This thesis investigates the feasibility of implementing a real time quality control program into a data stream of hydrometeorlogical data. The vast array of data used in the forecasting of river levels and avalanches calls for a point of entry quality control method that is both efficient from a communications standpoint and practical given the computer resources available. The first step in this process is to find a normalization scheme to enable the direct comparison of precipitation events between different stations. The normalization scheme derived uses the climatic database of historical records. The largest set of historical records available is in the daily time frame. However, the quick response needed in this type of forecasting calls for the testing of data in a hourly format. This calls for the need to develop some sort of transformation between events of differing time scales. Once the normalization scheme is in place four tests are used to analyze the data. These tests compare the incoming data to what is expected given the climate, forecasted value, previous weather, and what is occurring at neighboring stations. The results from these four tests are composited to make a final opinion of the validity of the incoming data. The data are then assigned two descriptive parameters. These parameters quantify the sophistication of the tests performed on the data, and the believed accuracy of the data. The two scores are then taken into account to give a final broad description of the program's "opinion" as to whether the data should be rejected, questioned, screened, or verified. Generally the program performs very well. The accuracy and precision of the tests are left somewhat vague at this point. The stress in the development of this test was in the modularity and portability of the program; the testing scheme is not meant to be limited to the purpose of flood forecasting or even precipitation data. The threshold parameters, therefore, need to be set by the end user. These thresholds will be defined by the type of data as well as the purpose and accuracy of the data checking needed. / Graduation date: 1997

Work has been successfully performed by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) to synthesize the nation’s hydrologic data. Through the building of a national Hydrologic Information System, the organization has demonstrated a successful structure which promotes data sharing. While the access to and synthesis of observations data has been improved, the same cannot be said for spatiotemporal data. Data available on grids (e.g. meteorological data) has yet to be organized in a manner that can easily be shared. The development of a national Hydrometeorological Information System which incorporates temporal, spatial and spatiotemporal data is necessary for the improved synthesis of hydrologic phenomena which inherently is a coupled process that integrates both principles in hydrologic science and meteorology. / text

Regionalization of hydrometeorological variables such as rainfall and temperature is necessary for various applications related to water resources planning and management. Sampling variability and randomness associated with the variables, as well as non-availability and paucity of data pose a challenge in modelling the variables. This challenge can be addressed by using stochastic models that utilize information from hydrometeorologically similar locations for modelling the variables. A set of locations that are hydrometeorologically similar are referred to as homogeneous region or pooling group and the process of identifying a homogeneous region is referred to as regionalization. The thesis concerns development of new approaches to regionalization of (i) extreme rainfall,(ii) maximum and minimum temperatures, and (iii) rainfall together with maximum and minimum temperatures. Regionalization of extreme rainfall and frequency analysis based on resulting regions yields quantile estimates that find use in design of water control (e.g., barrages, dams, levees) and conveyance structures (e.g., culverts, storm sewers, spillways) to mitigate damages that are likely due to floods triggered by extreme rainfall, and land-use planning and management. Regionalization based on both rainfall and temperature yield regions that could be used to address a wide spectrum of problems such as meteorological drought analysis, agricultural planning to cope with water shortages during droughts, downscaling of precipitation and temperature. Conventional approaches to regionalization of extreme rainfall are based extensively on statistics derived from extreme rainfall. Therefore delineated regions are susceptible to sampling variability and randomness associated with extreme rainfall records, which is undesirable. To address this, the idea of forming regions by considering attributes for regionalization as seasonality measure and site location indicators (which could be determined even for ungauged locations) is explored. For regionalization, Global Fuzzy c-means (GFCM) cluster analysis based methodology is developed in L-moment framework. The methodology is used to arrive at a set of 25 homogeneous extreme rainfall regions over India considering gridded rainfall records at daily scale, as there is dearth of regionalization studies on extreme rainfall in India Results are compared with those based on commonly used region of influence (ROI) approach that forms site-specific regions for quantile estimation, but lacks ability to delineate a geographical area into a reasonable number of homogeneous regions. Gridded data constitute spatially averaged rainfall that might originate from a different process (more synoptic) than point rainfall (more convective). Therefore to investigate utility of the developed GFCM methodology in arriving at meaningful regions when applied to point rainfall data, the methodology is applied to daily rainfall records available for 1032 gauges in Karnataka state of India. The application yielded 22 homogeneous extreme rainfall regions. Experiments carried out to examine utility of GFCM and ROI based regions in arriving at quantile estimates for ungauged sites in the study area reveal that performance of GFCM methodology is fairly close to that of ROI approach. Errors were marginally lower in the case of GFCM approach in analysis with observed point rainfall data over Karnataka, while its converse was noted in the case of analysis with gridded rainfall data over India. Neither of the approaches (CA, ROI) was found to be consistent in yielding least error in quantile estimates over all the sites. The existing approaches to regionalization of temperature are based on temperature time series or their related statistics, rather than attributes effecting temperature in the study area. Therefore independent validation of the delineated regions for homogeneity in temperature is not possible. Another drawback of the existing approaches is that they require adequate number of sites with contemporaneous temperature records for regionalization, because the delineated regions are susceptible to sampling variability and randomness associated with the temperature records that are often (i) short in length, (ii) limited over contemporaneous time period and (iii) spatially sparse. To address these issues, a two-stage clustering approach is developed to arrive at regions that are homogeneous in terms of both monthly maximum and minimum temperatures ( and ). First-stage of the approach involves (i) identifying a common set of possible predictors (LSAVs) influencing and over the entire study area, and (ii) using correlations of those predictors with and along with location indicators (latitude, longitude and altitude) as the basis to delineate sites in the study area into hard clusters through global k-means clustering algorithm. The second stage involves (i) identifying appropriate LSAVs corresponding to each of the first-stage clusters, which could be considered as potential predictors, and (ii) using the potential predictors along with location indicators (latitude, longitude and altitude) as the basis to partition each of the first-stage clusters into homogeneous temperature regions through global fuzzy c-means clustering algorithm. A set of 28 homogeneous temperature regions was delineated over India using the proposed approach. Those regions are shown to be effective when compared to an existing set of 6 temperature regions over India for which inter-site cross-correlations were found to be weak and negative for several months, which is undesirable. Effectiveness of the newly formed regions is demonstrated. Utility of the proposed maxTminT homogeneous temperature regions in arriving at PET estimates for ungauged locations within the study area was demonstrated. The estimates were found to be better when compared to those based on the existing regions. The existing approaches to regionalization of hydrometeorological variables are based on principal components (PCs)/ statistics/indices determined from time-series of those variables at monthly and seasonal scale. An issue with use of PCs for regionalization is that they have to be extracted from contemporaneous records of hydrometeorological variables. Therefore delineated regions may not be effective when the available records are limited over contemporaneous time period. A drawback associated with the use of statistics/indices is that they (i) may not be meaningful when data exhibit nonstationarity and (ii) do not encompass complete information in the original time series. Consequently the resulting regions may not be effective for the desired purpose. To address these issues, a new approach is proposed. It considers information extracted from wavelet transformations of the observed multivariate hydrometeorological time series as the basis for regionalization by global fuzzy c-means clustering procedure. The approach can account for dynamic variability in the time series and its nonstationarity (if any). Effectiveness of the proposed approach in forming homogeneous hydrometeorological regions is demonstrated by application to India, as there are no prior attempts to form such regions over the country. The investigations resulted in identification of 29 regions over India, which are found to be effective and meaningful. Drought Severity-Area-Frequency (SAF) curves are developed for each of the newly formed regions considering the drought index to be Standardized Precipitation Evapotranspiration Index (SPEI).

Freqüentemente, a população das áreas metropolitanas é surpreendida pela ocorrência de inundações muito rápidas que causam danos diversos. O sistema de alerta antecipado contra inundações é uma ferramenta que visa minimizar tais impactos. O componente de previsão do sistema será abordado neste trabalho. Tal previsão é feita através de um modelo conceitual de previsão hidrometeorológica de precipitação baseado em equações termodinâmicas e modelo simplificado de física das nuvens seguido de um modelo chuva-vazão. A antecedência proporcionada pelo modelo hidrometeorológico aplicado é de 30 minutos para variáveis de entrada observadas. Este tempo pode ser estendido com a inclusão de estimativas futuras das variáveis de entrada. A calibração do modelo foi feita manualmente com o uso de duas medidas de desempenho, esta etapa pode ser aprimorada em pesquisas futuras. Apesar da simplicidade do modelo hidrometeorológico apresentou-se satisfatório em algumas simulações, conseguindo prever o início das precipitações. / Urban population are often surprised by flash floods which cause several kinds of damages. An early warning system is a tool which aims to minimize such impacts. This work will approach the forecast component of this system. A conceptual hydrometeorological precipitation forecasting model, based on thermodynamics equations and simplified cloud physics, will be used to perform the forecast. Model lead time is 30 minutes for measured inputs, this time can be extended by the use of estimated inputs instead of the measured ones. Calibration was performed manually based on conservation of precipitation volume and its distribution in time. This step can be improved on future researches. In spite of model’s simplicity, some simulations presented satisfactory results, being able to forecast precipitation’s beginning.

Freqüentemente, a população das áreas metropolitanas é surpreendida pela ocorrência de inundações muito rápidas que causam danos diversos. O sistema de alerta antecipado contra inundações é uma ferramenta que visa minimizar tais impactos. O componente de previsão do sistema será abordado neste trabalho. Tal previsão é feita através de um modelo conceitual de previsão hidrometeorológica de precipitação baseado em equações termodinâmicas e modelo simplificado de física das nuvens seguido de um modelo chuva-vazão. A antecedência proporcionada pelo modelo hidrometeorológico aplicado é de 30 minutos para variáveis de entrada observadas. Este tempo pode ser estendido com a inclusão de estimativas futuras das variáveis de entrada. A calibração do modelo foi feita manualmente com o uso de duas medidas de desempenho, esta etapa pode ser aprimorada em pesquisas futuras. Apesar da simplicidade do modelo hidrometeorológico apresentou-se satisfatório em algumas simulações, conseguindo prever o início das precipitações. / Urban population are often surprised by flash floods which cause several kinds of damages. An early warning system is a tool which aims to minimize such impacts. This work will approach the forecast component of this system. A conceptual hydrometeorological precipitation forecasting model, based on thermodynamics equations and simplified cloud physics, will be used to perform the forecast. Model lead time is 30 minutes for measured inputs, this time can be extended by the use of estimated inputs instead of the measured ones. Calibration was performed manually based on conservation of precipitation volume and its distribution in time. This step can be improved on future researches. In spite of model’s simplicity, some simulations presented satisfactory results, being able to forecast precipitation’s beginning.

There is ample growth in scientific evidence about climate change. Since, hydrometeorological processes are sensitive to climate variability and changes, ascertaining the linkages and feedbacks between the climate and the hydrometeorological processes becomes critical for environmental quality, economic development, social well-being etc. As the river basin integrates some of the important systems like ecological and socio-economic systems, the knowledge of plausible implications of climate change on hydrometeorology of a river basin will not only increase the awareness of how the hydrological systems may change over the coming century, but also prepare us for adapting to the impacts of climate changes on water resources for sustainable management and development. In general, quantitative climate impact studies are based on several meteorological variables and possible future climate scenarios. Among the meteorological variables, sic “cardinal” variables are identified as the most commonly used in impact studies (IPCC, 2001). These are maximum and minimum temperatures, precipitation, solar radiation, relative humidity and wind speed. The climate scenarios refer to plausible future climates, which have been constructed for explicit use for investigating the potential consequences of anthropogenic climate alterations, in addition to the natural climate variability. Among the climate scenarios adapted in impact assessments, General circulation model(GCM) projections based on marker scenarios given in Intergovernmental Panel on Climate Change’s (IPCC’s) Special Report on Emissions Scenarios(SRES) have become the standard scenarios. The GCMs are run at coarse resolutions and therefore the output climate variables for the various scenarios of these models cannot be used directly for impact assessment on a local(river basin)scale. Hence in the past, several methodologies such as downscaling and disaggregation have been developed to transfer information of atmospheric variables from the GCM scale to that of surface meteorological variables at local scale. The most commonly used downscaling approaches are based on transfer functions to represent the statistical relationships between the large scale atmospheric variables(predictors) and the local surface variables(predictands). Recently Support vector machine (SVM) is proposed, and is theoretically proved to have advantages over other techniques in use such as transfer functions. The SVM implements the structural risk minimization principle, which guarantees the global optimum solution. Further, for SVMs, the learning algorithm automatically decides the model architecture. These advantages make SVM a plausible choice for use in downscaling hydrometeorological variables. The literature review on use of transfer function for downscaling revealed that though a diverse range of transfer functions has been adopted for downscaling, only a few studies have evaluated the sensitivity of such downscaling models. Further, no studies have so far been carried out in India for downscaling hydrometeorological variables to a river basin scale, nor there was any prior work aimed at downscaling CGCM3 simulations to these variables at river basin scale for various IPCC SRES emission scenarios. The research presented in the thesis is motivated to assess the impact of climate change on streamflow at river basin scale for the various IPCC SRES scenarios (A1B, A2, B1 and COMMIT), by integrating implications of climate change on all the six cardinal variables. The catchment of Malaprabha river (upstream of Malaprabha reservoir) in India is chosen as the study area to demonstrate the effectiveness of the developed models, as it is considered to be a climatically sensitive region, because though the river originates in a region having high rainfall it feeds arid and semi-arid regions downstream. The data of the National Centers for Environmental Prediction (NCEP), the third generation Canadian Global Climate Model (CGCM3) of the Canadian Center for Climate Modeling and Analysis (CCCma), observed hydrometeorological variables, Digital Elevation model (DEM), land use/land cover map, and soil map prepared based on PAN and LISS III merged, satellite images are considered for use in the developed models. The thesis is broadly divided into four parts. The first part comprises of general introduction, data, techniques and tools used. The second part describes the process of assessment of the implications of climate change on monthly values of each of the six cardinal variables in the study region using SVM downscaling models and k-nearest neighbor (k-NN) disaggregation technique. Further, the sensitivity of the SVM downscaling models to the choice of predictors, predictand, calibration period, season and location is evaluated. The third part describes the impact assessment of climate change on streamflow in the study region using the SWAT hydrologic model, and SVM downscaling models. The fourth part presents summary of the work presented in the thesis, conclusions draws, and the scope for future research. The development of SVM downscaling model begins with the selection of probable predictors (large scale atmospheric variables). For this purpose, the cross-correlations are computed between the probable predictor variables in NCEP and GCM data sets, and the probable predictor variables in NCEP data set and the predictand. A pool of potential predictors is then stratified (which is optional and variable dependant) based on season and or location by specifying threshold values for the computed cross-correlations. The data on potential predictors are first standardized for a baseline period to reduce systemic bias (if any) in the mean and variance of predictors in GCM data, relative to those of the same in NCEP reanalysis data. The standardized NCEP predictor variables are then processed using principal component analysis (PCA) to extract principal components (PCs) which are orthogonal and which preserve more than 98% of the variance originally present in them. A feature vector is formed for each month using the PCs. The feature vector forms the input to the SVM model, and the contemporaneous value of predictand is its output. Finally, the downscaling model is calibrated to capture the relationship between NCEP data on potential predictors (i.e feature vectors) and the predictand. Grid search procedure is used to find the optimum range for each of the parameters. Subsequently, the optimum values of parameters are obtained from the selected ranges, using the stochastic search technique of genetic algorithm. The SVM model is subsequently validated, and then used to obtain projections of predictand for simulations of CGCM3. Results show that precipitation, maximum and minimum temperature, relative humidity and cloud cover are projected to increase in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with theCOMMIT. The projected increase in predictands is high for A2 scenario and is least for B1 scenario. The wind speed is not projected to change in future for the study region for all the aforementioned scenarios. The solar radiation is projected to decrease in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with the COMMIT. To assess the monthly streamflow responses to climate change, two methodologies are considered in this study namely (i) downscaling and disaggregating the meteorological variables for use as inputs in SWAT and (ii) directly downscaling streamflow using SVM. SWAT is a physically based, distributed, continuous time hydrological model that operates on a daily time scale. The hydrometeorologic variables obtained using SVM downscaling models are disaggregated to daily scale by using k-nearest neighbor method developed in this study. The other inputs to SWAT are DEM, land use/land cover map, soil map, which are considered to be the same for the present and future scenarios. The SWAT model has projected an increase in future streamflows for A1B, A2 andB1 scenarios, whereas no trend is discerned with the COMMIT. The monthly projections of streamflow at river basin scale are also obtained using two SVM based downscaling models. The first SVM model (called one-stage SVM model) considered feature vectors prepared based on monthly values of large scale atmospheric variables as inputs, whereas the second SVM model (called two-stage SVM model) considered feature vectors prepared from the monthly projections of cardinal variables as inputs. The trend in streamflows projected using two-stage SVM model is found to be similar to that projected by SWAT for each of the scenarios considered. The streamflow is not projected to change for any of the scenarios considered with the one-stage SVM downscaling model. The relative performance of the SWAT and the two SVM downscaling models in simulating observed streamflows is evaluated. In general, all the three models are able to simulate the streamflows well. Nevertheless, the performance of SWAT model is better. Further, among the two SVM models, the performance of one-stage streamflow downscaling model is marginally better than that of the two-stage streamflow downscaling model.

This study aimed at describing the characteristics of daily precipitation and discharge extremes in the Adige river basin at the city of Trento. Annual maximum series for the period 1975−2014 were analyzed in terms of trends, seasonality indices and L-moments. A Mann-Kendall trend analysis showed a weak but significant signal of decreasing ex-tremes; the percentages of sites with significant negative trends were overall larger than the significance levels. Precipitation extremes were characterized primarily by autumn storms, while floods had a stronger seasonality with peaks occurring predominantly in June and July which indicated that the timing not solely explained by rainfall maxima. The Adige basin was found to be a homogenous region with respect to precipitation, but the results did not support a corresponding assumption for discharge. A regional fre-quency analysis was performed for precipitation data and found both the Pearson type III and generalized normal distributions to be adequate regional frequency distributions. The extreme daily precipitation at Trento with a 100-year return period was estimated to be between 114 and 148 mm/d. / Egenskaperna hos extremvärden av dygnsnederbörd och -vattenföring i Adigeflodens av-rinningsområde vid staden Trento undersöktes. Serier med årsmaxima för perioden 1975–2014 analyserades med avseende på trender, säsongsindex och L-moment. Trendanalys med Mann-Kendallmetod antydde en svag men signifikant signal om minskande extrem-värden, då andelen mätstationer med signifikant negativa trender överlag var större än signifikansnivån. Den extrema nederbörden karakteriserades huvudsakligen av höststor-mar, medan vattenföringen hade en starkare säsongsbundenhet då maxima inträffade främst under juni och juli. Vattenföringens extremvärden kunde därmed inte enbart för-klaras av nederbördsmaxima. Avrinningsområdet kunde betraktas som en homogen reg-ion för nederbörd, men resultaten gav inte stöd åt ett motsvarande antagande för vatten-föring. En regional frekvensanalys genomfördes för nederbördsdata och visade att Pear-son typ III och den generaliserade normalfördelningen var lämpliga regionala sannolik-hetsfördelningar. Över Trento uppskattades den extrema dygnsnederbörden med en åter-komstperiod på 100 år till mellan 114 och 148 mm/d.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-11-06T16:08:46Z No. of bitstreams: 1 PAULO ROMERO GUIMARÃES SERRANO DE ANDRADE - DISSERTAÇÃO PPGECA 2000..pdf: 36173335 bytes, checksum: 8c355842ff686dced645eaae16c63cfd (MD5) / Made available in DSpace on 2018-11-06T16:08:46Z (GMT). No. of bitstreams: 1 PAULO ROMERO GUIMARÃES SERRANO DE ANDRADE - DISSERTAÇÃO PPGECA 2000..pdf: 36173335 bytes, checksum: 8c355842ff686dced645eaae16c63cfd (MD5) Previous issue date: 2000-12-14 / A notória subutilização dos reservatórios do Nordeste do Brasil, mormente em sua região semi-árida, derivando, regra geral, da ausência de um manejo adequado e de instrumental técnico eficiente aplicáveis à funcionalidade dos seus perímetros de irrigação, desperta, quase sempre, o receio de esgotá-los. O uso mais racional dos recursos hídricos e a busca da maximização dos benefícios advindos de aproveitamentos hidráulicos já existentes, a fim de que as populações dessa área possam ser melhor atendidas, motivaram a elaboração deste trabalho. Neste contexto, procurou-se estudar a operação do sistema hídrico formado pelos reservatórios Jucazinho e Carpina, e três perímetros de irrigação, localizados na bacia do rio Capibaribe, em Pernambuco, com o objetivo de maximizar os benefícios financeiros líquidos advindos da agricultura irrigada e da piscicultura, atendidos o requerimento de água para o abastecimento urbano, prioritariamente, necessidades hídricas da regularização e controle de cheia. Para analisar o comportamento do sistema hídrico e tentar prover solução ótima para a sua operação, foi aplicado o modelo ORNAP (Curi e Curi, 1999) de otimização, de base mensal, apoiado em técnicas de programação não linear. A função objetivo que visa a maximização do lucro da prática agrícola irrigada e piscicultura, é sujeita a restrições diversas, representadas por equações de natureza linear e não linear, que traduzem no processo de otimização, a nível mensal, as limitações físicas dos reservatórios, perímetros e equipamentos hidráulicos, limitações hidrológicas, legais, econômicas e sociais, que são próprias de sistemas de múltiplos usos Abordagens determinísticas foram necessárias, idealizando-se o futuro do sistema hídrico como conhecido através de cenários de planejamento, caracterizados por três situações climáticas distintas (média, seca e chuvosa), que são completados, basicamente, pela definição de valores para variáveis de entrada para o modelo, relacionadas aos elementos naturais e artificiais identificados como pertinentes ao sistema, que envolvem reservatórios, demandas de abastecimento urbano, calhas de rio e perímetros de irrigação. Os resultados otimizados para as diversas variáveis de decisão, como descargas dos reservatórios e áreas irrigadas, máximas e mínimas, são gerados para cada situação climática, combinadas com diferentes aspectos operacionais adotados para os reservatórios Jucazinho e Carpina. O estudo de otimização mostrou que, respeitadas as restrições operacionais impostas, neste estudo, à funcionalidade do sistema hídrico, as áreas máximas cogitadas para os perímetros não seriam totalmente irrigadas. Os resultados alcançados mostram a viabilidade do modelo ORNAP na prática do planejamento e gerenciamento de reservatórios e perímetros, constituindo-se numa interessante ferramenta de apoio à tomada de decisão. / The not utilization in its full potential of the reservoirs in the Northeast of Brazil, especially in its semi-arid area, derives, most of the time, of the absence of an appropriate handling and the fear of empty them. The motivation for this work was the achievement of a more rational use of the water resources and the search of the maximization of the benefits generated by the hydraulic uses already existent, so that the population of that area can be better assisted. In this context, it is studied the operation of the water resource system formed by the reservoirs Jucazinho and Carpina, and three irrigation sites, located in the basin of the Capibaribe river, in Pernambuco, North-east Brazil, with the objective of maximizing the net income generated by the irrigated agriculture and fish farming, respecting the needs of water for urban uses, flow and flood control. To analyze the behavior of the water resources system in order to obtain an optimal solution for its operation, was applied an optimization model called ORNAP (Curi and Curi, 1999), of monthly base, based on a nonlinear optimization technique. The objective function that seeks the maximization of the profit of the irrigated agricultural and and extensive fishing activities, is subject to several constraints, represented by equations of linear and non linear nature that accounts, in the optimization process, at monthly level, for the physical limitations of the reservoirs, perimeters and hydraulics equipment, hydrological limitations, legal, economical and social requirements, that are inherent of water resource systems of multiple uses. A deterministic approach was necessary, where the future was idealized through planning scenarios, characterized by three different climate situations (average, dry and rainy). The optimal values assumed by the several decision variables, such as discharges of the reservoirs and irrigated areas for each crop, are generated for each climatic situation, taking in account the several operational aspects adopted for the reservoirs Jucazinho and Carpina. The optimization study showed that, respected the imposed operational constraints, in this study, the maximum areas cogitated for the perimeters would not be totally irrigated. The reached results show the viability of the model ORNAP for the planning and management of reservoirs and irrigated sites, constituting in an interesting tool for a decision support system.

Cette recherche doctorale porte sur la modélisation 3D de la dynamique des teneurs en eau dans le sol et le soussol lorsque les écoulements sont à saturation variable. La modélisation est basée sur une version généralisée de la loi de Darcy-Buckingham et de l’équation de Richards multidimensionnelle. Les recherches présentées dans cette thèse concernent différents volets, présentés ci-dessous, dont le fil conducteur est l’analyse de phénomènes d’écoulements en milieux poreux, contenant de fortes hétérogénéités et/ou perturbés par des fluctuations temporelles. Dans le cadre d’un partenariat de recherche entre l’IMFT et l'IRSN sur la problématique du stockage souterrain de déchets radioactifs, nous avons modélisé en 3D la dynamique du front de désaturation d’une couche argileuse autour d’une galerie souterraine ventilée, à l’aide du code volumes finis BIGFLOW 3D. Ce travail a permis de mettre au point une approche d’immersion pour la modélisation des écoulements en milieux composites. Un autre volet de cette thèse concerne une étude analytique et numérique des profils verticaux de succion et de teneur en eau lors d’une infiltration verticale, non-saturante, dans un sol hétérogène finement stratifié. Des solutions analytiques exactes et approchées sont obtenues en régime permanent, à l’aide de transformations de variables, et sont comparées avec des solutions numériques pour différents degrés d’hétérogénéité. De même, les phénomènes de « barrière capillaire » sont étudiés d’une part analytiquement et d’autre part, par expérimentations numériques transitoires d’infiltration sur des systèmes bicouches, en présence d’une nappe plus ou moins profonde. D’autre part, les écoulements nonsaturés sont étudiés, cette fois, en présence d’un forçage transitoire fortement oscillatoire, dans une colonne de sable fin homogène, sous l’effet de fluctuations périodiques du niveau de la surface libre. Une méthode multi-front mise au point lors d’une thèse précédente à l’IMFT est validée numériquement en montrant que cette méthode simule efficacement la dynamique oscillatoire des flux et des profils de pression avec un nombre limité de « fronts ». De plus, nous avons analysé la phénoménologie capillaire/gravitaire des écoulements oscillatoires dans la colonne grâce à un suivi dynamique du plan de flux nul. Enfin, nous présentons, comme extension aux travaux précédents, une étude préliminaire des phénomènes 3D d’infiltration et de redistribution d’eau, notamment lorsque l’hétérogénéité du sol est de type aléatoire. Les premiers essais d’infiltration permettent de tester, en réplique unique, des méthodes de prises de moyennes spatiales des champs de succion et teneur en eau et évaluer la taille minimum du domaine de calcul 3D permettant d’obtenir des profils verticaux moyens représentatifs de l’infiltration dans une réplique unique du sol aléatoire. / This doctoral research, defended at the Institut de Mécanique des Fluides de Toulouse, is devoted to modeling water pressure and water content in soils and in subsurface geologic formations, in the case of variably saturated flow. One of the main scientific objectives of this work is to analyze the response of unsaturated flow systems, and particularly capillary and gravitational effects, in the presence of material heterogeneities, discontinuities, and/or space-time fluctuations. Modeling is based on a generalized version of Darcy- Buckingham’s law, and of Richards’ flow equation. Overall, the topics developed in this PhD thesis focus on several related aspects of variably saturated water flow in the subsurface. These aspects all occur at once in most applications (drying/wetting,heterogeneity, temporal forcing), but they are "decoupled" here for convenience. A preliminary research (collaborative project IMFT / IRSN) was developed to study the 2D/3D drying process at the porous wall of a deep cylindrical excavation in response to hydrometeorological signals. This project has motivated the design and testing of a novel approach to include cavities in the modeling domain. A detailed study of steady state infiltration was developed for the case of finely stratified soils, with parameters that vary continuously and cyclically with depth. Exact and approximate analytical solutions are calculated based on variable transformation methods and on perturbation type approximations, and they are tested numerically using a finite volume code (BIGFLOW 3D). The sensitivity of suction fluctuations vs. stratification wavelength is investigated, as well as the effect of the degree of heterogeneity, and of water table depth. Capillary barrier effects are studied for the case of unsaturated infiltration in multilayer soil systems characterized by a discontinuity of soil properties at interfaces. Numerical experiments are developed for transient infiltration towards a water table through a two-layer system, the goal being to analyze possible capillary barrier effects under various scenarios. On the other hand, we study numerically the case of a partially saturated / unsaturated soil column submitted to highly variable oscillatory pressure at the bottom of the column: this leads to vertical flow oscillations in the unsaturated zone above the water table influenced by tides (coastal beach sand). We analyze the dynamics of this oscillatory flow, where capillary and gravitational effects compete; for this purpose we use a novel method that tracks the positions of the zero flux plane in the unsaturated column. Finally, we also present, as an extension to the previous studies, a preliminary investigation of multidimensional infiltration/redistribution phenomena, particularly for the case of fully 3D random-type soil heterogeneity. The first numerical experiments of 3D infiltration are undertaken based on the single realization approach to soil heterogeneity, and assuming a uniform distribution of wetting at soil surface.