14,657 research outputs found

    Saturated hydraulic conductivity determined by on ground mono-offset Ground-Penetrating Radar inside a single ring infiltrometer

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    In this study we show how to use GPR data acquired along the infiltration of water inside a single ring infiltrometer to inverse the saturated hydraulic conductivity. We used Hydrus-1D to simulate the water infiltration. We generated water content profiles at each time step of infiltration, based on a particular value of the saturated hydraulic conductivity, knowing the other van Genuchten parameters. Water content profiles were converted to dielectric permittivity profiles using the Complex Refractive Index Method relation. We then used the GprMax suite of programs to generate radargrams and to follow the wetting front using arrival time of electromagnetic waves recorded by a Ground-Penetrating Radar (GPR). Theoretically, the 1D time convolution between reflectivity and GPR signal at any infiltration time step is related to the peak of the reflected amplitude recorded in the corresponding trace in the radargram. We used this relation ship to invert the saturated hydraulic conductivity for constant and falling head infiltrations. We present our method on synthetic examples and on two experiments carried out on sand soil. We further discuss on the uncertainties on the retrieved saturated hydraulic conductivity computed by our algorithm from the van Genuchten parameters

    Final Report of the DAUFIN project

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    DAUFIN = Data Assimulation within Unifying Framework for Improved river basiN modeling (EC 5th framework Project

    Evaluation of the Algorithms and Parameterizations for Ground Thawing and Freezing Simulation in Permafrost Regions

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    Ground thawing and freezing depths (GTFDs) strongly influence the hydrology and energy balances of permafrost regions. Current methods to simulate GTFD differ in algorithm type, soil parameterization, representation of latent heat, and unfrozen water content. In this study, five algorithms (one semiempirical, two analytical, and two numerical), three soil thermal conductivity parameterizations, and three unfrozen water parameterizations were evaluated against detailed field measurements at four field sites in Canada’s discontinuous permafrost region. Key findings include: (1) de Vries’ parameterization is recommended to determine the thermal conductivity in permafrost soils; (2) the three unfrozen water parameterization methods exhibited little difference in terms of GTFD simulations, yet the segmented linear function is the simplest to be implemented; (3) the semiempirical algorithm reasonably simulates thawing at permafrost sites and freezing at seasonal frost sites with site-specific calibration. However, large interannual and intersite variations in calibration coefficients limit its applicability for dynamic analysis; (4) when driven by surface forcing, analytical algorithms performed marginally better than the semiempirical algorithm. The inclusion of bottom forcing improved analytical algorithm performance, yet their results were still poor compared with those achieved by numerical algorithms; (5) when supplied with the optimal inputs, soil parameterizations, and model configurations, the numerical algorithm with latent heat treated as an apparent heat capacity achieved the best GTFD simulations among all algorithms at all sites. Replacing the observed bottom temperature with a zero heat flux boundary condition did not significantly reduce simulation accuracy, while assuming a saturated profile caused large errors at several sites

    Improving the Accuracy and Scope of Control-Oriented Vapor Compression Cycle System Models

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    The benefits of applying advanced control techniques to vapor compression cycle systems are well know. The main advantages are improved performance and efficiency, the achievement of which brings both economic and environmental gains. One of the most significant hurdles to the practical application of advanced control techniques is the development of a dynamic system level model that is both accurate and mathematically tractable. Previous efforts in control-oriented modeling have produced a class of heat exchanger models known as moving-boundary models. When combined with mass flow device models, these moving-boundary models provide an excellent framework for both dynamic analysis and control design. This thesis contains the results of research carried out to increase both the accuracy and scope of these system level models. The improvements to the existing vapor compression cycle models are carried out through the application of various modeling techniques, some static and some dynamic, some data-based and some physics-based. Semiempirical static modeling techniques are used to increase the accuracy of both heat exchangers and mass flow devices over a wide range of operating conditions. Dynamic modeling techniques are used both to derive new component models that are essential to the simulation of very common vapor compression cycle systems and to improve the accuracy of the existing compressor model. A new heat exchanger model that accounts for the effects of moisture in the air is presented. All of these model improvements and additions are unified to create a simple but accurate system level model with a wide range of application. Extensive model validation results are presented, providing both qualitative and quantitative evaluation of the new models and model improvements.Air Conditioning and Refrigeration Project 17

    Snow cover properties and soil moisture derived from GPS signals

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    Microwave soil moisture measurements and analysis

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    An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented
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