O presente trabalho tem por finalidade o uso da abordagem bayesiana para a estimativa de parâmetros sazonais dos modelos periódicos auto-regressivos (PAR). Após a determinação dos estimadores bayesianos, estes são comparados com os estimadores de máxima verossimilhança. A previsão para 12 meses é realizada usando os dois estimadores e os resultados comparados por meio de gráficos, tabelas e pelos erros de previsão. Para ilustrar o problema as séries escolhidas foram as séries hidrológicas da Usinas Hidroelétricas de Furnas e Emborcação. Tais séries foram selecionadas tendo em vista a necessidade de previsões com reduzido erro já que o sistema de operação das usinas hidroelétricas depende muito da quantidade de água existente em seus reservatórios e de planejamento e gerenciamento eficazes. / The objective of this research is to use bayesian method to estimate of sazonal parameters of periodic autoregressive models (PAR). The bayesian estimators are then compared with maximum likelihood estimators. The forecast for 12 months is made by using two estimators and comparing their results though graphs, tables and forecast error. The hydrological time series chosen were from Furnas and Emborcação Hydroeletric Power Plant. These series were chosen having in mind the necessity of series with reduced error in their forecast because system of operation in the Hydroeletric Power Plant depends on the quantity of the water in their resevoirs, eficient planning and management.

La mobilisation et la gestion de l’eau de surface constitue la clé de voûte du bien-être social et économique des populations des zones arides d’Afrique de l’Ouest. Cependant l’utilisation des outils de gestion et de prédétermination hydrologique est entravée par les changements climatiques et environnementaux que connait l’Afrique de l’Ouest depuis les années 1970. Les impacts de ces changements sont assez bien documentés sur les caractéristiques moyennes des régimes hydrologiques mais le sont moins lorsqu’on s’intéresse aux caractéristiques des extrêmes. Cette thèse s’inscrit dans le cadre d’une contribution à un projet d’actualisation des normes hydrologiques en Afrique de l’Ouest, et constitue le premier pas essentiel pour ce projet. Son objectif général est de caractériser les régimes de crues dans la région en répondant aux questions suivantes : Quelles sont les évolutions observées sur les régimes des crues en Afrique de l’Ouest ? Ces évolutions sont-elles en rapport avec les changements climatiques et/ou les modifications environnementales ? Quels sont les scénarii possibles de l’évolution des crues au regard des simulations climatiques futures ? La difficulté majeure de ce travail est liée à la disponibilité des données hydro climatiques et environnementales dans la région, aussi, l’analyse s’est basée sur des outils reconnus robustes dans la littérature. Dans un premier temps, l’utilisation des données de 14 stations hydrométriques de la région... / Water resources plays a key role in the social progress and economic development of west african countries. But the mobilization of water is hampered by climate and environmental changes that undergoes the region since 1970. Extremes parts of hydrological regimes are also impacted, but less studies have focus on their evolution, in relation with climate and environmental changes. The main objective of this thesis is to characterize hydrological extreme events in West Africa, we tried to answer the following questions:- What are the trends of maximum discharge in west Africa?- Are these trends due to climate changes or enviromental changes?- Which speculations can be made from these evolutions, according to future climate simulations?In the first part of the work, we analyzed the trends of floods over 14 watersheds of the region. This analysis allowed us to highlight a clustering behavior of flood according to the climatic region the catchments belong to. Increasing trends have been found on flood magnitude and flood frequency of the 3 sahelian catchments used, and decreasing trends of flood magnitude were found on three sudanian catchments. Finally, the remaining catchments did not showed significant trend in their flood regime...

A modelagem matemática da hidrologia de bacias hidrográficas é largamente utilizada em estudos de diversos tipos de problemas encontrados na engenharia hidráulica e de recursos hídricos. Nestes últimos 150 anos, muitos pesquisadores realizaram observações e experimentos sobre a natureza do ciclo hidrológico para que pudessem entender e equacionar seu comportamento. Diversos modelos diferentes surgiram baseando-se em equacionamentos físicos e empíricos, sendo que muitos destes modelos clássicos são utilizados até hoje. Para se ter uma visão mais abrangente do tema, uma revisão do estado da arte é apresentada, com uma perspectiva histórica destes modelos e seus criadores, assim como uma classificação fundamentada em suas características. Também são examinados alguns dos sistemas computacionais para modelagem hidrológica de bacias hidrográficas mais utilizados atualmente. São discutidas as hipóteses de uma simplificação do ciclo hidrológico para eventos intensos utilizados em projetos. Cada componente do ciclo hidrológico simplificado é modelado utilizando um dos diferentes modelos hidrológicos propostos, com graus de complexidade distintos. Para cada um destes modelos é realizada uma análise de sensibilidades dos seus parâmetros. Baseado nos avanços tecnológicos mais recentes na ciência da computação foi desenvolvido, em paralelo a esta pesquisa, uma ferramenta computacional que compila todos os conceitos aqui apresentados e tem distribuição acadêmica livre. / The mathematical modeling of the watershed hydrology is widely used in studies of several problems related to hydraulic and water resources engineering. On these last 150 years, many researchers accomplished observations and experiments on the nature of the hydrologic cycle in order to understand and equates its behavior. Several different models appeared basing on physical and empiric equating, and many of these classic models are being used until today. To get a more comprehensive view on the theme, a state of the art revision is presented, with an historical perspective about these models and its creators, such as a classification based on its characteristics are presented. Also some computational systems of hydrologic modeling of watershed are also examined more used now. The hypotheses of a simplification of the hydrologic cycle are discussed for intense events used in projects. Each component of the simplified hydrologic cycle is modeled using one of the different hydrologic models proposed, with distinct grades of complexity. For each one of these models a sensibility analysis of their parameter is performed. Based on the more recent technological progresses in the computational science was developed, parallel to this research, a computational tool that compiles all the concepts here presented and has free academic distribution.

Sob a perspectiva de aumento da demanda global por biocombustíveis, em particular o etanol durante as próximas décadas, espera-se um crescimento ainda maior da indústria sucroalcooleira no Brasil. Aliada à expansão da cultura da cana-de-açúcar, as bacias nas quais se inserem esses plantios estão sujeitas a alterações no regime hidrológico, bem como à elevação do uso de fertilizantes nitrogenados, o que possui implicações na quantidade e qualidade da água nos corpos hídricos. Com intuito de avaliar esses impactos, o presente estudo visou caracterizar as vias hidrológicas e o transporte de nitrogênio associado a elas em vertentes cobertas por cana-de-açúcar localizadas em microbacias do Rio Corumbataí, noroeste do estado de São Paulo. Para isso, foram monitorados alguns processos hidrológicos, entre eles: precipitação total, precipitação interna, escoamento pelo caule, escoamento superficial, umidade do solo em quatro profundidades (15 cm, 30 cm, 50 cm e 90 cm) e deflúvio durante período de 21 de julho de 2012 a 22 de maio de 2013. A precipitação totalizou 1095 mm durante o período de estudo, dos quais em torno de 35% foram interceptados pela cultura. Não foram encontradas diferenças significativas entre o efeito de diferentes variedades de cana-de-açúcar no que se refere às perdas por interceptação. Além dessa, a parcela de água de chuva escoada pelo caule, a precipitação interna, o escoamento superficial e o deflúvio corresponderam, respectivamente, a 14%, 51%, 4,7% e 7,7% do total precipitado. Nesses compartimentos hidrológicos, de um modo geral, foram observadas baixas concentrações de nitrogênio, com exceção ao escoamento superficial, que apresentou altas concentrações, principalmente de nitrato. O aporte (deposição) de nitrogênio ao sistema, 2,81 kg N ha-¹, foi superior à perda fluvial: 0,45 kg N ha-¹ / The recent years have shown us that there is a perspective of increasing the global biofuels demand, particularly ethanol. In conjunction with the expansion of sugarcane crop, the watersheds in which these crops are founded are subject to hydrological changes, as well as the elevation of the use of nitrogen fertilizers. It has implications in the quantity and quality of water in streams. In order to assess these impacts, the present study aimed to characterize the hydrological flow paths and the associated nitrogen transport in hillslopes under sugarcane in two small watersheds at Corumbataí River, northwest of São Paulo. For this, we monitored some hydrological flow paths, including: gross rainfall, throughfall, stemflow, surface runoff, soil moisture at four depths (15 cm, 30 cm, 50 cm and 90 cm) and streamflow during period of 21 July 2012 to May 22, 2013. Gross rainfall was 1095 mm and around 35% was intercepted by the sugarcane canopy. No significant differences between different varieties of sugarcane were found for interception losses. In addition, rainfall was partitioned into stemflow, throughfall, surface runoff and streamflow as the following: 14%, 51%, 4.7% and 7.7%, respectively. Hydrological flow paths in general carried low nitrogen concentration, being the surface runoff the exception, which carried high levels of nitrate. The nitrogen input in the system was 2.81 kg N ha-¹, and the loss by streamflow was 0.45 kg N ha-1

O presente trabalho tem por finalidade o uso da abordagem bayesiana para a estimativa de parâmetros sazonais dos modelos periódicos auto-regressivos (PAR). Após a determinação dos estimadores bayesianos, estes são comparados com os estimadores de máxima verossimilhança. A previsão para 12 meses é realizada usando os dois estimadores e os resultados comparados por meio de gráficos, tabelas e pelos erros de previsão. Para ilustrar o problema as séries escolhidas foram as séries hidrológicas da Usinas Hidroelétricas de Furnas e Emborcação. Tais séries foram selecionadas tendo em vista a necessidade de previsões com reduzido erro já que o sistema de operação das usinas hidroelétricas depende muito da quantidade de água existente em seus reservatórios e de planejamento e gerenciamento eficazes. / The objective of this research is to use bayesian method to estimate of sazonal parameters of periodic autoregressive models (PAR). The bayesian estimators are then compared with maximum likelihood estimators. The forecast for 12 months is made by using two estimators and comparing their results though graphs, tables and forecast error. The hydrological time series chosen were from Furnas and Emborcação Hydroeletric Power Plant. These series were chosen having in mind the necessity of series with reduced error in their forecast because system of operation in the Hydroeletric Power Plant depends on the quantity of the water in their resevoirs, eficient planning and management.

There is overwhelming scientific evidence that shows the temperature of the Earth's atmosphere is rising at an unprecedented rate. This is attributed to increased levels of greenhouse gas emissions, a large proportion of which originates from anthropogenic combustion of carbon-based fossil fuels for energy. There is therefore a strong argument for the increased role of less environmentally damaging, low carbon energy sources including renewable energy technologies. Run-of-river hydropower is one such renewable energy option, considered more environmentally benign than traditional hydropower which requires the construction of large dams to create a reservoir. The aim of this study was to develop a model to search for, and map, economically viable run-of-river hydropower resource that can function on any global catchment of any size. Development and testing of the model was conducted on China's 2 million km2 Yangtze River drainage basin, the third longest river in the world and a rich landscape for hydropower. A gridded, distributed hydrological model was developed integrating high-resolution meteorological datasets and a digital elevation model (DEM). Using the model, the surface hydrology of the Yangtze catchment was simulated at a timestep of 6 minutes to obtain the mean daily surface runoff for every day from the beginning of 1979 to the end of 2007. Observed river flow data from sub-catchments of the Yangtze were used to calibrate the model by differential optimisation, an evolutionary computation technique. Validation was carried out on a 1.6 million km2 sub-catchment resulting in a mean objective function of 0.95 (where a perfect fit would be 1.0) across 8 objective functions commonly used in hydrology. Catchment wide mean daily runoff data was used to develop flow duration curves across the catchment river network. Virtual power stations were constructed at each river cell, iteratively testing differing scheme configurations, and costed using the RETScreen methodology. A best performing hydropower network was determined by a conflict algorithm, designed to prioritise high profit schemes and to remove lower performing and conflicting schemes. This resulted in a potential run-of-river installed capacity across the Yangtze catchment of 103GW (at 10% discount rate), generating 394TWh per annum. This model would be a valuable tool in finding optimal locations for future hydropower resource.

Les systèmes aquifères constituent la partie souterraine du cycle hydrologique. Ils transfèrent les pluies infiltrées à travers les sols sur des distances variables. Après un temps caractéristique de l’ordre du mois au millier d’années, les eaux souterraines regagnent la surface en alimentant les rivières et en satisfaisant en partie l’évapotranspiration. Les aquifères sont ainsi une ressource en eau majeure pour l’Homme et les écosystèmes. La prédiction de leur réponse aux pressions anthropiques et climatiques se heurte à deux difficultés (1) la faible densité d’informations directes sur les milieux géologiques et leur grande hétérogénéité (2) la complexité des échanges entre la surface et la profondeur. L’enjeu est donc de développer des modèles représentant au mieux les processus aux différentes échelles spatiotemporelles. Pour aborder cette question, nous étudions le contenu informatif de différents types d’observables (piézométrie, débit de rivière, déformation de surface...) afin de déterminer comment ils peuvent améliorer la paramétrisation des modèles. Notre travail s’appuie sur la modélisation hydrologique du site de Ploemeur (échelle locale) et du bassin du Rhin (échelle continentale). Dans les deux cas, des modèles simples sont développés en utilisant des solutions analytiques et numériques. Le modèle ModFlow a également été couplé à un modèle hydrologique. À petite échelle, les résultats illustrent l’intérêt de différents types de données transitoires pour contraindre les processus. À grande échelle, le modèle développé ainsi que les observables permettent d’affiner le rôle des systèmes aquifères dans la disponibilité de l’eau en surface. Les deux approches illustrent un contrôle des flux à différentes échelles par la topographie, la géologie et l’hétérogénéité. / Groundwater systems (GW) constitute an important part of the hydrological cycle. GW transfer water infiltrated through soils on variable distances. After a characteristic time ranging from the month to thousand of years, GW reach the surface supporting rivers and evapotranspiration. Thus, they are a major resource for human and ecosystems. PredictingGWresponse to human and climate pressures is limited by (1) the scarcity of direct information on the highly heterogeneous geological media (2) the complexity of surface-depth exchanges. So, it seems necessary to develop models representing at best the processes at different spatiotemporal scales. To address this issue, we study the informative content of different observation types (piezometry, streamflow, surface deformation. . . ) to assess how they can improve models parametrization. Our work is based on GW modeling of the Ploemeur site (local scale) and of the Rhine basin (continental scale). For both approaches, simple models are developed, using analytical or numerical solutions. Also, the ModFlow model was coupled to an hydrological model. At small scale, results show the interest of temporal and multidisciplinary data to better constrain processes. At large scale, the developed model, as well as observations, allows to precise the role ofGWfor water availability on surface. Both approaches highlight a flows control at different scales by topography, geology and heterogeneity.

O modelo Soil and Water Assessment Tool (SWAT) tem sido utilizado para avaliar os impactos do uso e manejo da terra nos recursos hídricos, sedimentos e agroquímicos em diversas escalas e condições ambientais em todo o mundo. Entretanto, pelo fato de ter sido desenvolvido em centros de pesquisa norte-americanos, alguns parâmetros e rotinas de simulação não refletem adequadamente determinados processos de bacias localizadas em regiões tropicais. Nesse sentido, o presente trabalho visou aprimorar a modelagem hidrológica do SWAT através da revisão e modificação de processos relacionados à simulação da evapotranspiração. Os procedimentos propostos incluíram a alteração das rotinas de dormência vegetal no código fonte do modelo e a modificação dos cronogramas de operações de manejo e parâmetros do banco de dados de crescimento das plantas, visando reproduzir com maior precisão o ciclo das culturas em bacias tropicais. As modificações foram testadas em cinco bacias localizadas no Estado de São Paulo, com áreas entre 42 e 5.959 km², sendo comparados os resultados obtidos antes e depois da implementação das mesmas. Com as alterações, a análise do balanço hídrico anual evidenciou um aumento nos valores de evapotranspiração de cerca de 61% nas bacias, aproximando-se dos totais anuais de evapotranspiração calculados através de métodos empíricos, bem como houve redução significativa do escoamento superficial. Verificou-se uma melhoria da simulação de vazão em todas as bacias, sendo obtidos valores superiores para o Coeficiente de Eficiência de Nash-Sutcliffe (NSE) quando comparados à simulação sem as alterações. A calibração e validação foram realizadas com base na simulação modificada, sendo obtidos valores de NSE mensais entre 0,71 e 0,93 na calibração e 0,53 e 0,88 na validação, enquanto os valores diários de NSE situaram-se entre 0,51 e 0,82 na calibração e 0,38 e 0,83 na validação. A calibração a partir de uma simulação na qual as distorções dos processos hidrológicos da bacia estivessem previamente minimizadas resultou em bons resultados sem alteração excessiva dos parâmetros, indicando uma simulação hidrológica de melhor consistência. / The Soil and Water Assessment Tool (SWAT) has been used to predict the impact of land management practices on water, sediment, and agricultural chemical yields in a wide range of scales and environmental conditions across the globe. However, originally developed in the United States, some parameters and routines are unrealistic for simulating in tropical watersheds. In this sense, this work aims to improve the hydrologic modeling of SWAT model by reviewing and modifying parameters and routines related to evapotranspiration process. In order to adequately represent crop growth in tropical basins, the proposed procedures included changes in dormancy routines of SWAT source code and modifications of scheduled management operations and plant growth database parameters. These modifications were tested in five different basins at São Paulo State, Brazil, with areas ranging from 42 to 5959 km², by comparing the results before and after their implementation. Annual water balance analysis showed an increase in evapotranspiration about 61% for basins, approaching the total annual evapotranspiration estimated by empirical methods. Hence, it was observed that surface runoff and base flow components showed a decrease. The modifications resulted in improved flow simulation for all basins, showing better Nash-Sutcliffe Efficiency Coefficient (NSE) values compared to the unchanged simulation. Calibration and validation processes used the modified simulation database, being achieved monthly NSE between 0.71 – 0.73 at calibration and 0.53 – 0.88 at validation, while daily NSE were 0.51 – 0.82 at calibration and 0.38 – 0.83 at validation. Overall, minimizing distortions in hydrological processes at pre-calibration step resulted in good estimations without excessive modification of parameters at calibration, attesting a consistent hydrological modeling for the basins analyzed.

Space-borne remote sensing datasets have the potential to allow us to progress towards global scale flood prediction systems. However, these datasets are limited in terms of space-time resolution and accuracy, and the best use of such data requires understanding how uncertainties propagate through hydrological models. An unbiased investigation of different datasets for hydrological modeling requires a parsimonious calibration-free model, since calibration masks uncertainties in the data and model structure. This study, which addresses these issues, consists of two parts: 1) the development and validation of a multi-scale distributed hydrological model whose parameters can be directly linked to physical properties of the watershed, thereby avoiding the need of calibration, and 2) application of the model to demonstrate how data uncertainties propagate through the model and affect flood simulation across scales. I based the model development on an interactive approach for model building. I systematically added processes and evaluated their effects on flood prediction across multiple scales. To avoid the need for parameter calibration, the level of complexity in representing physical processes was limited by data availability. I applied the model to simulate flows for the Cedar River, Iowa River and Turkey River basins, located in Iowa. I chose this region because it is rich in high quality hydrological information that can be used to validate the model. Moreover, the area is frequently flooded and was the center of an extreme flood event during the summer of 2008. I demonstrated the model's skills by simulating medium to high-flow conditions; however the model's performance is relatively poor for dry (low flow) conditions. Poor model performance during low flows is attributed to highly nonlinear dynamics of soil and evapotranspiration not incorporated in the model. I applied the hydrological model to investigate the predictability skills of satellite-based datasets and to investigate the model's sensibility to certain hydro-meteorological variables such as initial soil moisture and bias in evapotranspiration. River network structure and rainfall are the main components shaping floods, and both variables are monitored from space. I evaluated different DEM sources and resolution DEMs as well as the effect of pruning small order channels to systematically decreasing drainage density. Results showed that pruning the network has a greater effect on simulated peak flow than the DEM resolution or source, which reveals the importance of correctly representing the river network. Errors on flood prediction depend on basin scale and rainfall intensity and decrease as the basin scale and rainfall intensity increases. In the case of precipitation, I showed that simulated peak flow uncertainties caused by random errors, correlated or not in space, and by coarse space-time data resolution are scale-dependent and that errors in hydrographs decrease as basin scale increases. This feature is significant because it reveals that there is a scale for which less accurate information can still be used to predict floods. However, the analyses of the real datasets reveal the existence of other types of error, such as major overall bias in total volumes and the failure to detect significant rainfall events that are critical for flood prediction.

Significant challenges in water resources management arise because of the ever-increasing pressure on the world’s heavily exploited and limited water resources. These stressors include demographic growth, intensification of agriculture, climate variability, and climate change. These challenges to water resources are usually tackled using a top-down approach, which suffers from many limitations including the use of a limited set of climate change scenarios, the lack of methodology to rank these scenarios, and the lack of credibility, particularly on extremes. The bottom-up approach, the recently introduced approach, reverses the process by assessing vulnerabilities of water resources systems to variations in future climates and determining the prospects of such wide range of changes. While it solves some issues of the top-down approach, several issues remain unaddressed. The current project seeks to provide end-users and the research community with an improved version of the bottom-up framework for streamlining climate variability into water resources management decisions. The improvement issues that are tackled are a) the generation of a sufficient number of climate projections that provide better coverage of the risk space; b) a methodology to quantitatively estimate the plausibility of a future desired or undesired outcome and c) the optimization of the size of the projections pool to achieve the desired precision with the minimum time and computing resources. The results will hopefully help to cope with the present-day and future challenges induced mainly by climate. In the first part of the study, the adequacy of stochastically generated climate time series for water resources systems risk and performance assessment is investigated. A number of stochastic weather generators (SWGs) are first used to generate a large number of realizations (i.e. an ensemble of climate outputs) of precipitation and temperature time series. Each realization of the generated climate time series is then used individually as an input to a hydrological model to obtain streamflow time series. The usefulness of weather generators is evaluated by assessing how the statistical properties of simulated precipitation, temperatures, and streamflow deviate from those of observations. This is achieved by plotting a large ensemble of (1) synthetic precipitation and temperature time series in a Climate Statistics Space (CSS), and (2) hydrological indices using simulated streamflow data in a Risk and Performance Indicators Space (RPIS). The performance of the weather generator is assessed using visual inspection and the Mahalanobis distance between statistics derived from observations and simulations. A case study was carried out using five different weather generators: two versions of WeaGETS, two versions of MulGETS and the k-nearest neighbor weather generator (knn). In the second part of the thesis, the impacts of climate change, on the other hand, was evaluated by generating a large number of representative climate projections. Large ensembles of future series are created by perturbing downscaled regional climate models’ outputs with a stochastic weather generator, then used as inputs to a hydrological model that was calibrated using observed data. Risk indices calculated with the simulated streamflow data are converted into probability distributions using Kernel Density Estimations. The results are dimensional joint probability distributions of risk-relevant indices that provide estimates of the likelihood of unwanted events under a given watershed configuration and management policy. The proposed approach offers a more complete vision of the impacts of climate change and opens the door to a more objective assessment of adaptation strategies. The third part of the thesis deals with the estimation of the optimal size of SWG realizations needed to calculate risk and performance indices. The number of realizations required to reach is investigated utilizing Relative Root Mean Square Error and Relative Error. While results indicate that a single realization is not enough to adequately represent a given stochastic weather generator, results generally indicate that there is no major benefit of generating more than 100 realizations as they are not notably different from results obtained using 1000 realizations. Adopting a smaller but carefully chosen number of realizations can significantly reduce the computational time and resources and therefore benefit a larger audience particularly where high-performance machines are not easily accessible. The application was done in one pilot watershed, the South Nation Watershed in Eastern Ontario, yet the methodology will be of interest for Canada and beyond. Overall, the results contribute to making the bottom-up more objective and less computationally intensive, hence more attractive to practitioners and researchers.