This thesis aims to predict the probable undiscovered geothermal systems through investigation of spatial relation between geothermal occurrences and its surrounding geological phenomenon in Western Anatolia. In this context, four different public data, which are epicenter map, lineament map, Bouger gravity anomaly and magnetic anomaly maps, are utilized. In order to extract the necessary information for each map layer the raw public data is converted to a synthetic data which are directly used in the analysis. Synthetic data employed during the investigation process include Gutenberg-Richter b-value map, distance to lineaments map and distance to major grabens present in the area. Thus, these three layers including directly used magnetic anomaly maps are combined by means of Boolean logic model and Weights of Evidence method (WofE), which are multicriteria decision methods, in a Geographical Information System (GIS) environment. Boolean logic model is based on the simple logic of Boolean operators, while the WofE model depends on the Bayesian probability. Both of the methods use binary maps for their analysis. Thus, the binary map classification is the key point of the analysis. In this study three different binary map classification techniques are applied and thus three output maps were obtained for each of the method. The all resultant maps are evaluated within and among the methods by means of success indices. The findings reveal that the WofE method is better predictor than the Boolean logic model and that the third binarization approach, which is named as optimization procedure in this study, is the best estimator of binary classes due to obtained success indices. Finally, three output maps of each method are combined and the favorable areas in terms of geothermal potential are produced. According to the final maps the potential sites appear to be Aydin, Denizli and Manisa, of which first two have been greatly explored and exploited since today and thus not surprisingly found as potential in the output maps, while Manisa when compared to first two is nearly virgin.

The research attempts to resolve which method of estimation is the most consistent for the parameters of the earthquake model, and how these different methods of estimation, as well as other changes, in the earthquake model parameters affect the damage estimates for a specific area. The research also investigates different methods of parameter estimation in the context of the log-linear relationship characterised by the Gutenberg-Richter relation. Traditional methods are compared to those methods that take uncertainty in the underlying data into account. Alternative methods based on Bayesian statistics are investigated briefly. The efficiency of the feasible methods is investigated by comparing the results for a large number of synthetic earthquake catalogues for which the parameters are known and errors have been incorporated into each observation. In the second part of the study, the effects of changes in key parameters of the earthquake model on damage estimates are investigated. This includes an investigation of the different methods of estimation and their effect on the damage estimates. It is found that parameter estimates are affected by observation errors. If errors are not included in the method of estimation, the estimate is subject to bias. The nature of the errors determines the level of bias. It is concluded that uncertainty in the data used in earthquake parameter estimates is largely a function of the quality of the data that is available. The inaccuracy of parameter estimates depends on the nature of the errors that are present in the data. In turn, the nature of the errors in an earthquake catalogue depends on the method of compilation of the catalogue and can vary from being negligible, for single source catalogues for an area with a sophisticated seismograph network, to fairly impactful, for historical earthquake catalogues that predate seismograph networks. Probabilistic seismic risk assessment is used as a catastrophe modelling tool to circumvent the problem of scarce loss data in areas of low seismicity and is applied in this study for the greater Cape Town region in South Africa. The results of the risk assessment demonstrate that seemingly small changes in underlying earthquake parameters as a result of the incorporation of errors can lead to significant changes in loss estimates for buildings in an area of low seismicity. / Dissertation (MSc)--University of Pretoria, 2014. / Insurance and Actuarial Science / MSc / Unrestricted