Search Results (107)

Hazards stemming from extreme natural events have exhibited heightened prominence in recent years. The natural hazard management process adopts a comprehensive approach that encompasses all stakeholders involved in the disaster management cycle. “Actions for Resilience” (A4R) represents a standardised concept derived from ISO/TR 22370:2020 that integrates principles from various scientific disciplines to enhance resilience in systems, whether they are socio-ecological systems, communities, or organisations. A4R emphasises proactive measures and interventions aimed at fostering resilience rather than merely reacting to crises or disruptions. It recognises that resilience is a multifaceted concept influenced by various factors, including social, economic, environmental, and institutional dimensions. Central to A4R is the understanding of complex system dynamics. Also, A4R involves rigorous risk assessment to identify potential threats and vulnerabilities within a system, as well as to build adaptive capacity within systems. A4R advocates for the development of resilience metrics and monitoring systems to assess the effectiveness of interventions and track changes in resilience over time. These metrics may include indicators related to social cohesion, ecosystem health, economic stability, and public infrastructure resilience. In this context, the study aims to apply the proposed hierarchy of factors and group decision-making using fuzzy numbers to identify strategic priorities for improving the urban resilience of the pilot area. The identified priority factors are then analysed across different scenarios, and corresponding actions are described in detail. Full article

Urbanization and climate change have disrupted natural water circulation by increasing impervious surfaces and altering rainfall patterns, leading to reduced groundwater infiltration, deteriorating water quality, and heightened flood risks. This study investigates the application of Low Impact Development (LID) and flood control facilities as structural measures to address these challenges in the upper watershed of the Fucha River in Bogotá, Colombia. The methodology involved analyzing watershed characteristics, defining circulation problems, setting hydrological targets, selecting facility types and locations, evaluating performance, and conducting an economic analysis. To manage the target rainfall of $26.5$$\mathrm{m}$$\mathrm{m}$ under normal conditions, LID facilities such as vegetated swales, rain gardens, infiltration channels, and porous pavements were applied, managing approximately 2362 ${\mathrm{m}}^3$ of runoff. For flood control, five detention tanks were proposed, resulting in a 31.8% reduction in peak flow and a 7.3% decrease in total runoff volume. The flooded area downstream was reduced by $46.8$$\mathrm{h}\mathrm{a}$, and the benefit–cost ratio was calculated at 1.02. These findings confirm that strategic application of LID and detention facilities can contribute to effective urban water cycle management and disaster risk reduction. While the current disaster management approach in Bogotá primarily focuses on post-event response, this study highlights the necessity of transitioning toward proactive disaster preparedness. In particular, the introduction and expansion of flood forecasting and warning systems are recommended as non-structural measures, especially in urban areas with complex infrastructure and climate-sensitive hydrology. Full article

In recent years, numerous regions worldwide have experienced devastating natural disasters, leading to significant structural damage to buildings and loss of human lives. The reconstruction process highlights the need for a reliable method to document and track the maintenance history of buildings. This paper introduces a novel approach for managing and monitoring restoring interventions using a secure and transparent digital framework. We will also present an application aimed at improving building structures with respect to earthquake resistance. The proposed system, referred as the “Building Ledger Dossier”, leverages a Digital Twin approach applied to blockchain to establish an immutable record of all structural interventions. The framework models buildings using OpenSees, while all maintenance, repair activities, and documents are registered as Non-Fungible Tokens on a blockchain network, ensuring timestamping, transparency, and accountability. A Decentralized Autonomous Organization oversees identity management and work validation, enhancing security and efficiency in building restoration efforts. This approach provides a scalable and globally applicable solution for improving both ante-disaster monitoring and post-disaster reconstruction, ensuring a comprehensive, verifiable history of structural interventions and fostering trust among stakeholders. The proposed method is also applicable to other types of processes that require the aforementioned properties for document monitoring, such as the life-cycle management of tax credits and operations in the financial or banking sectors. Full article

Sustainable risk and disaster management in the built environment has become a critical research focus amid escalating environmental challenges. Building Information Modeling (BIM) is recognized as a key digital tool for enhancing disaster resilience through simulation, data integration, and collaborative management. This study systematically reviews BIM applications in sustainable risk and disaster management from 2014 to 2024, employing the PRISMA framework, literature coding, and network analysis. Five primary research clusters are identified: (a) sustainable construction and life cycle assessment, (b) performance evaluation and implementation, (c) technology integration and digital innovation, (d) Historic Building Modeling (HBIM) and post-disaster reconstruction, and (e) project management and technology adoption. Despite increasing scholarly attention, the field remains dominated by conceptual studies, with limited empirical exploration of emerging technologies such as artificial intelligence (AI). Four key challenges are highlighted: weak foundational integration with structural risk research, technological bottlenecks in AI and digital applications, limited practical implementation, and insufficient linkage between sustainability and risk management. Future trends are expected to focus on achieving Industry 4.0 interoperability, advancing AI-driven intelligent disaster response, and adopting multi-objective optimization strategies balancing resilience, sustainability, and cost-effectiveness. This study provides a comprehensive overview of the field’s evolution and offers insights into strategic directions for future research and practical innovation. Full article

In early 2025, the Santorini–Amorgos area (Aegean Volcanic Arc, Greece) experienced a seismic swarm, with dozens of M ≥ 4.0 earthquakes and a maximum magnitude of M = 5.2. Beyond its seismological interest, the sequence was notable for triggering rare increased preparedness actions by Greek Civil Protection operational structures in anticipation of an imminent destructive earthquake. These actions included (i) risk communication, (ii) the reinforcement of operational structures with additional personnel and equipment on the affected islands, (iii) updates to local emergency plans, (iv) the dissemination of self-protection guidance, (v) the activation of emergency alert systems, and (vi) volunteer mobilization, including first aid and mental health first aid courses. Although it was in line with contingency plans, public participation was limited. Volunteers helped bridge this gap, focusing on vulnerable groups. The implemented actions in Greece are also compared with increased preparedness during the 2024–2025 seismic swarms in Ethiopia, as well as preparedness before the highly anticipated major earthquake in Istanbul (Turkey). In Greece and Turkey, legal and technical frameworks enabled swift institutional responses. In contrast, Ethiopia highlighted the risks of limited preparedness and the need to embed disaster risk reduction in national development strategies. All cases affirm that preparedness, through infrastructure, planning, communication, and community engagement, is vital to reducing earthquake impacts. Full article

Risk analysis is critical for preventing catastrophic failures in complex systems, as exemplified by the Deepwater Horizon disaster, a stark reminder of systemic vulnerabilities in offshore drilling operations, where inadequate appraisal of overlapping failures led to severe environmental and human losses. This study addresses the absence of a predictive framework capable of capturing cumulative risk interactions across both time stages and defensive layers. To fill this gap, and by drawing on prior frameworks such as the Swiss Cheese Model (SCM) and the Risk Matrix (RM), as well as critiques of their limitations, we introduce the Synergy and Accumulation Model for Analysis (SAMA). This model defines project life-cycle stages and risk recipients, characterizes each risk by four parameters (the focus of impact, suddenness, frequency, and effectiveness), and calculates horizontal (RF_h) and vertical (RF_v) risk factors. We applied SAMA to fifteen identified failure modes of the Macondo well, categorizing them across two time stages (operational and construction) and four defensive layers. Horizontal analysis revealed that the regulatory-laws layer accumulated the highest risk factors, RFh_1laws = 129.25 during the operational stage and RFh_2laws = 95.98 during the construction stage. Vertical analysis showed that the safety objective experienced the greatest systemic vulnerability, with RF_vsafety = 135.8 across ten overlapping risks, followed by the quality objective at RF_vquality = 128.39. These findings demonstrate SAMA’s enhanced capability to identify critical collapse paths often overlooked by conventional models. For researchers, SAMA offers a transparent, parameter-driven methodology applicable across engineering and construction domains. For industry stakeholders, regulators, project managers, and safety engineers, this model provides actionable insights to prioritize resource allocation and strengthen specific defensive layers, thereby enhancing both preventive planning and resilience against future disasters. Full article

Natural disasters and emergencies continue to increase in frequency and severity worldwide, necessitating robust emergency management (EM) systems and evaluation methodologies. This study addresses critical gaps in current emergency response capacity (ERC) evaluation frameworks by developing a comprehensive quantitative decision-making model to assess ERC more effectively. This research constructs a systematic ERC assessment framework based on the four phases of the disaster management cycle (DMC): prevention, preparedness, response, and recovery. The methodology employs multi-criteria decision analysis to evaluate ERC using three distinct information representation environments: intuitionistic fuzzy (IF) sets, linguistic variables (LV), and a novel mixed IF-LV environment. For each environment, we derive appropriate aggregation operators, weight determination methods, and information fusion mechanisms. The proposed model was empirically validated through a case application to emergency plan selection in Shenzhen, China. A statistical analysis of results demonstrates high consistency across all three decision environments (IF, LV, and mixed IF-LV), confirming the model’s robustness and reliability. A sensitivity analysis of key parameters further validates the model’s stability. Results indicate that the proposed decision-making approach provides significant value for EM by enabling more objective, comprehensive, and flexible ERC assessment. The indicator system and evaluation methodology offer decision-makers (DMs) tools to quantitatively analyze ERC using various information expressions, accommodating both subjective judgments and objective metrics. This framework represents an important advancement in emergency preparedness assessment, supporting more informed decision-making in emergency planning and response capabilities. Full article

This paper focuses on the stability issues of geological and engineering structures and conducts research from two perspectives: the mechanism of slope landslides under micro-seismic action and the cyclic failure behavior of concrete materials. In terms of slope stability, through the combination of model tests and theories, the cumulative effect of circulating micro-seismic waves on the internal damage of slopes was revealed. This research finds that the coupling of micro-vibration stress and static stress significantly intensifies the stress concentration on the slope, promotes the development of potential sliding surfaces and the extension of joints, and provides a scientific basis for the prediction of landslide disasters. This helps protect mountain ecosystems and reduce soil erosion and vegetation destruction. The number of cyclic loads has a power function attenuation relationship with the compressive strength of concrete. After 1200 cycles, the strength drops to 20.5 MPa (loss rate 48.8%), and the number of cracks increases from 2.7 per mm³ to 34.7 per mm³ (an increase of 11.8 times). Damage evolution is divided into three stages: linear growth, accelerated expansion, and critical failure. The influence of load amplitude on the number of cracks shows a threshold effect. A high amplitude (>0.5 g) significantly stimulates the propagation of intergranular cracks in the mortar matrix, and the proportion of intergranular cracks increases from 12% to 65%. Grey correlation analysis shows that the number of cycles dominates the strength attenuation (correlation degree 0.87), and the load amplitude regulates the crack initiation efficiency more significantly (correlation degree 0.91). These research results can optimize the design of concrete structures, enhance the durability of the project, and indirectly reduce the resource consumption and environmental burden caused by structural damage. Both studies are supported by numerical simulation and experimental verification, providing theoretical support for disaster prevention and control and sustainable engineering practices and contributing to ecological environment risk management and the development of green building materials. Full article

Accurately understanding flood evolution and its attribution is crucial for watershed water resource management as well as disaster prevention and mitigation. The source region of the Yellow River (SRYR) has experienced several severe floods over the past few decades, but the driving factor influencing flood volume variation in the SRYR remains unclear. In this study, the Budyko framework was used to quantify the effects of climate change, vegetation growth, and permafrost degradation on flood volume variation in six basins of the SRYR. The results showed that the flood volume decreased before 2000 and increased after 2000, but the average value after 2000 remained lower than that before 2000. Flood volume is most sensitive to changes in precipitation, followed by changes in landscape in all basins. The decrease in flood volume was primarily influenced by changes in active layer thickness in permafrost-dominated basins, while it was mainly controlled by other landscape changes in non-permafrost-dominated basins. Meanwhile, the contributions of changes in potential evapotranspiration and water storage changes to the reduced flood volume were negative in all basins. Furthermore, the impact of vegetation growth on flood volume variation cannot be neglected due to its regulating role in the hydrological cycle. These findings can provide new insights into the evolution mechanism of floods in cryospheric basins and contribute to the development of strategies for flood control, disaster mitigation, and water resource management under a changing climate. Full article

With the global increase in disaster risks, enhancing urban resilience has become a critical strategy for risk mitigation and sustainable development. This study develops a two-dimensional indicator framework based on urban systems and resilience capacity from the perspective of the disaster management cycle and applies an improved CRITIC-TOPSIS method to evaluate the resilience levels of the Chengdu–Chongqing urban agglomeration, China. The spatiotemporal evolution of urban resilience from 2010 to 2022 is systematically examined. Furthermore, the dynamics of urban resilience transitions are investigated using a spatial Markov chain model, and the driving factors behind the spatial distribution of resilience are explored through the Geo-detector method. The results indicate the following: (1) Comprehensive resilience demonstrated a steady upward trend during the study period, with Chengdu and Chongqing, as core cities, driving regional resilience improvement and reducing disparities within the urban agglomeration. (2) Significant spatial heterogeneity was observed in the distribution of the comprehensive resilience index and the indices of individual resilience dimensions. (3) The Markov chain analysis revealed a distinct “club convergence” pattern in the dynamic transitions of resilience levels, with development trends closely tied to spatial factors. (4) The Geo-detector model analysis highlighted that infrastructure development and technological innovation exert long-term and substantial impacts on resilience improvement. These findings provide valuable insights for enhancing resilience and promoting sustainable development in the Chengdu–Chongqing region and other similar urban systems. Full article

Robustness in networks plays a vital role in mitigating the effects of failures caused by nodes or links, which can disrupt essential services. Among the various vulnerability parameters in graph theory, such as connectivity and integrity, their applications to fuzzy graphs remain underexplored, despite fuzzy graphs being a powerful tool for modeling uncertainty. In this paper, we introduce the parameter ’fuzzy node integrity’, which considers both the number of disrupted elements and the strength of residual connections. We derive general formulas for different types of symmetric and asymmetric fuzzy graph structures, including cycle graphs, wheel graphs, and star graphs, to systematically demonstrate the utility of this parameter. The proposed parameter is then applied to a military logistics problem to gain insights into the identification of critical nodes and route optimization under uncertainty. This study bridges an important gap in fuzzy graph theory by redefining node integrity through the inclusion of connection strength, offering a promising tool for assessing network vulnerability. These findings lay the foundation not only for theoretical research but also for practical improvements in transportation, disaster management, and communication networks. Full article

The Haihe River system, located in the East Asian monsoon climate zone, experiences uneven precipitation and significant variability, leading to frequent droughts and floods that disrupted economic and social development. While many studies have assessed the risks of droughts and floods in the Haihe River Basin, most focus on the basin as a whole, leaving a notable gap in research on the dynamics of the northern region. This study analyzed historical drought and flood data, incorporating instrument precipitation records from 1960 to 2009 to reconstruct conditions in the northern Haihe River Basin from 1470 to 2009. Using methods like the Mann–Kendall test, sliding averages, continuous wavelet technology, and spatial analysis, this study examined the trends, change points, periodicity, and spatial patterns of drought and flood variability. The findings showed that from 1470 to 2009, drought and flood variabilities occurred 73.15% of the time in the northern Haihe system, with peak disaster periods in the 17th, 19th, and 20th centuries. The region has alternated between wet and dry cycles, with a notable dry trend emerging in the 21st century. A prominent 35~50-year cycle in drought and flood occurrences was identified, along with high-frequency oscillations. Flood periods were most frequent in the eastern plains, while drought periods were more prevalent in the western areas, gradually shifting eastward since 1950. The research also revealed correlations between drought and flood variability and solar activity, with peak years coinciding with higher frequencies of these events. El Niño events were associated with drought periods, while La Niña events tended to cause flood periods. Factors such as solar activity, El Niño–Southern Oscillation, monsoon climate patterns, topography, and human influences shaped the dynamics of drought and flood variability in the northern Haihe River Basin. A comparison with other regions showed consistent wet and dry cycles over the past 500 years, particularly between the northern and southern parts of the basin. However, since the 21st century, the southern region has remained humid, while the northern region has become increasingly drier. Despite similar temperature trends, humidity changes have diverged in the modern warming period. Although the underlying factors driving drought and flood variability were not fully understood and required a further exploration of the global climate system’s interactions, these findings emphasized the need for targeted strategies to address the ongoing challenges of drought and flood management in the northern Haihe River Basin. Full article

In early 2024, the largest full-scale exercise (FSE) for earthquakes and related geohazards in Greece was implemented in Crete Island (southern Greece). Crete is characterized by intense seismicity with historical and recent destructive earthquakes with considerable impact on both the natural and built environment and subsequently on the population. The uniqueness of this FSE lies in the creation and coordination of a multi-agency, multijurisdictional, and multidisciplinary environment in which a multitude of central, regional, and local stakeholders and a large percentage of the total population of Crete actively participated. This paper constitutes a descriptive study focusing on the main steps of the exercise management cycle comprising planning, implementation, and evaluation of the FSE. Furthermore, emphasis is given on its purpose and objectives, its main events and subsequent incidents, the participants and their roles, as well as the material developed and distributed to the participants. Through this study, the implemented actions for increasing preparedness of the Civil Protection mechanism in case of earthquakes and related geohazards are highlighted aiming to inform the scientific community and operational staff and to contribute to the seismic risk reduction of regions worldwide with similar seismotectonic and demographic characteristics with Crete. Furthermore, suggestions are made for the integration of multi-hazard episodes in the FSE scenario in order that the Civil Protection authorities will be prepared to handle the synergy of hazards of different types that may arise during a post-earthquake period that create compounding challenges during the emergency response and further increase recovery time. Full article

Soil moisture is a key variable that affects ecosystem carbon and water cycles and that can directly affect climate change. Remote sensing is the best way to obtain global soil moisture data. Currently, soil moisture remote sensing products have coarse spatial resolution, which limits their application in agriculture, the ecological environment, and urban planning. Soil moisture downscaling methods rely mainly on optical data. Affected by weather, the spatial discontinuity of optical data has a greater impact on the downscaling results. The synthetic aperture radar (SAR) backscatter coefficient is strongly correlated with soil moisture. This study was based on the Google Earth Engine (GEE) platform, which integrated Moderate-Resolution Imaging Spectroradiometer (MODIS) optical and SAR backscattering coefficients and used machine learning methods to downscale the soil moisture product, reducing the original soil moisture with a resolution of 10 km to 1 km and 100 m. The downscaling results were verified using in situ observation data from the Shandian River and Wudaoliang. The results show that in the two study areas, the downscaling results after adding SAR backscattering coefficients are better than before. In the Shandian River, the R increases from 0.28 to 0.42. In Wudaoliang, the R value increases from 0.54 to 0.70. The RMSE value is 0.03 (cm³/cm³). The downscaled soil moisture products play an important role in water resource management, natural disaster monitoring, ecological and environmental protection, and other fields. In the monitoring and management of natural disasters, such as droughts and floods, it can provide key information support for decision-makers and help formulate more effective emergency response plans. During droughts, affected areas can be identified in a timely manner, and the allocation and scheduling of water resources can be optimized, thereby reducing agricultural losses. Full article

The priority during an emergency, regardless of the type, is to rescue as many lives as possible. Field hospitals are usually installed to provide the primary relief to the affected population when hospitals are compromised or absent. There are several sanitary units worldwide ready to be transported to disaster areas. An average field hospital is equipped with an operating room, laboratory, and radiological equipment, but it does not include a unit for the infectious hospital solid waste treatment, which results in improper management with high infection risks and emissions due to incorrect operations (e.g., open incineration). Therefore, the present study identified two market-available solutions (an incinerator and a sterilizer) designed to be transported even under the challenging conditions typical of disasters and are suitable for treating infectious waste. The systems were assessed by a life cycle assessment (LCA), proving an emission savings >90% (considering all impact categories) using the sterilization system. The avoided combustion allows to halve the effect on climate change due to a portable incinerator. This study supplies interesting food for thought for the emergency managers, proving the possibility of integrating the sustainability also in the planning of the response to catastrophic events. Full article