Economic Hotspots: Visualizing Vulnerability to Flooding

Abstract

We simulate a large-scale flooding in the province of South-Holland in the economic centre of the Netherlands. In traditional research, damage due to flooding is computed with a unit loss method coupling land use information to depth-damage functions. Normally only direct costs are incorporated as an estimate of damage to infrastructure, property and business disruption. We extend this damage concept with the indirect economic effects on the rest of the regional and national economy on basis of a bi-regional input output table.We broaden this damage estimation to the concept of vulnerability. Vulnerability is defined as a function of dependence, redundancy and susceptibility. Susceptibility is the probability and extent of flooding. Dependency is the degree to which an activity relates to other economic activities in the rest of the country. Input–output multipliers form representations of this dependency. Redundancy is the ability of an economic activity to respond to a disaster by deferring, using substitutes or relocating. We measure redundancy as the degree of centrality of an economic activity in a network. The more central an activity is, the less it encounters possibilities to transfer production and the more vulnerable it is for flooding. Vulnerability of economic activities is then visualized in a GIS. Kernel density estimation is applied to generalize point information on inundated firms to sectoral information in space. We apply spatial interpolation techniques for the whole of the province of South-Holland. Combining information of sectoral data on dependency and redundancy, we are able to create maps of economic hotspots. Our simulation of a flood in the centre of Holland reveals the vulnerability of a densely populated delta.