Oligochaeta (Annelida, Clitellata) in lotic environments in the state of São Paulo, Brazil

Despite the importance of Oligochaeta to the dynamics of aquatic ecosystems and to studies of the biology of pollution, there is currently a dearth of information on this group's ecology in Brazil. The aim of this study was to describe the Oligochaeta fauna in four watercourses - three urban and one rural - in the state of São Paulo: the Pinheirinho stream, the Água Branca stream, the Monjolinho River and the Gouveia stream, respectively. Sediment samples were taken with a Van Veen grab in two areas from each watercourse, during the summer and winter of 2001. In all collection areas, measurements of the pH, electrical conductivity, dissolved oxygen and turbidity of the water were made with a Horiba U-10 device. Principal component analysis showed that axes 1 and 2 explained 68.18% of the results' variability, with the first axis predominantly associated with the granulometric data and the second one with the limnological data. Cluster analysis indicated that area II of the Monjolinho River differed from the other collection sites. In the present study, the Oligochaeta group was represented by Tubificidae, Naididae, Alluroididae, Narapidae and Enchytraeidae. Among the three species of Tubificidae, Limnodrilus hoffmeisteri Claparede, 1862, was the most abundant and most frequent species. The results provided important information on the ecology and distribution of limnic Oligochaeta.

Diversity and structure of microcrustacean assemblages (Cladocera and Copepoda) and limnological variability in perennial and intermittent pools in a semi-arid region, Bahia, Brazil

Temporary wetlands undergo recurrent drought due to the scarcity of water, which disrupts the hydrological connectivity with adjacent aquatic systems. However, some environments retain water for longer periods, allowing greater persistence of the community. The current study evaluated differences in the microcrustacean assemblages and limnological variability between perennial and intermittent pools in a semi-arid region of Brazil. The abiotic features (water temperature, pH, total alkalinity, electrical conductivity and depth) of intermittent pools were affected more than perennial pools due to loss of water volume. This may have contributed to a higher average richness and diversity index in some intermittent pools and differences in the structure of the assemblages. The lowest species richness and diversity were recorded where physical factors, such as a large quantity of suspended solids and variability in the electrical conductivity of the water and pH, make the environment unsuitable for these organisms. These results suggest that community development in intermittent pools is interrupted by the dry season; when the water returns, due to rainfall or rising groundwater, each pond undergoes a different process of colonization. In these circumstances, the biological importance of temporary aquatic environments is clear, since such pools provide shelters and have an important role in the maintenance of the regional diversity of aquatic environments.

Elaboració de membranes de fibra buida modificades amb nanopartícules metàl·liques per aplicacions catalítiques

Investigación producida a partir de una estancia en la Université Paul Sabatier, Toulouse III - CNRS, entre 2007 y 2009. Durante los últimos años la investigación centrada en nuevos materiales de tamaño nanoscòpico (nanopartículas, quantum dots, nanotubos de carbono,...) ha experimentado un crecimiento considerable debido a las especiales propiedades de los "nanoobjetos" con respecto a magnetismo, catálisis, conductividad eléctrica, etc ... Sin embargo, hoy en día todavía existen pocas aplicaciones de las nanopartículas en temas medioambientales. Uno de los motivos de esta situación es la posible toxicidad de los nanoobjetos, pero existe también una dificultad tecnológica dado que las nanopartículas tienden a agregarse y es muy difícil manipularlas sin que pierdan sus propiedades especiales. Así, aunque la preparación de materiales catalíticos nanoestructurados es muy interesante, es necesario definir nuevas estrategias para prepararlos. Este proyecto de investigación tiene como objetivo principal la preparación de nuevas membranas catalíticas con nanopartículas metálicas en el interior para aplicaciones de tratamiento de agua. La innovación principal de este proyecto consiste en que las nanopartículas no son introducidas en la matriz polimérica una vez preformadas sino que se hacen crecer en el interior de la matriz polimérica mediante una síntesis intermatricial. El único requisito es que la matriz polimérica contenga grupos funcionales capaces de interaccionar con los precursores de las nanopartículas. Una vez finalizado el proyecto se puede afirmar que se han logrado parte de los objetivos planteados inicialmente. Concreamente ha quedado demostrado que se pueden sintetizar nanopartículas metálicas de metales nobles (platino y paladio) en membranas de fibra hueca de micro- y ultrafiltración siguiendo dos metodologías diferentes: modificación fotoquímica de polímeros y deposición de multicapas de polielectrolitos. Los nuevos materiales son efectivos en la catálisis de reducción de un compuesto modelo (4-nitrofenol con borohidruro de sodio) y, en general, los resultados han sido satisfactorios. Sin embargo, se ha puesto de manifiesto que el uso de un reactivo que genera hidrógeno gas en contacto con la solución acuosa dificulta enormemente la implementación de la reacción catalítica al ser el medio de la membrana una matriz porosa. Así, como conclusión principal se puede decir que se han encontrado las limitaciones de esta aproximación y se sugieren dos posibilidades de continuidad: la utilización de las membranas sintetizadas en contactores gas-líquido o bien el estudio y optimización del sistema de membrana en configuración de membranas planas, un objetivo más asequible dada su menor complejidad. Esta investigación se ha realizado en el seno del “Laboratoire de Génie Chimique” de Toulouse y del Departamento de Química de la Michigan State University y ha sido posible gracias a un proyecto financiado por la “Agence National pour la Recherce” y al programa PERMEANT entre el CNRS y la NSF.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

Source wavelet estimation for waveform inversion of crosshole georadar data

AbstractFor a wide range of environmental, hydrological, and engineering applications there is a fast growing need for high-resolution imaging. In this context, waveform tomographic imaging of crosshole georadar data is a powerful method able to provide images of pertinent electrical properties in near-surface environments with unprecedented spatial resolution. In contrast, conventional ray-based tomographic methods, which consider only a very limited part of the recorded signal (first-arrival traveltimes and maximum first-cycle amplitudes), suffer from inherent limitations in resolution and may prove to be inadequate in complex environments. For a typical crosshole georadar survey the potential improvement in resolution when using waveform-based approaches instead of ray-based approaches is in the range of one order-of- magnitude. Moreover, the spatial resolution of waveform-based inversions is comparable to that of common logging methods. While in exploration seismology waveform tomographic imaging has become well established over the past two decades, it is comparably still underdeveloped in the georadar domain despite corresponding needs. Recently, different groups have presented finite-difference time-domain waveform inversion schemes for crosshole georadar data, which are adaptations and extensions of Tarantola's seminal nonlinear generalized least-squares approach developed for the seismic case. First applications of these new crosshole georadar waveform inversion schemes on synthetic and field data have shown promising results. However, there is little known about the limits and performance of such schemes in complex environments. To this end, the general motivation of my thesis is the evaluation of the robustness and limitations of waveform inversion algorithms for crosshole georadar data in order to apply such schemes to a wide range of real world problems.One crucial issue to making applicable and effective any waveform scheme to real-world crosshole georadar problems is the accurate estimation of the source wavelet, which is unknown in reality. Waveform inversion schemes for crosshole georadar data require forward simulations of the wavefield in order to iteratively solve the inverse problem. Therefore, accurate knowledge of the source wavelet is critically important for successful application of such schemes. Relatively small differences in the estimated source wavelet shape can lead to large differences in the resulting tomograms. In the first part of my thesis, I explore the viability and robustness of a relatively simple iterative deconvolution technique that incorporates the estimation of the source wavelet into the waveform inversion procedure rather than adding additional model parameters into the inversion problem. Extensive tests indicate that this source wavelet estimation technique is simple yet effective, and is able to provide remarkably accurate and robust estimates of the source wavelet in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity as well as significant ambient noise in the recorded data. Furthermore, our tests also indicate that the approach is insensitive to the phase characteristics of the starting wavelet, which is not the case when directly incorporating the wavelet estimation into the inverse problem.Another critical issue with crosshole georadar waveform inversion schemes which clearly needs to be investigated is the consequence of the common assumption of frequency- independent electromagnetic constitutive parameters. This is crucial since in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behaviour. In particular, in the presence of water, there is a wide body of evidence showing that the dielectric permittivity can be significantly frequency dependent over the GPR frequency range, due to a variety of relaxation processes. The second part of my thesis is therefore dedicated to the evaluation of the reconstruction limits of a non-dispersive crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. I show that the inversion algorithm, combined with the iterative deconvolution-based source wavelet estimation procedure that is partially able to account for the frequency-dependent effects through an "effective" wavelet, performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

Gestão Integrada dos Recursos Hídricos da Ilha do Maio (Cabo Verde): o Contributo das Águas Subterrâneas

Cabo Verde é constituído por 10 ilhas, sendo a ilha do Maio a mais antiga do arquipélago, com uma área de 269 km2, tendo como comprimento máximo 24100 m, uma largura máxima de 16300 m e uma população total de 6740 habitantes. No que concerne à geomorfologia e geologia, a ilha é considerada plana e é composta por formações eruptivas e sedimentares, sendo as formações sedimentares dominantes na ilha. Apresenta as formações mais antigas de Cabo Verde, de idade jurássica e cretácica. No entanto, não apresenta as formações eruptivas mais recentes como as restantes ilhas. A ilha do Maio enquadra-se num clima do tipo árido e semiárido, com uma temperatura média de 24.5 ºC e uma precipitação anual de 125.4 mm. Estimativas efectuadas com base no modelo do balanço hídrico sequencial diário mostram que cerca de 7% da precipitação corresponde a escoamento superficial e 14.1% a escoamento subterrâneo. Pela aplicação deste modelo e do método do balanço químico do ião cloreto, os recursos hídricos subterrâneos renováveis anualmente na ilha do Maio estão, em ano médio, compreendidos entre 3.44 x 106 m3 e 4.76 x 106 m3.por sua vez, o escoamento total é estimado em 7.8 x 106 m3 anuais, o que equivale a cerca de 21 400 m3/dia. O escoamento subterrâneo na ilha do Maio faz-se globalmente de um modo centrífugo a partir das elevações do maciço central. O gradiente hidráulico assume valores entre 0.05% e 2.9%, sendo que o valor mais baixo ocorre no sector norte da ilha, o que favorece o fenómeno de intrusão salina. Relativamente à qualidade da água, verifica-se que as amostras recolhidas correspondem a águas muito mineralizadas, com valores de condutividade eléctrica compreendidos entre 832 μS/cm e 7730 μS/cm. Por sua vez, os valores de TDS estão compreendidos entre 705.8 mg/L e 4210.4 mg/L. Nestas condições, as águas subterrâneas analisadas podem ser consideradas águas salobras. A fácies hidroquímica dominante é a cloretada sódica, sendo que grande parte das amostras pode ser considerada cloretada-bicarbonatada sódica. Admitindo que a amostragem efectuada tem significado estatístico, poderá dizer-se que, a nível físico-químico, cerca de 20% das águas subterrâneas são próprias para o consumo humano. No que respeita à utilização da água para rega, as águas analisadas apresentam baixo a alto perigo de alcalinização do solo e alto a muito alto perigo de salinização. Em síntese, pode concluir-se que, não obstante o carácter árido da ilha do Maio, a mesma apresenta um potencial de recursos hídricos não negligenciável, eventualmente suficiente para suprir as necessidades hídricas da população. No entanto, o estudo desenvolvido mostra a necessidade de implementar medidas susceptíveis de proporcionarem um aproveitamento sustentado dos recursos hídricos, no quadro da gestão integrada dos recursos hídricos da ilha do Maio.

Chemical changes in argisols under irrigated grape production in the central São Francisco river valley, Brazil

This study compares the chemical composition of the solution and exchange complex of soil in a 3-year-old irrigated vineyard (Vitis vinifera L., Red Globe cultivar) with that of adjacent clearing in the native hyperxerophyllic 'caatinga' vegetation. The soils are classified as Plinthic Eutrophic Red-Yellow Argisol; according to Soil Taxonomy they are isohyperthermic Plinthustalfs. Detailed physiographic characterization revealed an impermeable gravel and cobble covering the crystalline rocks; the relief of this layer was more undulating than the level surface. Significant higher concentrations of extractable Na, K, Mg and Ca were observed within the vineyard. Lower soil acidity, higher Ca/Mg ratios, as well as lower sodium adsorption and Na/K ratios reflected additions of dolomitic lime, superphosphate and K-bearing fertilizers. As the water of the São Francisco River is of good quality for irrigation (C1S1), the increases in Na were primarily attributed to capillary rise from the saline groundwater table. None of the soil in the study area was found to be sodic. About 62% of the vineyard had an Ap horizon with salinity levels above 1.5dSm-1 (considered detrimental for grape production); according to average values for this horizon, a potential 13% reduction in grape production was predicted. Differences in chemical composition in function of distance to the collector canals were observed in the clearing, but not in the vineyard. The influence of differences in the elevations of the surface and impermeable layers, as well as pediment thickness, was generally weaker under irrigation. Under irrigation, soil moisture was greater in points of convergent surface waterflow; the effect of surface curvature on chemical properties, though less consistent, was also stronger in the vineyard.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Localization and characterization of an active fault in an urbanized area in central Guatemala by means of geoelectrical imaging

The Polochic and Motagua faults define the active plate boundary between the North American and Caribbean plates in central Guatemala. A splay of the Polochic Fault traverses the rapidly growing city of San Miguel Uspantan that is periodically affected by destructive earthquakes. This fault splay was located using a 2D electrical resistivity tomography (ERT) survey that also characterized the fault damage zone and evaluated the thickness and nature of recent deposits upon which most of the city is built. ERT images show the fault as a similar to 50 m wide, near-vertical low-resistivity anomaly, bounded within a few meters by high resistivity anomalies. Forward modeling reproduces the key aspects of the observed electrical resistivity data with remarkable fidelity thus defining the overall location, geometry, and internal structure of the fault zone as well as the affected lithologies. Our results indicate that the city is constructed on a similar to 20 m thick surficial layer consisting of poorly consolidated, highly porous, water-logged pumice. This soft layer is likely to amplify seismic waves and to liquefy upon moderate to strong ground shaking. The electrical conductivity as well as the major element chemistry of the groundwater provides evidence to suggest that the local aquifer might, at least in part, be fed by water rising along the fault. Therefore, the potential threat posed by this fault splay may not be limited to its seismic activity per se, but could be compounded its potential propensity to enhance seismic site effects by injecting water into the soft surficial sediments. The results of this study provide the basis for a rigorous analysis of seismic hazard and sustainable development of San Miguel Uspantan and illustrate the potential of ERT surveying for paleoseismic studies.

Properties of nitrogen doped silicon films deposited by low-pressure chemical vapor deposition from silane and ammonia

Nitrogen doped silicon (NIDOS) films have been deposited by low-pressure chemical vapor deposition from silane SiH4 and ammonia NH3 at high temperature (750°C) and the influences of the NH3/SiH4 gas ratio on the films deposition rate, refractive index, stoichiometry, microstructure, electrical conductivity, and thermomechanical stress are studied. The chemical species derived from silylene SiH2 into the gaseous phase are shown to be responsible for the deposition of NIDOS and/or (silicon rich) silicon nitride. The competition between these two deposition phenomena leads finally to very high deposition rates (100 nm/min) for low NH3/SiH4 gas ratio (R¿0.1). Moreover, complex variations of NIDOS film properties are evidenced and related to the dual behavior of the nitrogen atom into silicon, either n-type substitutional impurity or insulative intersticial impurity, according to the Si¿N atomic bound. Finally, the use of NIDOS deposition for the realization of microelectromechanical systems is investigated.

Aluminum hydroxy-interlayered minerals and chemical properties of a subtropical Brazilian Oxisol under no-tillage and conventional tillage

No tillage systems significantly influence the soil system, but knowledge about the effects on the mineralogy of tropical and subtropical soils is limited. This study evaluated the long-term effects (26 years) of no-tillage (NT) on aluminum hydroxy-interlayered minerals of a subtropical Oxisol in Southern Brazil (Guarapuava, PR), compared to the same soil under conventional tillage (CT). The clay fraction (< 2 µm) in soil samples of the surface horizons of a field experiment under both management systems was analyzed by X-ray diffraction (XRD) to identify and characterize Al hydroxy-interlayered minerals before and after treatment with sodium citrate to remove intra-layer material. Soil liquid (solution) and solid phases were also characterized. The contents of total organic C, exchangeable cations, P, and the values of extractable acidity and cation exchange capacity as well as electrical conductivity and levels of dissolved organic C, basic cations, aluminum, Si, and sulfur in the soil solution were higher in the NT soil. Under both soil management systems, more than 90 % of the total soluble Al was complexed with organic compounds, with similar Al activity. No significant changes were detected by 2:1 clay mineral XRD analyses in terms of extension or intercalation of Al-hydroxy-polymers in the no-tilled in comparison to the conventionally tilled soil. In both soil management systems, Al and Si activities in the soil solution indicated thermodynamic stability of 2:1 clay minerals with partially occupied by hydroxy-Al, suggesting deceleration in the intercalation process and a tendency of transforming clay minerals from extensive into partial intercalation.

Attributes of irrigated rice and soil solution as affected by salinity levels of the water layer

In the State of Rio Grande do Sul, Brazil, flooded rice fields using Patos Lagoon as the source of water for irrigation are subject to be damaged by salinity, since this source is bound to the sea on its southern end. The sensitivity of rice is variable during plant development, being higher in the seedling and reproductive periods. However, there is not enough information about the behavior of plants under salt stress during the course of its development, especially in the vegetative stage. This study evaluated the effect of different levels of salinity of irrigation water on the salinity of soil solution over time and on some plant attributes, during the vegetative stage of rice. The study was conducted in a greenhouse, where seeds of the variety IRGA 424 were sown in pots and irrigated with water with electrical conductivity (ECi) levels of: 0.3, 0.75, 1.5, 3.0 and 4.5 dS m-1; from the tillering initiation (V4) until the panicle initiation (PI). The evaluations made were the electrical conductiviy of soil solution (ECe), the dry biomass of plants and stems, tillering, height and the transpiration of plants. The ECe increased with the ECi over time, and was determined by water transpiration flux in pots. The ECe values at the end of the experiment were high and, in most cases, higher than the critical values for flooded rice. The growth attributes of rice were negatively affected from ECi of 2.0 dS m-1 and ECe of 4.0 dS m-1.

Chemical and physical properties of organic residues

Due to human activity, large amounts of organic residue are generated daily. Therefore, an adequate use in agricultural activities requires the characterization of the main properties. The chemical and physical characterization is important when planning the use and management of organic residue. In this study, chemical and physical properties of charcoal, coffee husk, pine-bark, cattle manure, chicken manure, coconut fiber, sewage sludge, peat, and vermiculite were determined. The following properties were analyzed: N-NH4+, N-N0(3)-, and total concentrations of N, P, S, K, Ca, Mg, Mn, Zn, Cu, and B, as well as pH, Electrical Conductivity (EC) and bulk density. Coffee husk, sewage sludge, chicken manure and cattle manure were generally richer in nutrients. The EC values of these residues were also the highest (0.08 - 40.6 dS m-1). Peat and sewage sludge had the highest bulky density. Sodium contents varied from 0 to 4.75 g kg-1, with the highest levels in chicken manure, cattle manure and sewage sludge. Great care must be taken when establishing proportions of organic residues in the production of substrates with coffee husk, cattle or chicken manure or sewage sludge in the calculation of the applied fertilizer quantity in crop fertilization programs.