Ingurune eraikiaren ebaluazio eta kudeaketa modeloak

CLIMATE CHANGE RISK MANAGEMENT FOR THE SUSTAINABLE DEVELOPMENT OF THE HISTORIC CITY: FROM THE MATERIAL TO THE TERRITORY

Doktoregaia:
Alessandra Gandini
Urtea:
2017
Unibertsitatea:
Euskal Herriko Unibertsitatea (UPV/EHU)
Zuzendaria(k):
José Tomás San José Lombera & Maria Cristina Giambruno
Deskribapena:

Cities are complex and interdependent systems, vulnerable to threats from natural hazards. Over recent years, sea-level rise, the increasing frequency of storms, and numerous other extreme precipitation events have all occurred, impacting on a large number of historic structures and increasing concern over risks due to weather patterns and global climate change.

Conservation of urban areas of historic value involves the management of change that, when properly addressed, is an opportunity to improve the quality of urban areas, ensuring the protection of social values as well as the authenticity and integrity of the physical material. Disaster risk reduction and adaptation toclimate change should be seen as components of conservation, as they all share the objective of addressing the challenges of sustainable urban development.

The scope of this thesis is to analyse the impacts of flooding events caused by extreme precipitation and sea-level rise in urban areas with historic value, in order to prioritize interventions in the most sensitive areas.

A methodological approach for vulnerability and risk assessment has been developed, supported by an information strategy and a multi-scale urban model. The MIVES (Integrated Value Model for Sustainability Assessment) methodology was applied, in order to provide decision-making with objective and justified prioritization. The methodology delivers a balanced solution in terms of accurate results and data requirements, by using a categorization method for urban modelling. Information is organized and structured in hierarchical levels, permitting the comparison of building vulnerabilities and risks through the use of a unique index, thus facilitating the decision-making that is needed for the prioritization of efficient interventions.

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