Search Results (142)

This study addresses the technical gaps in current flood simulation for regulated lakes, such as insufficient accuracy in simulating complex gate and dam operation processes and low computational efficiency that fails to meet practical engineering needs. By employing an improved two-dimensional (2D) hydrodynamic model, it systematically analyzes flood control strategies for large regulated lakes. Using the August 2018 flood event for model validation, the final simulation results indicate that the current flood control capacity meets standards for 50-year floods (Nanyang 36.79 m, Weishan 35.99 m) but fails for 100-year floods, exceeding limits by 0.23 m (Nanyang 37.22 m) and 0.15 m (Weishan 36.64 m). The designed conditions reduce 100-year flood levels to 36.98 m and 36.47 m, respectively, achieving the required flood defense standard for 100-year events. The findings provide a quantitative framework for evaluating flood control capacity across different planning scenarios, which advances flood risk management and offers implementable insights for achieving sustainable water resource management in regulated lake basins globally. This, in turn, contributes directly to two United Nations Sustainable Development Goals (SDGs): enhancing human community safety and resilience (SDG 11: Sustainable Cities and Communities) through improved flood control engineering and operations, and strengthening climate adaptation (SDG 13: Climate Action) by boosting basin-wide resilience to extreme rainfall and flooding. Full article

The waterlogging tolerance of Lindera megaphylla, an evergreen species valued for ecological restoration and its role in landscapes, remains unclear, hindering its broader use in riparian green spaces and rain gardens. This study systematically assessed its physiological responses to simulated waterlogging stress (control/CK, mild/W1, moderate/W2, and severe/W3) and exogenous abscisic acid (ABA) applications (0, 1, and 3 μmol/L). The results showed that severe waterlogging (28 d) drastically reduced seedling survival to 30%, inhibited growth, induced significant reactive oxygen species (ROS) accumulation and membrane damage (malondialdehyde (MDA) +118.59%, relative conductivity (REC) +85.54%), and decreased photosynthetic pigments (Chla −41.60%, Chlb −40.02%, Car −34.33%). Exogenous ABA (3 μmol/L) substantially alleviated stress, increasing survival by 60.61% and enhancing tolerance through three integrated processes: (1) enhancing antioxidant defense (superoxide dismutase (SOD) +10.63%, peroxidase (POD) +9.33%) and reducing ROS; (2) stabilizing osmotic regulation (lower soluble sugars, proteins, and proline and increased leaf water content by +7.89%); (3) preserving photosynthetic integrity, evidenced by restored chlorophyll levels and significantly improved photosystem II and I efficiency. This study is the first comprehensive demonstration that ABA enhances L. megaphylla’s waterlogging tolerance by coordinating antioxidant, osmotic, and photosynthetic responses. Full article

Urban coastal areas are increasingly vulnerable to compound flooding due to the convergence of extreme rainfall, storm surges, and infrastructure aging, especially in high-density settings. This study proposes and empirically validates a multi-scale strategy for enhancing urban flood resilience in the Macau Peninsula, a densely built coastal city with complex flood exposure patterns. Building on a previously developed network-based resilience assessment framework, the study integrates hydrodynamic simulation and complex network analysis to evaluate the effectiveness of targeted interventions, including segmented storm surge defense barriers, drainage infrastructure upgrades, and spatially optimized low-impact development (LID) measures. The Macau Peninsula was partitioned into multiple shoreline defense zones, each guided by context-specific design principles and functional zoning. Based on our previously developed flood simulation framework covering extreme rainfall, storm surge, and compound events in high-density coastal zones, this study validates resilience strategies that achieve significant reductions in inundation extent, water depth, and recession time. Additionally, the network-based resilience index showed marked improvement in system connectivity and recovery efficiency, particularly under compound hazard conditions. The findings highlight the value of integrating spatial planning, ecological infrastructure, and systemic modeling to inform adaptive flood resilience strategies in compact coastal cities. The framework developed offers transferable insights for other urban regions confronting escalating hydrometeorological risks under climate change. Full article

To address the flood risks driven by climate change and urbanization, this study proposes the DRIRA model (Driving Force, Resistance, Influence, Recoverability, Adaptability). Distinct from BRIC (Baseline Resilience Indicators for Communities) and PEOPLES (Population, Environmental/Ecosystem, Organized Governmental Services, Physical Infrastructure, Lifestyle, Economic Development, Social–Cultural Capital), the model emphasizes dynamic interactions across the entire disaster lifecycle, introduces the “Influence” dimension, and integrates SNA (Social Network Analysis) with a modified gravity model to reveal cascading effects and resilience linkages among cities. Based on an empirical study of 30 cities in the Central Plains Urban Agglomeration, and using a combination of entropy weighting, a modified spatial gravity model, and social network analysis, the study finds that: (1) Urban flood resilience increased by 35.5% from 2012 to 2021, but spatial polarization intensified, with Zhengzhou emerging as the dominant core and peripheral cities falling behind; (2) Economic development, infrastructure investment, and intersectoral governance coordination are the primary factors driving resilience differentiation; (3) Intercity resilience connectivity has strengthened, yet administrative fragmentation continues to undermine collaborative effectiveness. In response, three strategic pathways are proposed: coordinated development of sponge and resilient infrastructure, activation of flood insurance market mechanisms, and intelligent cross-regional dispatch of emergency resources. These strategies offer a scientifically grounded framework for balancing physical flood defenses with institutional resilience in high-risk urban regions. Full article

Distributed denial-of-service (DDoS) attacks are a prevalent threat to resource-constrained IoT deployments. We present an edge-based detection and mitigation system integrated with the oneM2M architecture. By using a Raspberry Pi 4 client and five Raspberry Pi 3 attack nodes in a smart-home testbed, we collected 200,000 packets with 19 features across four traffic states (normal, SYN/UDP/ICMP floods), trained Decision Tree, 2D-CNN, and LSTM models, and deployed the best model on an edge computer for real-time inference. The edge node classifies traffic and triggers per-attack defenses on the device (SYN cookies, UDP/ICMP iptables rules). On a held-out test set, the 2D-CNN achieved 98.45% accuracy, outperforming the LSTM (96.14%) and Decision Tree (93.77%). In end-to-end trials, the system sustained service during SYN floods (time to capture 200 packets increased from 5.05 s to 5.51 s after enabling SYN cookies), mitigated ICMP floods via rate limiting, and flagged UDP floods for administrator intervention due to residual performance degradation. These results show that lightweight, edge-deployed learning with targeted controls can harden oneM2M-based IoT systems against common DDoS vectors. Full article

Software-Defined Networking (SDN) is a network architecture that decouples the control plane from the data plane, enabling centralized, programmable management of network traffic. SDN introduces centralized control and programmability to modern networks, improving flexibility while also exposing new security vulnerabilities across the application, control, and data planes. This paper provides a comprehensive overview of SDN security threats and defenses, covering recent developments in controller hardening, trust management, route optimization, and anomaly detection. Based on these findings, we present a comparative analysis of SDN controllers in terms of performance, scalability, and deployment complexity. This culminates in the introduction of the Cloud-to-Edge Layer Two (CELT)-Secure switch, a virtual OpenFlow-based data-plane security mechanism. CELT-Secure detects and blocks Internet Control Message Protocol flooding attacks in approximately two seconds and actively disconnects hosts engaging in Address Resolution Protocol-based man-in-the-middle attacks. In comparative testing, it achieved detection performance 10.82 times faster than related approaches. Full article

Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies. Full article

A critical gap exists between coastal communities’ need for accessible flood risk assessment tools and the availability of sophisticated modeling, which remains limited by technical barriers and computational demands. This study introduces three key innovations through Coastal Defense Pro: (1) the first operational web-based AI ensemble for coastal flood risk assessment integrating real-time multi-agency data, (2) an automated regional calibration system that corrects systematic model biases through machine learning, and (3) browser-accessible implementation of research-grade modeling previously requiring specialized computational resources. The system combines Bayesian neural networks with optional LSTM and attention-based models, implementing automatic regional calibration and multi-source elevation consensus through a modular Python architecture. Real-time API integration achieves >99% system uptime with sub-3-second response times via intelligent caching. Validation against Hurricane Isabel (2003) demonstrates correction from 197% overprediction (6.92 m predicted vs. 2.33 m observed) to accurate prediction through automated identification of a Chesapeake Bay-specific reduction factor of 0.337. Comprehensive validation against 15 major storms (1992–2024) shows substantial improvement over standard methods (RMSE = 0.436 m vs. 2.267 m; R² = 0.934 vs. −0.786). Economic assessment using NACCS fragility curves demonstrates 12.7-year payback periods for flood protection investments. The open-source Streamlit implementation democratizes access to research-grade risk assessment, transforming months-long specialist analyses into immediate browser-based tools without compromising scientific rigor. Full article

River embankments are critical flood defense structures, stretching for thousands of kilometers across alluvial plains. They often originated as natural levees resulting from overbank flows and were later enlarged using locally available soils yet rarely designed according to modern engineering standards. Substantially under-characterized, their performance to extreme events provides an invaluable opportunity to highlight their vulnerability and then to improve monitoring, management, and reinforcement strategies. In May 2023, two extreme meteorological events hit the Emilia-Romagna region in rapid succession, causing numerous breaches along river embankments and therefore widespread flooding of cities and territories. These were followed by two additional intense events in September and October 2024, marking an unprecedented frequency of extreme precipitation episodes in the history of the region. This study presents the methodology adopted to create a regional database of 66 major breaches and damages that occurred during May 2023 extensive floods. The database integrates multi-source information, including field surveys; remote sensing data; and eyewitness documentation collected before, during, and after the events. Preliminary interpretation enabled the identification of the most likely failure mechanisms—primarily external erosion, internal erosion, and slope instability—often acting in combination. The database, unprecedented in Italy and with few parallels worldwide, also supported a statistical analysis of breach widths in relation to failure mechanisms, crucial for improving flood hazard models, which often rely on generalized assumptions about breach development. By offering insights into the real-scale behavior of a regional river defense system, the dataset provides an important tool to support river embankments risk assessment and future resilience strategies. Full article

Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster risk assessment model through systematic analysis of four key factors—hazard (H), exposure (E), susceptibility/sensitivity (S), and disaster prevention capabilities (C)—and establishes an evaluation index system. Using the Analytic Hierarchy Process (AHP), we determined indicator weights and quantified flood risk via the following formula R = H × E × V × C. After we applied this model to 16 towns in coastal Zhejiang Province, the results reveal three distinct risk tiers: low (R < 0.04), medium (0.04 ≤ R ≤ 0.1), and high (R > 0.1). High-risk areas (e.g., Longxi and Shitang towns) are primarily constrained by natural hazards and socioeconomic vulnerability, while low-risk towns benefit from a robust disaster mitigation capacity. Risk typology analysis further classifies towns into natural, social–structural, capacity-driven, or mixed profiles, providing granular insights for targeted flood management. The spatial risk distribution offers a scientific basis for optimizing flood control planning and resource allocation in the district. Full article

Arundo donax L. has been introduced in markets worldwide due to its economic value. However, it is listed in the world’s 100 worst alien invasive species because it easily escapes from cultivation, and forms dense monospecific stands in riparian areas, agricultural areas, and grassland areas along roadsides, including in protected areas. This species grows rapidly and produces large amounts of biomass due to its high photosynthetic ability. It spreads asexually through ramets, in addition to stem and rhizome fragments. Wildfires, flooding, and human activity promote its distribution and domination. It can adapt to various habitats and tolerate various adverse environmental conditions, such as cold temperatures, drought, flooding, and high salinity. A. donax exhibits defense mechanisms against biotic stressors, including herbivores and pathogens. It produces indole alkaloids, such as bufotenidine and gramine, as well as other alkaloids that are toxic to herbivorous mammals, insects, parasitic nematodes, and pathogenic fungi and oomycetes. A. donax accumulates high concentrations of phytoliths, which also protect against pathogen infection and herbivory. Only a few herbivores and pathogens have been reported to significantly damage A. donax growth and populations. Additionally, A. donax exhibits allelopathic activity against competing plant species, though the allelochemicals involved have yet to be identified. These characteristics may contribute to its infestation, survival, and population expansion in new habitats as an invasive plant species. Dense monospecific stands of A. donax alter ecosystem structures and functions. These stands impact abiotic processes in ecosystems by reducing water availability, and increasing the risk of erosion, flooding, and intense fires. The stands also negatively affect biotic processes by reducing plant diversity and richness, as well as the fitness of habitats for invertebrates and vertebrates. Eradicating A. donax from a habitat requires an ongoing, long-term integrated management approach based on an understanding of its invasive mechanisms. Human activity has also contributed to the spread of A. donax populations. There is an urgent need to address its invasive traits. This is the first review focusing on the invasive mechanisms of this plant in terms of adaptation to abiotic and biotic stressors, particularly physiological adaptation. Full article

Autonomous vehicles (AVs) rely on a heterogeneous sensor suite of RGB cameras, LiDAR, GPS/IMU, and emerging event-based dynamic vision sensors (DVS) to perceive and navigate complex environments. However, these sensors can be deceived by realistic cyberattacks, undermining safety. In this work, we systematically implement seven attack vectors in the CARLA simulator—salt and pepper noise, event flooding, depth map tampering, LiDAR phantom injection, GPS spoofing, denial of service, and steering bias control—and measure their impact on a state-of-the-art end-to-end driving agent. We then equip each sensor with tailored defenses (e.g., adaptive median filtering for RGB and spatial clustering for DVS) and integrate a unsupervised anomaly detector (EfficientAD from anomalib) trained exclusively on benign data. Our detector achieves clear separation between normal and attacked conditions (mean RGB anomaly scores of 0.00 vs. 0.38; DVS: 0.61 vs. 0.76), yielding over 95% detection accuracy with fewer than 5% false positives. Defense evaluations reveal that GPS spoofing is fully mitigated, whereas RGB- and depth-based attacks still induce 30–45% trajectory drift despite filtering. Notably, our research-focused evaluation of DVS sensors suggests potential intrinsic resilience advantages in high-dynamic-range scenarios, though their asynchronous output necessitates carefully tuned thresholds. These findings underscore the critical role of multi-modal anomaly detection and demonstrate that DVS sensors exhibit greater intrinsic resilience in high-dynamic-range scenarios, suggesting their potential to enhance AV cybersecurity when integrated with conventional sensors. Full article

In recent decades, climate change has led to more frequent episodes of extreme rainfall, increasing the risk of river flooding. Streams and rivers characterized by short flow times are subject to rapid and impressive floods; for this reason, the modeling of their beds is of fundamental importance for the execution of hydraulic calculations capable of predicting the flow rates and identifying the points where floods may occur. In the context of studies conducted on three watercourses in Calabria (Italy), different survey and restitution techniques were used (aerial LiDAR, terrestrial laser scanner, GNSS, photogrammetry). By integrating these methodologies, multi-resolution models were generated, featuring a horizontal accuracy of ±16 cm and a vertical accuracy of ±15 cm. These models form the basis for the hydraulic calculations performed. The results demonstrate the feasibility of producing accurate models that are compatible with the memory and processing capabilities of modern computers. Furthermore, the technique set up and implemented for the refined representation of both the models and the effects predicted by hydraulic calculations in the event of exceptional rainfall (such as flow, speed, flooded areas, and critical points along riverbanks) serves as a valuable tool for improving hydrogeological planning, designing appropriate defense works, and preparing evacuation plans in case of emergency, all with the goal of mitigating hydrogeological risk. Full article

As sea levels rise and extreme weather events become more frequent due to climate change, coastal urban areas are increasingly vulnerable to wave overtopping and flooding. Retrofitting existing vertical seawalls with retreated storm walls represents a key adaptive strategy, especially in the Mediterranean, where steep foreshores and limited public space constrain conventional coastal defenses. This study investigates the effectiveness of storm walls in reducing wave overtopping on vertical walls with steep foreshores (1:7 to 1:10) through high-fidelity numerical simulations using the SWASH model. A comprehensive parametric study, involving 450 test cases, was conducted using Latin Hypercube Sampling to explore the influence of geometric and hydrodynamic variables on overtopping rate. Model validation against Eurotop/CLASH physical data demonstrated strong agreement (r = 0.96), confirming the reliability of SWASH for such applications. Key findings indicate that longer promenades (Gc) and reduced impulsiveness of the wave conditions reduce overtopping. A new empirical reduction factor, calibrated for integration into the Eurotop overtopping equation for plain vertical walls, is proposed based on dimensionless promenade width and water depth. The modified empirical model shows strong predictive performance (r = 0.94) against SWASH-calculated overtopping rates. This work highlights the practical value of integrating storm walls into urban seawall design and offers engineers a validated tool for enhancing coastal resilience. Future research should extend the framework to other superstructure adaptations, such as parapets or stilling basins, to further improve flood protection in the face of climate change. Full article

Applicable recommendations play a key role in improving training and procedures used in civil protection. Since 1 January 2025, the Law on Civil Protection and Civil Defense has been in force in Poland. It responds to the experience of current threats, including the war in Ukraine, the 2024 floods in Western Poland, the COVID-19 pandemic, and other crises. The Act systemically regulates the problem of building social resilience, which must be developed and applied regarding today’s modern threats. The primary actor in civil protection is the fire brigade system, in which volunteer firefighters are recruited from local communities and act for their benefit. In this context, it is interesting to ask whether and what solutions should be applied in order to improve the effectiveness of the training and exercise system of volunteer fire brigades (TSOs) in the field of civil protection and crisis management. The aim of this investigation was to develop evaluations and applicable recommendations to improve the effectiveness of the training system for volunteer firefighters based on a survey of volunteer firefighters in the Cracow Poviat. Two survey diagnostic techniques were used: expert interviews and questionnaire research. The findings were compared with the results of an analysis of source documents obtained in TSO units. The expert interviews covered all chief fire officers of the municipalities in the Cracow Poviat. The paper begins with an introduction and a systematic literature review. The conclusions consist of the proposal of applicable changes in the scope of basic, specialist, and additional training. Areas of missing training are also identified. The firefighters’ knowledge of crisis management procedures is verified, deficiencies are identified, and applicable changes in the organization of field exercises are proposed. Full article