Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595247
Title: A two-stage runoff detention model for a green roof
Author: Vesuviano, Gianni Michael
ISNI:       0000 0004 5348 6104
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2014
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Abstract:
Urbanization has caused an increase in per-event stormwater runoff volumes. Existing combined sewer systems are becoming less able to take in storm runoff without overflowing, which may cause flooding and water quality issues. Sustainable drainage systems (SUDS) are structures and practices intended to reduce the volume and rate of a site’s runoff to pre-development levels. Green roofs, not requiring exclusive land use, can be easily integrated into dense urban areas. However, their hydrological behaviour requires further understanding. A generic tool was created for routing detained rainwater through separately-modelled substrate and drainage layer components of a green roof. Components were monitored in isolation, in purpose-built rainfall simulators, under laboratory conditions. Configuration variables (e.g. roof slope) were varied and their effects on runoff response assessed. Nonlinear storage routing methods were used to fit modelled to monitored runoff profiles, by optimizing routing parameters. The sensitivity of these parameters to test variables was assessed, greatly reducing the number of individual values required for modelling either layer. The runoff response of a two-layered green roof system at field capacity was tested under laboratory conditions. The substrate model, in series with the drainage layer model, was parameterized for the two-layered system, and time-series runoff predictions and observations were compared. The model produced consistently accurate results. This model was reparameterized for three monitored test beds in Sheffield, UK, using estimated parameter values for the three untested system configurations. The model was found to be fit for purpose, approaching laboratory accuracy in the best cases. Peak flow predictions were improved by allowing limited runoff to occur before a roof’s water content completely reached field capacity. Further work should extend the model’s applicability to long time-series, through improved evapotranspiration modelling. Further laboratory observations of individual roof components are desirable, to increase the range of modellable green roof configurations.
Supervisor: Stovin, Virginia Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.595247  DOI: Not available
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