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Nowadays, logistics is one of the most important tools in disaster relief operations. The logistic planning is essential and a key component in covering the initial needs in the immediate aftermath of any disaster. Planning is both necessary and practical, as it is generally possible to predict the types of disasters that should affect a given location and the needs that such disasters will be likely to cause. Transport planning, reception and distribution of emergency supplies, type and quantity of the resources, the way of procurement and storage of the supplies, the tools of the tracking and means transportation to the stricken area, the specialization of teams participating in the operation and plan of cooperation between these teams, are some vital life-saving coordination roles after natural disasters are connected directly to logistic planning. Turkey is located in one of the most active earthquake and volcanic regions which causes to many major earthquake-prone, in the world with a majority of the population living in these earthquake-prone areas. Earthquakes are one of the major disasters that require emergency logistic planning strategies due to their devastating effects, the large-scale natural disasters could cause major problem on commodities such as food, medicine etc. In this paper, a game theoretical model for emergency logistic planning is developed. To do this a cooperative game model is constructed from a flow problem which occurred after an earthquake in Istanbul. Several solution concepts for maximizing the transferred commodity are given. The paper ends with a conclusion and outlook to future studies. [ABSTRACT FROM AUTHOR]

This paper describes a rapid response and risk mitigation system Istanbul Natural Gas Distribution Network Seismic Risk Reduction Project (IGRAS) for the Istanbul Natural Gas Network (IGDAŞ). Upon the trigger signal received from the earthquake early warning system in Istanbul, the real-time algorithm at IGRAS system district regulators checks the threshold levels of ground-motion parameters and interrupts the gas flow if any exceedance is detected. Then the system: (1) produces almost real-time earthquake hazard maps by using on-line strong-motion data from the strong-motion network in Istanbul: (2) estimates the distribution of damage to the natural gas network; and (3) transfers these damage distribution maps to stakeholders to enable dispatching rapid response teams to high damage areas. [ABSTRACT FROM AUTHOR]

The disaster experiences of the past resulted in the need for a new international policy. The paper examines the transfer of the international policy for disaster risk reduction (DRR) into a local context, Turkey and Turkish, where new and old perspectives meet. Analyzed is a corpus consisting of two texts, with the purpose of examining the concepts' actual use and contexts shaped by different attitudes, based on the three-dimensional framework of critical discourse analysis, translation studies and conceptual history. The concept transfer from international to the local level inevitably involves translation. The texts included 'new' DRR terms as a result of the concealed translation attempts to adjust the old and contemporary terminologies. Thus, non-functional terms with blurred meanings arose. The awareness that such processes of transfer are complex would help to overcome this kind of simplistic top-down approaches and to give priority to 'communicative labor.' The framework is not presented due to space limitations. It was also observed that the Turkish terminology lacks clear definitions. To affirm this, an in-depth analysis is needed. Terms transferred across contexts may end lacking conceptualizations due to non-functional translation choices. When adopting new social policies, this can be overcome through making effort for communication. This research looks at conceptual struggles related to social issues from a different aspect. The vague terms and inefficiencies in social implementations can be avoided by authorities being aware that discourse, translation and their production are parts of social action. [ABSTRACT FROM AUTHOR]

Given its intense seismic activity and damaging earthquake generation potential, the western part of the North Anatolian Fault constitutes a serious natural hazard. As a result, the fault is monitored with a broad range of seismological and geodetic instrumentation making it a natural laboratory environment for scientific studies. One of the long-term projects in this region is GONAF (Geophysical Borehole Observatory at the North Anatolian Fault) which is the first borehole seismometer network project in Turkey. GONAF is a joint research project that started in 2011 as joint initiative of the Turkish Ministry of Interior, Disaster and Emergency Management Presidency AFAD and GFZ and the German Research Center for Geoscience Helmholtz Center Potsdam. The aim of GONAF is to detect, examine, and monitor the microseismic activity in the region and to observe the physical processes before, during and after a large Marmara earthquake (M > 7.0) that is expected to rupture the western part of the North Anatolian Fault, below the Marmara Sea along the Princes Islands segment or even further to the west. For this purpose, the permanent GONAF observatory was established consisting of 7 borehole seismometer arrays installed down to a depth of 300 m. In this paper, we report on regional stress changes in the western part of the North Anatolian Fault Zone (NAFZ) using instrumental data and the Coulomb stress method. We also present preliminary results of the observation and evaluation of microseismic activity obtained from the GONAF observatory. For the automatic evaluation of real-time data, Seiscomp3, RTQUAKE, and Earthworm Softwares were used. Within the scope of automatic earthquake detection studies, between March, 2016 and November, 2017, a total of 2568 earthquakes were detected using the RTQUAKE software. Of these, 1459 could be analyzed. While the magnitude of the analyzed earthquakes varies between 0.8 and 4.2, the depth of these events ranges from 2 to 30 km. [ABSTRACT FROM AUTHOR]

Revealing the dynamic link between rainfall and runoff, which are the main components of the hydrological cycle, is significant for the planning and managing water resources, disaster risk management, and construction of water structures. This study used feed-forward neural network (FFNN), adaptive neuro-fuzzy inference system (ANFIS), and long short-term memory (LSTM) network to model the rainfall-runoff relationship. Various variations of lagged precipitation, temperature, relative humidity, and flows were presented as inputs, and the flow values of Munzur River were estimated as outputs. During the selection of input parameters, variables with high correlation to flow values were utilized. The model's success was tested using several statistical indicators, including the coefficient of correlation (R), coefficient of determination (R2), and root mean square error (RMSE). When measuring values and model results are compared, FFNN and ANFIS models show accurate predictive results with high accuracy, while LSTM prediction results are not satisfactory. However, it was concluded that the FFNN model with the hyperbolic tangent sigmoid transfer function and Levenberg-Marquardt training algorithm made a slightly more accurate estimation. In addition, it was revealed that the best ANFIS-Sugeno model was obtained with a hybrid learning algorithm, Gaussmf membership function, and eight subsets. As a result of the analysis, it has been found that FFNN is superior to ANFIS in flow prediction. These results provide policymakers and planners with helpful information for developing flood and drought management strategies. [ABSTRACT FROM AUTHOR]

Extreme rainfall has enormous importance in hazard management as well as the design of critical infrastructures for urban and rural areas. Also, complex terrain has a vast influence on spatial and temporal patterns of extreme rainfall. In this study, therefore, many different properties such as spatial similarity (regionalization) and temporal variability (trends and seasonality) of extreme rainfall were quantified over Turkey in which topography heavily influences meteorological parameters in short distances due to orientation and height of mountain chains. Moreover, spatial and temporal extreme rainfall characteristics are poorly quantified and investigated in Turkey. Principal component analyses (PCA) were used in order to reveal the parameters that have influence on rainfall, and three components were observed based on Kaiser Rule. The three PC explain the effect of topography, large-scale weather systems, and seasonality on extreme rainfall. Model-based clustering via retained component scores were used to generate the extreme rainfall regions. Eight different extreme rainfall regions have been obtained with different return periods and growth curves calculated based on regional frequency analysis via generalized extreme values distribution (GEV) distribution based on the goodness-of-fit measure. SWM (Southwest Mediterranean) and HEBS (Humid Eastern Black Sea) are remarkable regions than other extreme rainfall regions in terms of the magnitude of extreme rainfall because of the interaction of topography with tracks of weather systems. The circular statistic shows a strong gradient in terms of extreme rainfall seasonality between the coastal and interior parts of Anatolia. Moreover, positive trends and persistence in extreme rainfall have been detected in all regions as a signal of the increase in natural hazards. In general, orographic barriers and their interaction with large-scale weather systems shape the spatiotemporal variability of extreme rainfall and creating a negative gradient between interior and frontal parts of the Anatolian plateau. [ABSTRACT FROM AUTHOR]

It would be beneficial to consider the results of the long-term evaluation of natural disasters in the decision-making process for disaster damage reduction/prevention. However, disaster evaluation is a complex and time-consuming process depending on different factors such as data type and data period. In this study, a new approach is proposed to determine the risk groups of the provinces in Turkey according to the disaster types (avalanche, landslide, rockfall, and flood) at regional and national scales. Disaster data between 1950 and 2020 were evaluated by considering the number of disasters in the provinces. The obtained data were subjected to cluster analysis, and then, the cluster groups were converted into risk classes. Finally, the risk weight ratios of the provinces and regions were calculated and thematically mapped by integrating them with GIS methods. According to the results, when four disaster types were considered together, Trabzon is the riskiest province on a provincial basis and the Black Sea is the riskiest region on a regional basis in Turkey. Additionally, the results of the study show that cluster analysis offers an effective solution for the evaluation of long-term large datasets. Furthermore, it was found that the new approach, which is used to minimize the errors that may be caused by surface area differences, makes a significant contribution to the evaluation process. This new approach will make a positive contribution to the analysts at the stage of giving priority to disasters and establishing protective and preventive policies on a national and global scale. [ABSTRACT FROM AUTHOR]

Based on morphobathymetric and seismic reflection data, we studied a large landslide body from the eastern Sea of Marmara (NW Turkey), along the main strand of the North Anatolian Fault, one of the most seismically active geological structures on Earth. Due to its location and dimensions, the sliding body may cause tsunamis in case of failure possibly induced by an earthquake. This could affect heavily the coasts of the Sea of Marmara and the densely populated Istanbul Metropolitan area, with its exposed cultural heritage assets. After a geological and geometrical description of the landslide, thanks to high-resolution marine geophysical data, we simulated numerically possible effects of its massive mobilization along a basal displacement surface. Results, within significant uncertainties linked to dimensions and kinematics of the sliding mass, suggest generation of tsunamis exceeding 15–20 m along a broad coastal sector of the eastern Sea of Marmara. Although creeping processes or partial collapse of the landslide body could lower the associated tsunami risk, its detection stresses the need for collecting more marine geological/geophysical data in the region to better constrain hazards and feasibility of specific emergency plans. [ABSTRACT FROM AUTHOR]

In this study, we present a novel methodology that may be used to analyze tsunami risk along coastal regions. The application of the proposed methodology is demonstrated for the Eastern Mediterranean coast. Economic, social and environmental dimensions of risk are calculated and aggregated to obtain the overall risk maps for a number of elements at risk (EaR) that are identified from seven countries located along the Eastern Mediterranean coastline. Historical earthquakes that are recorded in the region during the period 1900–2013 are used as data, and probabilistic tsunami modeling is carried out using Monte Carlo analysis. Based on historical data, randomly generated earthquakes are simulated, and wave propagation analysis is performed using NAMI-DANCE software. Inundation depth–damage analysis and exceedance probabilities of tsunami inundations are used to evaluate social and economic risks while the environmental risk is calculated using a binary approach. The overall risk map is constructed in the geographic information system environment. Cairo Agricultural Area in Egypt and Fethiye City in Turkey are identified as high-risk EaR in the Eastern Mediterranean coastline. The new risk assessment methodology may be utilized in coastal regions of the world, and the results obtained for the Eastern Mediterranean may be effectively used in developing preventive measures and disaster management strategies for tsunamis that may develop the region. [ABSTRACT FROM AUTHOR]

Disaster mitigation as a pre-disaster measure within the scope of disaster risk management is significant in the sense of reducing the adverse effects of earthquakes in the context of earthquake-sensitive risk planning. In the urban planning context, the existence of numerous decision makers and alternatives, which are depending on many criteria, makes decision-making process difficult. This difficulty was overcomed through geographical information systems (GIS). In the context of GIS-based multicriteria decision-making (MCDM) analysis, we used analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine earthquake-risky areas in Yalova City Center. First, AHP analysis related to geological and superstructure/infrastructure criteria was conducted and two separate AHP maps were obtained. Then, we conducted TOPSIS analysis to consider both criteria in the sense of earthquake risk-sensitive planning. Then, overall earthquake risk map obtained which could be used as an input for disaster mitigation processes. [ABSTRACT FROM AUTHOR]

The purpose of this study is to revaluate the changing spatial and temporal trends of precipitation in Turkey. Turkey is located in one of the regions at greatest risk from the potential effects of climate change. Since the 1970s, a decreasing trend in annual precipitation has been observed, in addition to an increasing number of precipitation-related natural hazards such as floods, extreme precipitation, and droughts. An understanding of the temporal and spatial characteristics of precipitation is therefore crucial to hazard management as well as planning and managing water resources, which depend heavily on precipitation. The ordinary kriging method was employed to interpolate precipitation estimates using precipitation records from 228 meteorological stations across the country for the period 1976-2010. A decreasing trend was observed across the Central Anatolian region, except for 1996-2000 which saw an increase in precipitation. However, this same period is identified as the driest year in Eastern and South Eastern Anatolia. The Eastern Black Sea region has the highest precipitation in the country; after 1996, an increase in annual precipitation in this region is observed. An overall reduction is also seen in southwest Turkey, with less variation in precipitation. [ABSTRACT FROM AUTHOR]

This study estimates the relative efficiency of disaster relief organizations that participated in the relief activities following the Marmara and Düzce earthquakes that took place in Turkey in 1999. For this purpose, the activities in the response and relief phases of the disaster management cycle following the 1999 earthquakes are classified into four groups: 'search and rescue,' 'infrastructure rehabilitation and debris removal,' 'health care' and 'providing basic needs to the disaster victims.' Next, the unbounded data envelopment analysis (DEA) model is applied to estimate the efficiency scores and optimal input/output weights of the decision-making units (DMUs) in these groups. The efficient and inefficient units are then determined, and the target input and output values are determined for the inefficient units. However, some inputs and outputs are found to be zero or are outlier values in the unbounded model results. To eliminate this deficiency, the bounded model is applied by including additional constraints in the unbounded model. After determining a solution with this model, the optimal input/output weights, the efficiency scores of the DMUs and the efficient and inefficient units are determined. The results of the bounded version of the DEA are more accurate than those of the unbounded model. More accurate and reliable results are obtained from the unbounded model because zero and outlier values are eliminated. [ABSTRACT FROM AUTHOR]