Buoyant flows are characterized with unsteady large-scale structures and thus time-dependent large eddy simulation (LES) is generally favored. In this dissertation, to further explore LES for buoyant flow, an LES code based on a collocated grid system is first developed. A multigrid solver using a control strategy is developed for the pressure Poisson equations. The control strategy significantly accelerated the convergence rate. A temperature solver using a fourth-order Runge-Kutta approach is also developed. The LES code is extensively tested before it is applied. Although the collocated grid system will introduce conservation errors, in tests of a steady lid-driven cavity flow and transient start-up flow, the effect of the non-conservation of the collocated grid system was not significant. <p>In LES, the effect of SGS scales is represented by SGS models. A novel dynamic nonlinear model (DNM) for SGS stress is tested using isothermal channel flow at Reynolds number 395. The kinetic energy dissipation and geometrical characteristics of the resolved scale and SGS scale with respect to the DNM are investigated. In general, the DNM is reliable and has relatively realistic geometrical properties in comparison with the conventional dynamic model in the present study. In contrast to a pure advecting velocity field, a scalar (temperature) field displays very different characteristics. The modelling of SGS heat flux has not been as extensively studied as that of SGS stress partly due to the complexity of the scalar transport. In this dissertation, LES for a turbulent combined forced and natural convection is studied. The DNM model and a nonlinear dynamic tensor diffusivity model (DTDM-HF) are applied for the SGS stress and heat flux, respectively. The combined effect of the nonlinear models is compared to that of linear models. Notable differences between the nonlinear and linear SGS models are observed at the subgrid-scale level. At the resolved scale, the difference is smaller but relatively more distinguishable in terms of quantities related to the temperature field. <p>Finally, the geometrical properties of the resolved velocity and temperature fields of the thermal flow are investigated based on the LES prediction. Some universal geometrical patterns have been reproduced, e.g. the positively skewed resolved enstrophy generation and the alignment between the vorticity and vortex stretching vectors. The present research demonstrates that LES is an effective tool for the study of the geometrical properties of a turbulent flow at the resolved-scales. The wall imposed anisotropy on the flow structures and orientation of the SGS heat flux vector are also specifically examined. In contrast to the dynamic eddy diffusivity model, the DTDM-HF successfully predicts the near-wall physics and demonstrates a non-alignment pattern between the SGS heat flux and temperature gradient vector.

The boreal forest is one of the worlds largest forest biomes and comprises a major portion of the terrestrial carbon (C) sink. Quantifying the net C change in forest ecosystems is an important step in understanding and modeling the global C cycle. The goals of this project were: to estimate and compare the total change in ecosystem C over a 10-year period in two boreal forest stands using biometric and eddy-covariance approaches, and to evaluate the year-to-year changes in C uptake. This study utilized 10 years of eddy-covariance data and ecosys model data from the Old Aspen (OA) and Old Jack Pine (OJP) sites in central Saskatchewan, part of the Boreal Ecosystem Research and Monitoring Sites (BERMS). According to the eddy-covariance and C stock approaches, between 1994 and 2004 the net change in C storage at OA was 15.6 ± 4.0 and 18.2 ± 8.0 Mg C ha-1, respectively. At OJP, the 10-year net change in C storage from eddy-covariance was 5.8 ± 2.0 Mg C ha-1 in comparison to 6.9 ± 1.6 Mg C ha-1 from the carbon stock approach. While both sites were sinks of C between 1994 and 2004, the greatest increase in C occurred in different components - the forest floor at OA (14.6 Mg C ha-1) and in the living vegetation at OJP (8.0 Mg C ha-1). In 2004, total ecosystem C content was greater at OA (180.6 Mg C ha-1) than OJP (78.9 Mg C ha-1), with 50% (OA) and 39% (OJP) of the C in the detritus and mineral soil pools. During the 10-year period of eddy-covariance measurements, there was a positive correlation between both annual and growing season gross ecosystem photosynthesis (GEP) and live stem C biomass increment at OA, whereas no significant relationships were found at OJP. Stem C increment accounted for 30% of total net primary productivity (NPP) at both sites, and NPP/GEP ratios were 0.36 and 0.32 at OA and OJP, respectively. Overall, this study found good agreement between eddy-covariance and biometric estimates of ecosystem C change at OA and OJP between 1994 and 2004. Over that period at OA, eddy-covariance estimates of photosynthesis captured the inter-annual variability in C uptake based on the growth of tree rings.

Large-eddy simulation (LES) is emerging as a promising computational tool for reacting flows. High-order schemes for LES are desirable to achieve improved solution accuracy with reduced computational cost. In this study, a parallel, block-based, three-dimensional high-order central essentially non-oscillatory (CENO) finite-volume scheme for LES of premixed turbulent combustion is developed for Cartesian mesh. This LES formulation makes use of the flame surface density (FSD) for subfilter-scale reaction rate modelling. An algebraic model is used to approximate the FSD. A detailed explanation of the governing equations for LES and the mathematical framework for CENO schemes are presented. The CENO reconstruction is validated and is also applied to three-dimensional Euler equations prior to its application to the equations governing LES of reacting flows.

Methane fluxes were calculated from measurements carried out at a temperate upland forest in Central Ontario using the eddy covariance method over five months in the summer and fall seasons of 2011. Measurements were made by an off-axis integrated cavity output spectrometer Fast Greenhouse Gas Analyzer (FGGA) which simultaneously measured methane (CH4), carbon dioxide (CO2), and water at 10 Hz sampling rates. Observed methane fluxes showed net uptake of methane over the measurement period with an average uptake flux value (±standard deviation of the mean) of -2.7±0.13 nmol m-2 s-1. Methane fluxes showed a diurnal pattern of increased uptake during the day and increasing uptake with seasonal progression. There was also a significant correlation in methane fluxes with soil water content and wind speed. Comparison of the FGGA measurements to those using a static chamber method and canister sampling showed close agreement in flux and mixing ratio values respectively.

Large-eddy simulation (LES) is emerging as a promising computational tool for reacting flows. High-order schemes for LES are desirable to achieve improved solution accuracy with reduced computational cost. In this study, a parallel, block-based, three-dimensional high-order central essentially non-oscillatory (CENO) finite-volume scheme for LES of premixed turbulent combustion is developed for Cartesian mesh. This LES formulation makes use of the flame surface density (FSD) for subfilter-scale reaction rate modelling. An algebraic model is used to approximate the FSD. A detailed explanation of the governing equations for LES and the mathematical framework for CENO schemes are presented. The CENO reconstruction is validated and is also applied to three-dimensional Euler equations prior to its application to the equations governing LES of reacting flows.

Methane fluxes were calculated from measurements carried out at a temperate upland forest in Central Ontario using the eddy covariance method over five months in the summer and fall seasons of 2011. Measurements were made by an off-axis integrated cavity output spectrometer Fast Greenhouse Gas Analyzer (FGGA) which simultaneously measured methane (CH4), carbon dioxide (CO2), and water at 10 Hz sampling rates. Observed methane fluxes showed net uptake of methane over the measurement period with an average uptake flux value (±standard deviation of the mean) of -2.7±0.13 nmol m-2 s-1. Methane fluxes showed a diurnal pattern of increased uptake during the day and increasing uptake with seasonal progression. There was also a significant correlation in methane fluxes with soil water content and wind speed. Comparison of the FGGA measurements to those using a static chamber method and canister sampling showed close agreement in flux and mixing ratio values respectively.

The Antarctic Circumpolar Current (ACC) is well known for its multiple bands with large meridional property gradients in the upper waters, each associated with a deep-reaching current core. A revised nineteen-year time series (1992?2011) of altimeter data from the CNES/CLS AVISO is analyzed to identify and trace the spatial distribution of ACC fronts. Specific contours of sea surface height (SSH) are selected within narrow continuous bands of relative maxima SSH slope in the Southwest Atlantic Ocean sector, where they closely follow the distribution of ACC fronts derived from inspection of concurrent high-resolution profile data at hydrographic stations. When applied to the full circumpolar belt, the frontal distribution derived from these new altimeter-based indicators also agrees well with the traces of current jets and in-situ dynamic height fields calculated from concurrent Argo profile data. The temporal variability of ACC fronts is analyzed in relation to dominant modes of atmospheric forcing variability in the Southern Ocean. All three ACC fronts have experienced large seasonal to decadal variability throughout the satellite altimetry era. The general seasonal tendency for each of these jets, with respect to long-term mean positions, is to be located farther to the south during the austral summer and to north in the winter. Circumpolar-mean annual frontal locations show a consistent linear trend of southward migration. However, the estimated decadal variability of the frontal distributions is highly localized, and due to selective response mechanisms to atmospheric variability. A persistent poleward drift of ACC fronts is observed in the Indian sector consistent with increasing sea surface temperature trends. In contrast, a vacillation in the meridional location of ACC fronts is observed in the Pacific sector in association to minor sea surface cooling trends. Therefore, unlike in the Indian sector, the regional Pacific Ocean response is significantly sensitive to dominant atmospheric forcing indices. Mesoscale eddies derived from instabilities at strong current cores are successfully identified with specific SSH gradient criteria. The new estimates of rings population in the Southern Ocean are tightly linked to interannual to decadal atmospheric variability. Increased number of mesoscale eddies correlate with positive SAM forcing about two years earlier, or negative ENSO forcing two to three months earlier. These cross-correlations might explain a prominent peak in rings abundance estimated during 2000 and 2001, and the short-lived maximum that appeared in 2010. There are no persistent trends in the estimated sea surface slope across Drake Passage, and therefore neither in the transport of the ACC. High cross-correlation between the abundance of mesoscale eddies and atmospheric forcing suggests that the overall ACC system is in an eddy-saturated state. However, Drake Passage positive sea level slope anomalies were two-year lagged with negative SAM forcing and with positive ENSO events. These regional responses are characteristic of eastward-propagating signals from a buoyancy-dominated Pacific sector of the Southern Ocean.

Hydrogen (H2) enrichment of hydrocarbon fuels in lean premixed systems is desirable since it can lead to a progressive reduction in greenhouse-gas emissions, while paving the way towards pure hydrogen combustion. In recent decades, large-eddy simulation (LES) has emerged as a promising tool to computationally describe and represent turbulent combustion processes. However, a considerable complication of LES for turbulent premixed combustion is that chemical reactions occur in a thin reacting layer at small scales which cannot be entirely resolved on computational grids and need to be modelled. In this thesis, subfilter-scale (SFS) modelling for LES of lean H2-enriched methane-air turbulent premixed combustion was investigated. Two- and three-dimensional fully-compressible LES solvers for a thermally perfect reactive mixture of gases were developed and systematically validated. Two modelling strategies for the chemistry-turbulence interaction were pursued: the artificially thickened flame model with a power-law SFS wrinkling approach and the presumed conditional moment (PCM) coupled with the flame prolongation of intrinsic low-dimensional manifold (FPI) chemistry tabulation technique. Freely propagating and Bunsen-type flames corresponding to stoichiometric and lean premixed mixtures were considered. Validation of the LES solvers was carried out by comparing predicted solutions with experimental data and other published numerical results. Head-to-head comparisons of different SFS approaches, including a transported flame surface density (FSD) model, allowed to identify weaknesses and strengths of the various models. Based on the predictive capabilities of the models examined, the PCM-FPI model was selected for the study of hydrogen-enrichment of methane. A new progress of reaction variable was proposed to account for NO. The importance of transporting species with different diffusion coefficients was demonstrated, in particular for H2. The proposed approach was applied to a Bunsen-type configuration, reproducing key features observed in the experiments: the enriched flame was shorter, which is attributed to a faster consumption of the blended fuel; and the enriched flame displayed a broader two-dimensional curvature probability density function. Furthermore, reduced levels of carbon dioxide (CO2), increased levels of nitrogen monoxide (NO), and a slight increase in the carbon monoxide (CO) levels in areas of fully burned gas were predicted for the enriched flame.

Large-scale mining practices have disturbed many natural watersheds in northern Alberta, Canada. To restore disturbed landscapes and ecosystems functions, reconstruction strategies have been adopted with the aim of establishing sustainable reclaimed lands. The success of the reconstruction process depends on the design of reconstruction strategies, which can be optimized by improving the understanding of the controlling hydrological processes in the reconstructed watersheds. Evapotranspiration is one of the important components of the hydrological cycle; its estimation and analysis are crucial for better assessment of the reconstructed landscape hydrology, and for more efficient design. The complexity of the evapotranspiration process and its variability in time and space has imposed some limitations on previously developed evapotranspiration estimation models. The vast majority of the available models estimate the rate of potential evapotranspiration, which occurs under unlimited water supply condition. However, the rate of actual evapotranspiration (AET) depends on the available soil moisture, which makes its physical modeling more complicated than the potential evapotranspiration. The main objective of this study is to estimate and analyze the AET process in a reconstructed landscape.<p> Data driven techniques can model the process without having a complete understanding of its physics. In this study, three data driven models; genetic programming (GP), artificial neural networks (ANNs), and multilinear regression (MLR), were developed and compared for estimating the hourly eddy covariance (EC)-measured AET using meteorological variables. The AET was modeled as a function of five meteorological variables: net radiation (Rn), ground temperature (Tg), air temperature (Ta), relative humidity (RH), and wind speed (Ws) in a reconstructed landscape located in northern Alberta, Canada. Several ANN models were evaluated using two training algorithms of Levenberg-Marquardt and Bayesian regularization. The GP technique was employed to generate mathematical equations correlating AET to the five meteorological variables. Furthermore, the available data were statistically analyzed to obtain MLR models and to identify the meteorological variables that have significant effect on the evapotranspiration process. The utility of the investigated data driven models was also compared with that of HYDRUS-1D model, which is a physically based model that makes use of conventional Penman-Monteith (PM) method for the prediction of AET. HYDRUS-1D model was examined for estimating AET using meteorological variables, leaf area index, and soil moisture information. Furthermore, Wavelet analysis (WA), as a multiresolution signal processing tool, was examined to improve the understanding of the available time series temporal variations, through identifying the significant cyclic features, and to explore the possible correlation between AET and the meteorological signals. WA was used with the purpose of input determination of AET models, a priori.<p> The results of this study indicated that all three proposed data driven models were able to approximate the AET reasonably well; however, GP and MLR models had better generalization ability than the ANN model. GP models demonstrated that the complex process of hourly AET can be efficiently modeled as simple semi-linear functions of few meteorological variables. The results of HYDRUS-1D model exhibited that a physically based model, such as HYDRUS-1D, might perform on par or even inferior to the data driven models in terms of the overall prediction accuracy. The developed equation-based models; GP and MLR, revealed the larger contribution of net radiation and ground temperature, compared to other variables, to the estimation of AET. It was also found that the interaction effects of meteorological variables are important for the AET modeling. The results of wavelet analysis demonstrated the presence of both small-scale (2 to 8 hours) and larger-scale (e.g. diurnal) cyclic features in most of the investigated time series. Larger-scale cyclic features were found to be the dominant source of temporal variations in the AET and most of the meteorological variables. The results of cross wavelet analysis indicated that the cause and effect relationship between AET and the meteorological variables might vary based on the time-scale of variation under consideration. At small time-scales, significant linear correlations were observed between AET and Rn, RH, and Ws time series, while at larger time-scales significant linear correlations were observed between AET and Rn, RH, Tg, and Ta time series.

This dissertation consists of two parts, i.e. dynamic approaches for subgrid-scale (SGS) stress modelling for large eddy simulation and advanced assessment of the resolved scale motions related to turbulence geometrical statistics and topologies. The numerical simulations are based on turbulent Couette flow. The first part of the dissertation presents four contributions to the development of dynamic SGS models. The conventional integral type dynamic localization SGS model is in the form of a Fredholm integral equation of the second kind. This model is mathematically consistent, but demanding in computational cost. An efficient solution scheme has been developed to solve the integral system for turbulence with homogeneous dimensions. Current approaches to the dynamic two-parameter mixed model (DMM2) are mathematically inconsistent. As a second contribution, the DMM2 has been optimized and a modelling system of two integral equations has been rigorously obtained. The third contribution relates to the development of a novel dynamic localization procedure for the Smagorinsky model using the functional variational method. A sufficient and necessary condition for localization is obtained and a Picard's integral equation for the model coefficient is deduced. Finally, a new dynamic nonlinear SGS stress model (DNM) based on Speziale's quadratic constitutive relation [J. Fluid Mech., 178, p.459, 1987] is proposed. The DNM allows for a nonlinear anisotropic representation of the SGS stress, and exhibits a significant local stability and flexibility in self-calibration. In the second part, the invariant properties of the resolved velocity gradient tensor are studied using recently developed methodologies, i.e. turbulence geometrical statistics and topology. The study is a posteriori based on the proposed DNM, which is different than most of the current a priori approaches based on experimental or DNS databases. The performance of the DNM is further validated in terms of its capability of simulating advanced geometrical and topological features of resolved scale motions. Phenomenological results include, e.g. the positively skewed resolved enstrophy generation, the alignment between the vorticity and vortex stretching vectors, and the pear-shape joint probability function contour in the tensorial invariant phase plane. The wall anisotropic effect on these results is also examined.