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dc.contributor.advisorPaterson, Robert G.
dc.creatorHilde, Thomas Warren
dc.date.accessioned2018-02-08T17:13:31Z
dc.date.available2018-02-08T17:13:31Z
dc.date.created2017-12
dc.date.submittedDecember 2017
dc.identifierdoi:10.15781/T2DZ03J4S
dc.identifier.urihttp://hdl.handle.net/2152/63569
dc.description.abstractDespite growing disaster losses in the US, hazard mitigation and other forms of emergency management planning remain fragmented from other ‘mainstream’ local planning efforts. Surprisingly, there are few examples in local planning where connections have been made between disaster resilience and green infrastructure objectives, despite that green infrastructure planning is becoming more widespread as communities better understand the ecological and human benefits provided by open space, parkland and other protected natural areas. This is a missed opportunity for promoting urban resilience, since many green infrastructure functions are complementary to resiliency goals, and investments in green infrastructure generally resonate with a broader community constituency than single-function hazard mitigation projects. In this context, the objective of the dissertation is to test how innovative scenario planning techniques can be used to draw stronger connections between green infrastructure and disaster resilience objectives in local community planning. The following research questions are answered: (1) Examined retrospectively with historical counterfactual scenarios, how can modeling past disaster events help demonstrate missed opportunities for green infrastructure planning approaches to improve resilience? (2) Examined prospectively with exploratory scenarios, how can modeling plausible future disasters help inform long-term green infrastructure planning approaches for improving community resilience? (3) From the foregoing analyses, what are the strengths and weaknesses of the integrated scenario planning techniques for generating information flows about green infrastructure’s role in building community resilience? The utility of the integrated scenario-based planning approach is beta-tested in the context of flash flooding in two embedded study areas in the case city of Austin, TX: Onion Creek and Gilleland Creek. The analysis hinges on a methodological innovation that combines Geographic Information Systems (GIS), a disaster loss estimation software (Hazus), and an urbanization model (Envision Tomorrow) to support comparable assessments of green infrastructure impacts on vulnerability reduction and avoided disaster losses in addition to baseline sustainability outcomes. Semi-structured interviews were conducted with nine local planning stakeholders to identify key contextual issues, assumptions and objectives prior to conducting the scenario analysis. The study provides a new avenue for integrated resilience planning, in which relationships between the built environment, natural systems, and social systems are better understood within local planning efforts. It offers novel scenario-based methods for revisiting past missed opportunities and exploring plausible future events for generating information that supports resilient community planning.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectGreen infrastructure
dc.subjectDisaster resilience
dc.subjectScenario planning
dc.subjectPlanning support systems
dc.subjectGeographic information systems
dc.subjectLand use planning
dc.subjectEnvironmental planning
dc.titleGreen infrastructure for disaster resilience : exploring connections with scenario planning
dc.typeThesis
dc.date.updated2018-02-08T17:13:31Z
dc.contributor.committeeMemberMueller, Elizabeth J
dc.contributor.committeeMemberShearer, Allan
dc.contributor.committeeMemberWilson, Robert H
dc.description.departmentCommunity and Regional Planning
thesis.degree.departmentCommunity and Regional Planning
thesis.degree.disciplineCommunity and Regional Planning
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
dc.creator.orcid0000-0001-6584-3066
dc.type.materialtext


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