Dans la zone intertropicale, les précipitations sont le principal marqueur climatique saisonnier et déterminent très largement l’hydrologie de surface et de nombreuses activités anthropiques. Le bassin amazonien est caractérisé par divers régimes régionaux de précipitations, dont la variabilité spatiale et temporelle est forte. De nombreux travaux ont montré que cette variabilité est liée à des forçages externes de large échelle, comme les températures de surface de l’océan. L’étude des précipitations dans cette région porte le plus souvent sur les tendances ou les extrêmes pluviométriques. En revanche, la détection d’années similaires constituant des sous-régimes régionaux et leur lien avec une configuration océano-atmosphérique particulière a été, jusqu’à présent, peu abordée. L’objectif principal de cette thèse est ainsi de créer une typologie des sous-régimes de précipitations régionaux dans le bassin amazonien et de les mettre en relation avec le contexte océano-atmosphérique pouvant en partie les expliquer. Dans ce but, des données issues de 205 pluviomètres répartis sur 5 pays du Bassin Amazonien ont été sélectionnées et soumises à une série de tests statistiques et de reconstruction. Cette thèse utilise également des données de nébulosité (Outgoing Longwave Radiation), de flux d’humidité et de température de surface de l’océan ainsi que des données satellitaires (TRMM3B42 version 7) qui permettent de compléter les informations sur la variabilité spatiale des pluies.Au sein de chacune des sept régions amazoniennes déterminées dans ce travail, deux à quatre sous-régimes de précipitations ont été détectés. Parmi les vingt-six sous-régimes, vingt sont associés à des anomalies de circulation des flux d’humidité et de température de surface des océans. Les sous-régimes de pluies de la moitié nord et les Andes de l’ouest du bassin sont le plus liés à des anomalies océaniques. De plus, comme cela est régulièrement décrit, des déficits ou excédents correspondent souvent à des phases El Niño ou La Niña, mais cette thèse met également en évidence le rôle important de l’Atlantique, en particulier sud, sur le déplacement de la ZCIT et sur les flux d’humidité ; et elle souligne également le lien entre la temporalité des événements océaniques et celle des anomalies de pluies.Le produit TRMM 3B42 V7 permet d’aller plus loin dans l’analyse de la variabilité spatiale intra-régionale des pluies de la région Nord-est du bassin amazonien et de relativiser la cohérence spatiale des sous-régimes de précipitations de cette région. / Precipitations are the main seasonal climate marker between the tropics and largely determine surface hydrolosy as well as many anthropogenic activities. The Amazon Basin is characterized by various regional rainfall patterns, whose spatial and temporal variability is high. Numerous studies have shown that this variability is related to large scale external forcing, such as sea surface temperatures. The analysis of precipitation in this region is generally related to trends or extreme of rainfall. However, the detection of similar years associated with regional sub-regimes and the analysis of their links with a specific ocean-atmosphere configuration has only been fewly addressed until now. The main objective of this thesis is to create a typology of regional precipitation sub-régimes in the Amazon Basin and to link them to ocean-atmosphere areas able to partly explain them. For that purpose data from 205 raingauges in 5 countries of the Amazon Basin were selected and submitted to a series of statistical tests and reconstruction. Outgoing longwave radiation, specific humidity, sea surface temperature, as well as satellite data (TRMM 3B42 version 7) were also used with the aim of improving the understanding of the spatial rainfall variability.Within each of the seven Amazon regions identified in this work, two to four precipitation sub-regimes were detected. Among the twenty six sub-regimes, twenty are associated with specific humidity and sea surface temperature anomalies. The precipitation sub-regimes of the northern half and the westernmost Andes of the Amazon Basin are most closely related to oceanic anomalies. Moreover, as previously described in the literature, reduction or surplus of rain often correspond to El Niño or La Niña phases, but this thesis also highlights the important role of the Atlantic, more specifically the southern part, on the move of the ITZC and on specific humidity. This work also stresses the link between the temporality of ocean events anomalies and rainfall anomalies.The TRMM 3B42 v7 product allows to enhance the analysis of the spatial variability of rainfall at the intra-regional scale of the North region of the Amazon Basin and to relativize the spatial coherence of its precipitation sub-regimes.

Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul / Understanding the spatial and temporal rainfall occurrence, improves the water resources management, both in order to prevent losses related to the occurrence of floods and droughts events, as in relation to the supply of the various sectors. Thus, satellite rainfall estimates are an alternative to obtain representative data of large areas, since the gauge data from meteorological stations are scarce, frequently due the low density of stations per area. However, these satellite products contain uncertainties when compared to gauge data. In this way, this study aims to evaluate the representativeness of rainfall estimates derived from satellites in the Rio Grande do Sul state. To this, were used satellite TRMM (3B42 V7) products, which were compared with gauge data in the State provided by the Agência Nacional de Águas and by the Instituto Nacional de Meteorologia, considering the period from 1998 to 2013. This paper compared rainfall estimates and gauge data was accomplished through a set statistics like skill scores, such as event detection percentage (PC), hit rate (H), false alerts ratios (FAR and F), critical success index (CSI), the ratio of planned events and observed (B), and the indexes of Heidke (HSS) and Pierce (PSS). Some equations were applied too: correlation coefficient (r) mean absolute error (MPE), root mean square error (RMSE), the Nash-Sutcliffe efficiency coefficient (NS) and bias. The data were compared in daily and accumulated series of 15 and 30 days, through the following methods: Pixel to Point, Point to Point, Pixel to Pixel, from Sub-pixels and aggregate analysis. The 3B42 products were also evaluated for their skill to determine heavy rainfall, using as reference intensity-duration-frequency equations (IDF) derived from gauge data. The results obtained by the methods, except for the analysis of heavy rainfall, not differ much from each other. Spatial analysis showed the relationship of assessments estimates has to the density of stations and the regions of Rio Grande do Sul, while specific analyzes indicated the good performance of TRMM even in Pixel to Point comparison. The results improved in steps that the daily series were accumulated in 15 and 30 days. It was evident the decrease of the quality of the estimates in the eastern RS region, where the ocean effects generates overestimates. / A compreensão da ocorrência espacial e temporal da precipitação pluviométrica permite melhorar a gestão dos recursos hídricos, tanto no sentido de prevenir prejuízos relacionados à ocorrência de eventos de enchentes e estiagens, quanto em relação ao suprimento dos diversos setores. Assim, estimativas de precipitação de satélites são uma alternativa para obtenção de dados representativos de extensas áreas, tendo em vista que os dados observados em estações meteorológicas são escassos muitas vezes. Todavia, estes produtos de satélite contêm incertezas quando comparados aos dados medidos. O estudo procura avaliar a representatividade das estimativas de chuva oriundas de satélites no estado do Rio Grande do Sul. Para tal utilizaramse produtos do satélite TRMM (3B42 V7), que foram comparados com observados no Estado, disponibilizados pela Agência Nacional de Águas e pelo Instituto Nacional de Meteorologia, no período de 1998 a 2013. O trabalho consistiu em comparar dados de precipitações estimadas e observadas por meio de um conjunto de índices de desempenho, tais como o percentual de detecção de eventos (PC), percentual de acertos (H), percentual de falsos alertas (FAR e F), índice de sucesso crítico (CSI), a razão entre eventos previstos e observados (B), bem como os índices de Heidke (HSS), e Peirce (PSS). Além de outras equações como: coeficiente de correlação (r) erro médio absoluto (EMA), erro médio quadrático (EQM), o coeficiente de eficiência de Nash-Sutcliffe (NS) e viés. Os dados foram comparados em séries diárias e acumulados de 15 e 30 dias, por meio dos seguintes métodos: Pixel a Ponto, Ponto a Ponto, Pixel a Pixel, a partir de Sub-pixels e Análise agregada. Os produtos 3B42 também foram avaliados em relação a capacidade de determinar chuvas intensas, usando como referência equações de intensidade-duração-frequência derivadas de dados observados. Os resultados obtidos pelas metodologias, com exceção da análise de precipitações intensas, não diferenciaram muito entre si. As análises espaciais mostraram a intimidade das avaliações das estimativas tem com a densidade de postos e com as regiões do Rio Grande do Sul, enquanto as análises pontuais indicaram a boa performance do TRMM mesmo na comparação Pixel a Ponto. A medida que as séries diárias foram acumuladas em 15 e 30 dias, os resultados melhoraram. Ficou evidente o decréscimo da qualidade das estimativas na região Leste do RS, onde os efeitos da maritimidade acabam gerando superestimativas.

Le plateau des Guyanes est une région qui est caractérisée à 90% d’une forêt tropicale primaire et compte pour environ 20% des réserves mondiales d’eau douce. Ce territoire naturel, au vaste réseau hydrographique, montre des intensités pluviométriques annuelles atteignant 4000 mm/an ; ce qui fait de ce plateau une des régions les plus arrosées du monde. De plus les précipitations tropicales sont caractérisées par une variabilité spatiale et temporelle importante. Outre les aspects liés au climat, l’impact des précipitations dans cette région du globe est important en termes d’alimentation énergétique (barrages hydroélectriques). Il est donc important de développer des outils permettant d’estimer quantitativement et qualitativement et à haute résolution spatiale et temporelle les précipitations dans cette zone. Cependant ce vaste espace géographique est caractérisé par un réseau de stations pluviométriques peu développé et hétérogène, ce qui a pour conséquence une méconnaissance de la répartition spatio-temporelle précise des précipitations et de leurs dynamiques.Les travaux réalisées dans cette thèse visent à améliorer la connaissance des précipitations sur le plateau des Guyanes grâce à l’utilisation des données de précipitations satellites (Satellite Precipitation Product : SPP) qui offrent dans cette zone une meilleure résolution spatiale et temporelle que les mesures in situ, au prix d’une qualité moindre en terme de précision.Cette thèse se divise en 3 parties. La première partie compare les performances de quatre produits d’estimations satellitaires sur la zone d’étude et tente de répondre à la question : quelle est la qualité de ces produits au Nord de l’Amazone et sur la Guyane française dans les dimensions spatiales et temporelles ? La seconde partie propose une nouvelle technique de correction de biais des SPP qui procède en trois étapes : i) utiliser les mesures in situ de précipitations pour décomposer la zone étudiée en aires hydro-climatiques ii) paramétrer une méthode de correction de biais appelée quantile mapping sur chacune de ces aires iii) appliquer la méthode de correction aux données satellitaires relatives à chaque aire hydro-climatique. On cherche alors à répondre à la question suivante : est-ce que le paramétrage de la méthode quantile mapping sur différentes aires hydro-climatiques permet de corriger les données satellitaires de précipitations sur la zone d’étude ? Après avoir montré l’intérêt de prendre en compte les différents régimes pluviométriques pour mettre en œuvre la méthode de correction QM sur des données SPP, la troisième partie analyse l’impact de la résolution temporelle des données de précipitations utilisées sur la qualité de la correction et sur l’étendue spatiale des données SPP potentiellement corrigeables (données SPP sur lesquelles la méthode de correction peut s’appliquer avec efficacité). Concrètement l’objectif de cette partie est d’évaluer la capacité de notre méthode à corriger sur une large échelle spatiale le biais des données TRMM-TMPA 3B42V7 en vue de rendre pertinente l’exploitation de ce produit pour différentes applications hydrologiques.Ce travail a permis de corriger les séries satellites journalières à haute résolution spatiale et temporelle sur le plateau des Guyanes selon une approche nouvelle qui utilise la définition de zones hydro-climatiques. Les résultats positifs en terme de réduction du biais et du RMSE obtenus grâce à cette nouvelle approche, rendent possible la généralisation de cette nouvelle méthode dans des zones peu équipées en pluviomètres. / The Guiana Shield is a region that is characterized by 90% of a primary rainforest and about 20% of the world’s freshwater reserves. This natural territory, with its vast hydrographic network, shows annual rainfall intensities up to 4000 mm/year; making this plateau one of the most watered regions in the world. In addition, tropical rainfall is characterized by significant spatial and temporal variability. In addition to climate-related aspects, the impact of rainfall in this region of the world is significant in terms of energy supply (hydroelectric dams). It is therefore important to develop tools to estimate quantitatively and qualitatively and at high spatial and temporal resolution the precipitation in this area. However, this vast geographical area is characterized by a network of poorly developed and heterogeneous rain gauges, which results in a lack of knowledge of the precise spatio-temporal distribution of precipitation and their dynamics.The work carried out in this thesis aims to improve the knowledge of precipitation on the Guiana Shield by using Satellite Precipitation Product (SPP) data that offer better spatial and temporal resolution in this area than the in situ measurements, at the cost of poor quality in terms of precision.This thesis is divided into 3 parts. The first part compares the performance of four products of satellite estimates on the study area and attempts to answer the question : what is the quality of these products in the Northern Amazon and French Guiana in spatial and time dimensions ? The second part proposes a new SPP bias correction technique that proceeds in three steps: i) using rain gauges measurements to decompose the studied area into hydro climatic areas ii) parameterizing a bias correction method called quantile mapping on each of these areas iii) apply the correction method to the satellite data for each hydro-climatic area. We then try to answer the following question : does the parameterization of the quantile mapping method on different hydro-climatic areas make it possible to correct the precipitation satellite data on the study area ? After showing the interest of taking into account the different rainfall regimes to implement the QM correction method on SPP data, the third part analyzes the impact of the temporal resolution of the precipitation data used on the quality of the correction and the spatial extent of potentially correctable SPP data (SPP data on which the correction method can be applied effectively). In summary, the objective of this section is to evaluate the ability of our method to correct on a large spatial scale the bias of the TRMM-TMPA 3B42V7 data in order to make the exploitation of this product relevant for different hydrological applications.This work made it possible to correct the daily satellite series with high spatial and temporal resolution on the Guiana Shield using a new approach that uses the definition of hydro-climatic areas. The positive results in terms of reduction of the bias and the RMSE obtained, thanks to this new approach, makes possible the generalization of this new method in sparselygauged areas.

We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products-Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) Morphing Technique (CMORPH)-over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd) as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography) and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ) and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf) matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

As estimativas de chuva por meio do sensoriamento remoto são, atualmente, fonte potencialmente útil para as mais diversas aplicações hidrológicas e climatológicas, especialmente em regiões onde as medições convencionais são escassas, como a Amazônia. Neste trabalho, foram analisadas as estimativas de chuva por satélite como variáveis de entrada ao modelo hidrológico MGB-IPH (Collischonn, 2001). Este modelo simula o ciclo hidrológico através das relações físicas e conceituais de todo processo, sendo os produtos de chuva por satélite avaliados o 3B42, 3B42RT e CMORPH. A primeira área de estudo é a bacia do rio Huallaga localizada dentro do território do Peru, região caracterizada por ter uma topografia complexa e pertencente a uma das nascentes do rio Amazonas. A segunda avaliação foi feita para a bacia do rio Amazonas, sendo esta caracterizada por ter uma grande variabilidade climatológica a diferentes altitudes e regimes hidrológicos diferentes, além de uma pobre distribuição de postos pluviométricos. No caso da bacia do rio Huallaga foram realizadas comparações da chuva média estimada por satélite com observada em intervalos de tempo diário, mensal, sazonal e anual. Estes resultados mostram que os produtos 3B42 e CMORPH subestimam valores médios da bacia comparada com chuva média ponderada por pluviômetros. Na simulação da bacia do rio Huallaga se efetuaram calibrações dos parâmetros para cada fonte de chuva resultando com melhor ajuste de vazões máximas para o produto CMORPH e pior ajuste para o produto 3B42, estes ajustes melhoraram para a chuva do produto CMORPH corrigido com estações pluviométricas. Por outra parte, no caso de análises da bacia do rio Amazonas, foi calculada a chuva média anual para os três produtos de satélite (3B42, 3B42RT e CMORPH), os resultados mostraram maior chuva média a favor de CMORPH, seguido de 3B42RT e finalmente o produto 3B42. A simulação da bacia do rio Amazonas mostrou melhores coeficientes de Nash-Sutcliffe com o produto 3B42 em várias estações do Brasil. Com o produto 3B42RT mostram melhores coeficientes nas estações localizadas na rede principal do rio Amazonas, e com o produto CMORPH mostrou melhores coeficientes em algumas estações como na bacia dos rios Tapajós (Brasil) e Urubamba (Peru). / Currently, satellite rainfall estimates using remote sensing are a potential source of information for hydrological and climatological applications. It applies mainly for regions where conventional measurements are scarce such as the Amazon Basin. In this work, the satellite rainfall estimates were analyzed as input variables to the hydrological model MGBIPH (Collischonn, 2001). This model simulates the hydrological cycle through physical and conceptual relationships where products 3B42, 3B42RT and CMORPH are evaluated. The first evaluation case corresponds to the Huallaga basin located in Peru, being one of the current Amazon highlands characterized by a complex topography. The second evaluation case corresponds to the Amazon basin characterized by a great climatological variability at different altitudes, different hydrological regimes and poor distributions of raingauges. In the case of the Huallaga River basin, comparisons were made between the estimated average satellite rainfall and the observed rainfall for different intervals of time (daily, monthly, seasonal and annual). These results show that the products 3B42 and CMORPH underestimate the basin average rainfall when compared with the weighted average of raingauge measurements. During the Huallaga basin simulation, calibrations of some parameters for each rainfall data were realized. Obtaining the best and worst fitting results with the CMORPH and 3B42 products for the case of maximum discharges, respectively. This rainfall fitting improves for the CMORPH product when raingauge corrections are included. On the other hand, the annual average rainfall value was obtained for each satellite product (3B42, 3B42RT e CMORPH) for the analysis of the Amazon basin. In this calculation, the greater results for the annual average rainfall values are obtained in the following order CMORPH, 3B42RT and 3B42. Moreover, this simulation seems to yield best Nash-Sutcliffe coefficients for the 3B42 product for various Brazilian stations. For stations located in the main stream of the Amazon River the Nash-Sutcliffe coefficients obtained with the 3B42RT product are the best. The CMORPH product yield the best coefficients for the stations located in Tapajós (Brazil) and Urubamba (Peru) basin.

As estimativas de chuva por meio do sensoriamento remoto são, atualmente, fonte potencialmente útil para as mais diversas aplicações hidrológicas e climatológicas, especialmente em regiões onde as medições convencionais são escassas, como a Amazônia. Neste trabalho, foram analisadas as estimativas de chuva por satélite como variáveis de entrada ao modelo hidrológico MGB-IPH (Collischonn, 2001). Este modelo simula o ciclo hidrológico através das relações físicas e conceituais de todo processo, sendo os produtos de chuva por satélite avaliados o 3B42, 3B42RT e CMORPH. A primeira área de estudo é a bacia do rio Huallaga localizada dentro do território do Peru, região caracterizada por ter uma topografia complexa e pertencente a uma das nascentes do rio Amazonas. A segunda avaliação foi feita para a bacia do rio Amazonas, sendo esta caracterizada por ter uma grande variabilidade climatológica a diferentes altitudes e regimes hidrológicos diferentes, além de uma pobre distribuição de postos pluviométricos. No caso da bacia do rio Huallaga foram realizadas comparações da chuva média estimada por satélite com observada em intervalos de tempo diário, mensal, sazonal e anual. Estes resultados mostram que os produtos 3B42 e CMORPH subestimam valores médios da bacia comparada com chuva média ponderada por pluviômetros. Na simulação da bacia do rio Huallaga se efetuaram calibrações dos parâmetros para cada fonte de chuva resultando com melhor ajuste de vazões máximas para o produto CMORPH e pior ajuste para o produto 3B42, estes ajustes melhoraram para a chuva do produto CMORPH corrigido com estações pluviométricas. Por outra parte, no caso de análises da bacia do rio Amazonas, foi calculada a chuva média anual para os três produtos de satélite (3B42, 3B42RT e CMORPH), os resultados mostraram maior chuva média a favor de CMORPH, seguido de 3B42RT e finalmente o produto 3B42. A simulação da bacia do rio Amazonas mostrou melhores coeficientes de Nash-Sutcliffe com o produto 3B42 em várias estações do Brasil. Com o produto 3B42RT mostram melhores coeficientes nas estações localizadas na rede principal do rio Amazonas, e com o produto CMORPH mostrou melhores coeficientes em algumas estações como na bacia dos rios Tapajós (Brasil) e Urubamba (Peru). / Currently, satellite rainfall estimates using remote sensing are a potential source of information for hydrological and climatological applications. It applies mainly for regions where conventional measurements are scarce such as the Amazon Basin. In this work, the satellite rainfall estimates were analyzed as input variables to the hydrological model MGBIPH (Collischonn, 2001). This model simulates the hydrological cycle through physical and conceptual relationships where products 3B42, 3B42RT and CMORPH are evaluated. The first evaluation case corresponds to the Huallaga basin located in Peru, being one of the current Amazon highlands characterized by a complex topography. The second evaluation case corresponds to the Amazon basin characterized by a great climatological variability at different altitudes, different hydrological regimes and poor distributions of raingauges. In the case of the Huallaga River basin, comparisons were made between the estimated average satellite rainfall and the observed rainfall for different intervals of time (daily, monthly, seasonal and annual). These results show that the products 3B42 and CMORPH underestimate the basin average rainfall when compared with the weighted average of raingauge measurements. During the Huallaga basin simulation, calibrations of some parameters for each rainfall data were realized. Obtaining the best and worst fitting results with the CMORPH and 3B42 products for the case of maximum discharges, respectively. This rainfall fitting improves for the CMORPH product when raingauge corrections are included. On the other hand, the annual average rainfall value was obtained for each satellite product (3B42, 3B42RT e CMORPH) for the analysis of the Amazon basin. In this calculation, the greater results for the annual average rainfall values are obtained in the following order CMORPH, 3B42RT and 3B42. Moreover, this simulation seems to yield best Nash-Sutcliffe coefficients for the 3B42 product for various Brazilian stations. For stations located in the main stream of the Amazon River the Nash-Sutcliffe coefficients obtained with the 3B42RT product are the best. The CMORPH product yield the best coefficients for the stations located in Tapajós (Brazil) and Urubamba (Peru) basin.

As estimativas de chuva por meio do sensoriamento remoto são, atualmente, fonte potencialmente útil para as mais diversas aplicações hidrológicas e climatológicas, especialmente em regiões onde as medições convencionais são escassas, como a Amazônia. Neste trabalho, foram analisadas as estimativas de chuva por satélite como variáveis de entrada ao modelo hidrológico MGB-IPH (Collischonn, 2001). Este modelo simula o ciclo hidrológico através das relações físicas e conceituais de todo processo, sendo os produtos de chuva por satélite avaliados o 3B42, 3B42RT e CMORPH. A primeira área de estudo é a bacia do rio Huallaga localizada dentro do território do Peru, região caracterizada por ter uma topografia complexa e pertencente a uma das nascentes do rio Amazonas. A segunda avaliação foi feita para a bacia do rio Amazonas, sendo esta caracterizada por ter uma grande variabilidade climatológica a diferentes altitudes e regimes hidrológicos diferentes, além de uma pobre distribuição de postos pluviométricos. No caso da bacia do rio Huallaga foram realizadas comparações da chuva média estimada por satélite com observada em intervalos de tempo diário, mensal, sazonal e anual. Estes resultados mostram que os produtos 3B42 e CMORPH subestimam valores médios da bacia comparada com chuva média ponderada por pluviômetros. Na simulação da bacia do rio Huallaga se efetuaram calibrações dos parâmetros para cada fonte de chuva resultando com melhor ajuste de vazões máximas para o produto CMORPH e pior ajuste para o produto 3B42, estes ajustes melhoraram para a chuva do produto CMORPH corrigido com estações pluviométricas. Por outra parte, no caso de análises da bacia do rio Amazonas, foi calculada a chuva média anual para os três produtos de satélite (3B42, 3B42RT e CMORPH), os resultados mostraram maior chuva média a favor de CMORPH, seguido de 3B42RT e finalmente o produto 3B42. A simulação da bacia do rio Amazonas mostrou melhores coeficientes de Nash-Sutcliffe com o produto 3B42 em várias estações do Brasil. Com o produto 3B42RT mostram melhores coeficientes nas estações localizadas na rede principal do rio Amazonas, e com o produto CMORPH mostrou melhores coeficientes em algumas estações como na bacia dos rios Tapajós (Brasil) e Urubamba (Peru). / Currently, satellite rainfall estimates using remote sensing are a potential source of information for hydrological and climatological applications. It applies mainly for regions where conventional measurements are scarce such as the Amazon Basin. In this work, the satellite rainfall estimates were analyzed as input variables to the hydrological model MGBIPH (Collischonn, 2001). This model simulates the hydrological cycle through physical and conceptual relationships where products 3B42, 3B42RT and CMORPH are evaluated. The first evaluation case corresponds to the Huallaga basin located in Peru, being one of the current Amazon highlands characterized by a complex topography. The second evaluation case corresponds to the Amazon basin characterized by a great climatological variability at different altitudes, different hydrological regimes and poor distributions of raingauges. In the case of the Huallaga River basin, comparisons were made between the estimated average satellite rainfall and the observed rainfall for different intervals of time (daily, monthly, seasonal and annual). These results show that the products 3B42 and CMORPH underestimate the basin average rainfall when compared with the weighted average of raingauge measurements. During the Huallaga basin simulation, calibrations of some parameters for each rainfall data were realized. Obtaining the best and worst fitting results with the CMORPH and 3B42 products for the case of maximum discharges, respectively. This rainfall fitting improves for the CMORPH product when raingauge corrections are included. On the other hand, the annual average rainfall value was obtained for each satellite product (3B42, 3B42RT e CMORPH) for the analysis of the Amazon basin. In this calculation, the greater results for the annual average rainfall values are obtained in the following order CMORPH, 3B42RT and 3B42. Moreover, this simulation seems to yield best Nash-Sutcliffe coefficients for the 3B42 product for various Brazilian stations. For stations located in the main stream of the Amazon River the Nash-Sutcliffe coefficients obtained with the 3B42RT product are the best. The CMORPH product yield the best coefficients for the stations located in Tapajós (Brazil) and Urubamba (Peru) basin.

Les travaux réalisés au cours de cette Thèse ont contribué à améliorer l'estimation de l'humidité de surface du sol et de l'humidité racinaire sur la bande sahélienne en Afrique de l'ouest. La première partie a été consacrée à évaluer la capacité de différents algorithmes d'estimations de l'humidité du sol basées sur des mesures satellites dans le domaine spectral de l'infrarouge thermique. Dans un deuxième temps, une méthode a été développée dans le but d'obtenir une cartographie de l'humidité du sol à une résolution temporelle fine (< 3h) en se basant sur deux produits satellites: un produit satellite de précipitation et une cartographie journalière micro-onde sensible à l'humidité du sol. Dans un troisième temps, une évaluation de la fiabilité et de la robustesse de la méthodologie a été proposée. Enfin, une méthode semi-empirique a été utilisée afin de produire une cartographie de l'humidité de la zone racinaire (0-1 m) sur l'ensemble de la bande sahélienne. Les mesures de terrain obtenues sur trois sites situés au Mali, au Niger et au Bénin dans le cadre du programme AMMA ont servi de référence pour évaluer la qualité des estimations de l'humidité superficielle et racinaire à chaque étape de ce travail. Les résultats montrent qu'une estimation de l'humidité superficielle du sol est possible avec une précision de moins de 3 % vol. sur la bande sahélienne. L'erreur est de l'ordre de 5% vol. sur la zone soudanienne (Bénin). La précision est identique sur l'estimation de l'humidité racinaire. Enfin, la méthode développée permet parallèlement de corriger les produits satellites de précipitation et notamment la surestimation du cumul annuel et du nombre d'événements des trois produits satellites utilisés dans ce travail.