Integrated climate change risk assessment: A practical application for urban flooding during extreme precipitation

• Published in: Climate services Vol. 6; no. C; pp. 55 - 64
• Main Authors: Kaspersen, Per Skougaard, Halsnæs, Kirsten
• Format: Journal Article
• Language: English
• Published: Elsevier 01-04-2017
• Subjects: Climate change; Extreme precipitation; Flood damage; Risk assessment; Uncertainties; Urban flooding
• ISSN: 2405-8807; 2405-8807
• DOI: 10.1016/j.cliser.2017.06.012

Risk assessments of flooding in urban areas during extreme precipitation for use in, for example, decision-making regarding climate adaptation, are surrounded by great uncertainties stemming from climate model projections, methods of downscaling and the assumptions of socioeconomic impact models. The multidisciplinary character of such risk assessments also requires that research groups and experts from different scientific disciplines combine knowledge and share model outputs. This paper describes an integrated framework and tool, the Danish Integrated Assessment System (DIAS), which has been designed to address the complex linkages between the different kinds of data required in assessing climate adaptation. It emphasizes that the availability of spatially explicit data can reduce the overall uncertainty of the risk assessment and assist in identifying key vulnerable assets. The usefulness of such a framework is demonstrated by means of a risk assessment of flooding from extreme precipitation for the city of Odense, Denmark. A sensitivity analysis shows how the presence of particularly important assets, such as cultural and historical heritage, may be addressed in assessing such risks. The output of the risk assessment for Odense indicates that highly detailed geographical data reduce the overall uncertainty and assist climate adaptation decision-makers in focusing on protecting those assets that are considered to be relevant in the given context. Also, using an integrated framework such as DIAS enables the relative importance of the different factors (i.e. degree of climate change, assets value, discount rate etc.) to be determined, thus influencing the overall output of the assessment.