The efficacy of pond treatment systems is dependent on the internal hydrodynamic and mixing interactions between aquatic vegetation and the adjacent flow. In attempting to improve pollution degradation and reduce the effects of hydraulic short circuiting, an understanding and quantification of these interactions was sought for seasonal changes in vegetation growth. Controlled laboratory studies were conducted using detailed Laser Induced Fluorometry (LIF) and Ultrasound Velocity Profiling (UVP) techniques to quantify mixing across vegetated shear layer, emergent Cattail reeds (Typha latifolia). An Optimised Finite Difference Model (OFDM) was developed to predict the best fit downstream concentration distributions given the input profiles of transverse mixing coefficient, Dy(y). The model provided strong fitting in artificial vegetation (R2 = 0.977 and 0.969 for high and low density rigid cylinders). A good fitting was also made for the winter reeds (R2 = 0.976); although the physical application of conventional shear layer theory failed to significantly improve predictions in the summer season reeds above those of a simple discontinuity functionality describing Dy(y). The form of the lateral variation in transverse mixing coefficient was confirmed in the artificial vegetation studies where peak mixing is enhanced by shear layer vortices. However, in real vegetated shear flows, the heterogeneities in stem morphology and distribution render the relative magnitude of shear layer mixing diminished when compared to other regions of the flow. It is shown that, while the OFDM provides good predictions of concentration distributions when using a physically justified profile of the transverse mixing coefficient, a discrete step formulation is sufficient for describing mixing in real vegetated shear flows. This study shows therefore, that, while shear layer mixing is dominant in artificial, uniform vegetation, transverse mixing in real vegetated flows is dominated by complex geometries, localised shear processes and bed roughness effects.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:694614 |
| Date | January 2016 |
| Creators | West, Patrick Oakley |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/81815/ |
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