No abstract

Abstract. This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

For the successful realization and productivity prediction of new hydrothermal projects in the South German Molasse Basin, the hydraulic matrix properties of the Upper Jurassic Malm reservoir have to be determined as accurately as possible. To obtain specific information on the distribution of the petrophysical parameters (e.g., rock density, porosity, and permeability) 363 samples of rare drilling cores from the reservoir northeast of Munich (wells Moosburg SC4 and Dingolfing FB) were investigated using different experimental methods. Additionally, porosity was calculated by a downhole resistivity log of a nearby borehole close to Munich for comparison and the attempt of transferability of the data set to other locations within the Central Molasse Basin. Core data were divided into groups of different stratigraphic and petrographic units to cover the heterogeneity of the carbonate aquifer and provide data ranges to improve reservoir and prediction models. Data for effective porosity show a high variance from 0.3 to 19.2% throughout this heterogeneous aquifer. Permeability measured on core samples is scattered over several orders of magnitude (10 −4-10 2 mD). Permeability models based on the porosity-permeability relationship were used to estimate permeability for the whole aquifer section and identify possible flow zones. A newly developed empirical model based on distinct lithofacies types allows a permeability estimation with a deviation < 10 mD. However, fractured, karstified, and vuggy zones occurring in this typically karstified, fractured, and porous reservoir cannot yet be taken into account by the model and result in an underestimation of permeability on reservoir scale. Overall, the dominant permeability trends can be mapped well using this model. For the regional transfer and the correlation of the results, a core-related porosity/ permeability log for the reservoir was compiled for a well close to Munich showing similarities to the core investigations. The validation of the regional transferability of the parameter set to other locations in the Molasse Basin was carried out by correlation with the interpreted log data of a well near Munich.

Abstract. Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach.Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunamisafe area. Most endangered areas feature longer estimatedevacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a subnational scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%.The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support.

In the framework of the German Indonesian Tsunami Early Warning System (GITEWS) the assessment of tsunami risk is an essential part of the overall activities. The scientific and technical approach for the tsunami risk assessment has been developed and the results are implemented in the national Indonesian Tsunami Warning Centre and are provided to the national and regional disaster management and spatial planning institutions in Indonesia. <br><br> The paper explains the underlying concepts and applied methods and shows some of the results achieved in the GITEWS project (Rudloff et al., 2009). The tsunami risk assessment has been performed at an overview scale at sub-national level covering the coastal areas of southern Sumatra, Java and Bali and also on a detailed scale in three pilot areas. The results are provided as thematic maps and GIS information layers for the national and regional planning institutions. From the analyses key parameters of tsunami risk are derived, which are integrated and stored in the decision support system of the national Indonesian Early Warning Centre. Moreover, technical descriptions and guidelines were elaborated to explain the developed approach, to allow future updates of the results and the further development of the methodologies, and to enable the local authorities to conduct tsunami risk assessment by using their own resources