{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/89116"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/89116","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Reliability analysis of green roofs under different storm scenarios","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["William, Reshmina Keren"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil & Environmental Engineering","degree_department":null,"school":null,"contributors":["Stillwell, Ashlynn S."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-03-02T20:23:33Z","date_published":"2016-03-02T20:23:33Z","updated_at":"2026-07-22T22:26:32Z","subjects":["Green roofs","stormwater","reliability"],"languages":["en"],"rights":["Copyright 2015 Reshmina William"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/89116","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stillwell, Ashlynn S."]},{"key":"dc:creator","label":"Author","values":["William, Reshmina Keren"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-03-02T20:23:33Z","2018-03-03T10:15:34Z","2015-11-20","2015-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil & Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Green roofs","stormwater","reliability"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2015 Reshmina William"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/89116"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2017-12-01","The student, Reshmina William, accepted the attached license on 2015-11-19 at 10:31.","The student, Reshmina William, submitted this Thesis for approval on 2015-11-19 at 10:37.","This Thesis was approved for publication on 2015-11-20 at 14:34.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8806 on 2016-03-02 at 14:05:58","Made available in DSpace on 2016-03-02T20:23:33Z (GMT). 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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.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2017-12-01","The student, Reshmina William, accepted the attached license on 2015-11-19 at 10:31.","The student, Reshmina William, submitted this Thesis for approval on 2015-11-19 at 10:37.","This Thesis was approved for publication on 2015-11-20 at 14:34.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8806 on 2016-03-02 at 14:05:58","Made available in DSpace on 2016-03-02T20:23:33Z (GMT). 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