initial conditions, mainly surface waters, on hydrological predictability on the main Amazon Rivers, while the knowledge of future precipitation may be secondary. Aiming at the optimal estimation of these hydrological states, we developed, for the first time, a data assimilation scheme for both gauged and satellite altimetry-based discharge and water levels into a large scale hydrologic-hydrodynamic model, and it showed a good performance. We also developed a forecast system prototype, where the model is based on initial conditions gathered by the data assimilation scheme and forced by satellite-based precipitation. Results are promising and the model was able to provide accurate discharge forecasts in the main Amazon rivers even for very large lead times (~1 to 3 months), predicting, for example, the historical 2005 drought. These results point to the potential of large scale hydrological models supported with remote sensing information for providing hydrological forecasts well in advance at world’s large rivers and poorly monitored regions.

Le bassin Amazonien est connu comme le plus grand système hydrologique du monde et pour son rôle important sur le système terre, influençant le cycle du carbone et le climat global. Les pressions anthropiques récentes, telles que la déforestation, les changements climatiques, la construction de barrage hydro-électriques, ainsi que l’augmentation des crues et sécheresse extrêmes qui se produisent dans cette région, motivent l’étude de l’hydrologie du bassin Amazonien. Dans le même temps, des méthodes hydrologiques de modélisation et de surveillance par observation satellitaire ont été développées qui peuvent fournir les bases techniques à cette fin. Ce travail a eu pour objectif la compréhension et la prévision du régime hydrologique du bassin Amazonien. Nous avons développé et évaluer des techniques de modélisation hydrologique-hydrodynamique de grande échelle, d’assimilation de données in situ et spatiales et de prévision hydrologique. L’ensemble de ces techniques nous a permis d’explorer le fonctionnement du bassin Amazonien en terme de processus physiques et de prévisibilité hydrologique. Nous avons utilisé le modèle hydrologique-hydrodynamique de grande échelle MGB-IPH pour simuler le bassin, le forçage précipitation étant fourni par l’observation spatiale. Les résultats de la modélisation sont satisfaisants lorsque validés à partir de données in situ de débit et de hauteurs d’eau mais également de données dérivées de l’observation spatiale incluant les niveaux d’eau déduits de l’altimétrie radar, le contenu en eau total issu de la gravimétrie satellitaire, l’extension des zones inondées. Nous avons montré que les eaux superficielles sont responsables en grande partie de la variation du stock total d’eau, l’influence des grands plans d’eau sur la variabilité spatiale des précipitations et l’influence des plaines d’inondation et des effets de remous sur la propagation des ondes de crues. Nos analyses ont montré le rôle prépondérant des conditions initiales, en particulier des eaux superficielles, pour la prévisibilité des grands fleuves Amazoniens, la connaissance des précipitations futures n’ayant qu’une influence secondaire. Ainsi, pour améliorer l’estimation des variables d’état hydrologiques, nous avons développé, pour la première fois, un schéma d’assimilation de données pour un modèle hydrologique-hydrodynamique de grande échelle, pour l’assimilation de données de jaugeages in situ et dérivées de l’altimétrie radar (débit et hauteur d’eau), dont les résultats se sont montrés satisfaisants. Nous avons également développé un prototype de système de prévision des débits pour le bassin Amazonien, basé sur le modèle initialisé avec les conditions initiales optimales fournies par le schéma d’assimilation de données, et en utilisant la pluie estimée par satellite disponible en temps réel. Les résultats ont été prometteurs, le modèle étant capable de prévoir les débits dans les principaux fleuves Amazoniens avec une antécédence importante (entre 1 et 3 mois), permettant d’anticiper, par exemple, la sècheresse extrême de 2005. Ces résultats démontrent le potentiel de la modélisation hydrologique appuyé par l’observation spatiale pour la prévision des débits avec une grande antécédence dans les grands bassins versant mondiaux. / A bacia Amazônica se destaca como o principal sistema hidrológico do mundo e pelo seu importante papel no sistema terrestre, influenciando o ciclo de carbono e o clima global. Recentes pressões antrópicas, como o desflorestamento, mudanças climáticas e a construção de barragens hidroelétricas, somados às crescentes cheias e secas extremas ocorridas nesta região, motivam o estudo da hidrologia da bacia Amazônica. Ao mesmo tempo, têm se desenvolvido métodos hidrológicos de modelagem e monitoramento via sensoriamento remoto que podem fornecer as bases técnicas para este fim. Este trabalho objetivou a compreensão e previsão da hidrologia da bacia Amazônica. Foram desenvolvidas e avaliadas diversas técnicas, incluindo de modelagem hidrológica-hidrodinâmica de larga escala, de assimilação de dados in situ e de sensoriamento remoto, e de previsão hidrológica. Este conjunto de técnicas foi utilizado para compreender o funcionamento da bacia Amazônica em termos de seus processos hidrológicos e sua previsibilidade hidrológica. O modelo hidrológico-hidrodinâmico de larga escala MGB-IPH foi utilizado para simular a bacia, sendo forçado com dados de chuva estimados por satélite. O modelo mostrou bom desempenho em uma validação detalhada contra observações de vazões e cotas in situ além de dados oriundos de sensoriamento remoto, incluindo níveis d’água de altimetria por radar, armazenamento d’água de gravimetria espacial e extensão de áreas alagadas. Mostrou-se a dominância das águas superficiais nas variações do armazenamento de água, a influência dos grandes corpos d’água sobre a variabilidade espacial da precipitação, além da importância das várzeas da inundação e efeitos de remanso sobre a propagação das ondas de cheia Amazônicas. As condições hidrológicas iniciais, com destaque para as águas superficiais, mostraram dominar a previsibilidade hidrológica nos grandes rios amazônicos, tendo assim a precipitação no futuro um papel secundário. Portanto, afim de melhor estimar os estados hidrológicos, de forma pioneira, foi desenvolvido um esquema de assimilação de dados para um modelo hidrológicohidrodinâmico de larga escala para assimilar informações in situ e de altimetria por radar, cujo desempenho se mostrou satisfatório. Desenvolveu-se também um protótipo de sistema de previsão de vazões para a bacia Amazônica, baseado no modelo inicializado com condições iniciais ótimas do esquema de assimilação de dados e utilizando precipitação estimada por satélite disponível em tempo real. Os resultados foram promissores e o modelo foi capaz de prever vazões nos principais rios amazônicos com grande antecedência (~1 a 3 meses), antecipando, por exemplo, a grande seca de 2005. Estes resultados mostram o potencial da modelagem hidrológica de larga escala apoiada por informação de sensoriamento remoto na previsão de vazões com alta antecedência nas grandes bacias hidrográficas do mundo. / The Amazon basin is known as the world’s main hydrological system and by its important role in the earth system, carbon cycle and global climate. Recent anthropogenic pressure, such as deforestation, climate change and the construction of hydropower dams, together with increasing extreme floods and droughts, encourage the research on the hydrology of the Amazon basin. On the other hand, hydrological methods for modeling and remotely sensed observation are being developed, and can be used for this goal. This work aimed at understanding and forecasting the hydrology of the Amazon River basin. We developed and evaluated techniques for large scale hydrologic-hydrodynamic modeling, data assimilation of both in situ and remote sensing data and hydrological forecasting. By means of these techniques, we explored the functioning of the Amazon River basin, in terms of its physical processes and its hydrological predictability. We used the MGB-IPH large scale hydrologichydrodynamic model forced by satellite-based precipitation. The model had a good performance when extensively validated against in situ discharge and stage measurements and also remotely sensed data, including radar altimetry-based water levels, gravimetric-based terrestrial water storage and flood inundation extent. We showed that surface waters governs most of the terrestrial water storage changes, the influence of large water bodies on precipitation spatial variability and the importance of the floodplains and backwater effects on the routing of the Amazon floodwaves. Analyses showed the dominant role of hydrological initial conditions, mainly surface waters, on hydrological predictability on the main Amazon Rivers, while the knowledge of future precipitation may be secondary. Aiming at the optimal estimation of these hydrological states, we developed, for the first time, a data assimilation scheme for both gauged and satellite altimetry-based discharge and water levels into a large scale hydrologic-hydrodynamic model, and it showed a good performance. We also developed a forecast system prototype, where the model is based on initial conditions gathered by the data assimilation scheme and forced by satellite-based precipitation. Results are promising and the model was able to provide accurate discharge forecasts in the main Amazon rivers even for very large lead times (~1 to 3 months), predicting, for example, the historical 2005 drought. These results point to the potential of large scale hydrological models supported with remote sensing information for providing hydrological forecasts well in advance at world’s large rivers and poorly monitored regions.