Istanbul Earthquake Research Articles

Determination of individual disaster resilience levels of hospital staff: A case study of Kartal Dr. Lütfi Kirdar City Hospital

Istanbul is one of Turkey's most important financial and industrial centers, and it is located in a region with a high potential for seismicity. Due to its historical architecture and high level of urbanization, the city has a large population and is particularly vulnerable due to the building stock that will be affected by earthquakes. In the event of a possible earthquake in Istanbul, it is crucial that the hospital staff have high levels of disaster resilience/resilience. This is particularly important given the seismically isolated and earthquake-resistant structure of Istanbul Kartal Dr. Lütfi Kırdar City Hospital and its capacity to serve those injured by the earthquake. This study examines the resilience levels of hospital staff at Kartal Dr. Lütfi Kırdar City Hospital in the face of earthquake disasters and the various factors that affect these resilience levels. The data for this study were collected using a 13-question personal information form and the ‘Individual Disaster Resilience Assessment (IDRA)’ scale developed by DiTirro (2018). Descriptive statistics, Pearson Chi-square tests, Independent Samples T-tests, and One-Way ANOVA were used to analyze the data. The research found that the hospital staff's IDRA scores averaged 3.27. It was concluded that the mean resilience score of the participants was above the medium level. The research findings show that receiving disaster training or being prepared for disasters in advance significantly influences individual resistance/resilience. In this context, it is essential to determine the earthquake resistance levels of all healthcare workers in Istanbul, especially those at the city hospital where the study was conducted. Necessary training should be provided, and simulation-based disaster drills should be planned and integrated into in-service training programs. Additionally, projects should be developed to ensure that healthcare workers can reach their hospitals safely during disaster situations.

Evaluation of Qualifications of Emergency Assembly Areas in Istanbul using the Spherical Fuzzy MAIRCA Process

Disasters are inevitable facts of life. It is difficult to deal with disasters and emergencies because of the uncertainties they contain. Managing disasters and emergencies requires integrity with before and after processes. No matter how well-informed people may be when faced with a disaster, they may not act consciously due to the shock of the event, fear and anxiety. Therefore, the recovery phase after a disaster is very important. In the presented paper, meeting areas after a disaster for Istanbul, which is one of the closest witnesses of the earthquake reality, were examined. The motivation of the paper is to evaluate the assembly areas in Istanbul on the basis of all districts under expert opinions and to compare and rank the suitability of the currently existing emergency assembly areas for the expected major Istanbul earthquake. This ranking was made by the help of the fuzzy logic integration of the Multi Attributive Ideal Real Comparative Analysis (MAIRCA) method, which is one of the Multi-Criteria Decision-Making Techniques (MCDM). It is thought that this ranking will be useful in revealing the current situation of the districts and raising awareness. As far as is known, according to the results obtained from the paper in which the spherical fuzzy logic integrated MAIRCA technique was used for the first time, Kadıköy district was determined as the district with the best conditions assembly areas.

A Brief Review of Vulnerability, Preparedness and Resilience Measures of Anticipated Istanbul Earthquake

This review examines the seismic vulnerability of Istanbul, a city uniquely positioned at the crossroads of Asia and Europe and exposed to significant earthquake risks due to the North Anatolian Fault (NAF). By synthesizing data on historical seismic events, urban development patterns, and current building and infrastructure resilience, the paper highlights the complexities of disaster management in a densely populated and rapidly growing metropolis. It critically evaluates the effectiveness of existing preparedness and mitigation strategies, including legislative frameworks, urban planning policies, and community-based resilience efforts. The review also identifies gaps in the current approach to earthquake risk reduction and suggests areas for improvement, emphasizing the need for an integrated, multi-sectoral approach to enhance the city's capacity to withstand and recover from future seismic events. The findings underscore the importance of proactive planning and the adoption of innovative technologies in building a resilient Istanbul.

Strategic Planning for Post-Earthquake Health Services Continuity: Leveraging Family Healthcare Centers in Istanbul

Abstract Earthquakes, known for their widespread devastation, annually inflict catastrophic consequences globally. Swift and well-structured healthcare responses following earthquakes are pivotal in reducing their impact and mitigating loss of life. However, achieving this demands proactive strategic planning and effective preparedness before disaster strikes. While countries craft disaster response plans, their implementation often proves inadequate in managing the ensuing crisis comprehensively. This study proposes a paradigm shift by advocating for the utilization of widely accessible Family Health Centers (FHCs) as crucial hubs for post-earthquake healthcare continuity. Focused on these community-centric health units, our research delineates a strategic blueprint ensuring uninterrupted health services post an Istanbul earthquake. Integrating SWOT analysis, balanced scorecard, and operations research, this study holistically assesses the current landscape of FHCs and identifies imperative post-earthquake requisites. Insights gleaned from extensive literature review and expert consultations underpin this multifaceted approach.

Hazardous Solid Waste Landfill Site Selection for İstanbul, Türkiye using Multi-Criteria Decision-Making Methods and GIS Data

The high toxicity of materials in disaster waste poses a significant risk to the environment, including the air, water, soil, and all living beings. One of the commonly used disposal methods for hazardous solid waste is landfilling. The selection of sites for hazardous solid waste disposal requires extreme care and attention to multiple factors from environmental, social, and economic points of view. Considering the anticipated earthquake in Istanbul and the city’s excessive population and urbanization, experts estimate that debris waste will be approximately 25 million tons. In this study, we propose a Geographic Information System (GIS) based fuzzy Multi-Criteria Decision Making (MCDM) approach to select hazardous solid waste landfill (HSWL) locations within the scope of disaster waste management for Istanbul. First, the evaluation criteria were identified through a literature review and expert opinions. Next, criteria are prioritized using the Fuzzy Analytic Hierarchy Process (FAHP). Then, GIS data for the criteria are gathered from multiple resources and entered into ArcGIS 10.8 for spatial analysis. Last, the suitability map of Istanbul for the HSWL construction is built. Considering five candidates, the Analytic Hierarchy Process (AHP) is applied to select the most suitable locations for Asian and European sites in the city. Accordingly, Fevzipaşa/Silivri for the European side and Hasanlı/Şile for the Asian side were selected as the most suitable two options. Last, a sensitivity analysis was performed to investigate the impact of the highest weight criterion on the final solution.

Remembering a disastrous past to imagine catastrophic future(s) on social media: The expected Istanbul earthquake

This article explores how collective memory of the 1999 Marmara earthquake frames collective thinking of “the expected Istanbul earthquake” through numerous catastrophic earthquake scenarios posted on the prominent Turkish social media platform called Ekşi Sözlük for nearly two decades. The article first integrates memory, media, and disaster studies to theorize how a looming catastrophe is (re)imagined in retrospect. It then analyzes earthquake scenarios using representative samples to illustrate how the oscillatory dynamics and acts of disaster memory shape the future thinking of a not-yet-come threat within a Turkish social media ecology.

A predictive multistage postdisaster damage assessment framework for drone routing

AbstractThis study focuses on postdisaster damage assessment operations supported by a set of drones. We propose a multistage framework, consisting of two phases applied iteratively to rapidly gather damage information within an assessment period. In the initial phase, the problem involves determining areas to be scanned by each drone and the optimal sequence for visiting these selected areas. We have adapted an electric vehicle routing formulation and devised a variable neighborhood descent heuristic for this phase. In the second phase, information collected from the scanned areas is employed to predict the damage status of the unscanned areas. We have introduced a novel, fast, and easily implementable imputation policy for this purpose. To evaluate the performance of our approach in real‐life disasters, we develop a case study for the expected 7.5 magnitude earthquake in Istanbul, Turkey. Our numerical study demonstrates a significant improvement in response time and priority‐based metrics.

Value of sorting and recovery in post-disaster relief aid distribution

In-kind donations gathered from the public after a disaster typically consist of an unknown and disorganized composition of both “useful” and “useless” items. Sending the donations directly to the affected people without any pre-processing leads to not only extra shipment and handling costs but also congestion in the disaster areas, and even chaos in local distribution. Motivated by this fact, we investigate the effect of relief aid sorting and subsequent recovery of items that do not fulfill immediate needs under demand, donation quantity, and donation type uncertainties. To this end, we propose a supply network configuration with sorting centers for pre-processing and optimize it by a three-stage stochastic programming model. We compare the case of the sorted donations with the case where donations are directly sent to points of distribution to victims. We apply the proposed model to the Istanbul earthquake case under different parameter settings and derive various managerial insights. We observe that sorting the donated relief aid items and sending only the useful ones to disaster victims may decrease the expected total cost, in addition to some intangible benefits, but at the same time may increase the expected time of the deliveries. However, it is possible to cope with this response time deterioration by increasing the workforce level at the sorting centers with an acceptable additional cost.

Evaluation of the Warehouse Location Alternatives for Possible Great Istanbul Earthquake

The "Great Istanbul Earthquake" is expected to occur in Istanbul within the next 10 years. Preparations have long been made for the great Istanbul earthquake, which is expected to cause heavy loss of life and property. One of the important parts of earthquake preparedness is the disaster logistics warehouses, where emergency supplies and shelter equipment are stored to be dispatched to earthquake victims. The aim of this study is determining the optimal locations of the warehouses in order to deliver the aid materials to the points of need as soon as possible and to meet the needs in the event of a possible large earthquake in Istanbul. The model was set up in two steps to determine the number of warehouses to be opened with the set covering problem in the first step, and to minimize the weighted distance with p-median in the second step. The established model was solved using The General Algebraic Modeling System (GAMS), and the optimum scenario was decided according to the results and the scenarios were mapped.

Earthquake, disaster capitalism and massive urban transformation in Istanbul

AbstractIn this paper, I discuss how the earthquake risk is exploited by ‘disaster capitalism’, in order to convert Istanbul to a massive construction site. The shock of the 1999 Marmara Earthquake has been effectively used by the neoliberal market and government as ‘a shock therapy’ to implement a construction‐led development model for Turkey and to favour the construction sector by introducing new incentives, exceptional rights and interventions, which otherwise might be challenged. The current Turkish government justify the ongoing massive urban transformation and new mass housing projects as an improvement of the housing stock to make residential buildings stronger and more resilient to earthquakes. However, areas actually under earthquake risk do not match the areas that are officially declared under disaster risk by the government. The Disaster Law #6306 that granted the government the absolute right to expropriate land based on the justification of ‘protecting residents against earthquakes and other natural disasters’ was applied in a selective way to seize valuable land in Istanbul. In the paper I explore how the disaster was quickly converted to an opportunity for economic growth. To do that I introduce stories of three different neighbourhoods in Istanbul, namely Moda, Tozkoparan and Fikirtepe, each of which experience the ongoing massive urban transformation differently based on the land value of the neighbourhoods, class position of the residents, and residents' capacity to organise in order to protect their rights. I describe, how disaster capitalism is lived and experienced differently in these three neighbourhoods. Although the massive construction projects are indifferent to life's sustainability, those projects are justified as interventions in terms of public health and safety through making housing resilient to earthquakes. I critically discuss how in each case biopolitics presents disaster capitalism's massive urban transformation projects as a manifestation of liveliness.

The Development of a Holistic and Inclusive Model for Disaster Priority Regeneration Area (DPRA): The Case of Istanbul, Turkey

Urban regeneration can be defined as a multi-functional, specifical zoning application for the improvement and sustainability of an urban area with its physical, environmental, social and economic conditions. The question of where the urban regeneration will take place constitutes the primary pillar of the applications. Considering the expected high-intensity earthquake in Istanbul, there is a significant number of risky regions in the earthquake zone that need to be regenerated. The important part of reducing damage in an earthquake disaster is improving the quality of the building stock. The identification, prioritization, analysis and visualization of disaster priority regeneration areas (DPRAs) is possible by creating a functional model based on a spatial basis. The main element in the scope of this study is to establish the processes related to the DPRAs and to determine the necessary criteria for the determination of these areas. Analyzing how much the existing DPRAs overlap with the areas suggested in this study and creating basis for the needed model in order to identify the undeclared areas, the destruction and losses that may be caused by the earthquake in the coming years can be prevented by the implementation of this sustainable and integrated urban regeneration model.

Prioritization of Districts in terms of Disaster Preparedness Planning: A Case Study for the Expected Istanbul Earthquake

Preparedness is the second among the four phases of disaster management after mitigation. In big cities with a crowded population like İstanbul, development of a single holistic disaster preparedness plan would be too complex. At this point, prioritization of districts is needed because of the existence of limited amount of available resources (time, staff, money, etc.) plan development stage. This decision can be affected by several factors, so this decision can be defined as a multiple criteria decision-making problem. The main aim in this paper is to develop an analytic approach to obtain the priority rank of districts of the city for disaster preparedness plan development. To do so, a hybrid multiple criteria decision-making model based on SWARA (Stepwise Weight Assessment Ratio Analysis) and WASPAS (Weight Aggregated Sum Product Assessment) is proposed. A case study on earthquake preparedness planning in districts of İstanbul is presented to demonstrate the applicability of the proposed model. Obtained results of the model would be helpful for policy making in volunteer organizations, municipality, and government level.

Seismological and engineering characteristics of strong motion data from 24 and 26 September 2019 Marmara Sea earthquakes

An MW 4.5 earthquake took place on September 24, 2019 in the Marmara Sea. Two days after, on September 26, 2019, Marmara region was rattled by an MW5.7 earthquake. With the intention of compiling an ample strong ground motion data set of recordings, we have utilized the stations of Istanbul Earthquake Rapid Response and Early Warning System operated by the Department of Earthquake Engineering of Boğaziçi University and of the National Strong Motion Network operated by AFAD. Altogether 438 individual records are used to calculate the source parameters of events; namely, corner frequency, radius, rupture area, average source dislocation, source duration and stress drop. Some of these parameters are compared with empirical relationships and discussed extensively. Duration characteristics are analysed in two steps; first, by making use of the time difference between P-wave and S-wave onsets and then, by considering S-wave durations and significant durations. It is observed that they yield similar trends with global models. PGA, PGV and SA values are compared with three commonly used ground motion prediction models. At distances closer than about 60 km, observed intensity measures mostly conform with the GMPE predictions. Beyond 60 km, their attenuation is clearly faster than those of GMPEs. A frequency-dependent Q model is developed by using both events. Its consistency with existing regional models is confirmed.

Intermodal transportation in humanitarian logistics with an application to a Turkish network using retrospective analysis

In the event of disruptions in a transportation network following a disaster, humanitarian organizations find it challenging to provide basic requirements for beneficiaries. Demand may be met using intermodal transportation as an alternative when the unimodal transportation infrastructure is damaged. This study proposes a mathematical model for utilizing intermodal transportation using 40 ft standard containers while delivering relief supplies by road, rail, and sea modes. The proposed model is a capacitated multi-period multicommodity intermodal network flow model in which relief supplies are delivered to beneficiaries in three echelons (i.e., supply, intermodal hub, and demand). The Turkish Disaster and Emergency Management Presidency's container warehouses (i.e., supply), logistics centers and container ports (i.e., intermodal hubs) are utilized to test the mathematical model with real-life demand parameters. Retrospective analysis was performed to determine the most frequently used container warehouses, logistics centers, and origin-destination pairs. Hence, an increase in operational capacity and infrastructure reinforcement is recommended to mitigate the effects of future disasters. We found that intermodal transportation is more robust to network disruptions in rapidly delivering relief supplies. We observed that intermodal transportation is utilized in disasters with more than 50,000 beneficiaries or disrupted unimodal infrastructure. For instance, after the future Istanbul earthquake, it would be impossible to deliver the relief materials only by road transportation within the urgent response period. Thus, the benefits of intermodal transportation in humanitarian logistics are more visible in large-scale disasters in which transportation resources are scarce, and transportation infrastructure is more likely to be destroyed.

Simulation analysis of critical factors of casualty transportation for disaster response: a case study of Istanbul earthquake

PurposeThe purpose of this paper is to statistically assess the effects of the design factors including usage of data-driven decision support tool (DST), classification of patients (triage), prioritization based on vital scores of patients, number of ambulances and hospital selection rules, on the casualty transportation system’s performance in large-scale disasters. Besides, a data-driven DST for casualty transportation is proposed to enhance the casualty survival and ambulance transportation times during the disaster response stage.Design/methodology/approachIn this study, the authors applied simulation and statistical analysis to evaluate the effects of usage of data-driven DST, classification of patients (triage), prioritization of the patients based on vital scores, number of ambulances and hospital selection rules, on the patient survival and transportation time of the casualty transportation system. An experimental design was made, and 16 scenarios were formulated. Simulation models were developed for all scenarios. The number of unrecoverable casualties and time-spent by the casualties until arriving at the hospital was observed. Then, a statistical analysis was applied to the simulation results, and significant factors were determined.FindingsUtilization of the proposed DST was found to improve the casualty transportation and coordination performance. All main effects of the design factors were found statistically significant for the number of unrecoverable casualties. Besides, for the Time spent Until Arrival of T1-Type Casualty at the Hospital, all of the main factors are significant except the number of ambulances. Respiratory rate, pulse rate, motor response score priority and hospital selection rule based on available hospital capacities must be considered to reduce the number of unrecoverable casualties and time spent until arrival of the casualties at the hospitals.Originality/valueIn this study, the factors that significantly affect the performance of the casualty transportation system were revealed, by simulation and statistical analysis, based on an expected earthquake case, in a metropolitan city. Besides, it was shown that using a data-driven DST that tracks victims and intends to support disaster coordination centers and medical staff performing casualty transportation significantly improves survival rate of the victims and time to deliver the casualties. This research considers the whole systems’ components, contributes to developing the response stage operations by filling gaps between using the data-driven DST and casualty transportation processes.

Earth in practice: Uncertainty, expertise and the expected Istanbul earthquake

In 1999, two devastating earthquakes occurred in Northwestern Turkey, which claimed around 18,000 lives. Since the disaster, many scientific studies and projects, both international and national, have been conducted, concluding that another earthquake at the magnitude of at least six will hit Istanbul. Even though there is a consensus among scientists that an earthquake will happen in Istanbul, there is a plethora of different theories and arguments about the anticipated earthquake. This paper is an historical account of how different technoscientific practices have enacted different North Anatolian Faults stretching across Anatolia and Marmara Sea. The multiplicity of the fault does not emerge as an epistemic problem of having different perspectives, but it is an ontological question of how plural realities are being made in different scientific practices. We argue that scientific uncertainties emerge when these different faults do not fit together in technoscientific circles and across public venues.

A game theoretical approach to emergency logistics planning in natural disasters

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.

Blood supply planning during natural disasters under uncertainty: a novel bi-objective model and an application for red crescent

In natural disasters, having a capable network of collecting and distributing crucial items such as blood is one of the major concerns. However, due to damage to the infrastructure after disasters, mobile blood collecting facilities (blood mobiles) are usually required. This paper aims to decide the locations of mobile facilities in each period for collecting donated blood, plan the blood distribution from the fixed and mobile facilities to the main blood centers, as well as from blood centers to the hospitals and field-hospitals, under uncertain conditions. To do so, a multi-period, bi-objective mixed-integer mathematical model is developed under a multiple-scenario, aiming to minimize the unsatisfied blood demand as well as the total cost of the network. In the proposed model, the blood group compatibility matrix, failure rate of the facilities, and patients’ urgency levels are considered. An augmented e-constraint method is applied to solve this bi-objective model. Due to the complex nature of the proposed blood supply chain model, the Lagrangian relaxation approach is used to solve the proposed model. An expected Istanbul earthquake is considered, and the blood supply planning through the Red Crescent’s European branch is performed utilizing the proposed model to examine its validity. According to the numerical results, the mobile facilities' locations in each period under each scenario are determined, the unsatisfied demand in each hospital and field-hospital for each blood type are reported, and the tradeoff between the supply chain costs and unsatisfied demand are discussed in detail. Finally, to illustrate the robustness of the proposed model, a detailed sensitivity analysis is performed. According to the study results, opening new blood centers near the high-demand sub-districts for faster testing and supply, increasing the hospitals' capacities, and usage of drones and helicopters for blood distribution are suggested can be considered as managerial insights.

Evolution of the Kandilli Observatory and Earthquake Research Institute (KOERI) Seismic Network and the Data Center Facilities as a Primary Node of EIDA

AbstractAs the earliest institute in Turkey dedicated to locating, recording, and archiving earthquakes in the region, the Kandilli Observatory and Earthquake Research Institute (KOERI) has a long history in seismic observation, which dates back to the installation of its first seismometers soon after the devastating Istanbul earthquake of 10 July 1894. For over a century, since the deployment of its first seismometer, the KOERI seismic network has grown steadily in time. In this article, we present the KOERI seismic network facilities as a data center for the seismological community, providing data and services through the European Integrated Data Archive (EIDA) and the Rapid Raw Strong-Motion (RRSM) database, both integrated in the Observatories and Research Facilities for European Seismology (ORFEUS). The objective of this article is to provide an overview of the KOERI seismic services within ORFEUS and to introduce some of the procedures that allow to check the health of the seismic network and the quality of the data recorded at KOERI seismic stations, which are shared through EIDA and RRSM.

The optimization of UAV routing problem with a genetic algorithm to observe the damages of possible Istanbul earthquake

In this study, the problem is to find a route for a UAV that takes off from Istanbul to observe the damages that may occur after the possible Istanbul earthquake within the first 24 hours. In the problem, 230 candidate grid points that UAV can visit on Istanbul are determined and the weight values combining the risk values based on earthquake degree zones and the population densities of the grid points are calculated for each candidate point. It is aimed to find a route for the UAV to maximize the total weights of the visited grid points under the UAV range constraint. The described problem is adapted to the Orienteering Problem in the literature. Since the Orienteering Problem is an NP-hard problem, a problem-specific genetic algorithm and a simulated annealing algorithm are developed to solve the problem. The parameters of the algorithms are tuned by experiments. 15 different scenarios including the daily number of visits (of taken images) and the airports that the UAV takes and lands off after the earthquake are created and tried to be solved exactly via ILOG and approximately via developed metaheuristics. While the optimal solutions are found for 2 of 15 scenarios via ILOG, the designed genetic algorithm has better solutions and can solve the problem within acceptable CPU times for the rest of the scenarios.