Harmonizing and comparing single-type natural hazard risk estimations

Single-type hazard and risk assessment is the usual framework followed by disaster risk reduction (DRR) practitioners. There is therefore a need to present and compare the results arising from different hazard and risk types. Here we describe a simple method for combining risk curves arising from different hazard types in order to gain a first impression of the total risk. We show how the resulting total (and individual) risk estimates can be examined and compared using so-called risk matrices, a format preferred by some DRR practitioners. We apply this approach to Cologne, Germany, which is subject to floods, windstorms and earthquakes. We then use a new series of risk calculations that consider epistemic uncertainty. The Mann-Whitney test is applied to determine if the losses arising from pairs of hazards are comparable for a given return period. This benefits decision makers as it allows a ranking of hazards with respect to expected damage. Such a comparison would assist planners in the allocation of resources towards the most efficient mitigation actions. However, the results are dependent upon the distribution of estimates (i.e., level of uncertainty), which is in turn a function of our state of knowledge

Towards a cross-border exposure model for the Earthquake Model Central Asia

This work provides an insight into the development of the first harmonized exposure model for Central Asia. The model was derived in the frame of the Earthquake Model Central Asia (EMCA) project, which is the regional initiative for Central Asia to the Global Earthquake Model (GEM). The EMCA exposure model combines commonly used data sources and acquisition techniques (e.g., rapid visual screening) with novel rapid assessment approaches (e.g., satellite remote sensing and omnidirectional imaging) in the framework of an integrated sampling scheme and stores the data in a multi-resolution spatio-temporal database. The exposure model implements a newly developed building typology, harmonized for the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) and follows the international building taxonomy of the GEM. Emphasis is given to the multi-scale nature and the temporal dynamics of exposure data. Results from a selected urban area are provided to illustrate the current state of the continuously updated exposure model