Decision-support for climate change adaptation – applications for coastal regions
In DTU Management Engineering. PhD thesis, 2014
Abstract
This Ph.D. project aims at developing a new decision-support framework for managing climate change in coastal areas. The framework is developed in order to facilitate screening of climate change impacts in all coastal areas worldwide and is designed as a complete system for combined multi-hazard-assessment and multi-hazard-management. The framework addresses the hazards of ecosystem disruption, gradual inundation, salt water intrusion, erosion and flooding and can be used for hazard management at local, regional and national level. It is developed as a simple system that can be applied in areas with limited data availability and institutional capacity and is especially targeted the needs of developing countries. In order to make the framework easily accessible to coastal managers, it is designed as a graphical tool – the Coastal Hazard Wheel – that functions as a key for determining the characteristics of a coastline, its hazard profile and possible management options, and can be used for screening purposes prior to more detailed feasibility studies. The project has applied the framework for multi-hazard-assessments for the state of Karnataka, India and for the state of Djibouti to showcase its application in two very different coastal settings. The assessments are carried out in a GIS using basic and publicly available data, and a range of thematic hazard maps and hazard management recommendations have been developed for the two areas. Along with this, the assessments include discussions of practical challenges, uncertainties and limitations. Based on the applications on Karnataka and Djibouti, feedback from coastal experts and a range of selected spot-assessments, a slightly revised version of the Coastal Hazard Wheel has been developed. This is presented in an overview paper together with general guidelines for applying the framework for coastal hazard assessment and management.