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Title: The interaction amongst aquatic macrophytes, hydraulic resistance and river channel flow
Author: Green, J. C.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 1999
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In order to determine the effect of aquatic macrophytes on channel hydrology, a model was developed to calculate channel resistance for rivers containing vegetation growth. Separate models of grain resistance and vegetation resistance were developed, which can then be combined to estimate the total resistance. The grain resistance model uses a measure of the size of grains on the channel bed. The choice of which grain size percentile to use, for such a model, is founded on both theoretical and empirical assessments of the precision of sampling different percentiles. Studies are presented, which demonstrate the complexity of the velocity distribution in the vicinity of aquatic plants; a distribution which is dependent on the types of plant present. These findings are used to identify the major ways in which in-channel vegetation affects channel resistance, for use in the vegetation resistance model. Consequently, this model uses the blockage factor, which is the proportion of the channel that is occupied by vegetation. This is a measure of the volume displacement effect of the vegetation, in acknowledgement that most of the flow is displaced from within a plant body. The model also includes a measure of the relative length of the vegetation boundary to that of the channel's wetted perimeter, since this factor controls the resistance to the flow between the vegetation stands. The effectiveness of this model is compared against other vegetation resistance studies, while the possibility of developing a predictive model which calculates channel resistance under different hydraulic conditions is also discussed. The results of these models are then used to assess if aquatic macrophytes significantly contribute to flooding, and to consider whether it is necessary to manage these channels. New management techniques are also proposed based on the findings of the models developed in this thesis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available