Uncertainties are present in the inverse analysis of damage identification with respect to the given measurements, mainly the modelling uncertainties and the measurement uncertainties. Modelling uncertainties occur due to constructing a representative model of the real structure through finite element modelling, and representing damage in the real structures through changes in material parameters of the finite element model (assuming smeared crack approach). Measurement uncertainties are always present in the measurements despite the accuracy with which the measurements are measured or the precision of the instruments used for the measurement. The modelling errors in the finite element model are assumed to be encompassed in the updated uncertain parameters of the finite element model, given the uncertainties in the measurements and in the prior uncertainties of the parameters. The uncertainties in the direct measurement data are propagated to the estimated output data. Empirical models from codal provisions and standard recommendations are normally used for prediction of long-time deformations in concrete structures. Uncertainties are also present in the creep and shrinkage models, in the parameters of these models, in the shrinkage and creep mechanisms, in the environmental conditions, and in the in-situ measurements. All these uncertainties are needed to be considered in the damage identification and prediction of long-time deformations in concrete structures. In the context of modelling uncertainty, uncertainties can be categorized into aleatory or epistemic uncertainty. Aleatory uncertainty deals with the irresolvable indeterminacy about how the uncertain variable will evolve over time, whereas epistemic uncertainty deals with lack of knowledge. In the field of damage detection and prediction of long time deformations, aleatory uncertainty is modeled through probabilistic analysis, whereas epistemic uncertainty can be modeled through (1) Interval analysis (2) Ellipsoidal modeling (3) Fuzzy analysis (4) Dempster-Shafer evidence theory or (5) Imprecise probability. Many a times it is di cult to determine whether a particular uncertainty is to be considered as an aleatory or as an epistemic uncertainty, and the model builder makes the distinction. The model builder makes the choice based on the general state of scientific knowledge, on the practical need for limiting the model sophistication to a significant engineering importance, and on the errors associated with the measurements. Measurement uncertainty can be stated as the dispersion of real data resulting from systematic error (instrumental error, environmental error, observational error, human error, drift in measurement, measurement of wrong quantity) and random error (all errors apart from systematic errors). Most of instrumental errors given by the manufacturers are in terms of plus minus ranges and can be better represented through interval bounds. The vagueness involved in the representation of human error, observational error, and drift in measurement can be represented through interval bounds. Deliberate measurement of wrong quantity through cheaper and more convenient measurement units can lead to bad quality data. Quality of data can be better handled through interval analysis, with good quality data having narrow width of interval bounds and bad quality data having wide interval bounds. The environmental error, the electronic noise coming from transmitting the data and the random errors can be represented through probability distribution functions. A major part of the measurement uncertainties is better represented through interval bounds and the other part, is better represented through probability distributions. The uncertainties in the direct measurement data are propagated to the estimated output data (in damage identification techniques, the damaged parameters, and in the long-time deformation, the uncertain parameters of the deformation models, which are then used for the prediction of long-time deformations). Uncertainty based damage identification techniques and long-time deformations in concrete structures require further studies, when the measurement uncertainties are expressed through interval bounds only, or through both interval and probability using imprecise techniques. The thesis is divided into six chapters. Chapter 1 provides a review of existing literature on uncertainty based techniques for damage identification and prediction of long-time deformations in concrete structures. A brief review of uncertainty based methods for engineering applications is made, with special highlight to the need of interval analysis and imprecise probability for modeling uncertainties in the damage identification techniques. The review identifies that the available techniques for damage identification, where the uncertainties in the measurements and in the structural and material parameters are expressed in terms of interval bounds, lack e ciency, when the size of the damaged parameter vector is large. Studies on estimating the uncertainties in the damage parameters when the uncertainties in the measurements are expressed through imprecise probability analysis, are also identified as problems that will be considered in this thesis. Also the need for estimating the short-term time period, which in turn helps in accurate prediction of long-time deformations in concrete structures, along with a cost effective and easy to use system of measuring the existing prestress forces at various time instances in the short-time period is noted. The review identifies that most of modelers and analysts have been inclined to select a single simulation model for the long-time deformations resulted from creep, shrinkage and relaxation, rather than take all the possibilities into consideration, where the model selection is made based on the hardly realistic assumption that we can certainly select a correct, and the lack of confidence associated with model selection brings about the uncertainty that resides in a given model set. The need for a single best model out of all the available deformation models is needed to be developed, when uncertainties are present in the models, in the measurements and in the parameters of each models is also identified as a problem that will be considered in this thesis. In Chapter 2, an algorithm is proposed adapting the existing modified Metropolis Hastings algorithm for estimating the posterior probability of the damage indices as well as the posterior probability of the bounds of the interval parameters, when the measurements are given in terms of interval bounds. A damage index is defined for each element of the finite element model considering the parameters of each element are intervals. Methods are developed for evaluating response bounds in the finite element software ABAQUS, when the parameters of the finite element model are intervals. Illustrative examples include reinforced concrete beams with three damage scenarios mainly (i) loss of stiffness, (ii) loss of mass, and (iii) loss of bond between concrete and reinforcement steel, that have been tested in our laboratory. Comparison of the prediction from the proposed method with those obtained from Bayesian analysis and interval optimization technique show improved accuracy and computational efficiency, in addition to better representation of measurement uncertainties through interval bounds. Imprecise probability based methods are developed in Chapter 3, for damage identifi cation using finite element model updating in concrete structures, when the uncertainties in the measurements and parameters are imprecisely defined. Bayesian analysis using Metropolis Hastings algorithm for parameter estimation is generalized to incorporate the imprecision present in the prior distribution, in the likelihood function, and in the measured responses. Three different cases are considered (i) imprecision is present in the prior distribution and in the measurements only, (ii) imprecision is present in the parameters of the finite element model and in the measurement only, and (iii) imprecision is present in the prior distribution, in the parameters of the finite element model, and in the measurements. Illustrative examples include reinforced concrete beams and prestressed concrete beams tested in our laboratory. In Chapter 4, a steel frame is designed to measure the existing prestressing force in the concrete beams and slabs when embedded inside the concrete members. The steel frame is designed to work on the principles of a vibrating wire strain gauge and is referred to as a vibrating beam strain gauge (VBSG). The existing strain in the VBSG is evaluated using both frequency data on the stretched member and static strain corresponding to a fixed static load, measured using electrical strain gauges. The crack reopening load method is used to compute the existing prestressing force in the concrete members and is then compared with the existing prestressing force obtained from the VBSG at that section. Digital image correlation based surface deformation and change in neutral axis monitored by putting electrical strain gauges across the cross section, are used to compute the crack reopening load accurately. Long-time deformations in concrete structures are estimated in Chapter 5, using short-time measurements of deformation responses when uncertainties are present in the measurements, in the deformation models and in the parameters of the deformation models. The short-time period is defined as the least time up to which if measurements are made available, the measurements will be enough for estimating the parameters of the deformation models in predicting the long time deformations. The short-time period is evaluated using stochastic simulations where all the parameters of the deformation models are defined as random variables. The existing deformation models are empirical in nature and are developed based on an arbitrary selection of experimental data sets among all the available data sets, and each model contains some information about the deformation patterns in concrete structures. Uncertainty based model averaging is performed for obtaining the single best model for predicting the long-time deformation in concrete structures. Three types of uncertainty models are considered namely, probability models, interval models and imprecise probability models. Illustrative examples consider experiments in the Northwestern University database available in the literature and prestressed concrete beams and slabs cast in our laboratory for prediction of long-time prestress losses. A summary of contributions made in this thesis, together with a few suggestions for future research, are presented in Chapter 6. Finally the references that were studies are listed.

In our aging society, the design and implementation of a high-performance autonomous distributed vision information system for autonomous physical services become ever more important. In line with this development, the proposed Intelligent Vision Agent System, IVAS, is able to automatically detect and identify a target for a specific task by surveying a human activities space. The main subject of this thesis is the optimal configuration of a sensor system meant to capture the target objects and their environment within certain required specifications. The thesis thus discusses how a discrete sensor causes a depth spatial quantisation uncertainty, which significantly contributes to the 3D depth reconstruction accuracy. For a sensor stereo pair, the quantisation uncertainty is represented by the intervals between the iso-disparity surfaces. A mathematical geometry model is then proposed to analyse the iso-disparity surfaces and optimise the sensors’ configurations according to the required constrains. The thesis also introduces the dithering algorithm which significantly reduces the depth reconstruction uncertainty. This algorithm assures high depth reconstruction accuracy from a few images captured by low-resolution sensors. To ensure the visibility needed for surveillance, tracking, and 3D reconstruction, the thesis introduces constraints of the target space, the stereo pair characteristics, and the depth reconstruction accuracy. The target space, the space in which human activity takes place, is modelled as a tetrahedron, and a field of view in spherical coordinates is proposed. The minimum number of stereo pairs necessary to cover the entire target space and the arrangement of the stereo pairs’ movement is optimised through integer linear programming. In order to better understand human behaviour and perception, the proposed adaptive measurement method makes use of a fuzzily defined variable, FDV. The FDV approach enables an estimation of a quality index based on qualitative and quantitative factors. The suggested method uses a neural network as a tool that contains a learning function that allows the integration of the human factor into a quantitative quality index. The thesis consists of two parts, where Part I gives a brief overview of the applied theory and research methods used, and Part II contains the five papers included in the thesis.

This thesis is motivated by the need for noise control in aircraft engine with orifices and perforated liner. The presence of high-level acoustic excitation, different flow situations either bias flow, grazing flow or any combination in the aircraft engine, makes the acoustic behavior complex due to the interaction between sound and flow over the lined wall. Both systematic acoustic prediction of aircraft engines and liner optimization necessitate progress in impedance measurement methods by including the effect of the complex flow situations. The aim of the present thesis is to experimentally study the change in acoustic properties of orifices and perforated liners under bias or grazing flow. In order to study the effect of different combinations of bias flow and high-level acoustic excitation, an in-duct orifice has been investigated with finely controlled acoustic excitation levels and bias flow speeds. This provides a detailed study of the transition from cases when high-level acoustic excitation causes flow reversal in the orifice to cases when the bias flow maintains the flow direction. Nonlinear impedance is measured and compared, and a scattering matrix and its eigenvalues are investigated to study the potentiality of acoustic energy dissipation or production. A harmonic method is proposed for modelling the impedance, especially the resistance, which captures the change in impedance results at low frequencies compared with experimental results. The presence of grazing flow can increase the resistance of acoustic liners and shift their resonator frequency. So-called impedance eduction technology has been widely studied during the past decades, but with a limited confidence due to the interaction of grazing flow and acoustic waves. A comparison has been performed with different test rigs and methods from the German Aerospace Center (DLR). Numerical work has been performed to investigate the effect of shear flow and viscosity. Our study indicates that the impedance eduction process should be consistent with that of the code of wave propagation computation, for example with the same assumption regarding shear flow and viscosity. A systematic analysis for measurement uncertainties is proposed in order to understand the essentials for data quality assessment and model validation. The idea of using different Mach numbers for wave dispersion and in the Ingard-Myers boundary condition has been tested regarding their effect on impedance eduction. In conclusion, a local Mach number based on friction velocity is introduced and validated using both our own experimental results and those of previous studies. / <p>QC 20150522</p>

As emissões globais de gases do efeito estufa (GEE) devido a ações do ser humano tem levado a um aumento na temperatura média da superfície terrestre de 0,55oC, e mudanças climáticas como aumento de eventos climáticos extremos, elevação dos níveis dos oceanos, e mudanças nos regimes pluviométricos são alguns exemplos das possíveis implicações deste aquecimento. O carbono orgânico do solo (COS) é o principal reservatório terrestre de C, contendo mais que o dobro do C da atmosfera, portanto, dependendo do manejo os solos podem se transformar em importantes fontes ou drenos de C atmosférico, influenciando significativamente os efeitos do aquecimento global. O objetivo desta pesquisa foi estimar as mudanças nos estoques do COS devido às mudanças no uso da terra e sistemas de manejo nos estados de Rondônia e Mato Grosso entre 1970 e 1985 e 1985 a 2002 utilizando dados específicos da região; e realizar a análise de incerteza destas estimativas mediante o método de Monte Carlo. Para alcançar o objetivo principal, a presente pesquisa foi composta das seguintes etapas: i) cálculo dos estoques do COS sob vegetação nativa (carbono de referência); ii) obtenção dos dados (áreas) das principais categorias de uso da terra nos estados de Rondônia e Mato Grosso para os anos de 1970, 1985 e 2002, a partir da combinação de técnicas de sensoriamento remoto, dados dos censos agropecuários, e informações de especialistas do setor agropecuário; iii) desenvolvimento dos fatores de emissão específicos para os principais sistemas de manejo da região de estudo utilizando um modelo linear misto; iv) e a etapa final que consistiu em combinar as etapas anteriores para se estimar as mudanças nos estoques de COS, e realizar a análise das incertezas associadas. Sucintamente, foram derivados fatores de emissão para as pastagens degradadas (0,91 ± 0,14), típicas em Latossolos (0,99 ± 0,08), típicas nos demais tipos de solos (1,24 ± 0,07), e pastagens melhoradas em Latossolos (1,19 ± 0,07), todos os fatores representam a comparação entre as pastagens manejadas e a vegetação nativa. Nos sistemas agrícolas foi possível derivar fatores de emissão para sistemas de plantio direto (PD) em áreas de Cerrado (1,08 ± 0,06), PD em áreas de floresta Amazônica e Cerradão (1,01 ± 0,17), cultivo convencional (CC) (0,94 ± 0,04) e culturas perenes (0,98 ± 0,14), sendo que o fator para o CC foi comparado aos dados de PD, enquanto que os demais fatores foram obtidos a partir da comparação com os estoques sob vegetações nativas. Quanto às emissões de COS, foi encontrado que usando o método de Monte Carlo com 20000 simulações no período de 1970 a 1985, os solos minerais apresentaram uma perda de C com fluxos anuais de 4,28 e 1,14 Tg C ano-1, para Mato Grosso e Rondônia, respectivamente, e com 95% de intervalo de confiança as incertezas foram de ± 41,5 e 21,9%, respectivamente. No segundo período, as emissões foram de 2,86 e 0,91 Tg C ano-1, com incertezas de ± 40,1 e 33,8%, respectivamente, para Mato Grosso e Rondônia. Quanto às fontes de incerteza, o carbono de referência, a opinião dos especialistas sobre as condições das pastagens e os fatores de emissão para pastagens típicas e degradadas foram às variáveis responsáveis por mais de 90% das incertezas das estimativas das emissões de C do solo. / Global emissions of greenhouse gases (GHG) due to human beings actions have led to an increase in average temperature of the earth of 0,55oC, and climate changes such as increases of the extreme weather events, sea level rise and precipitation changes are some examples of the possible implications of this global warming. Soil organic carbon (SOC) is the largest terrestrial organic carbon pool, containing more than the double of the atmospheric C; therefore, depending on the management the soils can became a source or a sink for the atmospheric C, influencing the effects of global warming. The objective of this research was to estimate the changes in SOC stocks due to the land-use and management systems in the states of Rondônia and Mato Grosso from 1970 to 1985 and from 1985 to 2002 using regional specific data, and perform the uncertainty analysis of these estimates through the Monte Carlo method. To achieve the main objective, this research was composed by the following steps: i) the estimate of the SOC stocks under native vegetation (reference carbon), ii) obtain data (areas) of the main land-use categories in the states of Rondônia and Mato Grosso for the years 1970, 1985 and 2002, from a combination of remote sensing, agricultural census data, and information from experts of the agricultural sector, iii) to derive the emission factors specific to the major management systems in the region of study using a linear-mixed model; iv) the final step was to combine the above steps to estimate the changes in SOC stocks, and carry out the uncertainty analysis associated with them. Briefly, emission factors were derived to the degraded grasslands (0.91 ± 0.14), typical in Oxisols (0.99 ± 0.08), typical in other soil types (1.24 ± 0.07), and improved grasslands in Oxisols (1.19 ± 0.07), all factors represent the comparison between managed pastures and native vegetation. In agricultural systems could be derived emission factors for no tillage (NT) systems in the Cerrado areas (1.08 ± 0.06), NT in Amazon Forest and Cerradão areas (1.01 ± 0.17), conventional tillage (CT) (0.94 ± 0.04), and perennial crops (0.98 ± 0.14). However, the CT factor was obtained from the comparison with NT data, while the other factors were compared to SOC stocks under the native vegetation. Using the Monte Carlo approach with 20000 simulations it was estimated the changes in the SOC stocks and the uncertainties associated to them. In the period from 1970 to 1985, mineral soils had a loss of C with annual fluxes of 4.28 and 1.14 Tg C yr-1, in Mato Grosso and Rondônia, respectively, and with a 95% confidence interval the uncertainties were of ± 41.5 and 21.9% respectively. In the second period, emissions were of 2.86 and 0.91 Tg C yr-1, with uncertainty of ± 40.1 and 33.8%, respectively, in Mato Grosso and Rondônia. In terms of the sources of uncertainty, the reference carbon, the experts opinions about the grasslands, and the emission factors for typical and degraded grassland were the variables responsible for more than 90% of the uncertainties in the SOC emissions estimates.

Overheating in buildings is predicted to increase as a result of a warming climate and urbanisation in most cities. With regards to responding to this challenge, decision makers ranging from_ design teams, local authorities, building users, national programs and market innovators; and during the different stages of a building’s service life, want to know a few pertinent matters: What space characteristics and buildings are at a higher risk and by how much?; What are the tradeoffs between alternative design and/or user-based actions?; What are the likely or possible consequences of their decisions?; What is the impact of climate change to indoor overheating?; among other decision support questions. However, such decision appraisal information still remains buried and dispersed in existing simulation models, and empirical studies, and not yet been clearly articulated in any existing study or model. Especially decision support information articulated in a way that gives each decision maker maximum capacity to anticipate and respond to thermal discomfort in different spaces and through the lifetime of a building. There is a need for an integrated and systematic means of building adaptation decision-support, which provides analytical leverage to these listed decision makers. A means that: 1) assimilates a range of indoor thermal comfort's causal and solution space processes; 2) reveals and enhances the exploration of the space and time-dependent patterns created by the dynamics of the indoor overheating phenomenon through time; and one that 3) imparts insight into decision strategy and its synthesis across multiple decision makers. This study recognises the lack of an overarching framework attending to the listed concerns. Therefore, the key aim of this thesis is to develop and test a building adaptation decision-support framework, which extends the scope of existing frameworks and indoor overheating risk models to facilitate trans-sectional evaluations that reveal temporal decision strategies. The generic framework frames a multi-method analysis aiming to underpin decision appraisal for different spaces over a 50 to 100-year time horizon. It constitutes an underlying architecture that engages the dimensions of decision support information generation, information structuring, its exploration and dissemination, to ease in drawing decision strategy flexibly and transparently. The multi-method framework brings together: 1) Systems thinking methods to a) facilitate the systematic exposure of the elements that shape indoor overheating risk, and b) reveal the processes that shape multi-stakeholder decision-making response over time; 2) The use of normative, predictive and exploratory building scenarios to a) examine the overheating phenomenon over time, and b) as a lens through which to explore the micro-dynamics brought about by aspects of heterogeneity and uncertainty; and 3) The application of both computational and optimization techniques to appraise potential routes towards indoor thermal comfort over an extended time scale by a) tracking shifts in frequency, intensity and distribution of indoor overheating vulnerability by causal elements over time and space; and b) tracking shifting optima of the heat mitigation solution space, with respect to time, climate futures, heterogeneity of spaces, and due to thermal comfort assumptions. The framework’s potential has been demonstrated through its application to office buildings in Nairobi.

L’analyse de cycle de vie des bâtiments (ACV) permet d’évaluer les impacts environnementaux associés à une construction sur l’ensemble de son cycle de vie mais aussi d’aider à choisir les variantes les plus durables dans une démarche d’écoconception. De nombreuses sources d’incertitudes pèsent sur la modélisation environnementale des bâtiments. L’objectif de cette thèse est de proposer une méthodologie pour les prendre en compte et ainsi progresser vers une fiabilisation de l’ACV des bâtiments. Les éléments du modèle qui ont le plus d’influence sur les résultats, et qu’il serait utile de connaître de manière plus précise sont identifiés à l’aide de méthodes d’analyse de sensibilité (AS). Les temps de calcul peuvent être longs pour ces méthodes alors qu’en conception, un temps limité est généralement consacré aux études d’ACV des bâtiments. Plusieurs AS sont comparées en termes de compromis temps de calcul / précision. L’effet des incertitudes sur le choix d’une variante bâtie est étudié en appliquant une méthodologie intégrant des AS et des analyses d’incertitude (AI) adaptées au contexte de comparaison de variantes. Cela permet de rechercher des améliorations d’un projet à un niveau de confiance donné en se concentrant sur les indicateurs environnementaux pour lesquels le choix d’une variante affecte significativement les résultats. La démarche de quantification des incertitudes proposée peut être appliquée au cycle de vie complet de bâtiment et prendre en compte des sources d’incertitudes variées rencontrées en ACV des bâtiments. Les méthodes employées ont été intégrées à une plateforme d’écoconception intégrant des outils de simulation énergétique dynamique (SED) et d’ACV. / Building life cycle assessment (LCA) is a tool used to assess the environmental impact of a construction over its entire life cycle, and to help choosing the most sustainable building alternative in an ecodesign context. Many uncertainty sources arise in the environmental modelling of buildings. The aim of this thesis is to propose a methodology to take them into account and to progress towards more reliable building LCA tools. Model inputs and parameters having the most influence on the results and that should be more precisely known were identified using sensitivity analysis (SA) methods. The calculation time required for the application of these methods may be long, whereas a limited time is generally available to conduct a building LCA study. Several SA methods were therefore compared in terms of a calculation time / precision compromise. The effect of uncertainties on the choice of a built alternative was studied using SA and uncertainty analysis (UA) that are suitable in the context of variants comparison. In that way, the environmental improvements of a project are chosen at a given level of confidence and focusing on the environmental indicators for which the choice of an alternative affects the results significantly. The proposed uncertainty quantification process is applicable to the whole building life cycle and makes it possible to take into account various uncertainty sources arising in building LCA. The used methods were integrated into an ecodesign platform consisting in a dynamic building energy simulation (DBES) and an LCA tool.

As emissões globais de gases do efeito estufa (GEE) devido a ações do ser humano tem levado a um aumento na temperatura média da superfície terrestre de 0,55oC, e mudanças climáticas como aumento de eventos climáticos extremos, elevação dos níveis dos oceanos, e mudanças nos regimes pluviométricos são alguns exemplos das possíveis implicações deste aquecimento. O carbono orgânico do solo (COS) é o principal reservatório terrestre de C, contendo mais que o dobro do C da atmosfera, portanto, dependendo do manejo os solos podem se transformar em importantes fontes ou drenos de C atmosférico, influenciando significativamente os efeitos do aquecimento global. O objetivo desta pesquisa foi estimar as mudanças nos estoques do COS devido às mudanças no uso da terra e sistemas de manejo nos estados de Rondônia e Mato Grosso entre 1970 e 1985 e 1985 a 2002 utilizando dados específicos da região; e realizar a análise de incerteza destas estimativas mediante o método de Monte Carlo. Para alcançar o objetivo principal, a presente pesquisa foi composta das seguintes etapas: i) cálculo dos estoques do COS sob vegetação nativa (carbono de referência); ii) obtenção dos dados (áreas) das principais categorias de uso da terra nos estados de Rondônia e Mato Grosso para os anos de 1970, 1985 e 2002, a partir da combinação de técnicas de sensoriamento remoto, dados dos censos agropecuários, e informações de especialistas do setor agropecuário; iii) desenvolvimento dos fatores de emissão específicos para os principais sistemas de manejo da região de estudo utilizando um modelo linear misto; iv) e a etapa final que consistiu em combinar as etapas anteriores para se estimar as mudanças nos estoques de COS, e realizar a análise das incertezas associadas. Sucintamente, foram derivados fatores de emissão para as pastagens degradadas (0,91 ± 0,14), típicas em Latossolos (0,99 ± 0,08), típicas nos demais tipos de solos (1,24 ± 0,07), e pastagens melhoradas em Latossolos (1,19 ± 0,07), todos os fatores representam a comparação entre as pastagens manejadas e a vegetação nativa. Nos sistemas agrícolas foi possível derivar fatores de emissão para sistemas de plantio direto (PD) em áreas de Cerrado (1,08 ± 0,06), PD em áreas de floresta Amazônica e Cerradão (1,01 ± 0,17), cultivo convencional (CC) (0,94 ± 0,04) e culturas perenes (0,98 ± 0,14), sendo que o fator para o CC foi comparado aos dados de PD, enquanto que os demais fatores foram obtidos a partir da comparação com os estoques sob vegetações nativas. Quanto às emissões de COS, foi encontrado que usando o método de Monte Carlo com 20000 simulações no período de 1970 a 1985, os solos minerais apresentaram uma perda de C com fluxos anuais de 4,28 e 1,14 Tg C ano-1, para Mato Grosso e Rondônia, respectivamente, e com 95% de intervalo de confiança as incertezas foram de ± 41,5 e 21,9%, respectivamente. No segundo período, as emissões foram de 2,86 e 0,91 Tg C ano-1, com incertezas de ± 40,1 e 33,8%, respectivamente, para Mato Grosso e Rondônia. Quanto às fontes de incerteza, o carbono de referência, a opinião dos especialistas sobre as condições das pastagens e os fatores de emissão para pastagens típicas e degradadas foram às variáveis responsáveis por mais de 90% das incertezas das estimativas das emissões de C do solo. / Global emissions of greenhouse gases (GHG) due to human beings actions have led to an increase in average temperature of the earth of 0,55oC, and climate changes such as increases of the extreme weather events, sea level rise and precipitation changes are some examples of the possible implications of this global warming. Soil organic carbon (SOC) is the largest terrestrial organic carbon pool, containing more than the double of the atmospheric C; therefore, depending on the management the soils can became a source or a sink for the atmospheric C, influencing the effects of global warming. The objective of this research was to estimate the changes in SOC stocks due to the land-use and management systems in the states of Rondônia and Mato Grosso from 1970 to 1985 and from 1985 to 2002 using regional specific data, and perform the uncertainty analysis of these estimates through the Monte Carlo method. To achieve the main objective, this research was composed by the following steps: i) the estimate of the SOC stocks under native vegetation (reference carbon), ii) obtain data (areas) of the main land-use categories in the states of Rondônia and Mato Grosso for the years 1970, 1985 and 2002, from a combination of remote sensing, agricultural census data, and information from experts of the agricultural sector, iii) to derive the emission factors specific to the major management systems in the region of study using a linear-mixed model; iv) the final step was to combine the above steps to estimate the changes in SOC stocks, and carry out the uncertainty analysis associated with them. Briefly, emission factors were derived to the degraded grasslands (0.91 ± 0.14), typical in Oxisols (0.99 ± 0.08), typical in other soil types (1.24 ± 0.07), and improved grasslands in Oxisols (1.19 ± 0.07), all factors represent the comparison between managed pastures and native vegetation. In agricultural systems could be derived emission factors for no tillage (NT) systems in the Cerrado areas (1.08 ± 0.06), NT in Amazon Forest and Cerradão areas (1.01 ± 0.17), conventional tillage (CT) (0.94 ± 0.04), and perennial crops (0.98 ± 0.14). However, the CT factor was obtained from the comparison with NT data, while the other factors were compared to SOC stocks under the native vegetation. Using the Monte Carlo approach with 20000 simulations it was estimated the changes in the SOC stocks and the uncertainties associated to them. In the period from 1970 to 1985, mineral soils had a loss of C with annual fluxes of 4.28 and 1.14 Tg C yr-1, in Mato Grosso and Rondônia, respectively, and with a 95% confidence interval the uncertainties were of ± 41.5 and 21.9% respectively. In the second period, emissions were of 2.86 and 0.91 Tg C yr-1, with uncertainty of ± 40.1 and 33.8%, respectively, in Mato Grosso and Rondônia. In terms of the sources of uncertainty, the reference carbon, the experts opinions about the grasslands, and the emission factors for typical and degraded grassland were the variables responsible for more than 90% of the uncertainties in the SOC emissions estimates.

One of the major problems for the implementation of water resources planning and management in arid and semi-arid environments is the scarcity of hydrological data and, consequently, research studies. In this thesis, the hydrology of dryland river systems was analyzed and a semi-distributed hydrological model and a forecasting approach were developed for flow transmission processes in river-systems with a focus on semi-arid conditions. Three different sources of hydrological data (streamflow series, groundwater level series and multi-temporal satellite data) were combined in order to analyze the channel transmission losses of a large reach of the Jaguaribe River in NE Brazil. A perceptual model of this reach was derived suggesting that the application of models, which were developed for sub-humid and temperate regions, may be more suitable for this reach than classical models, which were developed for arid and semi-arid regions. Summarily, it was shown that this river reach is hydraulically connected with groundwater and shifts from being a losing river at the dry and beginning of rainy seasons to become a losing/gaining (mostly losing) river at the middle and end of rainy seasons. A new semi-distributed channel transmission losses model was developed, which was based primarily on the capability of simulation in very different dryland environments and flexible model structures for testing hypotheses on the dominant hydrological processes of rivers. This model was successfully tested in a large reach of the Jaguaribe River in NE Brazil and a small stream in the Walnut Gulch Experimental Watershed in the SW USA. Hypotheses on the dominant processes of the channel transmission losses (different model structures) in the Jaguaribe river were evaluated, showing that both lateral (stream-)aquifer water fluxes and ground-water flow in the underlying alluvium parallel to the river course are necessary to predict streamflow and channel transmission losses, the former process being more relevant than the latter. This procedure not only reduced model structure uncertainties, but also reported modelling failures rejecting model structure hypotheses, namely streamflow without river-aquifer interaction and stream-aquifer flow without groundwater flow parallel to the river course. The application of the model to different dryland environments enabled learning about the model itself from differences in channel reach responses. For example, the parameters related to the unsaturated part of the model, which were active for the small reach in the USA, presented a much greater variation in the sensitivity coefficients than those which drove the saturated part of the model, which were active for the large reach in Brazil. Moreover, a nonparametric approach, which dealt with both deterministic evolution and inherent fluctuations in river discharge data, was developed based on a qualitative dynamical system-based criterion, which involved a learning process about the structure of the time series, instead of a fitting procedure only. This approach, which was based only on the discharge time series itself, was applied to a headwater catchment in Germany, in which runoff are induced by either convective rainfall during the summer or snow melt in the spring. The application showed the following important features: • the differences between runoff measurements were more suitable than the actual runoff measurements when using regression models; • the catchment runoff system shifted from being a possible dynamical system contaminated with noise to a linear random process when the interval time of the discharge time series increased; • and runoff underestimation can be expected for rising limbs and overestimation for falling limbs. This nonparametric approach was compared with a distributed hydrological model designed for real-time flood forecasting, with both presenting similar results on average. Finally, a benchmark for hydrological research using semi-distributed modelling was proposed, based on the aforementioned analysis, modelling and forecasting of flow transmission processes. The aim of this benchmark was not to describe a blue-print for hydrological modelling design, but rather to propose a scientific method to improve hydrological knowledge using semi-distributed hydrological modelling. Following the application of the proposed benchmark to a case study, the actual state of its hydrological knowledge and its predictive uncertainty can be determined, primarily through rejected hypotheses on the dominant hydrological processes and differences in catchment/variables responses. / Die Bewirtschaftung von Wasserressourcen in ariden und semiariden Landschaften ist mit einer Reihe besonderer Probleme konfrontiert. Eines der größten Probleme für die Maßnahmenplanung und für das operationelle Management ist der Mangel an hydrologischen Daten und damit zusammenhängend auch die relativ kleine Zahl wissenschaftlicher Arbeiten zu dieser Thematik. In dieser Arbeit wurden 1) die grundlegenden hydrologischen Bedingungen von Trockenflusssystemen analysiert, 2) ein Modellsystem für Flüsse unter semiariden Bedingungen, und 3) ein nichtparametrisches Vorhersage-verfahren für Abflussvorgänge in Flüssen entwickelt. Der Wasserverlust in einem großen Abschnitt des Jaguaribe Flusses im nordöstlichen Brasilien wurde auf Basis von Daten zu Abflussraten, Grundwasserflurabstände und mit Hilfe multitemporaler Satellitendaten analysiert. Dafür wurde zuerst ein konzeptionelles hydrologisches Modell über die Mechanismen der Transferverluste in diesem Abschnitt des Trockenflusses erstellt. Dabei ergab sich, dass der Flussabschnitt mit dem Grundwasser hydraulisch verbunden ist. Der Flussabschnitt weist in der Trockenenzeit und am Anfang der Regenzeit nur Wasserverlust (Sickerung) zum Grundwasser auf. Im Laufe der Regenzeit findet auch ein gegenseitiger Austausch vom Grundwasser mit dem Flusswasser statt. Aufgrund dieser hydraulischen Kopplung zwischen Flusswasser und Grundwasser sind für diesen Flussabschnitt hydrologische Modellansätze anzuwenden, die generell für gekoppelte Fluss-Grundwassersysteme, v.a. in feuchtgemäßigten Klimaten, entwickelt wurden. Es wurde ein neuartiges hydrologisches Simulationsmodell für Transferverluste in Trockenflüssen entwickelt. Dieses Modell ist für unterschiedliche aride und semiaride Landschaften anwendbar und hat eine flexible Modellstruktur, wodurch unterschiedliche Hypothesen zur Relevanz einzelner hydrologische Prozesse getestet werden können. Es wurde für den zuvor genannten großen Abschnitt des Jaguaribe Flusses im nordöstlichen Brasilien und für einen kleinen Flussabschnitt im „Walnut Gulch Experimental Watershed“ (WGEW) in Arizona, Südwest-USA, angewendet. Für die eine prozess-orientierte Simulation von Abflussbedingungen und Transferverlusten im Einzugsgebiet des Jaguaribe hat sich gezeigt, dass die am besten geeignete Modellstruktur sowohl den Austausch zwischen Flusswasser und Grundwasser (senkrecht zur Fließrichtung des Flusses) als auch die parallel zum Fluss verlaufende Grundwasserströmung enthält. Die Simulationsexperimente mit unterschiedlichen Modellstrukturen („Hypothesentest“) reduzierte nicht nur die Modellstrukturunsicherheit, sondern quantifizierte auch die Qualität der Modellergebnisse bei folgenden Varianten der Modellstruktur: a) Abflluss im Fluss ohne Interaktion mit dem Grundwasser (keine Transferverluste) und b) Interaktion zwischen Fluss und Grundwasser ohne parallelen Grundwasserstrom zum Flussstrom. Durch die Anwendung auf die beiden unterschiedlichen Trockenflusssysteme wurden neue Erkenntnisse über die Sensitivität des Modells unter verschiedenen Bedingungen erworben. Beispielsweise waren die Parameter der ungesättigten Zone, die von hoher Relevanz für den kleinen Flussabschnitt im WGEW waren, viel sensitiver als die Parameter der gesättigten Zone, die besonders relevant für den Jaguaribe Flussabschnitt in Brasilien waren. Die Ursache für diese sehr unterschiedliche Sensitivität liegt darin, dass beim WGEW das Flusswasser nur mit der ungesättigten Zone in Kontakt steht, da sich in diesem Gebiet, welche im Vergleich zur Jaguaribe-Region noch deutlich trockener ist, kein Grund-wasserleiter bildet. Letztlich wurde ein nicht-parametrisches Verfahren, zur Simulation der deterministischen Evolution und stochastischen Fluktuation der Abflussdynamik entwickelt. Im Unterschied zu prozessbasiertem Modellsystemen basiert dieses Verfahren nicht auf Modellkalibrierung sondern auf einem Lernprozess, basierend auf Zeitreihendaten. Als Anwendungsbeispiel wurde ein mesoskaliges Einzugsgebiet im Erzgebirge, NO-Deutschland gewählt, in dem starke Abflussereignisse entweder durch konvektive Niederschlagsereignisse oder durch Schneeschmelze generiert werden. Die folgenden wichtigsten Ergebnisse wurden erzielt: • Regressionsmodellansätze basierend auf den zeitlichen Änderungen der Abflüsse liefern bessere Ergebnisse gegenüber Ansätzen basierend auf direkten Abflussdaten; • mit zunehmendem Vorhersagehorizont wandelt sich das hydrologische System von einem mit Zufallsanteilen verrauschten dynamischen System zu einem linearen probabilistischen Zufallsprozess; • Bei zunehmendem Abfluss (ansteigenden Ganglinie) erfolgt meist eine Abflussunterschätzung, bei abnehmendem Abfluss (fallende Ganglinie) erfolgt meist eine Abflussüberschätzung. Dieses nichtparametrische Verfahren ergibt im Vergleich mit einem prozess-orientierten und flächenverteilten hydrologischen Hochwasservorhersagemodell bis zu einem Vorhersagezeitraum von 3 Stunden Ergebnisse von vergleichbar guter Qualität. Letztendlich wurde ein Vorgehen bzgl. künftiger Forschungen zu hydrologischer Modellierung vorgeschlagen. Das Ziel dabei war ein wissenschaftliches Verfahren zur Verbesserung des hydrologischen Wissens über ein Einzugsgebiet. Diese Verfahren basiert auf einem Hypothesentest zu den relevanten hydrologischen Prozessen und der Untersuchung der Sensitivitäten der hydrologischen Variablen bei unterschiedlichen Einzugsgebieten.

The United States coastline contain some of the most valued ecological resources, the most populated urban areas, the most complex infrastructure systems, the most prolific economic engines, and the busiest ports of trade. However important the coastline may be to our nation, the history of our coastal communities suggests that they are extremely vulnerable to natural disasters, including hurricane landfall. There are many potential reasons for this vulnerability, and several of them are considered in this work. The common goal of research presented here is to better understand the hydrodynamic forces developed as hurricanes impact the coast so that the resulting effects on coastal resources can be better understood and managed, and vulnerability can be significantly minimized. This work begins with consideration of the hydraulic domain at the interface between inland riverine and coastal environments. Regulators, and therefore those being regulated, generally prefer to separate riverine systems from coastal systems in the design and analysis of coastal infrastructure. Although analysis is greatly simplified, important synergistic hydrodynamic effects are not considered which can have dramatic negative effects on the ability of infrastructure to withstand hurricane impact. Research continues by evaluating how society delineates the coastal flood hazard. Current methods apply a deterministic, steady-state approach to defining this highly dynamic feature influenced by multiple uncertain and variable parameters. By ignoring the variability inherent in the coastal floodplain, society is not able to correctly define the flood hazard, and therefore cannot fully asses the risk to which it is exposed. A methodology is presented to more realistically quantify the coastal flood hazard and to calculate an appropriate flood risk metric. Finally, this research considers the reliability of a coastal community's water distribution system under hurricane impact. By understanding system vulnerability and system interdependence, community leaders can provide more reliable infrastructure systems, thereby reducing the magnitude of disaster and shortening the recovery time. A methodology is presented to quantify the reliability of a water system under several hurricane impact scenarios.

The objective of this thesis is to develop and implement an algorithm for inverting the sound speed profile via estimation of the parameters embedded in a geoacoustic model. The environmental model inscribes a continuously-varying marine sediment layer with density and sound speed distributions represented by the generalized-exponential and inverse-square functions, respectively. Based upon a forward problem of plane-wave reflection from a non-uniform sediment layer overlying a uniform elastic basement, an inversion procedure for estimating the sound speed profile from the reflected sound field under the influence of noise is established and numerically implemented. The inversion invokes a probabilistic approach quantified by the posterior probability density for measuring the uncertainties of the estimated parameters from synthetic noisy data. Preliminary analysis on the solution of the forward problem and the sensitivity of the model parameters is first conducted, leading to a determination of the parameters chosen for inversion in the ensuing study. The parameter uncertainties referenced 1-D and 2-D marginal posterior probability densities are then examined, followed by the statistical estimation for the sound speed profile in terms of 99 % credibility interval. The effects of, the signal-to-noise ratio (SNR), the dimension of data vector, the region in which the data sampled, on the statistical estimation of sound speed profile are demonstrated and discussed.