Analysing Disaster Impact Using Advanced Computation

Abstract

Natural hazards can occur in the form of Space Weather events, severe flooding, earthquakes, severe storms and tsunamis. Some of them will likely become more frequent and intense as global warming accelerates (IPCC, 2013). They will have an impact on society's infrastructure - networks of trade, transport and production. Links in global economic chains and world markets mean that natural disaster in one place can have repercussions elsewhere. Imports and exports currently account for 20% of global Gross Domestic Product (GDP) and this number is likely to further increase in the future. Consequently, the influence of natural disaster on the worldwide flows of materials, electricity, communications and energy, including interactions between them needs to be modelled and understood. New global and national Multi-Regional Input-Output (MRIO) models that provide such details are presented in this thesis. With them and a new computational approach called global MRIO Lab IO models are suited more than ever to unravel impacts on trade and supply chain linkages and other dependencies evolving through globalization. The global MRIO Lab is presented in Chapter 2. The lab is then used to construct and update an environmental extended global MRIO model called EXIOLAB. In Chapter 3, a new MRIO model of the German economy is developed and used to assess the economic impacts of the severe flood in Germany and other parts of Europe in 2013. In Chapter 4 a new model for improved space weather forecast is developed first. With it a first attempt is made to couple a physical impact model with an economic model of global trade showing how a space weather event in three different regions (China, Europe and North America) would drive impacts across the world economy. It reinforces the message that a physical impact in one region can damage economies far from the impact site