Die immer komplexer werdenden geologischen Verhältnisse aktueller Lagerstätten, sowie die Umsetzung einer hoch-selektiven Rohstoffgewinnung, machen eine Modellierung auf Basis von geostatistischen Simulationsverfahren in einem modernen Lagerstättenmanagement notwendig, da diese Verfahren die in-situ Variabilität der struktur- und qualitätsbeschreibenden Lagerstättenparameter realistisch vorhersagen und damit auch realitätsnahe betriebswirtschaftliche Risikoabschätzungen zu den Auswirkungen der Unsicherheiten in der Vorhersage, aufgrund eines unvollständigen Kenntnisstandes, ermöglichen. Die Arbeit beschreibt die Weiterentwicklung und Anwendung von Verfahren der geostatistischen Simulation für die Modellierung komplexer, sedimentartig ausgebildeter Lagerstätten in einem praxisrelevanten Umfang und unter Berücksichtigung der besonderen Anforderungen, welche aus der Charakteristik der Lagerstätte und der Zielsetzung einer selektiven Rohstoffgewinnung abgeleitet wurden. Zunächst wird ein geeigneter Ansatz identifiziert, welcher die Grundlage für eine methodische Erweiterung und effiziente Implementierung, hinsichtlich der zu erfüllenden Anforderungen, bildet. Danach wird die komplette Prozesskette für eine zuverlässige Lagerstättenmodellierung untersucht und praktikable Modellierungsstrategien werden vorgestellt. Ein komplexes Anwendungsbeispiel aus dem Braunkohlenbergbau dient der Evaluierung der vorgestellten Modellierungsverfahren. / The more and more complex geological conditions of current deposits, as well as the implementation of a highly selective extraction of raw materials, require new approaches for the reservoir management. The use of geostatistical simulation methods for modelling the shape and quality of deposits is necessary, because these methods taking into account the natural variability of the deposit attributes and the resulting geological uncertainties. Furthermore this methods allow faithfully and realistic economic risk assessments on the impact of uncertainties in the prediction, due to an incomplete state of knowledge. This work describes the further development and application of geostatistical simulation algorithms for the modelling of complex sediment-like formed deposits in a practically scope, taking into account the special requirements, which are derived from the characteristics of such deposits and the objective of the selective extraction of raw material. First an appropriate simulation approach is identified, which then forms the basis for a methodical expansion and efficient implementation, in terms of fulfilling requirements. In addition, the complete process chain for reliable reservoir modelling is studied and a viable modelling strategy is presented. A complex application example from the lignite mining is used for evaluation of the presented modelling methods.

Near-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices.

Made available in DSpace on 2015-03-26T13:32:11Z (GMT). No. of bitstreams: 1 texto completo.pdf: 446864 bytes, checksum: 1ba8efc18a08b922adc7e2c5eb3dc55c (MD5) Previous issue date: 2011-02-24 / The aim of this study was to evaluate the efficiency of spatial analysis, which considers spatially dependent errors, for classification of common bean families in relation to traditional analysis in randomized blocks and lattice that assuming independent errors. Were considered different degrees of spatial dependence and experimental precision. Were taken as reference to simulate the results of seven experiments carried out in simple square lattice for genetic evaluation of yield (g/plot) of families and bean cultivars of winter crops and water used in 2007 and 2008. From the results presented in the simulation, it was possible to assess the quality of their experiments based on different analysis (Block, lattice and Spatial) and simulated average of 100 families in different scenarios for Spatial Dependence (DE) and Accuracy Selective (AS). In the process of simulation, the average yield (645 g/plot) and the residual variance (7744.00), was defined based on the analysis results of the tests in blocks of bean breeding program at UFV. To make up the four simulated scenarios were considered magnitude of spatial dependence (null, low, medium and high), corresponding to ranges of 0, 25, 50 and 100% of the maximum distance between plots. Were also simulated three classes of selective accuracy (0.95, 0.80 and 0.60), corresponding to the experimental precision very high, high and average, respectively. The actual classification of families was used to evaluate the efficiency of analysis methods tested by Spearman correlation applied to orders and genotypic classification of Selection Efficiency between classifications based on tested methodologies and the actual classification for the selection of 10, 20 and 30% of the best families. To compare the efficiency of adjustment of the models tested, was used the Akaike information criterion (AIC), based on likelihood. Spatial analysis has provided estimates of residual variance very close to the simulated residual variance and higher selective accuracy estimated in all scenarios, indicating greater experimental accuracy. With the reduction in the accuracy and selective increase in spatial dependence, there was greater influence of analysis on the classification of families, and the spatial analysis showed the best results, providing more efficient selection of bean families than traditional analysis of randomized blocks and lattice, mainly for the selection of fewer families. The results for selective accuracy estimated on the basis of F statistics were very close to those obtained with the Spearman correlation between estimated and simulated averages for families, indicating that the accuracy should be used selectively as a measure of experimental precision tests of genetic evaluation. / O objetivo deste trabalho foi avaliar a eficiência da análise Espacial, que considera erros dependentes espacialmente, para classificação de famílias de feijoeiro em relação às análises tradicionais em blocos casualizados e em látice que assumem erros independentes. Considerou-se diferentes graus de dependência espacial e de precisão experimental. Foram tomados como referência para simulação os resultados de sete ensaios instalados em látice quadrado simples para avaliação genética da produtividade de grãos (g/parcela) de famílias e cultivares de feijoeiro das safras de inverno e das águas de 2007 e 2008. A partir dos resultados apresentados na simulação, foi possível avaliar a qualidade dos respectivos experimentos com base nas diferentes análises (Bloco, Látice e Espacial) e médias simuladas das 100 famílias nos diferentes cenários para Dependência Espacial (DE) e Acurácia Seletiva (AS). No processo de simulação, a média de produção (645 g/parcela), bem como a variância residual (7744,00), foi definida com base nos resultados de análises em blocos de ensaios do programa de melhoramento do feijoeiro da UFV. Para a composição dos cenários simulados foram consideradas quatro magnitudes de dependência espacial (nula, baixa, média e alta), correspondendo aos alcances 0, 25, 50 e 100% da distância máxima entre parcelas. Também foram simuladas três classes de acurácia seletiva (0,95, 0,80 e 0,60), correspondente a precisão experimental muito alta, alta e média, respectivamente. A classificação real das famílias foi utilizada para avaliar a eficiência das metodologias de análise testadas através da correlação de Spearman aplicada às ordens de classificação genotípica e da Eficiência de Seleção entre classificações com base nas metodologias testadas e na classificação real, para a seleção de 10, 20 e 30% das melhores famílias. Para comparar a eficiência de ajuste dos modelos testados, foi utilizado o critério de Informação de Akaike (AIC), baseado em verossimilhança. A análise Espacial apresentou estimativas de variância residual muito próxima da variância residual simulada e maior acurácia seletiva estimada em todos os cenários, indicando maior precisão experimental. Com a redução na acurácia seletiva e aumento na dependência espacial, observou-se maior influência do tipo de análise sobre a classificação das famílias, sendo que a análise espacial apresentou os melhores resultados, proporcionando seleção mais eficiente das famílias do feijoeiro do que as análises tradicionais em Látice e em Blocos casualizados, principalmente, para seleção de menor número de famílias. Os resultados para acurácia seletiva estimada em função da estatística F foram muito próximos aos obtidos para a correlação de Spearman entre médias estimadas e simuladas para as famílias, indicando que a acurácia seletiva deve ser utilizada como medida de precisão experimental nos ensaios de avaliação genética.

O padrão espacial de ocorrência de atributos de espécies florestais, tal como a área basal das árvores, pode fornecer informações para o entendimento da estrutura da comunidade vegetal. Uma vez que fatores ambientais podem influenciar tanto o padrão espacial de ocorrência quanto os atributos das espécies em florestas nativas. Desse modo, investigar a relação entre as características ambientais e o padrão espacial de espécies florestais pode ajudar a entender a dinâmica das florestas. Especificamente, neste trabalho, o objetivo é avaliar métodos estatísticos que permitam identificar quais atributos do solo são capazes de explicar a variação da área basal de cada espécie de árvore. A área basal foi considerada como variável resposta e como covariáveis, um grande número de atributos físicos e químicos do solo, medidos em uma malha de localizações cobrindo a área de estudo. Foram revisados e utilizados os métodos de regressão linear múltipla com método de seleção stepwise, modelos aditivos generalizados e árvores de regressão. Em uma segunda fase das análises, adicionou-se um efeito espacial aos modelos, com o intuito de verificar se havia ainda padrões na variabilidade, não capturados pelos modelos. Com isso, foram considerados os modelos autoregressivo simultâneo, condicional autoregressivo e geoestatístico. Dado o grande número de atributos do solo, as análises foram também conduzidas utilizando-se as covariáveis originais, fatores identificados em uma análise fatorial prévia dos atributos de solo. A seleção de modelos com melhor ajuste foi utilizada para identificar os atributos de solo relevantes, bem como a presença e melhor descrição de padrões espaciais. A área de estudo foi a Estação Ecológica de Assis, da Unidade de Conservação do Estado de São Paulo em parcelas permanentes, dentro do projeto \"Diversidade, Dinâmica e Conservação em Florestas do Estado de São Paulo: 40 ha de parcelas permanentes\", do programa Biota da FAPESP. As análises reportadas aqui se referem à área basal das espécies Copaifera langsdorffii, Vochysia tucanorum e Xylopia aromatica. Com os atributos de solo reduzidos e consistentemente associados à área basal, a declividade, altitude, saturação por alumínio e potássio mostraram-se relevantes para duas das espécies. Resultados obtidos mostraram a presença de um padrão na variabilidade, mesmo levando-se em consideração os efeitos das covariáveis, ou seja, os atributos do solo explicam parcialmente a variabilidade da área basal, mas existe um padrão que ocorre no espaço que não é capturado por essas covariáveis. / The spatial pattern of occurrenceis of forest species and their attributes, such as the basal area of trees, can provide information for understanding the structure of the vegetable community. Considering the environmental factors can influence the spatial pattern of occurrences of species in native forests and related attributes, describing relationship between environmental characteristics and spatial pattern of forest species can be associated with the dynamics of forests. The objective of the present study is to assess different statistical methods used to identify which soil attributes are associated with the basal area of each tree selected species. The basal area was considered as the response variable and the covariates are given by a large number of physical and chemical attributes of the soil, measured at a grid of locations covering the study area. The methods considered are the multiple linear regression with stepwise model selection, generalized additive models and regression trees. Spatial effects were added to the models, in order to ascertain whether there is residual spatial patterns not captured by the covariates. Thus, simultaneous autoregressive model, autoregressive conditional and geostatistical were considered. Considering the large number of soil attributes, analysis were were conducted both ways, using the original covariates, and using factors identified in a preliminar factor analysis of the soil attributes. Model selection was used to identify the relevant attributes of soil as well as the presence and better description of spatial patterns. The study area was the Ecological Station of Assis, the Conservation Unit of the State of São Paulo in permanent plots within the \"Diversity Dynamics and Conservation Forests in the State of São Paulo: 40 ha of permanent plots\" project, under the research project FAPESP biota. The analyzes reported here refer to the basal area of the species Copaifera langsdorffii, Vochysia tucanorum and Xylopia aromatica. Results differ among the considered methods reinforcing the reccomendation of considering differing modeling strategies. Covariates consistently associated with basal area are slope, altitude and aluminum saturation, potassium, relevant to at least two of the species. Results obtained showed the presence of patterns in residual variability, even taking into account the effects of covariates. The soil characteristics only partially explain the variability of the basal area and there are spatial patterns not captured by these covariates.

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior / Dunas costeiras exercem um importante papel na manutenÃÃo do fluxo de sedimentos da zona costeira. O Parque Nacional de Jericoacoara, localizado no estado do CearÃ, regiÃo Nordeste do Brasil, possui uma morfologia pouco frequente, trata-se de um promontÃrio associado com um campo de dunas mÃveis denominadas barcanas, dunas individuais, de grande porte com formato de ferraduras que se deslocam em direÃÃo L â O. Elas realizam o by-pass, o transporte de sedimentos, essencial para a manutenÃÃo da linha de costa. Neste trabalho, foi priorizada a definiÃÃo da evoluÃÃo morfodinÃmica de dunas mÃveis isoladas (dunas Papai Noel, PÃr-do-Sol e Arraia), tendo como referencial teÃrico a anÃlise das paisagens e como procdimento tÃcnico principal a anÃlise espaÃo-temporal do recobrimento de imagens multitemporais dos satÃlites Landsat e Quickbird entre os anos de 1973 a 2014. AtravÃs da comparaÃÃo da distribuiÃÃo espaÃo temporal das morfologias dunares, nesse perÃodo de 41 anos, evidenciaram-se mudanÃas significativas na Ãrea, perÃmetro e deslocamento das dunas. Foi possÃvel constatar a aÃÃo dos fluxos de matÃria e energia vinculados com migraÃÃo continuada direcionada para a faixa de praia (setor de bypassing de sedimentos). A dinÃmica de migraÃÃo das dunas, quando analisadas apÃs as imagens de 2000, evidenciou possibilidades de alteraÃÃes dos aspectos morfolÃgicos influenciados pelo incremento do fluxo turÃstico, quando instituÃdo o PARNA de Jericoacoara. As mudanÃas foram mais significativas, sobretudo, entre os anos de 2001 a 2005, o que pode estar relacionado a uma maior intervenÃÃo humana (fluxo de turistas). A utilizaÃÃo das tÃcnicas de geoprocessamento para o mapeamento da evoluÃÃo morfodinÃmica do campo de dunas do Parque Nacional de Jericoacoara constituiu- se uma ferramenta essencial para a produÃÃo de informaÃÃes que certamente subsidiarÃo a continuidade do planejamento ambiental da referida, que se constitui como uma Unidade de ConservaÃÃo de ProteÃÃo Integral. / Coastal dunes play an important role in the sediment flow of the coastal zone. The unique morphology of the Jericoacoara National Park in the northeastern Brazilian state of Cearà consists of a promontory covered by a mobile dune field consisting of large, horseshoe-shaped dunes known locally as barcanas that migrate from east to west. These dunes are responsible for the by-pass, the transport of sediments essential for the maintenance of the coastline. The present study focused on the morphodynamic evolution of these isolated mobile dunes through the recovery of multitemporal Landsat and Quickbird satellite images from the years between 1975 and 2014. The comparison of the spatio-temporal distribution of the morphology of these dunes over this 41-year period revealed significant shifts in their area, perimeter, and movement. It was possible to confirm that the flow of material and energy were linked to a process of continuous migration in the direction of the beach (sediment bypassing sector). The dynamics of the dune migration in the years following 2000, when the national park was established, indicate possible impacts of the increase in tourism within the area on the morphology of the dunes. The changes were most significant between 2001 and 2005, possibly reflecting a greater influx of tourists and thus more intense anthropogenic impacts. The different geoprocessing techniques applied to the mapping of the morphodynamic evolution of the dune field of the Jericoacoara National Park proved to be an essential tool for the production of information that will guarantee the long-term environmental planning of this integral conservation unit.

Made available in DSpace on 2014-07-29T14:52:11Z (GMT). No. of bitstreams: 1 Eduardo.pdf: 1760527 bytes, checksum: c1e3df85130dbf89d9ce86b4244ef585 (MD5) Previous issue date: 2009-02-18 / The hydrological behavior of watersheds derives mainly from the processes of climate variability and land use, and thus, may be affected by human action. The João Leite river is the main source of water supply of Goiânia, in addition to providing water to multiple uses throughout the basin. In the last decades, this catchment have been pass for intensive changes in land use, and recently, with the increasing pressure on water resources, conflicts because the relative scarcity of water quantity and quality, have been reported among users. In this context, this study aimed to analyze the trend of hydrological variables between 1975 and 2005; to test the semivariograma model spherical, exponential and Gaussian, adjusted by the method of weighted least squares in the mapping by kriging of monthly and annual average precipitation; classify the land use between 1979 and 2005, establishing the qualitative and quantitative association of the flow rate with the land use and climate variability and finally, assess the available water produced by the combination of different flow rates of reference and criteria for award. For this, we used satellite images from the years of 1979, 1989, 1997 and 2005, data flow from the Captação João Leite gauging station and rainfall from 14 stations, provided by National Water Agency of Brazil. It was found a good performance of geostatistics techniques to map the average monthly and annual precipitation, with emphasis on exponential model that show the best fit. The land use was marked by 17.8% of the deforestation, expansion of the urbanization and agriculture at 6.6 and 15.2% respectively, and expressive area of grassland, about 40% over of time. The declining trend observed in the flow can be explained, in part, by the reduction of the rain rate, however, due to the significant increase in stream water collected at João Leite river and lack of historical records, there was difficulty in the qualitative association between flow rate and land use, however, quantitative analysis models show coefficients of determination (R ²) above 0.75. It was noted that the establishment of a single value for the flow of reference, regardless in irrational use of water. The adoption of the monthly reference flow show highly promising alternative to optimize the use of surface water resources in the João Leite watershed, and consequently, to the Goiás state, providing 40% more water than that provided by the criterion of single value. / O comportamento hidrológico de uma bacia hidrográfica decorre principalmente da variabilidade dos processos climáticos e do uso do solo e desta maneira, pode ser afetado pela ação antrópica. A bacia hidrográfica do ribeirão João Leite constituise no principal manancial de abastecimento de Goiânia, além de prover água a múltiplos usos ao longo da bacia. Essa área passou ao longo das ultimas décadas por intensas modificações no uso do solo, e recentemente, com a crescente pressão sobre os recursos hídricos, vêm sendo relatados conflitos entre usuários, decorrentes da relativa escassez quantitativa e qualitativa da água. Nesse contexto, esse estudo teve como objetivos: analisar a tendência das variáveis hidrológicas entre 1975 e 2005; testar os modelos de semivariograma esférico, exponencial e gaussiano, ajustados pelo método dos mínimos quadrados ponderados no mapeamento por krigagem da precipitação média mensal e anual; classificar o uso do solo entre 1979 e 2005; realizar a associação qualitativa e quantitativa das vazões com o uso do solo e a variabilidade climática e por fim, avaliar as disponibilidades hídricas produzidas pela associação de diferentes vazões de referência e critérios de outorga. Para isso, foram utilizadas imagens Landsat dos anos de 1979, 1989, 1997 e 2005, dados de vazão da estação fluviométrica Captação João Leite e de precipitação de 14 estações pluviométricas disponibilizadas pela Agência Nacional de Águas (ANA). Foi constatado bom desempenho das técnicas geoestatíscas no mapeamento da precipitação média mensal e anual, com destaque ao modelo exponencial que se sobressaiu na maioria dos eventos estudados. O uso do solo foi marcado pelo desmatamento de 17,8% da vegetação nativa, expansão das áreas de urbanização e agricultura em 6,6 e 15,2%, respectivamente, e pela expressiva área de pastagens, em torno de 40% ao longo do tempo. A tendência de redução observada para o escoamento pode ser explicada, em parte, pela redução do regime de chuvas, contudo, devido ao expressivo aumento da água captada no ribeirão João Leite e a ausência de registros históricos, houve dificuldade na associação qualitativa entre o escoamento e o uso do solo, contudo, na análise quantitativa, foram gerados modelos por regressão linear com coeficientes de determinação (R²) acima de 0,75. Ficou constatado que o estabelecimento de um valor único anual para a vazão de referência, independentemente dos critérios de outorgas, resulta em utilização irracional do manancial. A adoção de vazões de referência mensal mostrou-se uma alternativa altamente promissora para otimização da utilização dos recursos hídricos superficiais na bacia do ribeirão João Leite, e por conseqüência, para o estado de Goiás, disponibilizando um volume 40% maior que o disponibilizado pelo critério de outorga atualmente em vigor.

Made available in DSpace on 2014-08-20T14:36:56Z (GMT). No. of bitstreams: 1 Tese_ Alvaro_ Luiz_ Carvalho_ Nebel.pdf: 1615608 bytes, checksum: cf5d12660d9ae82ddc2e973b92c9812e (MD5) Previous issue date: 2009-04-24 / The understanding of the dynamics of the water in the soil-plant-atmosphere system, including the water availability to the crops, soil water infiltration, drainage and soil solute movement, depends on the knowledge of the relation between the soil water content and the matric potential, represented by the soil water retention curve (SWRC). However, the establishment of SWRCs is laborious and time consuming, besides being costly. A alternative is its estimate through statistical equations called Pedotransfer Functions (PTFs). The aim of this study was to evaluate the ability of some existing PTFs, in predicting the soil water retention and to capture its spatial variability structure, using geostatistical tools, when applied in a lowland soil of the south region of Brazil. For this, an experimental 10 x 10 m grid was established and soil disturbed and undisturbed samples were collected in the 0-0.20 m soil depth, totaling 100 experimental points. The following soil attributes were determined in each point: soil texture, soil organic carbon, pH, cation exchange capacity, soil bulk density, and the soil water retention curve. Eight developed PTFs for estimating gravimetric soil water content, eight for estimating volumetric water content and five for estimating the van Genuchten model parameters were evaluated using the statistical measures mean error (ME), and the root mean square error (RMSE). Results indicated that the Oliveira et al. (2002) PTF presented the best performance for estimating the gravimetric soil water content at the tension of 33kPa, with mean error (ME) value of 0.0136g.g-1, while for the gravimetric water content at tension of 1500kPa the Pidgeon (1972) FPT was the best, with ME value of -0,0054g.g-1. Concerning to the potential of describing the spatial variability structure the Bell & van Keulen (1995 and 1996) and of Urach (2007) PTFs presented the best performance based on the results from the cross validation technique. For estimating the soil water volumetric content at the tension of 10kPa the Tomasela et al. (2002) was the best (ME of 0.019cm3.cm-3), while Rawls et al. (1982) and van den Berg et al. (1997) PTFs were the best for estimating soil water content at the tension of 33kPa (ME of 0.001cm3.cm-3) and 1500kPa (ME of -0.008cm3.cm-3), respectively. The range and sill geostatistical parameters for the tension of 33kPa were reasonable estimated, while for the tension of 1500kPa they were underestimated by the evaluated PTFs. The Parametric Pedotransfer Function constructed by Vereecken et al.(1989) presented the lowest value of ME (0.0247cm3.cm-3), while the Hodnett and Tomasella (2002) PTF presented the lowest value of RMSE (0.0367 cm3.cm-3). Both PTFs well described the experimental semivariograms of the soil water content at the tensions of 10kPa and 33kPa, however their performance was not good for the tension of 1500kPa. / Estudos que envolvem a dinâmica da água no sistema solo-planta-atmosfera tais como disponibilidade de água no solo para as culturas, infiltração, drenagem e movimento de solutos no solo necessitam do conhecimento da relação entre o conteúdo de água no solo e o potencial matricial, representada pela curva de retenção de água no solo. No entanto, sua execução é laboriosa, demanda considerável tempo e custos. Uma alternativa é sua estimativa através de equações estatísticas denominadas Funções de Pedotransferência (FPTs). O objetivo deste estudo foi avaliar o desempenho de funções de pedotransferência em estimar a retenção de água no solo e capturar a sua estrutura de variabilidade espacial, usando ferramentas geoestatísticas, quando aplicadas em um solo de várzea da região sul do Brasil. Para isto, uma malha experimental de 10m x 10m foi estabelecido e amostras deformadas e indeformadas do solo foram coletadas representativas da camada de 0 0,20m, totalizando 100 pontos amostrais. Os seguintes atributos do solo foram determinados em cada ponto: textura, carbono orgânico, pH, capacidade de troca de cátions, densidade do solo e a curva de retenção de água no solo. Oito FPTs desenvolvidas para estimar o conteúdo gravimétrico de água no solo, oito para estimar o conteúdo volumétrico e cinco para estimar os parâmetros do modelo de van Genuchten foram avaliadas, usando as medidas estatísticas erro médio (ME) e raiz quadrada do erro médio ao quadrado (RMSE). Os resultados obtidos para a estimativa do conteúdo de água gravimétrico mostram que a FPT de Oliveira et al. (2002) apresentou o melhor desempenho para a tensão de 33kPa, com erro médio (ME) de 0,0136g.g-1, enquanto para a tensão de 1500kPa a FPT de Pidgeon (1972) foi melhor, com ME de -0,0054g.g-1. Com relação ao potencial de descrever a estrutura de variabilidade espacial do conjunto de dados medidos, as FPTs desenvolvidas por Bell & van Keulen (1995 e 1996) e Urach (2007) foram as que apresentaram melhor desempenho baseado nos resultados da validação cruzada. Para o conteúdo volumétrico de água retida no solo, os melhores desempenhos foram obtidos pela FPT de Tomasela et al.(2003) para a tensão de 10kPa, Rawls et al. (1982) para 33kPa e van den Berg et al.(1997) para 1500kPa, com ME iguais a 0,019cm3.cm-3, 0,001cm3.cm-3 e -0,008cm3.cm-3, respectivamente. Os parâmetros da estrutura de dependência espacial, alcance e patamar, para a tensão de 33kPa foram razoavelmente estimados, enquanto para a tensão de 1500kPa foram subestimados pelas FPTs avaliadas. A FPT paramétrica desenvolvida por Vereecken et al. (1989) apresentou o menor valor de ME (0,0247cm3.cm-3), enquanto a FPT de Hodnett e Tomasella (2002) apresentou o menor valor de RMSE (0,0367 cm3.cm-3). Ambas FPTs descreveram bem os semivariogramas experimentais do conteúdo de água retido no solo a 10kPa e 33kPa, entretanto para a tensão de 1500kPa nenhuma das FPTs testadas apresentou bom desempenho.

This work was based in methods of classic descriptive statistics, methods of geostatistics and geoprocessing, in the identification of the size and the structure of the spatial variability of the physical and chemical attributes of the soil in area of Paraguay Tea forestry. The area of study, localized in the Tupian Farm, in the municipality of New Silver, RS, where were raised samples from January to March, 2005, embracing the Latosoil humic dystrophic soil. It was accomplished systematic sample with grid of regular spacing among the one hundred meter points, totalizing thirty-six sample points and the six hundred and thirty pairs of data, in an area of thirty-six hectares. Were collected samples of soil in situ for analysis in laboratory of the physic attributes of the bulky sand (BS), thin sand (TS) , silt (SIL), argil (ARG), soil density (SD), particle density (PD) and whole porosity (WP) and chemical attributes of argil, texture, pH (H2O), phosphorus (P), potassium(P), organic material (OM), aluminum (AL), calcium (Ca), magnesium (Mg), exchangeable aluminum (H + Al), cations real exchange capacity (CTCe), cations exchange capacity to pH7 (CTCpH7) and saturation of basis (V%). The magnitudes of spatial variabilities were obtained by the variation of coefficient (CV%), with confidence level of 95%, through Microsoft Office Excel 2003 program, while the structure was identified by semivariogrames, in applications geostatistics establishing the necessary parameters to the krigagem . All models of semivariogrames presented zones of anisotropic influence, having its spatial variability the greatest in the perpendicular sense to these areas the declivity. The chemical attribute that presented greatest variability was phosphorus (P), with CV%=127,73, followed by the aluminum attribute (Al), com CV%= 99,23 and the attribute of least variability was the pH (H2O), com CV%=0,0013. To the physical attributes in the distribution of particles size (%), the attribute of greatest variability was bulky sand, with CV%=36,39, while the statistics made to the density attributes of soil, what present the greatest variability was the attribute of whole porosity, with CV%=95,49 and they least variability was verified was the argil, with CV%=12,32. IN the analysis of the structure of the spatial variability through geostatistics, the chemical attribute Ca presented IDE (%)=64,42 and the physical attribute ARG with IDE (%)=62,50, getting the greatest rates. To the accomplishment of agreement in the program VARIOWIN® 2.21- Software for Spatial Data Analysis , the method used was the visual, named the feeling , where the Spherical model was what better was adapted to the studied attributes, indicated in 55% of the variogrames. The Gaussian s model to the attribute of texture got the most overtaking with a (m)=421. A crusade validation with the usage of the program GSLIB90 Geostatistical Software Library pointed out accuracy in the agreement of the variographic models, having the attributes Ca, Al and ARG with R² (%) of 0,841; 0,705 and 0,760, respectively. The usual krigagem of the studied attributes permitted the detailed of the distribution of these through the maps of isolineas. / Este trabalho utilizou-se de métodos de estatística descritiva clássica, métodos de geoestatística e de geoprocessamento, na identificação do tamanho e da estrutura da variabilidade espacial de atributos físico-químicos do solo em área de florestamento de erva-mate. A área de estudo, localizada na Fazenda Tupi, no município de Nova Prata, RS, foi levantada amostras nos meses de janeiro a março de 2005, compreendendo a classe de solo Latossolo Húmico Distrófico Álico. Realizou-se amostragem sistemática com grid de espaçamento regular entre os pontos de 100 metros, totalizando 36 pontos amostrais e 630 pares de dados, em uma área de 36 hectares. Foram coletadas amostras de solo in situ para análise em laboratório dos atributos físicos areia grossa (AG), areia fina (AF), silte (SIL), argila (ARG), densidade de solo (DS), densidade de partícula (DP) e porosidade total (PoT) e atributos químicos argila, textura, pH (H2O), fósforo (P), potássio (K), matéria orgânica (M.O.), alumínio (Al), cálcio (Ca), magnésio (Mg), alumínio trocável (H+Al), capacidade de troca de cátions efetiva (CTCe), capacidade de troca de cátions à pH7 (CTCpH7) e saturação de bases (V%). As magnitudes das variabilidades espaciais foram obtidas pelo coeficiente de variação (CV%), com nível de confiança de 95,0%, através do programa Microsoft Office Excel 2003, enquanto que a estrutura foi identificada por meio de semivariogramas, em aplicativos geoestatísticos, definindose os parâmetros necessários para a krigagem. Todos os modelos de semivariogramas apresentaram zonas de influência anisotrópicas, tendo sua variabilidade espacial maior no sentido perpendicular a declividade destas áreas. O atributo químico que apresentou maior variabilidade foi o fósforo (P), com CV%=127,73, seguido do atributo alumínio (Al), com CV%=99,23 e o atributo de menor variabilidade, foi o pH(H2O), com CV%=13,79. Para os atributos físicos, na distribuição do tamanho de partículas (%), o atributo de maior variabilidade foi areia grossa, com CV%=36,39, enquanto a estatística realizada para os atributos densidade do solo, o que apresentou maior variabilidade foi o atributo porosidade total, com CV%=95,49 e a menor variabilidade foi constatada a argila, com CV%=12,32. Na análise de estrutura da variabilidade espacial através da geoestatística, o atributo químico Ca apresentou IDE(%)=64,42 e o atributo físico ARG com IDE(%)=62,50, obtendo os maiores índices. Para realização do ajuste no programa VARIOWIN® 2.21 Software for Spatial Data Analysis , o método utilizado foi o visual, denominado a sentimento , onde o modelo Esférico foi o que melhor se ajustou aos atributos estudados, indicado em 55% dos semivariogramas. O modelo Gaussiano para o atributo textura obteve o maior alcance com a(m)=421. A validação cruzada, com o uso do programa GSLIB 90 Geostatistical Software Library mostrou acuracidade no ajuste dos modelos variográficos, tendo os atributos Ca, Al e ARG com R²(%) de 0,841; 0,705 e 0,760, respectivamente. A krigagem ordinária dos atributos estudados permitiu o detalhamento da distribuição destas a partir dos mapas de isolinhas.

La pollution atmosphérique constitue un risque environnemental majeur dont les effets néfastes sur la santé et sur l’environnement sont déjà clairement démontrés. Toutefois, la mesure d’exposition des populations aux polluants tels que les particules fines et l’ozone troposphérique demeure approximative en raison de la faible densité des stations d’échantillonnage de ces polluants. Peu d’études ont considéré la variation spatiale intra-urbaine dans la modélisation spatiale des concentrations de polluants. Certaines études ont cependant combiné interpolation spatiale et corrélation avec des facteurs locaux. De plus, l’effet du régime météorologique (par exemple l’occurrence d’une inversion de température) sur l’amplitude de ces corrélations n’est pas pris en compte. Cette thèse a donc pour objectif d’évaluer de nouvelles manières de caractériser la distribution spatiale et temporelle des particules fines (PM2.5) et de l’ozone troposphérique (O3) à l’échelle intra-urbaine. Plus particulièrement, nous avons développé un modèle de géostatistique multivariable appelée krigeage avec dérive externe (KED, kriging with external drift) basé sur l’intégration de variables auxiliaires dans le processus d’estimation journalière des PM2.5 et de l’O3. Le krigeage constitue une forme d’interpolation spatiale des données de stations de mesures éparses, alors que la dérive externe mise sur des corrélations entre des conditions locales (axes de transport routier, espaces verts, etc.) et la concentration des polluants atmosphériques. Afin de prendre en compte les variations temporelles, notamment celles reliées aux conditions météorologiques, ces modèles ont été développés par groupes basés sur des conditions synoptiques et six classes d’états établies selon la température, le vent, l’humidité relative et les précipitations, d’après des données météorologiques journalières. Les résultats montrent que l’intégration des variables auxiliaires telles que la densité de la végétation et les zones des activités industrielles locales dans le KED expliquent en partie les variations intra-urbaines des PM2.5 de l’île de Montréal, mais que cet apport est variable selon la classe météorologique. Ainsi, lorsque les corrélations sont très faibles, une interpolation spatiale simple, comme la méthode IDW (inverse distance weighting) est plus exacte que l’interpolation multivariable, alors que pour d’autres conditions synoptiques le KED produit les prédictions les plus certaines. Nous avons pour cette raison proposé un modèle d’interpolation hybride (KED-IDW) s’adaptant aux conditions météorologiques. Nous avons également montré, particulièrement dans le cas de l’O3, que le krigeage avec dérive externe améliore les résultats obtenus par krigeage ordinaire (sans variables auxiliaires). Cette thèse a aussi permis d’évaluer l’apport d’un modèle spatio-temporel (BME, bayesian maximum entropy) dans l’estimation de l’effet à court terme de l’exposition à l’O3 sur les décès à Montréal. Les résultats suggèrent que ce modèle spatio-temporel dans les conditions développées (par ex. basé sur les données de 12 stations de mesures, pour un territoire de 1 310 km2) n’apporte pas de gains significatifs dans l’estimation de l’effet de l’exposition. Dans l’ensemble, cette thèse contribue au progrès de modélisation spatiale empirique des polluants atmosphériques en se fondant notamment sur l’adaptation aux conditions météorologiques et par l’ajout de certains facteurs météorologiques comme prédicteurs. Dans ce contexte, cette thèse ouvre une voie prometteuse pour l’amélioration des estimations de polluants atmosphériques à l’échelle intra-urbaine et de la capacité à évaluer les risques à la santé de la population par une meilleure caractérisation de l’exposition. Mots-clés : pollution de l’air, particules fines, ozone troposphérique, santé, géostatistique, krigeage avec dérive externe, environnement urbain. / Air pollution is a major environmental hazard with clearly demonstrable adverse effects on health and the environment. However, the measurement of populations’ exposure to pollutants such as particulate matter and ground-level ozone remains approximate due to the low density of sampling stations for these pollutants. Moreover, intra-urban spatial variation in the spatial modeling of pollutant concentrations has received little research attention. If anything, some studies have combined spatial interpolation and correlation with local factors; however, they do so without examining the effect of the weather regime (e.g., a temperature inversion) on the magnitude of these correlations. In order to overcome these shortcomings, this dissertation aims to evaluate new ways of characterizing the spatial and temporal distribution of fine particles (PM2.5) and ground-level ozone (O3) at the intra-urban scale. In particular, we developed a multivariable geostatistical model called “kriging with external drift” (KED) based on the integration of auxiliary variables into the process of estimating daily PM2.5 and O3 concentrations. Kriging is a form of spatial interpolation of data from measurement stations that are dispersed, while external drift is based on correlations between local conditions (road transport arteries, green spaces, etc.) and the concentration of atmospheric pollutants. In order to take account of temporal variations, especially those related to weather conditions, we designed these models around six synoptic weather classes based on daily meteorological data (such as temperature, wind, relative humidity and precipitation). v The results show that the integration of auxiliary variables (such as vegetation density and local industrial activity areas) in KED partly explains the intra-urban variations of PM2.5 on the island of Montreal, but that this contribution is variable depending on the weather conditions. Thus, when the correlations are very low, a simple spatial interpolation (such as the inverse distance weighting (IDW) method) is more accurate than multivariable interpolation, whereas for other synoptic conditions KED produces the most certain predictions. For this reason, we proposed a hybrid interpolation model (KED-IDW) that can adapt to different weather conditions. We have also shown, particularly in the case of O3, that KED improves the results obtained from ordinary kriging (without auxiliary variables). This dissertation also allowed to evaluate the contribution of a spatial-temporal model—BME (bayesian maximum entropy)—in the estimation of the short-term effect of exposure to O3 on deaths in Montreal. The results suggest that this spatio-temporal model under the determined conditions (e.g., based on data from 12 measurement stations, for a territory of 1 310 km2) does not offer significant improvements to the estimation of the effect of exposure. Overall, this dissertation contributes to the advancement of the empirical spatial modeling of air pollutants, namely by taking into account the adaptation to weather conditions as well as certain predictive meteorological factors. In this context, the dissertation opens up a promising path for improving the estimation of air pollution at the intra-urban scale and the capacity to assess population health risks through better characterization of exposure.

Die immer komplexer werdenden geologischen Verhältnisse aktueller Lagerstätten, sowie die Umsetzung einer hoch-selektiven Rohstoffgewinnung, machen eine Modellierung auf Basis von geostatistischen Simulationsverfahren in einem modernen Lagerstättenmanagement notwendig, da diese Verfahren die in-situ Variabilität der struktur- und qualitätsbeschreibenden Lagerstättenparameter realistisch vorhersagen und damit auch realitätsnahe betriebswirtschaftliche Risikoabschätzungen zu den Auswirkungen der Unsicherheiten in der Vorhersage, aufgrund eines unvollständigen Kenntnisstandes, ermöglichen. Die Arbeit beschreibt die Weiterentwicklung und Anwendung von Verfahren der geostatistischen Simulation für die Modellierung komplexer, sedimentartig ausgebildeter Lagerstätten in einem praxisrelevanten Umfang und unter Berücksichtigung der besonderen Anforderungen, welche aus der Charakteristik der Lagerstätte und der Zielsetzung einer selektiven Rohstoffgewinnung abgeleitet wurden. Zunächst wird ein geeigneter Ansatz identifiziert, welcher die Grundlage für eine methodische Erweiterung und effiziente Implementierung, hinsichtlich der zu erfüllenden Anforderungen, bildet. Danach wird die komplette Prozesskette für eine zuverlässige Lagerstättenmodellierung untersucht und praktikable Modellierungsstrategien werden vorgestellt. Ein komplexes Anwendungsbeispiel aus dem Braunkohlenbergbau dient der Evaluierung der vorgestellten Modellierungsverfahren. / The more and more complex geological conditions of current deposits, as well as the implementation of a highly selective extraction of raw materials, require new approaches for the reservoir management. The use of geostatistical simulation methods for modelling the shape and quality of deposits is necessary, because these methods taking into account the natural variability of the deposit attributes and the resulting geological uncertainties. Furthermore this methods allow faithfully and realistic economic risk assessments on the impact of uncertainties in the prediction, due to an incomplete state of knowledge. This work describes the further development and application of geostatistical simulation algorithms for the modelling of complex sediment-like formed deposits in a practically scope, taking into account the special requirements, which are derived from the characteristics of such deposits and the objective of the selective extraction of raw material. First an appropriate simulation approach is identified, which then forms the basis for a methodical expansion and efficient implementation, in terms of fulfilling requirements. In addition, the complete process chain for reliable reservoir modelling is studied and a viable modelling strategy is presented. A complex application example from the lignite mining is used for evaluation of the presented modelling methods.