Complex Network Theory and Earthquake Resistance

The communication infrastructures that form the foundation of modern societies can exhibit significant vulnerabilities in the face of natural disasters, particularly destructive events such as earthquakes. This vulnerability not only disrupts economic and social activities but also severely hampers disaster response and humanitarian aid efforts. The earthquakes centered in Kahramanmaraş on 6 February 2023 in southern Türkiye presented a tragic example of this vulnerability through widespread and prolonged outages in GSM (Global System for Mobile Communications) networks. In contrast, the relatively better performance of internet infrastructure in some areas highlights the fundamental structural differences between these two primary communication systems and underscores the resilience properties of the internet. This article aims to provide a theoretical depth in network science to understand the resilience of communication infrastructure against earthquakes.

Communication infrastructures are highly complex systems composed of numerous interacting components. Network science and complex systems theory offer advanced analytical frameworks and modeling techniques to understand how these systems behave under shocks such as earthquakes and to enhance their resilience.

Network science is an interdisciplinary field that studies the structure, dynamics, evolution, and functionality of complex networks using quantitative methods. Communication infrastructures can be abstracted as complex networks consisting of nodes (base stations, routers, data centers) and links connecting them (radio connections, fiber optic cables).

• Advanced Topological Analysis: In addition to basic topological properties (degree distribution, clustering coefficient, average path length, centrality measures), spectral analysis (eigenvalue distributions) and node/edge criticality analyses can be applied to gain deeper insights into network connectivity and resistance to failures. For instance, nodes with high centrality measures (betweenness centrality, eigenvector centrality) may be identified as having disproportionate impact on network functionality if lost. The high centrality of core control units in Türkiye’s GSM networks may indicate such a vulnerability.

• Modeling and Analysis of Interdependent Networks: Multiple and layered dependencies between different infrastructure systems (communication, energy, transportation) can be modeled within the framework of interdependent networks to examine the propagation dynamics of cascading failures. In the Türkiye case, the strong dependency of communication networks on the energy infrastructure can be modeled as the primary cause of sequential communication disruptions following power outages after the earthquake. These models enable quantitative evaluation of the effectiveness of different dependency-reduction strategies.

• Network Resilience and Attack Tolerance Analysis: Percolation theory and network fragmentation analyses can be used to assess how resilient communication networks are against random failures and targeted attacks (e.g., physical damage to critical infrastructure nodes). These analyses can help identify critical thresholds and weak points in the network. The simultaneous failure of base stations in densely concentrated areas of Türkiye’s GSM networks and their impact on overall network connectivity can be examined within this framework.

Complex systems theory provides a powerful framework not only for understanding the structural properties of communication infrastructures but also their time-dependent dynamic behaviors and adaptive capacities.

• Adaptive and Evolutionary Network Models: Approaches such as adaptive networks and evolutionary game theory can be used to model the post-disaster reconfiguration and adaptation processes of communication networks. These models allow simulation of dynamic processes such as the deployment of mobile base stations and user shifts toward alternative communication tools and their impact on overall network functionality.

• Analysis of Critical Thresholds and Phase Transitions: Tools from statistical physics and dynamical systems theory can be employed to identify critical thresholds and phase transitions in communication networks, such as congestion, cascading failures, or sudden changes in information dissemination. For example, a sudden collapse in network performance following the exceedance of a specific search request threshold may reflect such behavior.

• Modeling Feedback Loops and Systemic Risks: Complex feedback loops between factors such as information flow during disasters, panic behaviors, and resource allocation can be simulated using approaches like system dynamics or agent-based modeling. These models can help understand the long-term effects of different intervention strategies on the system.

The earthquakes in Kahramanmaraş on 6 February 2023 provide a rich case study on how communication infrastructure in Türkiye can be quantitatively analyzed through the lenses of network science and complex systems theory, and how it can serve as input data for future simulation models.

• Analysis of GSM Network Topology: The geographical distribution and interconnections of GSM base stations, control units, and core network elements in Türkiye can be modeled using network science tools to quantitatively analyze topological properties (degree distribution, centrality measures, etc.). This analysis can help identify critical nodes and potential vulnerability points. For example, if base stations in a specific region are heavily dependent on a single energy source or central controller, the impact of their loss on regional communication can be simulated.

• Modeling the Energy Dependency Network: The geographical and functional dependencies between communication and energy infrastructure can be modeled within the interdependent networks framework to simulate the propagation of communication disruptions caused by earthquake-induced power outages. This model enables quantitative evaluation of the effectiveness of different energy redundancy strategies, such as integrating independent power sources into base stations.

• Simulation of Overload Dynamics: The sudden surge in search and data traffic during disasters can be simulated using queueing theory and traffic engineering models to assess their impact on GSM and internet networks. These simulations can provide quantitative insights into the effectiveness of network capacity planning and prioritization mechanisms. Data such as search request rates and successful connection counts observed during the 6 February earthquakes can be used to calibrate these models.

• Optimization of Mobile Base Station (COW) Deployment: The impact of deploying mobile base stations in disaster zones under different scenarios (number, location, deployment speed) on overall network connectivity and capacity can be evaluated using network optimization algorithms and simulations. These analyses can help determine the most effective COW deployment strategies.

• Effectiveness Analysis of Satellite Communication Integration: The impact of integrating satellite internet and telecommunications systems with terrestrial networks under various disaster scenarios (with varying levels of damage to terrestrial infrastructure) can be simulated. These simulations can provide quantitative insights into satellite capacity requirements and integration strategies.

Establishing resilient communication infrastructure during disasters goes beyond a reductionist approach focused solely on technological solutions. As network science and complex systems theory teach us, communication infrastructures are complex socio-technical systems composed of tightly interlinked elements including not only technological layers but also strategic preparedness, administrative coordination, and even social behaviors. As observed during the 6 February earthquakes, the distinct topological properties and failure mechanisms of GSM and internet networks profoundly affect their performance during disasters. However, this performance is shaped not only by the physical and logical structure of the infrastructure but also by strategic foresight prior to the disaster and adaptive coordination capacity during it.

The centralized structure of GSM networks and their critical dependence on energy expose them to high vulnerability to single-point failures. Excessive demand during disasters can rapidly deplete network resources and trigger cascading failures. In contrast, while the distributed architecture and packet-switching mechanism of the internet offer flexibility and resistance to failures up to a certain level, power outages and physical damage can still severely limit its functionality.

In this context, technological improvements alone—such as energy redundancy, mobile base stations, fiber optic reinforcement, and alternative network technologies—are necessary but insufficient. Continuity of communication during disasters is also a matter of strategic preparedness and coordination. This requires understanding the complex networks of interactions among different institutions (telecom operators, disaster management agencies, energy providers, local administrations) and optimizing information flow, decision-making processes, and resource allocation within these networks.

From a systems dynamics perspective, the communication ecosystem during disasters is characterized by feedback loops, critical thresholds, and unpredictable emergent behaviors. For instance, inadequate or incorrect information flow can increase panic and distrust, further elevating demand on communication networks and intensifying congestion. An effective disaster management and coordination strategy must aim to understand such positive feedback loops and encourage negative feedback loops through targeted interventions.

In conclusion, building a more resilient communication infrastructure for future disasters requires a holistic approach that considers the structural differences between GSM and internet networks and their potential for complementarity. This approach must not only enhance the physical and logical resilience of infrastructure but also integrate elements such as strategic planning, effective coordination mechanisms, and public awareness. Communication in disasters is not merely a technological issue; it is a critical strategic imperative that saves lives and enhances societal resilience.