Natural disaster diversity assessment of Bitlis province

Bitlis ili hem jeomorfolojik yapısından hem de iklimsel özelliklerinden dolayı doğal afet türlerinin sıklıkla yaşandığı bir coğrafyada bulunmaktadır. Ancak, bu coğrafyada günümüze kadar gerekli düzeyde afet çeşitliliği envanteri çalışmaları ve buna bağlı olarak risk olasılığı analizleri gerçekleştirilmemiştir. Bu çalışmada bir ilk olarak Bitlis ili sınırları içinde meydana gelmiş heyelan, çığ düşmesi, kaya düşmesi ve sel gibi çeşitli doğal afetlerin zamansal ve mekânsal analizi yapılmıştır. Doğal afetlerin meydana gelmesiyle oluşan zararlar da göz önüne alınarak risk değerleri hesaplanmış ve buna bağlı olarak risk sınıflandırması yapılmıştır. Risk analizleri yapabilmek amacıyla olasılık, şiddet ve frekans parametrelerinin kullanıldığı yöntemlerden biri olan Fine-Kinney yönteminden yararlanılmıştır. İş sağlığı güvenliği çalışmalarında sıklıkla kullanılan yöntem, doğal afetler risk analizleri için ilk defa bu çalışmayla uygulanmış ve bu nedenle çalışmanın amacına uygun olabilecek yeni bir ölçek oluşturmuş ve hesaplamalar yapılmıştır. Heyelan, kaya düşmesi ve çığ olaylarının eğimli topografyalara sahip aynı zamanda da bol yağış alan yerleşim alanlarında günlük hayatı tehdit edecek seviyede olduğu belirlenmiştir. Ülkemizde çığ düşmesi olayından zarar görebilmeye en meyilli il olan Bitlis için olası bir afet anında uygulanabilecek acil durum eylemlerinin gerçekleştirilmesi önerilmektedir. Ayrıca, kaya düşmesi olaylarının yaşanma riskinin yüksek olduğu güney ilçelerde can ve mal kaybını önlemek amacıyla gerekli tedbirlerin acilen alınması gerekmektedir. Diğer taraftan, sel olayların ise ciddi bir tehlike arz etmediği belirlenmiştir.Bitlis province is located on a geography where natural disasters occur frequently due both to their geomorphologic structure and climatic features. However, necessary studies for disaster diversity inventory and consequently risk probability analyses have not been performed so far. In this study, temporal and spatial analyses of various natural disasters such as landslides, avalanches, rockfalls and floods occurred in Bitlis province were performed. Considering the damages resulted from the natural disaster occurrences, risk scores were calculated for the classifications. In order to perform risk analyses, the Fine-Kinney method, which is a method that uses the parameters of probability, severity and frequency, was employed. In this study, the method which is frequently used in occupational health safety studies was applied to risk analyses of natural disasters for the first time and therefore a new scale compatible with the aim of the study was determined and computations were made accordingly. It was decided that landslide, rockfall and avalanche events threaten the daily life in the districts which have sloped topographies and generally get heavy rainfall. Emergency actions that can be applied in case of a possible avalanche disaster are strongly recommended for Bitlis province that is most prone to be damaged by avalanche events. In addition, necessary precautions should be taken immediately to prevent the loss of life and property in the south districts, where the risk of rockfall events is high. On the other hand, it was determined that flooding events do not pose a serious danger

Parameter estimations from gravity and magnetic anomalies due to deep-seated faults: differential evolution versus particle swarm optimization

Estimation of causative source parameters is an essential tool in exploration geophysics and is frequently applied using potential field datasets. Naturally inspired metaheuristic optimization algorithms based on some stochastic procedures have attracted more attention during the last decade due to their capability in finding the optimal solution of the model parameters from the parameter space via direct search routines. In this study, the solutions obtained through differential evolution algorithm, a rarely used metaheuristic algorithm in geophysics, and particle swarm optimization, which is one of the most used global optimization algorithms in geophysics, have been compared in terms of robustness, consistency, computational cost, and convergence rate for the first time. Applications have been performed using both synthetic and real gravity and magnetic anomalies due to deep-seated fault structures. Before the parameter estimation studies, resolvability of the fault parameters have been examined by producing cost function/error energy topography maps to understand the suitability of the problem and also the mathematical nature of the inversion procedure. Optimum control parameters of both algorithms have also been determined via some parameter tuning studies performed on synthetic anomalies. Consequently, the tuned parameters clearly improved the effectiveness of both metaheuristics on the solution of the optimization problems under consideration. Moreover, reliabilities of the obtained solutions and also the possible uncertainties have been investigated using probability density function analyses. Real data applications have been performed using a residual gravity anomaly observed over the Graber oil field (Oklahoma, USA) and an airborne total field magnetic anomaly observed over the Perth Basin (Australia). Applications have shown that although both algorithms provided close results in both synthetic and real data experiments, the differential evolution algorithm yielded slightly better solutions in terms of robustness, consistency, computational cost, and convergence rate. Thus, the differential evolution algorithm is worth paying more attention to and is suggested as a powerful alternative to particle swarm optimization for the inversion of potential field anomalies

Backtracking Search Optimization: A Novel Global Optimization Algorithm for the Inversion of Gravity Anomalies

In this paper, an implementation of Backtracking search optimization (BSA), a non-gradient iterative evolutionary algorithm, is presented for model parameter estimation applications using gravity anomalies. This is the first study to use this promising bio-inspired and population-based global optimization algorithm to invert geophysical data sets. We concentrated on demonstrating the efficiency and robustness of the proposed algorithm using some gravity anomalies originated from anticlinal and synclinal structures. Anomaly equations of these geological structures are based on planar approximation. We restricted our study to relatively simple profile data sets. The nature of the inverse problem was assessed by producing cost function topography image maps for the model parameters. The resolvability characteristics and unanticipated possible dependencies between the model parameter pairs were determined using these low misfit region maps. Parameter tuning studies enabled us to determine optimum values for the algorithm-based control parameters of the BSA, and to get the best efficiency from the algorithm. Some synthetic anomalies and two field gravity data sets observed over the Pays De Bray anticline system (France) were successfully inverted through BSA algorithm. In addition, a Markov Chain Monte Carlo method performing Metropolis-Hastings sampler revealed that all solutions obtained are within the confidence intervals without uncertainties. This study shows that the BSA algorithm can be an alternative inversion tool to the most widely applied global optimizers for geophysical anomalies, such as other evolutionary-based algorithms and particle swarm optimization. Additionally, BSA can be used for more complex multi-dimensional geophysical problems having formidable anomaly equations

Seismic and Structural Analyses of the Eastern Anatolian Region (Turkey) Using Different Probabilities of Exceedance

Seismic hazard analysis of the earthquake-prone Eastern Anatolian Region (Turkey) has become more important due to its growing strategic importance as a global energy corridor. Most of the cities in that region have experienced the loss of life and property due to significant earthquakes. Thus, in this study, we attempted to estimate the seismic hazard in that region. Seismic moment variations were obtained using different types of earthquake magnitudes such as Mw, Ms, and Mb. The earthquake parameters were also determined for all provincial centers using the earthquake ground motion levels with some probabilities of exceedance. The spectral acceleration coefficients were compared based on the current and previous seismic design codes of the country. Additionally, structural analyses were performed using different earthquake ground motion levels for the Bingöl province, which has the highest peak ground acceleration values for a sample reinforced concrete building. The highest seismic moment variations were found between the Van and Hakkari provinces. The findings also showed that the peak ground acceleration values varied between 0.2–0.7 g for earthquakes, with a repetition period of 475 years. A comparison of the probabilistic seismic hazard curves of the Bingöl province with the well-known attenuation relationships showed that the current seismic design code indicates a higher earthquake risk than most of the others

Gravity data inversion for the basement relief delineation through global optimization: a case study from the Aegean Graben System, western Anatolia, Turkey

Aegean Graben System is a significant member of the complex geology of western Turkey. The depths to the metamorphic basement reliefs in two major grabens have been reported by many geophysical studies. However, the sediment thicknesses of these graben basins still remain controversial due to the findings differing from each other. Thus, we have inverted the gravity data of the sedimentary cover-metamorphic basement using a stochastic derivative-free vector-based metaheuristic named differential evolution algorithm (DEA). This is the first application of DEA adapted to the basement relief depth problem. Model parametrizations have been achieved by discretizing the basins using a group of juxtaposed vertical blocks. Before the inversion studies, mathematical nature of the inverse problem has been investigated via prediction cost function/error energy maps for some block pairs using a hypothetical basin model. These maps have shown the resolvability characteristic of the block thicknesses on such inversion problem. Parameter tuning studies for the optimum mutation constant/weighting factor have been performed to increase the efficiency of the algorithm. The synthetic data have been successfully inverted via the tuned control parameter and some smoothing operators. Probability density function (PDF) analyses have shown that the best solutions are within the confidence interval limits without uncertainties. In the field data case, long-wavelength anomalies caused by both crustal and deeper effects have been removed from the complete Bouguer anomalies through 2-D finite element method using the element shape functions. Some profiles extracted from the residual gravity anomaly map have been used for the inversion and obtained results have shown that the maximum depths to the metamorphic basement reliefs in the grabens are shallower than the findings of the previous studies. Information obtained from the lithological logs drilled in the grabens has supported our results. Moreover, PDF analyses have indicated the reliability of the obtained solutions without uncertainties