Fluctuating climate parameters or the intensified occurrence of extreme weather events can influence the net profits of industrial companies and thereby severely hurt the economic efficiency of production plants. To estimate the industrial vulnerability in the metropolitan region Stuttgart, an indicator-based analysis was developed and conducted. This analysis offers the possibility to combine region-specific characteristics like the population density or the building stock, the regional projection of the climate and industry-specific characteristics like dependence on electricity or water on community-level and to visualize these with the help of a geographic informational system.

To measure the vulnerability of the regional industry concerning an increasing number of hot & dry and ice & frost days as well as the changing maximum wind speeds and precipitation intensities and to assign comparable values to the aforementioned, different scenarios and quantifiers were established. Results show that some regions are especially be influenced by climate change, for example as a result of the typically high requirements of the automotive and electrical industry concentrated in the metropolitan region Stuttgart regarding their particularly high vulnerability of water and energy supply.

Energy-, water- and personnel-intensive companies are going to be mainly affected by the examined risks. On a community-level, this also implies that agglomerations with a high degree of specialization will especially be affected. Within the analysed area, Stuttgart as a city and its direct surrounding areas show a strong vulnerability for climate changes.

Project-specific publications:

MERZ, M., HIETE, M. COMES, T. & SCHULTMANN, F (2013): A composite indicator model to assess natural disaster risks in industry on a spatial level. Journal of Risk Research. 16(9), p. 1077-1099.

HIETE, M., MERZ. M., COMES, T. & SCHULTMANN, F. (2012): Trapezoidal Fuzzy DEMATEL method to analyse and correct for relations between variables in a composite indicator for disaster resilience. OR Spectrum, 34(4), p. 977-995.

MERZ, M. (2011): Entwicklung einer indikatorbasierten Methodik zur Vulnerabilitätsanalyse für die Bewertung von Risiken in der industriellen Produktion. KIT-Verlag, Karlsruhe.