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dc.contributor.authorPolitti, Emilio
dc.date.accessioned2018-02-28T11:52:18Z
dc.date.available2018-02-28T11:52:18Z
dc.date.issued30/01/2018
dc.date.submitted2018-02-28T10:50:52.054Z
dc.identifier.citationPolitti, E. 2018. Investigating and modelling the interaction among vegetation, hydrodynamics and morphology. Queen Mary University of Londonen_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/33928
dc.descriptionPhDen_US
dc.description.abstractThe dissertation presented in this manuscript contributes to river science by providing a detailed overview on the state of the art on the interaction between riparian vegetation and hydrogeomorphological processes, by devising a novel model encompassing most of such processes and by proposing a field methodology aimed at providing means for improving the modelling of such interactions. The state of the art is summarized in an extensive review describing riparian vegetation and hydrogeomorphological processes mutual feedbacks. Such review did not simply seek to describe these feedbacks but, compiling from a large array of results from field, laboratory and modelling studies, provides a set of physical thresholds that trigger system changes. Therefore, processes are not only described terms but also explained with a quantitative approach. Processes description provided the conceptual foundation for the development of the novel simulation model while model parameterization was based on the quantitative information collected in the review. Such novel model, encompasses the main relationships entwining riparian woody vegetation and hydrogeomorphological processes and is able of replicating long term riparian landscape dynamics considering disturbance events, environmental stressor and riparian woody vegetation establishment from seeds and large wood. The manuscript presents the model structure and its conceptual validation by means of hydrological scenarios aimed at testing the coherence of the simulation results with expected system behaviour. Examples of such coherences are vegetation growth rate in response to hydrological regime, entrainment and establishment of large wood in an unconfined river system and vegetation effect on erosion and deposition patterns. Analysis of sedimentation patterns from the modelled results suggested that vegetation flow resistance should be modelled with greater detail. These conclusions pointed the dissertation research towards the testing of a novel class of vegetation flow resistance equations, proposed by different authors, able of describing woody vegetation flow resistance on a physical basis. These equations have the advantage of considering flow stage, plants foliation level and species-specific flexibility. However, the use of such equations is limited by the difficulty of measuring the vegetation properties required as equation-inputs. In order to test if these equations could effectively improve sediment dynamics predictions, a field method was formulated and tested. The field method allows to sample vegetation properties that can be used with these novel class of flow resistance equations. In the manuscript, such method is applied and the resulting vegetation properties used in several modelling scenarios. Such scenario proved that hydraulic variables modelled with these novel flow resistance approaches are more realistic and thus that the model developed during the dissertation could benefit from inclusion of such flow resistance equations in its source code.en_US
dc.description.sponsorshipEdmund Mach Foundation
dc.language.isoenen_US
dc.publisherQueen Mary University of London
dc.subjectLawen_US
dc.subjectIntellectual propertyen_US
dc.subjectCollateralen_US
dc.subjectFinancingen_US
dc.titleInvestigating and modelling the interaction among vegetation, hydrodynamics and morphologyen_US
dc.typeThesisen_US
dc.rights.holderThe copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author


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  • Theses [4125]
    Theses Awarded by Queen Mary University of London

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