7 research outputs found

    Reliability analysis of green roofs under different storm scenarios

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    The rise of urban environments has created issues with localized flooding and water quality due to changes in runoff caused by increasing impervious area. Green infrastructure offers an alternative method of runoff reduction, by using natural processes to infiltrate, store, and treat runoff at its source. In particular, green roofs can promise multiple benefits in terms of runoff reduction, air quality improvement, and mitigation of the urban heat island effect, while taking up little additional land. However, few consistent standards exist to help designers and planners decide whether or not a green roof is performing as expected. This research provides a reliability analysis-based methodology that can be used to evaluate green roof runoff reduction. Green roof failure is characterized using a visual aid typically used in earthquake engineering: fragility curves. The 2D distributed surface water-groundwater coupled program MIKE SHE was used to model the runoff from a simple intensive green roof located on the University of Illinois at Urbana-Champaign (UIUC) campus under different storm scenarios. The results from these runs were then input into the reliability analysis software FERUM in order to calculate the probability of failure under the first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo analyses. The fragility curves generated show the efficiency in runoff reduction provided by a green roof compared to a conventional roof under different storm scenarios. The use of reliability analysis as a part of green roof design code can help test for weaknesses and areas for improvement pertaining to peak runoff reduction. It can also help to support the design of code that is more resilient and testable for failure than current standards

    The role of reliability in characterizing green stormwater infrastructure in urban areas

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    As cities continue to expand, the issues of flood control and urban water quality have risen to the forefront of modern sustainability challenges. Green infrastructure— the use of nature-based solutions to target, treat, and store stormwater at its source— has emerged as a possible solution. While green infrastructure does offer multiple benefits for urban users, its performance is also highly variable. This dissertation addresses a key gap in the literature by explicitly addressing how uncertainty in environmental and anthropogenic factors affects green infrastructure performance at modular, systemic, and policy levels. Three primary contributions are made by this research, using an underlying fragility function methodology. Firstly, an analysis of the impact of temporal and spatial variability on modular rain garden performance offers insights into challenges commonly faced by green infrastructure: clogging and maintenance, back-to-back rainfall, and variable urban soils. Building on these findings, the second contribution is the use of fragility functions to characterize green infrastructure performance within the context of an existing separated storm sewer network. A case study approach is used to analyze the effect of green infrastructure implementation at multiple spatial scales and configurations. Finally, an in-depth policy analysis incorporating game theory, environmental psychology, and environmental law evaluates how and why green infrastructure should be integrated into the existing urban policy landscape. This research fills an important gap in the literature by offering a new perspective on green infrastructure performance, using an interdisciplinary, risk-based approach to analyze how green infrastructure can be better integrated into the urban landscape
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