Keywords

Climate Change Adaptation; Quantitative Data; Qualitative Data; System Dynamics; Stakeholders; MICMAC Method; Scenarios

Location

Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity

Start Date

17-6-2014 9:00 AM

End Date

17-6-2014 10:20 AM

Abstract

Inherently, 'Climate Change Adaptation' is a complex issue requiring use of a range of methods and data, which involves many stakeholders. In this, often quantitative models relying on quantitative data are used to explore and predict the likely impact of a changing climate, and to evaluate adaptation alternatives. While such models do provide useful information, in addressing such complex issues they clearly need more data. In reality, quantitative data are not readily available, or too expensive to obtain. Therefore, to provide a more comprehensive insight, qualitative and quantitative data needs to be collected from a variety of stakeholders with different backgrounds and interests. These data are integrated for detailed analysis to transform opinions (data), into a model (system conceptualisation): especially, in the context of identifying important drivers and enablers, their interrelations, influence and dependencies. For the conceptualisation phase of such a model, the MICMAC method of structural analysis is particularly well suited for the analytical integration of culpable system parts and to identify causal feedback loops between variables. Further, the enhanced influence - dependence mapping from the method is a useful tool for the development of the resultant structural analysis to include the dynamics for a likely 'futures' scenario. In this, this paper aims to outline the systematically development of key variables integrating quantitative and qualitative data analysis into the development of a model suitable to address climate change adaptation issues.

COinS
 
Jun 17th, 9:00 AM Jun 17th, 10:20 AM

Modelling climate change adaptation using cross-impact analysis: an approach for integrating qualitative and quantitative data

Session H5: Systems Modeling and Climate Change: A Systematic Methodology for Disentangling Elements of Vulnerability, Adaptation and Adaptive Capacity

Inherently, 'Climate Change Adaptation' is a complex issue requiring use of a range of methods and data, which involves many stakeholders. In this, often quantitative models relying on quantitative data are used to explore and predict the likely impact of a changing climate, and to evaluate adaptation alternatives. While such models do provide useful information, in addressing such complex issues they clearly need more data. In reality, quantitative data are not readily available, or too expensive to obtain. Therefore, to provide a more comprehensive insight, qualitative and quantitative data needs to be collected from a variety of stakeholders with different backgrounds and interests. These data are integrated for detailed analysis to transform opinions (data), into a model (system conceptualisation): especially, in the context of identifying important drivers and enablers, their interrelations, influence and dependencies. For the conceptualisation phase of such a model, the MICMAC method of structural analysis is particularly well suited for the analytical integration of culpable system parts and to identify causal feedback loops between variables. Further, the enhanced influence - dependence mapping from the method is a useful tool for the development of the resultant structural analysis to include the dynamics for a likely 'futures' scenario. In this, this paper aims to outline the systematically development of key variables integrating quantitative and qualitative data analysis into the development of a model suitable to address climate change adaptation issues.