Le modèle de neige est souvent dépendant du modèle hydrologique avec lequel il est couplé, ce qui peut favoriser la représentation du débit au détriment de celle de la neige. L'objectif est de rendre le calage du modèle de neige plus indépendant de celui du modèle hydrologique en restant facilement utilisable en opérationnel. Dans cette optique, un modèle contraint sur des données d'observations de la neige permettrait d'améliorer d'une part la robustesse des paramètres du modèle de neige et d'autre part la simulation de l'état du manteau neigeux. Dans la première partie de cette thèse, nous avons étudié et modifié le modèle degrés-jour semi-distribué CemaNeige afin qu'il puisse simuler de manière plus réaliste la variable de surface d'enneigement du bassin versant. Cette modification, couplée au calage du modèle sur des données de surface enneigée et sur le débit, a permis d'améliorer la simulation de l'enneigement par le modèle sans détériorer significativement les performances en débits. Nous alors ensuite débuté le développement d'un nouveau modèle de neige à l'échelle ponctuelle. Celui-ci se compose d'un modèle de rayonnements, simulant les rayonnements incidents à partir de données d'amplitude de températures journalières, et d'un modèle de manteau neigeux. Le modèle de manteau neigeux résout les équations de la chaleur au sein du manteau neigeux à l'aide d'une représentation spectrale du profil de température. Cette représentation permet de simuler les profils et gradients de températures en utilisant moins de variables d'état qu'une discrétisation verticale par couches. Pour mieux prendre en compte les mesures ponctuelles de neige, ce modèle devra être distribué. / Snow models are often dependent on the hydrological model they are coupled with, which can promote higher performance on runoff simulation at the expense of snow state simulations performances. The objective of this thesis is to make the calibration of the snow model more independent from the calibration of the hydrological model, while remaining easily usable for runoff forecasting. Calibrating snow model on observed snow data would on one hand improve the robustness of the snow model parameters and on the other hand improve the snowpack modelling. In the first part of this manuscript, we modified the semi-distributed CemaNeige degree-day model so that it can explicitly simulate the watershed snow cover area. This modification coupled with the calibration of the model on snow cover area data and on river runoff data significantly improved the simulation of the snow cover area by the model without significantly deteriorating the runoff performances. Then we started the development of a new point scale snow model. It is based on a radiation model, which simulates incoming radiations from daily temperature range data, and a snowpack model. The snowpack model solves the heat equations within the snowpack by using a spectral representation of the temperature profile. This representation simulates the temperature profile and gradients using fewer state variables than a vertical discretization of the snowpack. In order to be able to use point scale snow observations in the model, it should be distributed on the watershed.

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WATCLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P-E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WATCLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P-E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.

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.

Estudos hidrológicos são extremamente importantes em projetos de obras lineares, nas quais o traçado deve minimizar o risco de instabilidade tanto na fase de construção como na fase de operação. O escoamento superficial, além de ser um parâmetro fundamental para a definição do traçado e dos projetos subsequentes, influencia diretamente a dinâmica dos processos geológico-geotécnicos na área do empreendimento. A presente pesquisa propõe um método para realizar uma estimativa das vazões máximas nas travessias de obras civis lineares, integrando modelos hidrológicos obtidos com Sistema de Informação Geográfica (SIG) e métodos usuais de cálculo de vazões de cheia. O método foi aplicado em um setor do oleoduto São Paulo – Brasília (OSBRA), entre os municípios de São Simão e Cravinhos (SP). O modelo hidrológico foi obtido no software ArcGIS 9.3, a partir da definição de uma área mínima de contribuição de 5 hectares, adequada para a escala da base cartográfica digital (1:10.000) e para as características da área de estudo. As 29 bacias de contribuição delimitadas foram posteriormente validadas na vistoria de campo. A compatibilidade entre as bacias geradas pelo modelo hidrológico e as bacias identificadas visualmente na área de estudo foi satisfatória. As vazões máximas foram calculadas pelo Método Racional (bacias com área inferior a 2 km²) e pelo Método Racional Modificado (bacias com área superior a 2 km²), que abrangeu o Método de McMath, o Método Racional com expoente redutor de área e o Método Racional com coeficiente de retardo, sendo o último o que apresentou os resultados mais razoáveis. O cálculo das vazões de cheia foi realizado para períodos de retorno de 10 e 50 anos, a partir dos quais foram gerados Mapas de Vazões Máximas, que foram utilizados para inferência de riscos de eventos perigosos de natureza geológico-geotécnica causados pela ação das águas pluviais na região do oleoduto. Como o traçado do oleoduto foi posicionado ao longo dos divisores principais, não foram identificados locais críticos. Posteriormente, o traçado do oleoduto foi utilizado como referência para uma aplicação do método proposto em um projeto de drenagem. As bacias com valores de vazões máximas classificados com muito baixos não foram incluídas devido aos fluxos pouco significativos. Para as bacias com valores de vazões de cheia classificados como baixos e médios, sugeriu-se a utilização de dispositivos de drenagem superficial. Para as bacias com vazões máximas classificadas como altas e muito altas, foi proposta a utilização de dispositivos de drenagem de transposição de talvegues. Os resultados obtidos na pesquisa permitiram a consolidação do método proposto para aplicação em outros tipos de obras lineares e em locais com diferentes características ambientais. / Hydrological studies are extremely important in linear constructions projects, in which the routing must minimize the risk of instability both during construction and in operation phase. The surface runoff, in addition of being a fundamental parameter to routing definition and subsequent projects, directly influences the dynamics of geological-geotechnical processes in the enterprise area. The present research proposes a method to estimate maximum flows in crossing locations in linear civil constructions, integrating hydrological models obtained with Geographic Information System (GIS) and usual methods of peak flows calculation. The method was applied in a sector of São Paulo – Brasília (OSBRA) oil pipeline, between the municipalities of São Simão and Cravinhos (SP). The hydrological model was obtained in ArcGIS 9.3 software, from the definition of a minimal area of contribution of 5 hectares, adequate for the scale of the digital cartographic base (1:10.000) and for the study area characteristics. The 29 delimited watersheds were subsequently validated in the field visit. The compatibility between watersheds generated in the hydrological model and watersheds visually identified in the study area was satisfactory. The maximum flows were calculated by Rational Method (watersheds with area less than 2 km²) e by Modified Rational Method (watersheds with area higher than 2 km²), which included McMath Method, Rational Method with reducing exponent area and Rational Method with retard coefficient, and the latter presented the most reasonable results. Peak flows calculation was performed for return periods of 10 and 50 years, from which were generated Maximum Flows Maps, which were used for inference of risks of hazardous events of geological-geotechnical nature caused by rainwater action in the pipeline region. The pipeline routing was positioned along the main dividers, therefore critical locations were not identified. Subsequently, the pipeline routing was used as a reference for application of the proposed method in a drainage project. Basins with maximum flows classified as very low were not included due to its low significance flows. For basins with peak flows values classified as low and medium, it was suggested the use of surface drainage devices. For basin with maximum flows classified as high and very high, it was proposed the use of thalwegs transposition drainage devices. The results obtained in the research allowed the consolidation of the proposed method to application in other types of linear constructions and in locals with different environmental characteristics.

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.

Studies from the Forestry Institute of São Paulo State have shown that in the end of the 20th century, the native forest cover of the state of SP reached the maximum level of forest loss. From that point on, a period of forest increase and expansion started. Industrialization, law enforcement, economic benefits, and social pressure experienced in recent years are believed to be contributing to the preservation and regrowth of the native vegetation cover in certain locations. This study proposed to model the dynamics of native vegetation cover in the Piracicaba River basin (12,500 km²) in the state of São Paulo, Brazil, to evaluate possible effects of these changes in ecosystem services related to river flow & regulation and landscape structure, linking to biodiversity & habitat supported by forest patches. To achieve the proposal set out in this research, dynamic models of native vegetation were established. Thematic land cover maps of the years 1990, 2000 and 2010, originated from Landsat 5 TM images, formed the spatiotemporal basis of this study. With the aid of Dinamica EGO (a dynamic modeling software), three future scenarios were created, called status quo (SQ), no deforestation (ND) and riparian restoration enforcement (RRE). An analysis using weights of evidence was done to identify forest transition drivers. The drivers are divided into two groups, (1) environmental & physical, consisting of soil types, hydrographic network, rainfall and presence of native forest fragments and (2) anthropic, consisting of population density, gross national product, road network, urban patches and predominant rural activities. Resulting scenarios were analyzed by means of landscape metrics to compare and qualify vegetation patches in relation to structure as proxy for supporting ecosystem services. Finally, Soil & Water Assessment Tool (SWAT), a hydrological model, was used to determine the influence of different forest scenarios in mean annual water yield and regulation processes throughout the basin, and, therefore, compare scenarios as to effects on regulating ecosystem services. Results show that forest transition is indeed occurring, with native vegetation cover parting from 24.4% in 1990, to 20.1% in 2000 and 21.8% in 2010. Scenario results were of 22.4% (SQ), 43.2% (ND) and 28.4% (RRE) for 2050. Forest loss was identified as a product of anthropogenic drivers while regrowth was of physical & environmental drivers. When the area was segmented, regions with greater environmental condition resulted in improved values of landscape structure. SQ scenario was the most affected, losing small patches of forest that could function as structural connectors, and therefore potentially affect biodiversity and habitat. Mean annual water yield was reduced with forest regrowth by as much as 10.3% in ND. We concluded that the dynamics occurring in the landscape and the proposed scenarios affect mean annual water yield, regulation and landscape structure, allowing us to discuss differences between the scenarios and the relation between forest dynamics, landscape structure, hydrology and overtime potential effects over regulating and supporting ecosystem services. / Levantamentos do Instituto Florestal de São Paulo têm mostrado que no final do século XX a cobertura florestal nativa total do estado atingiu um patamar de perda e que se iniciou então um período de expansão. Rigidez de leis, fiscalização, benefícios econômicos, além de pressão social demonstrados nos últimos anos têm contribuído para essa expansão da vegetação nativa em certos locais. Este estudo propôs modelar a dinâmica da cobertura florestal nativa na bacia do Rio Piracicaba (12.500 km2), localizada no Estado de São Paulo, para averiguar os possíveis efeitos dessas mudanças nos serviços ecossistêmicos ligados à vazão e regulação de rios, além da própria estrutura da paisagem simulada, interligando-se com biodiversidade e habitat, promovidos pelos remanescentes florestais. Para atingir a proposta estabelecida nesta pesquisa, modelos de dinâmica da vegetação nativa foram desenvolvidos. Foram utilizados mapas temáticos de cobertura e uso do solo dos anos 1990, 2000 e 2010 originados a partir de imagens Landsat 5 TM. Com auxílio do software Dinamica EGO, especializado em modelagem da paisagem, criaram-se três modelos espaciais e temporais da dinâmica florestal, levando em consideração os cenários status quo (SQ), no deforestation (ND) e riparian restoration enforcement (RRE). Uma análise usando pesos de evidência foi utilizada para identificar as variáveis de transição florestal. As variáveis foram divididas em dois grupos, (1) físicas e ambientais, consistindo de tipos de solo, rede de drenagem, pluviosidade e presença de fragmentos florestais e (2) antrópicos, consistindo de densidade populacional, produto interno bruto, rede viária, zonas urbanas e predominância de atividade rural. Os cenários resultantes foram analisados por métricas de paisagem para fim de comparação e qualificação dos fragmentos em relação a sua estrutura, interligando-se aos serviços ecossistêmicos de suporte. Por último, foi realizada uma modelagem hidrológica usando o modelo Soil & Water Assessment Tool (SWAT) para averiguar a influência da mudança florestal na regulação de vazão de rios e portanto comparar os cenários em relação aos seus efeitos sobre serviços ecossistêmicos de regulação interligados à água. Resultados mostraram que transição florestal ocorreu, passando a cobertura florestal de 24,4% em 1990 para 20,1% em 2000 e então 21,8% em 2010. Cenários resultaram em uma cobertura florestal de 22,4% (SQ), 43,2% (LE) e 28,4% (RRE) para o ano de 2050. A perda de floresta foi identificada como produto de variáveis de natureza antrópica enquanto o ganho florestal foi de variáveis físicas e ambientais. Regiões com melhores condições ambientais resultaram em melhores valores de estrutura da paisagem. SQ foi afetado principalmente pela perda de pequenos fragmentos florestais que funcionam como conectores estruturais da paisagem, potencialmente afetando a biodiversidade e habitat. O deflúvio médio anual foi reduzido em até 10,3% com o incremento florestal observado em ND. Conclui-se que a cobertura florestal na paisagem e os cenários propostos afetam o deflúvio, regulação e a estrutura da paisagem, nos permitindo discutir nas diferenças entre cada cenário e a relação entre dinâmica florestal, estrutura da paisagem, hidrologia e potenciais efeitos nos serviços ecossistêmicos de suporte e regulação.

Les environnements montagneux sont un lieu privilégié d'échange d'eau et d'énergie. Les rivières de montagne alimentent en eau 40% de la population mondiale et sont sujettes à une pression démographique et climatique important. Dans ce contexte, la compréhension des processus météorologiques, hydrologiques et hydrogéologiques est fondamentale pour la gestion globale de la ressource en eau. L'étude, présentée dans ce manuscrit de thèse, se positionne au sein des environnements montagneux où l'hydrologie est influencée par le couvert neigeux saisonnier et par les glaciers, et propose une approche de modélisation interdisciplinaire afin d'améliorer la compréhension des processus en jeu.Aujourd'hui, si les modèles sont capables de simuler le débit sur les rivières de montagnes jaugées sous influence nivale et glaciaire, un certain nombre d'incertitudes persistent quant à l'utilisation de tels modèles hors de leur conditions de validation (en réponse à un climat différent ou sur un domaine non-jaugé). La principale source d'incertitude est liée au manque de connaissance des précipitations en montagne, dont la mesure est rare et incertaine. C'est pourtant la principale composante du bilan hydrologique. A cet égard, nous proposons d'exploiter l'information fournie par la géométrie du couvert neigeux et des glaciers, en tant que “pluviomètres géants” à l'échelle de ces réservoirs, dans un modèle hydrologique à réservoirs conceptuels reposant sur la notion de bassin versant.L'information, hydrologique, nivale et glaciaire est évaluée dans un cadre de calibration multi-objectifs. Les résultats montrent que, dans cette configuration, la validation conjointe du modèle hydrologique par le débit journalier, le bilan de masse glaciaire annuel et la hauteur de neige locale journalier permet de réduire fortement l'incertitude sur le forçage météorologique journalier et d'améliorer la robustesse du modèle. Ce résultat préliminaire nous a permis de reconstruire, en conséquence, le bilan de masse local annuel à l'échelle des glaciers.Par ailleurs, la représentation des glaciers au sein d'un modèle hydrologique pose un certain nombre de défis, surtout dans la perspective de simuler les processus hydrologiques à l'échelle pluri-annuelle. En particulier, la prise en compte de l'évolution de la géométrie des glaciers au sein d'un modèle hydrologique est balbutiante. A cet égard, nous proposons, dans cette étude, des axes d'amélioration de la représentation des glaciers au sein d'un modèle hydrologique par un angle d'investigation géomorphologique. Cette approche a permis d'élaborer un modèle probabiliste permettant de décrire les surfaces englacées au sein d'un bassin versant selon une courbe de niveau. / Mountainous environments are a privileged place of water and energy exchange. Mountainous rivers feed about 40% of the world population and are subjected to climate change and a growing demography. In this context, the comprehension of meteorological, hydrological and hydrogeological processes is essential for a better overall management of water resource. This PhD study is focused squarely on the mountainous environments where hydrology is influenced by snow cover and glaciers, and introduces a multidisciplinary modeling approach in order to improve our comprehension of the process involved.Today, hydrological models are able to simulate gauged mountainous river streamflows under the influence of snow and glaciers but some uncertainties remain when applying such models out of their calibration phase (for instance in response to a different climate or on a ungauged basin). The main uncertainty source is the lack of knowledge of mountainous precipitations, whose measure is sparse and uncertain. It remains the principal component of the hydrological budget though. In this study, we suggest using the meteorological information provided by snow cover and glaciers as “giant pluviometers” to their reservoir scales, with a conceptual reservoir model associated with the concept of watershed.The information provided by hydrology processes, snow and glaciers is assessed in a multi-objective calibration phase. Results show that, in this configuration, the joint validation of the hydrological model by daily streamflow, annual mass balance and daily local snow depth reduces significantly the uncertainty on the meteorological forcing and improves the model robustness. This preliminary result has motivated, consequently, the local annual mass balance of the glaciers.Also, the representation of glaciers in a hydrological model raises a certain amount of issues, especially in the perspective of simulation long-term hydrological processes. In particular, the consideration of the evolution of the glacier geometry is at an early stage. To this end, we propose, in this study, ways of improvements for the representation of glaciers from a geomorphological perspective. This approach allowed us to build a probabilistic model able to describe the glaciated surfaces within a watershed according to a given topographic contour line.

abstract: The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) will provide the next generation of operational streamflow forecasts at different lead times across United States using the Weather Research and Forecasting (WRF)-Hydro hydrologic system. These forecasts are crucial for flood protection agencies and water utilities, including the Salt River Project (SRP). The main goal of this study is to calibrate WRF-Hydro in the Oak Creek Basin (OCB; ~820 km2), an unregulated mountain sub-watershed of the Salt and Verde River basins in Central Arizona, whose water resources are managed by SRP and crucial for the Phoenix Metropolitan area. As in the NWM, WRF-Hydro was set up at 1-km (250-m) resolution for the computation of the rainfall-runoff (routing) processes. Model forcings were obtained by bias correcting meteorological data from the North American Land Data Assimilation System-2 (NLDAS-2). A manual calibration approach was designed that targets, in sequence, the sets of model parameters controlling four main processes responsible for streamflow and flood generation in the OCB. After a first calibration effort, it was found that WRF-Hydro is able to simulate runoff generated after snowmelt and baseflow, as well as magnitude and timing of flood peaks due to winter storms. However, the model underestimates the magnitude of flood peaks caused by summer thunderstorms, likely because these storms are not captured by NLDAS-2. To circumvent this, a seasonal modification of soil parameters was adopted. When doing so, acceptable model performances were obtained during calibration (2008-2011) and validation (2012-2017) periods (NSE > 0.62 and RMSE = ~2.5 m3/s at the daily time scale). The process-based calibration strategy utilized in this work provides a new approach to identify areas of structural improvement for WRF-Hydro and the NWM. / Dissertation/Thesis / Masters Thesis Civil, Environmental and Sustainable Engineering 2020