THESEUS decision support system for coastal risk management

被引:55
|
作者
Zanuttigh, Barbara [1 ]
Simcic, Dario [2 ]
Bagli, Stefano [1 ]
Bozzeda, Fabio [1 ]
Pietrantoni, Luca [1 ]
Zagonari, Fabio [1 ]
Hoggart, Simon [3 ]
Nicholls, Robert J. [4 ]
机构
[1] Univ Bologna, I-40126 Bologna, Italy
[2] GeoGraphics Srl, Ferrara, Italy
[3] Univ Plymouth, Plymouth PL4 8AA, Devon, England
[4] Univ Southampton, Southampton SO9 5NH, Hants, England
关键词
Decision support system; Scenario analysis; Risk assessment; Risk mitigation; Society; Economy; Ecology; GIS; VULNERABILITY; MODEL; ADAPTATION; INUNDATION; EROSION; IMPACT; LEVEL; BEACHES; LESSONS; INDEX;
D O I
10.1016/j.coastaleng.2013.11.013
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
While planning coastal risk management strategies, coastal managers need to assess risk across a range of spatial and temporal scales. GIS-based tools are one efficient way to support them in the decision making process through a scenarios analysis starting from social, economic and environmental information integrated into a common platform. However, this integration process requires a significant effort from a team of scientists in terms of a) identifying the appropriate scales and data resolution for analysing social, environmental and economic issues; b) selecting and linking an appropriate set of tools to build a coupled model; c) representing key emerging (and hence challenging) research issues, such as risk perception and social resilience in the model; d) developing multi-criteria analysis to integrate social, environmental, economic impacts; and e) accounting for the expectations of the stakeholders and therefore optimizing the opportunity for them to interact with the tool development and with the final tool itself. In this spirit, this paper presents an open-source Spatial Decision Support System developed within the THESEUS Project to help decision makers to scopeg optimal strategies to minimise coastal risks. The exploratory tool allows the users to perform an integrated coastal risk assessment, to analyse the effects of different combinations of engineering, social, economic and ecologically based mitigation options, across short (2020s), medium (2050s) and long-term (2080s) scenarios, taking into account physical and non-physical drivers, such as climate change, subsidence, population and economic growth. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:218 / 239
页数:22
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