The analysis of large-scale watershed processes and development of an efficient and integrated modelling platform is the focus of this research. The research focused on developing a series of modelling tools that can be used in the simulation of the overall response of a watershed based on a localized or distributed hydrologic event. This is achieved through the introduction of a hybrid modelling concept using a combination of empirically based lumped hydrologic processes and a physics-based distributed model representation. The watershed simulation model (GFLOOD) was developed to account for the complexity of the watershed including the variations in climate, soils, topography, and landuse conditions across the watershed. GFLOOD stands for Guelph Flood Forecasting Model, a river basin or watershed scale flow prediction model. Two major modelling components of the GFLOOD model are the time parameters (time of concentration (Tc) and recession constant (K)) and the channel routing component. Each of these modelling components is evaluated separately. The equations developed in this study for estimating the time parameters can be used as an initial estimate for Tc and K for ungauged basins, and through calibration and/or sensitivity analysis the values of Tc and K can be finalized. The Saint Venant equations for flood routing are solved by transforming the momentum equation into a partial differential equation which has six parameters related to cross-sectional area and discharge of the channel, left floodplain and right floodplain. The simplified dynamic model was further modified to account for transmission losses, evaporation losses and bank storage within the channel. The model was compared with the solutions of the general dynamic wave model, diffusion wave model and the more complex dynamic wave model. The comparison shows that there is good agreement between the results of the simplified dynamic model and the other models however, the simplified dynamic model is easier to formulate and compute than the other models. The complete GFLOOD model was applied to the Welland River Watershed within Southern Ontario. The model was evaluated for its ability to predict streamflow and water levels along the main branch of the Welland River.

No description available.

Compressed Sensing (CS) is a framework where we measure data through a non-adaptive linear mapping with far fewer measurements that the ambient dimension of the data. This is made possible by the exploitation of the inherent structure (simplicity) in the data being measured. The central issues in this framework is the design and analysis of the measurement operator (matrix) and recovery algorithms. Restricted isometry constants (RIC) of the measurement matrix are the most widely used tool for the analysis of CS recovery algorithms. The addition of the subscripts 1 and 2 below reflects the two RIC variants developed in the CS literature, they refer to the ℓ1-norm and ℓ2-norm respectively. The RIC2 of a matrix A measures how close to an isometry is the action of A on vectors with few nonzero entries, measured in the ℓ2-norm. This, and related quantities, provide a mechanism by which standard eigen-analysis can be applied to topics relying on sparsity. Specifically, the upper and lower RIC2 of a matrix A of size n × N is the maximum and the minimum deviation from unity (one) of the largest and smallest, respectively, square of singular values of all (N/k)matrices formed by taking k columns from A. Calculation of the RIC2 is intractable for most matrices due to its combinatorial nature; however, many random matrices typically have bounded RIC2 in some range of problem sizes (k, n,N). We provide the best known bound on the RIC2 for Gaussian matrices, which is also the smallest known bound on the RIC2 for any large rectangular matrix. Our results are built on the prior bounds of Blanchard, Cartis, and Tanner in Compressed Sensing: How sharp is the Restricted Isometry Property?, with improvements achieved by grouping submatrices that share a substantial number of columns. RIC2 bounds have been presented for a variety of random matrices, matrix dimensions and sparsity ranges. We provide explicit formulae for RIC2 bounds, of n × N Gaussian matrices with sparsity k, in three settings: a) n/N fixed and k/n approaching zero, b) k/n fixed and n/N approaching zero, and c) n/N approaching zero with k/n decaying inverse logarithmically in N/n; in these three settings the RICs a) decay to zero, b) become unbounded (or approach inherent bounds), and c) approach a non-zero constant. Implications of these results for RIC2 based analysis of CS algorithms are presented. The RIC2 of sparse mean zero random matrices can be bounded by using concentration bounds of Gaussian matrices. However, this RIC2 approach does not capture the benefits of the sparse matrices, and in so doing gives pessimistic bounds. RIC1 is a variant of RIC2 where the nearness to an isometry is measured in the ℓ1-norm, which is both able to better capture the structure of sparse matrices and allows for the analysis of non-mean zero matrices. We consider a probabilistic construction of sparse random matrices where each column has a fixed number of non-zeros whose row indices are drawn uniformly at random. These matrices have a one-to-one correspondence with the adjacency matrices of fixed left degree expander graphs. We present formulae for the expected cardinality of the set of neighbours for these graphs, and present a tail bound on the probability that this cardinality will be less than the expected value. Deducible from this bound is a similar bound for the expansion of the graph which is of interest in many applications. These bounds are derived through a more detailed analysis of collisions in unions of sets using a dyadic splitting technique. This bound allows for quantitative sampling theorems on existence of expander graphs and the sparse random matrices we consider and also quantitative CS sampling theorems when using sparse non mean-zero measurement matrices.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 152-158).

Thesis (M.Sc.(Water Utilisation))--University of Pretoria, 2001. / Summaries in Afrikaans and English. Includes bibliographical references.

th. 3e cycle--Math. pures--Grenoble 1, 1983. N°: 117.

Polydentate ligands are useful in many industries, mainly because of their ability to form complexes. The aim of this thesis is to study acid-base and coordination properties of polydentate ligands from the group of polyaminopolyphosphonates DTPMP and HMDTMP. The protonation constants of ligands as well as stability constants of complexes with biologically relevant ions Cu2+ , Zn2+ , Ni2+ , Mg2+ , Ca2+ , Co2+ , K+ and Na+ were determined by potentiometric titration. 31 P-NMR titration was used to determine pKa on nitrogen atoms, which could not be measured by potenciometric titration. Seven pKa for HMDTMP ligand and nine for DTPMP were obtained. The stability constants show that the HMDTMP ligand forms less stable complexes than the DTPMP ligand.

The body of information concerning carbon-carbon spin-spin coupling constants now includes a large number of coupling constants, the establishment of a dihedral angular dependence on 3JCC, and the application of 3JCC to conformational analysis. This study adds another dimension to the growing wealth of information associated with 13 C-NMR: the influence of some non-bonded interactions on 3JCC Four types of non-bonded interactions that could influence vicinal carbon-carbon NMR coupling constants were investigated. To facilitate the NMR studies, a variety of 13C-labeled compounds were synthesized.

A model system to calculate single-path coupling constant was devised to see if the couplings are additive in a system which has a dual-pathway. The system chosen was o-methyl-13C-benzoic acid. Because of anomalies in the data, the series was extended. Hybridization of the label appeared to have relatively little effect, and the conformation of the substituents very important.

This thesis addresses the issue of the time variability of the fine structure constant, alpha. Recent claims of a varying alpha are set against the established standards of quantum electrodynamical theory and experiments. A study of the feasibility of extracting data on the time dependence of alpha using particles in Penning traps is compared to the results obtained by existing methods, including those using astrophysical data and those obtained in atomic clock experiments. Suggestions are made on the nature of trapped particles and the trapping fields.