943 resultados para Electrical Conductivity


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In this work, the thermal stability of TiAgx thin films, deposited by magnetron sputtering, was evaluated, envisaging their application in biomedical devices, namely as electrodes for biosignal acquisition. Based on the composition and microstructural characterization, a set of four representative TiAgx thin films was selected in order to infer whether they are thermally stable in terms of functional properties. In order to achieve this purpose, the structural and morphological evolution of the films with annealing temperature was correlated with their electrical, mechanical and thermal properties. Two distinct zones were identified and two samples from each zone were extensively analysed. In the first zone (zone I), Ti was the main component (Ti-rich zone) while in the second, zone II, the Ag content was more significant. The selected samples were annealed in vacuum at four different temperatures up to 500 oC. For the samples produced within zone I, small microstructural changes were observed due to the recrystallization of the Ti structure and grain size increment. Also, no significant changes were observed with annealing temperature regarding the f l ’ functional properties, being thermally stable up to 500 oC. For higher Ag contents (zone II) the energy supplied by thermal treatments was sufficient to activate the crystallization of Ti-Ag intermetallic phases. A strong increase of the grain size of these phases was also reported. The structural and morphological organization proved to be determinant for the physical responses of the TiAgx system. The hardness and Y g’s modulus were significantly improved with the formation of the intermetallic phases. The silver addition and annealing treatments also played an important role in the electrical conductivity of the films, which was once again improved by the formation of Ti-Ag phases. The thermal diffusivity of the films was practically unchanged with the heat-treatment. This set of results shows that this intermetallic-like thin film system has good thermal stability up to high temperatures (as high as 500 oC), which in case of the highest Ag content zone is particularly evident for electrical and mechanical properties, showing an important improvement. Hardness increases about three times, while resistivity values become half of those from the lowest Ag contents zone. These set of characteristics are consistent with the targeted applications, namely in terms of biomedical sensing devices.

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This paper reports the fabrication process and characterization of a flexible pressure sensor based on polydimethylsiloxane (PDMS) and multi-walled carbon nanotubes (CNT-PDMS). The proposed approach relies on patterned CNT-PDMS nanocomposite strain gauges fabricated with SU-8 microstructures (with the micropatterns) in a low‑cost and simple fabrication process. This nanocomposite polymer is mounted over a PDMS membrane, which, in turn, lies on top of a PDMS diaphragm like structure. This configuration enables the PDMS membrane to bend when pressure is applied, thereby affecting the nanocomposite strain gauges, effectively changing their electrical resistance. Carbon nanotubes have several advantages such as excellent mechanical properties, high electrical conductivity and thermal stability. Furthermore, the measurement range of the proposed sensor can be adapted according to the application by varying the CNTs content and geometry of microstructure. In addition, the sensor’s biocompatibility, low cost and simple fabrication makes it very appealing for biomechanical strain sensing. The sensor’s sensitivity was about 0.073%ΔR/mmHg.

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Tese de Doutoramento Programa Doutoral em Engenharia Electrónica e Computadores.

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Dissertação de mestrado em Geociências (área de especialização em Recursos Geológicos)

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A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

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The vulnerability to pollution and hydrochemical variation of groundwater in the mid-west karstic lowlands of Ireland were investigated from October 1992 to September 1993, as part of an EU STRIDE project at Sligo Regional Technical College. Eleven springs were studied in the three local authority areas of Co. Galway, Co. Mayo, and Co. Roscommon. Nine of the springs drain locally or regionally important karstic aquifers and two drain locally important sand and gravel aquifers. The maximum average daily discharge of any of the springs was 16,000 m3/day. Determination of the vulnerability of groundwater to pollution relies heavily on an examination of subsoil deposits in an area since they can act as a protecting or filtering layer over groundwater. Within aquifers/spring catchments, chemical reactions such as adsorption, solution-precipitation or acid-base reactions occur and modify the hydrochemistry of groundwater (Lloyd and Heathcote, 1985). The hydrochemical processes) that predominate depend cm the mineralogy of the aquifer, the hydrogeological environment, the overlying subsoils, and the history of groundwater movement. The aim of this MSc research thesis was to investigate the hydrochemical variation of spring outflow and to assess the relationship between these variations and the intrinsic vulnerability of the springs and their catchments. If such a relationship can be quantified, then it is hoped that the hydrochemical variation of a spring may indicate the vulnerability of a spring catchment without the need for determining it by field mapping. Such a method would be invaluable to any of the three local authorities since they would be able to prioritise sources that are most at risk from pollution, using simple techniques of chemical sampling, and statistical analysis. For each spring a detailed geological, hydrogeological and hydrochemical study was carried out. Individual catchment areas were determined with a water balance/budget and groundwater tracing. The subsoils geology for each spring catchment were mapped at the 1:10,560 scale and digitised to the 1:25,000 scale with AutoCad™ and Arclnfo™. The vulnerability of each spring was determined using the Geological Survey's vulnerability guidelines. Field measurements and laboratory based chemistry analyses of the springs were undertaken by personnel from both the EPA Regional Laboratory in Castlebar, Co. Mayo, and the Environment Section of Roscommon Co. Council. Electrical conductivity and temperature (°C) were sampled fortnightly, in the field, using a WTW microprocessor conductivity meter. A percentage (%) vulnerability was applied to each spring in order to indicate the areal extent of the four main classes of vulnerability (Extreme, High, Moderate, and Low) which occurred within the confines of each spring catchment. Hydrochemical variation for the springs were presented as the coefficient of variation of electrical conductivity. The results of this study show that a clear relationship exists between the degree of vulnerability of each catchment area as defined by the subsoil cover and the coefficient of variation of EC, with the coefficient of variation increasing as the vulnerability increases. The coefficient of variation of electrical conductivity is considered to be a parameter that gives a good general reflection of the degree of vulnerability occurring in a spring catchment in Ireland's karstic lowlands.

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ჩატარებულია ჰაერის ელექტროგამტარობის საშუალო თვიური მნიშვნელობების, როგორც ატმოსფეროს სისუფთავის ფაქტორის, ცვალებადობის გამოკვლევა და შეფასებულია მისი გავლენა ადამიანის ჯანმრთელობაზე

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.