Developing an integrated hydrograph separation and lumped modelling approach to quantifying hydrological pathways in Irish river catchments

An appreciation of the quantity of streamflow derived from the main hydrological pathways involved in transporting diffuse contaminants is critical when addressing a wide range of water resource management issues. In order to assess hydrological pathway contributions to streams, it is necessary to provide feasible upper and lower bounds for flows in each pathway. An important first step in this process is to provide reliable estimates of the slower responding groundwater pathways and subsequently the quicker overland and interflow pathways. This paper investigates the effectiveness of a multi-faceted approach applying different hydrograph separation techniques, supplemented by lumped hydrological modelling, for calculating the Baseflow Index (BFI), for the development of an integrated approach to hydrograph separation. A semi-distributed, lumped and deterministic rainfall runoff model known as NAM has been applied to ten catchments (ranging from 5 to 699 km2). While this modelling approach is useful as a validation method, NAM itself is also an important tool for investigation. These separation techniques provide a large variation in BFI, a difference of 0.741 predicted for BFI in a catchment with the less reliable fixed and sliding interval methods and local minima turning point methods included. This variation is reduced to 0.167 with these methods omitted. The Boughton and Eckhardt algorithms, while quite subjective in their use, provide quick and easily implemented approaches for obtaining physically realistic hydrograph separations. It is observed that while the different separation techniques give varying BFI values for each of the catchments, a recharge coefficient approach developed in Ireland, when applied in conjunction with the Master recession Curve Tabulation method, predict estimates in agreement with those obtained using the NAM model, and these estimates are also consistent with the study catchments’ geology. These two separation methods, in conjunction with the NAM model, were selected to form an integrated approach to assessing BFI in catchments.

The geometry and ionization structure of the wind in the eclipsing nova-like variables RW Tri and UX UMa

The UV spectra of nova-like variables are dominated by emission from the accretion disk, modified by scattering in a wind emanating from the disk. Here, we model the spectra of RW Tri and UX UMa, the only two eclipsing nova-like variables which have been observed with the Hubble Space Telescope in the far-ultraviolet, in an attempt to constrain the geometry and the ionization structure of their winds. Using our Monte Carlo radiative transfer code, we computed spectra for simply parameterized axisymmetric biconical outflow models and were able to find plausible models for both systems. These reproduce the primary UV resonance lines-N v, Si iv, and C iv-in the observed spectra in and out of eclipse. The distribution of these ions in the wind models is similar in both cases as is the extent of the primary scattering regions in which these lines are formed. The inferred mass-loss rates are 6%-8% of the mass accretion rates for the systems. We discuss the implication of our point models for our understanding of accretion disk winds in cataclysmic variables. © 2010. The American Astronomical Society. All rights reserved.

Understanding macroalgal dispersal in a complex hydrodynamic environment: a combined population genetic and physical modelling approach

Gene flow in macroalgal populations can be strongly influenced by spore or gamete dispersal. This, in turn, is influenced by a convolution of the effects of current flow and specific plant reproductive strategies. Although several studies have demonstrated genetic variability in macroalgal populations over a wide range of spatial scales, the associated current data have generally been poorly resolved spatially and temporally. In this study, we used a combination of population genetic analyses and high-resolution hydrodynamic modelling to investigate potential connectivity between populations of the kelp Laminaria digitata in the Strangford Narrows, a narrow channel characterized by strong currents linking the large semi-enclosed sea lough, Strangford Lough, to the Irish Sea. Levels of genetic structuring based on six microsatellite markers were very low, indicating high levels of gene flow and a pattern of isolation-by-distance, where populations are more likely to exchange migrants with geographically proximal populations, but with occasional long-distance dispersal. This was confirmed by the particle tracking model, which showed that, while the majority of spores settle near the release site, there is potential for dispersal over several kilometres. This combined population genetic and modelling approach suggests that the complex hydrodynamic environment at the entrance to Strangford Lough can facilitate dispersal on a scale exceeding that proposed for L. digitata in particular, and the majority of macroalgae in general. The study demonstrates the potential of integrated physical–biological approaches for the prediction of ecological changes resulting from factors such as anthropogenically induced coastal zone changes.

Accurate and Efficient Modelling to Calculate the Voltage Dependence of Liquid Crystal Based Reflectarray Cells

Two models that can predict the voltage-dependent scattering from liquid crystal (LC)-based reflectarray cells are presented. The validity of both numerical techniques is demonstrated using measured results in the frequency range 94-110 GHz. The most rigorous approach models, for each voltage, the inhomogeneous and anisotropic permittivity of the LC as a stratified media in the direction of the biasing field. This accounts for the different tilt angles of the LC molecules inside the cell calculated from the solution of the elastic problem. The other model is based on an effective homogeneous permittivity tensor that corresponds to the average tilt angle along the longitudinal direction for each biasing voltage. In this model, convergence problems associated with the longitudinal inhomogeneity are avoided, and the computation efficiency is improved. Both models provide a correspondence between the reflection coefficient (losses and phase-shift) of the LC-based reflectarray cell and the value of biasing voltage, which can be used to design beam scanning reflectarrays. The accuracy and the efficiency of both models are also analyzed and discussed.

The Application of Computational Chemistry and Chemometrics to Developing a Method for Online Monitoring of Polymer Degradation in the Manufacture of Bioresorbable Medical Implants

Bioresorbable polymers such as PLA have an important role to play in the development of temporary implantable medical devices with significant benefits over traditional therapies. However, development of new devices is hindered by high manufacturing costs associated with difficulties in processing the material. A major problem is the lack of insight on material degradation during processing. In this work, a method of quantifying degradation of PLA using IR spectroscopy coupled with computational chemistry and chemometric modeling is examined. It is shown that the method can predict the quantity of degradation products in solid-state samples with reasonably good accuracy, indicating the potential to adapt the method to developing an on-line sensor for monitoring PLA degradation in real-time during processing.

Multi-scale cortical keypoint representation for attention and object detection

Keypoints (junctions) provide important information for focus-of-attention (FoA) and object categorization/recognition. In this paper we analyze the multi-scale keypoint representation, obtained by applying a linear and quasi-continuous scaling to an optimized model of cortical end-stopped cells, in order to study its importance and possibilities for developing a visual, cortical architecture.We show that keypoints, especially those which are stable over larger scale intervals, can provide a hierarchically structured saliency map for FoA and object recognition. In addition, the application of non-classical receptive field inhibition to keypoint detection allows to distinguish contour keypoints from texture (surface) keypoints.

Multi-scale keypoint hierarchy for Focus-of-Attention and object detection

Hypercolumns in area V1 contain frequency- and orientation-selective simple and complex cells for line (bar) and edge coding, plus end-stopped cells for key- point (vertex) detection. A single-scale (single-frequency) mathematical model of single and double end-stopped cells on the basis of Gabor filter responses was developed by Heitger et al. (1992 Vision Research 32 963-981). We developed an improved model by stabilising keypoint detection over neighbouring micro- scales.