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Lookup NU author(s): Professor Richard DawsonORCiD
Assessments of changing risks in the future often focus on climate change alone, and ignore other relevant drivers such as socioeconomic changes. If other relevant drivers are considered at all, expert judgment is often used to create scenarios and the underlying logic is not always apparent. In this paper we describe an algorithm-based method for developing quantitative future scenarios of the built environment in East Anglia, England with a focus on a coastal management unit, designated sub-cell 3b. The four UK Foresight socioeconomic storylines were inputs to the study: World Markets, Local Stewardship, Global Sustainability, and National Enterprise. On the basis of estimated regional demand, the distributions of new residential and nonresidential properties were calculated under all scenarios using a GIS-based multicriteria analysis. The buildings are distributed across a large swath of East Anglia using four attraction factors with different weightings to reflect the storylines. The factors are the existing settlements, transport networks, coastline, and floodplain. The results show increases in the number of residential and nonresidential properties within the coastal flood plain of sub-cell 3b under all socioeconomic scenarios, especially under World Markets and National Enterprise. These increases may lead to a significant increase in flood risk and to a lesser extent in the erosion risk in the study site. More importantly, the multicriteria method presented here demonstrates an algorithm-based approach that provides feasible and flexible tools for the development of socioeconomic scenarios in the context of impact and risk assessment. Hence, the scenario assumptions are explicit, reproducible and easily adjustable, as required.
Author(s): Mokrech M, Nicholls RJ, Dawson RJ
Publication type: Article
Publication status: Published
Journal: Environment and Planning B: Planning & Design
Print publication date: 01/01/2012
Date deposited: 11/04/2012
ISSN (print): 0265-8135
ISSN (electronic): 1472-3417
Publisher: Pion Ltd.
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