995 resultados para Orbiting geophysical observatories.


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Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.

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In highly heterogeneous aquifer systems, conceptualization of regional groundwater flow models frequently results in the generalization or negligence of aquifer heterogeneities, both of which may result in erroneous model outputs. The calculation of equivalence related to hydrogeological parameters and applied to upscaling provides a means of accounting for measurement scale information but at regional scale. In this study, the Permo-Triassic Lagan Valley strategic aquifer in Northern Ireland is observed to be heterogeneous, if not discontinuous, due to subvertical trending low-permeability Tertiary dolerite dykes. Interpretation of ground and aerial magnetic surveys produces a deterministic solution to dyke locations. By measuring relative permeabilities of both the dykes and the sedimentary host rock, equivalent directional permeabilities, that determine anisotropy calculated as a function of dyke density, are obtained. This provides parameters for larger scale equivalent blocks, which can be directly imported to numerical groundwater flow models. Different conceptual models with different degrees of upscaling are numerically tested and results compared to regional flow observations. Simulation results show that the upscaled permeabilities from geophysical data allow one to properly account for the observed spatial variations of groundwater flow, without requiring artificial distribution of aquifer properties. It is also found that an intermediate degree of upscaling, between accounting for mapped field-scale dykes and accounting for one regional anisotropy value (maximum upscaling) provides results the closest to the observations at the regional scale.

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The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

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Stiffness values in geotechnical structures can range over many orders of magnitude for relatively small operational strains. The typical strain levels where soil stiffness changes most dramatically is in the range 0.01-0.1%, however soils do not exhibit linear stress-strain behaviour at small strains. Knowledge of the in situ stiffness at small strain is important in geotechnical numerical modelling and design. The stress-strain regime of cut slopes is complex, as we have different principle stress directions at different positions along the potential failure plane. For example, loading may be primarily in extension near the toe of the slope, while compressive loading is predominant at the crest of a slope. Cuttings in heavily overconsolidated clays are known to be susceptible to progressive failure and subsequent strain softening, in which progressive yielding propagates from the toe towards the crest of the slope over time. In order to gain a better understanding of the rate of softening it would be advantageous to measure changes in small strain stiffness in the field.

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We study the magnetospheric structure and the ionospheric Joule Heating of planets orbiting M-dwarf stars in the habitable zone using a set of magnetohydrodynamic models. The stellar wind solution is used to drive a model for the planetary magnetosphere, which is coupled with a model for the planetary ionosphere. Our simulations reveal that the space environment around close-in habitable planets is extreme, and the stellar wind plasma conditions change from sub- to super-Alfvénic along the planetary orbit. As a result, the magnetospheric structure changes dramatically with a bow shock forming in the super-Alfvénic sectors, while no bow shock forms in the sub-Alfvénic sectors. The planets reside most of the time in the sub-Alfvénic sectors with poor atmospheric protection. A significant amount of Joule Heating is provided at the top of the atmosphere as a result of the intense stellar wind. For the steady-state solution, the heating is about 0.1%-3% of the total incoming stellar irradiation, and it is enhanced by 50% for the time-dependent case. The significant Joule Heating obtained here should be considered in models for the atmospheres of habitable planets in terms of the thickness of the atmosphere, the top-side temperature and density, the boundary conditions for the atmospheric pressure, and particle radiation and transport. Here we assume constant ionospheric Pedersen conductance similar to that of the Earth. The conductance could be greater due to the intense EUV radiation leading to smaller heating rates. We plan to quantify the ionospheric conductance in future study.

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A significant portion of the UK’s transportation system relies on a network of geotechnical earthworks (cuttings and embankments) that were constructed more than 100 years ago, whose stability is affected by the change in precipitation patterns experienced over the past few decades. The vulnerability of these structures requires a reliable, cost- and time-effective monitoring of their geomechanical condition. We have assessed the potential application of P-wave refraction for tracking the seasonal variations of seismic properties within an aged clay-filled railway embankment, located in southwest England. Seismic data were acquired repeatedly along the crest of the earthwork at regular time intervals, for a total period of 16 months. P-wave first-break times were picked from all available recorded traces, to obtain a set of hodocrones referenced to the same spatial locations, for various dates along the surveyed period of time. Traveltimes extracted from each acquisition were then compared to track the pattern of their temporal variability. The relevance of such variations over time was compared with the data experimental uncertainty. The multiple set of hodocrones was subsequently inverted using a tomographic approach, to retrieve a time-lapse model of VPVP for the embankment structure. To directly compare the reconstructed VPVP sections, identical initial models and spatial regularization were used for the inversion of all available data sets. A consistent temporal trend for P-wave traveltimes, and consequently for the reconstructed VPVP models, was identified. This pattern could be related to the seasonal distribution of precipitation and soil-water content measured on site.

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Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofísica), Universidade de Lisboa, Faculdade de Ciências, 2014

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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

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This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

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The main objective of the present study is to model the gravity fields in terms of lithospheric structure below the western continental margin of India (WCMI) identify zones of crustal mass anomalies and attempt to infer the location of Ocean Continent transition in the Arabian Sea. In this study, the area starting from the western shield margin to the region covering the deep oceanic parts of the Arabian Sea which is bounded by Carlsberg and Cerg and Central Indian ridges in the south, eastern part of the Indus Cone in the west and falling between 630E and 800E longitudes, and 50N - 240N latitudes has been considered. The vast amount of seismic reflection and refraction data in the form of crustal velocities, basement configuration and crustal thicknesses available for the west coast as well as the eastern Arabian Sea has been utilized for this purpose

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The present study deals with the different hydrogeological characteristics of the coastal region of central Kerala and a comparative analysis with corresponding hard rock terrain. The coastal regions lie in areas where the aquifer systems discharge groundwater ultimately into the sea. Groundwater development in such regions will require a precise understanding of the complex mechanism of the saline and fresh water relationship, so that the withdrawals are so regulated as to avoid situations leading to upcoming of the saline groundwater bodies as also to prevent migration of sea water ingress further inland. Coastal tracts of Kerala are formed by several drainage systems. Thick pile of semi-consolidated and consolidated sediments from Tertiary to Recent age underlies it. These sediments comprise phreatic and confined aquifer systems. The corresponding hard rock terrain is encountered with laterites and underlined by the Precambrian metamorphic rocks. Supply of water from hard rock terrain is rather limited. This may be due to the small pore size, low degree of interconnectivity and low extent of weathering of the country rocks. The groundwater storage is mostly controlled by the thickness and hydrological properties of the weathered zone and the aquifer geometry. The over exploitation of groundwater, beyond the ‘safe yield’ limit, cause undesirable effects like continuous reduction in groundwater levels, reduction in river flows, reduction in wetland surface, degradation of groundwater quality and many other environmental problems like drought, famine etc.