Search Results (730)

Given the scarcity of initiatives to charge for urban stormwater services in Brazil and the need to recognise users’ efforts in adopting technologies such as Low Impact Development (LID), a proposal was developed for a stormwater drainage fee and incentives for environmental services in a Brazilian municipality, based on flows retained by LIDs, specifically infiltration wells. To this end, simulations were carried out using the Storm Water Management Model (SWMM) for a 0.5 km² area in a Brazilian city that does not yet implement such charges. Based on the identification of the total flow retained by users within the watershed, the avoided cost to the drainage system was estimated. The charging model was defined using the avoided cost method associated with the Simplified Equivalent Residential Unit (SERU). In the baseline scenario that allocates the operation and maintenance cost, the estimated annual fee was USD 17.22 per household without LID and USD 14.64 per household with LID, and the SERU area was 371.11 m², used as a property-area reference; in an incentive scenario designed to reduce the user payback period to approximately 10 years, the fee for households without LID was set at USD 73.78. An economic incentive policy was identified, consisting of fee discounts upon adoption of LIDs, as well as support for their installation and maintenance. Thus, it was validated that combining a drainage fee with economic incentives is both feasible and motivating for both system users and managers. Full article

Recent efforts to address flooding have explored incorporating flow-reduction capabilities into existing infrastructure. Roadside ditches have historically been viewed as an underutilized component of flood reduction, and a two-stage design has been proposed that modifies a conventional trapezoidal ditch by incorporating bench insets along the main channel. While it is expected that this second stage becomes inundated during storm events, resulting in flow attenuation, the exact impacts of this design are unknown. This study quantified the impact of the two-stage design by modeling a roadside ditch corridor in eastern Iowa. An existing single-stage ditch was converted to a two-stage design, and a HEC-RAS model was constructed to investigate the ditch’s impacts for four design storms (1-year, 2-year, 5-year, and 10-year). In the modeled results, peak flow rates were reduced by 22%, 21%, 7.5%, and 4.3%, respectively, while water volume reductions were near 6%. Maximum velocities throughout the ditch corridor also decreased, with reductions spanning 32% (1-year)–45% (10-year). These results indicate that increased travel times and infiltration associated with the two-stage design provide hydrologic and hydraulic benefits by lessening flood and erosion risk. While further study is needed to verify this behavior through monitoring and modeling at other locations, our findings suggest that two-stage ditches can be a useful best management practice for the transportation community. Full article

The high cost of mooring systems, driven by extreme peak tensions during storm conditions, remains a significant barrier to the commercialization of floating offshore wind turbines (FOWTs). This paper proposes an innovative active tension-regulating joint (TRJ) for FOWT mooring lines. The TRJ consists of nested cylinders and an actively controlled accumulator, designed to release additional line length under high tension and to recover it under low tension, thereby reducing extreme dynamic peaks. A finite element scheme is also developed for efficient line dynamics analysis. The TRJ concept is applied to a benchmark IEA 15-MW semi-submersible FOWT in 100 m water depth under 50-year return period environmental conditions. The simulation results demonstrate that the TRJ reduces the maximum mooring line tension by approximately 53% and the maximum suspended line length by over 23%. This active control technique enables the downsizing of mooring components and a significant cost reduction. Full article

Greenhouses in subtropical and tropical regions must be designed as agricultural engineering systems adapted to local climates, rather than simply replicating the “insulation” models of temperate areas. Under extreme climatic conditions such as persistent high temperatures, intense solar radiation, high humidity, heavy rainfall, and frequent extreme winds, greenhouses transform from enclosed insulation layers into selective climate filters, mitigating crop stress while maintaining close contact with the outdoor environment. This paper summarizes how these climate drivers are reshaping the use, structure, and control concepts of greenhouses, emphasizing that the performance of warm-zone greenhouses depends primarily on heat dissipation, humidity management, and biohazard control, rather than heating and insulation. In this review, we analyze the climatic boundary conditions that define warm-climate conservation cultivation, including long-term overheating risk, high UV radiation, vapor pressure deficit, and suppressed condensation tendency, as well as storm-induced uplift and dynamic loads. These constraints necessitate unique structural forms: tall, lightweight, well-ventilated building types with large roof and side openings, roof geometries that facilitate rainwater runoff, sophisticated drainage systems, and corrosion-resistant materials suitable for humid and coastal environments. Because insect netting significantly reduces ventilation, pest control and temperature regulation become co-design issues, requiring oversized vents, optimized airflow paths, and hybrid roof–mesh structures. Ventilation is considered the primary climate-control mechanism, supplemented by passive cooling measures such as shading and radiation/optical management (e.g., diffuse films and near-infrared-selective films). Active evaporative cooling is considered a conditional measure due to humidity limitations and disease risks. This paper also integrates the impacts on specific crops (fruits and vegetables, leafy greens, and orchids). It highlights emerging trends: typhoon-resistant and adaptive geometries, computational fluid dynamics (CFD)-based design, and sensor-rich IoT/digital twin control frameworks. These principles collectively establish a coherent design framework for achieving resilient, resource-efficient greenhouse production in warm climates. Full article

Rapid peri-urban sprawl is intensifying flood risk by replacing natural landscapes with dense, impervious residential developments. Thailand’s land use regulations require a 5% minimum green space allocation for new housing developments as a measure to promote livability and well-being. Green space also has the potential to sustainably manage stormwater runoff, but for Thailand’s peri-urban development, the question remains whether 5% green space is sufficient to reduce flood risk. As such, this study critically evaluates whether this 5% green space guideline is sufficient for peri-urban runoff and flood management in peri-urban Pathum Thani, particularly given the acceleration of Bangkok’s urban sprawl over the past 30 years. Using a multi-scalar framework, we integrated GIS spatial analysis of 164 gated communities (1995–2025) with site-specific PCSWMM hydrologic modeling to test baseline conditions and Nature-based Solution (NbS) interventions against 5-, 10-, 50-, and 100-year design storms. Findings reveal developers generally adhere to the 5% guideline, thereby addressing policy while maximizing salable land space. PCSWMM simulations show the 5% baseline alone does not adequately manage runoff, with localized residential flooding expected for a 5-year design storm under current baseline conditions. Scenario testing indicates a hybrid grey–green infrastructure approach would optimally manage flooding. Given economic barriers to expanding open space, converting roads to permeable pavements offers a possible optimization strategy. Ultimately, static area-based regulations remain insufficient; policies must transition to performance-based volumetric retention targets to mitigate downstream flooding and foster resilient communities. Full article

Rainfall-induced landslides result from interactions between terrain predisposition and hydrometeorological forcing. In event-scale susceptibility modelling, uncertainty often arises from non-landslide controls. Locations without recorded failures may differ in rainfall history, storm exposure, or inventory completeness, which can bias models trained on static absence samples. This study develops a hydrometeorological control sampling strategy for rainfall induced landslide susceptibility modelling. The strategy defines each sample by grid cell and rainfall date, and constructs non landslide controls from storm related risk sets. A background predisposition prior is used to screen candidate controls. Regional same date controls, annular hard controls near failed slopes, and cross year rainy season background controls are then integrated to represent complementary hydrometeorological and terrain conditions. Design weights and density ratio calibration are applied to account for control reliability and reduce distribution mismatch between the training sample and the mapping domain. In the sample-level evaluation, the method was evaluated in Pubei County, Guangxi, China, using terrain, geology, land cover, daily and antecedent rainfall, and surface wetness. It outperformed Buffer, LowSlope, and IV Low across five classifiers. Relative to IV Low, mean AUC increased from 0.887 to 0.958, accuracy from 81.8% to 91.6%, and Kappa from 63.6% to 83.3%. Holdout validation of two July 2006 landslide clusters also showed greater concentration in top-ranked areas. Averaged over RF and GBDT, top 10% capture rose from 0.227 to 0.322, while the frequency ratio increased from 2.264 to 3.213. These findings suggest that, under the evaluated conditions, the strategy improves sample discrimination, increases landslide concentration in areas ranked as highly susceptible, and reduces uncertainty in the selection of nonlandslide controls. Full article

Disaster governance in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) spans multiple administrative regions, institutions, and platforms, and hazards such as typhoons, storm surges, and urban waterlogging generate strong cross-boundary spillovers that no single city can manage alone. To explain the persistent problems of stakeholder hesitation, underinvestment, and free-riding, this study treats collaborative disaster governance as a multi-actor system and develops a tripartite evolutionary game model linking the regional coordinating regulatory authorities, local emergency management actors, and social participation actors. Static, linear dynamic, and nonlinear dynamic reward–punishment regimes are embedded into the payoff matrix and examined through stability analysis and numerical simulation. The results show that, without incentives, the system settles into an imbalanced “regulatory authorities-driven, weak collaboration” equilibrium; static mechanisms improve targeted behavior but erode the regulatory authorities’ willingness to lead; and linear dynamic mechanisms induce strategy oscillations in cross-regional settings. Under a parameter-adjusted nonlinear dynamic mechanism that combines incremental incentives with progressive constraints, the tested system converges toward “active leadership–proactive collaboration–active participation” under the assumed cost, benefit, and initial-condition settings. These findings provide a basis for designing differentiated subsidies, performance-based rewards, and liability recovery in GBA disaster governance. Full article

In this letter, a novel access and handover authentication scheme is proposed for Low Earth Orbit (LEO) satellite networks, aiming to achieve lightweight computation, privacy preservation, and seamless secure handover for massive sensor users. Different from traditional certificate-based and pairing-dependent authentication mechanisms, the proposed scheme is constructed on certificateless cryptography, which eliminates expensive bilinear pairing operations and avoids the complex certificate management overhead in traditional public-key systems. Meanwhile, it adopts lightweight elliptic curve point addition to further lower computational burden and adapt to the limited on-board computing resources of LEO satellites. To tackle the severe signaling storm and frequent handover dilemma caused by massive, densely deployed sensor terminals, a location-aware, user-grouping-based collaborative handover authentication protocol is specifically designed. The proposed scheme rigorously satisfies essential security properties, including mutual authentication, anonymous identity privacy, known-key security, and master key forward secrecy. Simulation results verify that the proposed protocol achieves superior security performance and remarkably reduces signaling interaction overhead. In the evaluated simulation setting, the proposed mechanism achieves up to $69.81\%$ improvement in handover success rate compared with the standalone handover scheme under high-density access conditions. Full article

Extreme atmospheric events are rare phenomena characterized by unusual intensity or chemical composition compared to the atmospheric background state. Many such events, in the context of global warming, pose threats to human health, thereby making their early detection and monitoring essential. The Infrared Atmospheric Sounding Interferometer (IASI), able to measure more than 30 atmospheric chemical species on a global scale, offers strong potential in this context. However, the large volume of current and upcoming satellite observations makes intelligent data screening more and more challenging. This work aims to overcome this limitation by developing a dedicated algorithm based on Principal Component Analysis (PCA) of Level 1C IASI spectra. Named IASI-PCA, it is designed for the systematic detection of fires, volcanic eruptions, dust storms, pollution plumes, and other extreme atmospheric events that remain unclassified. The detected events are defined as spectral outliers relative to the representative global variability of IASI observations under normal or unperturbed conditions. The detection of an individual spectrum is driven by its anomalous behavior in selected spectral domains, where a set of optimized indicators corresponding to more than 10 species has been defined to discriminate events according to their chemical signatures. This methodology has been implemented in a near-real-time operational system providing detection and classification products within one hour and one day, respectively. The IASI-PCA approach has been applied to multiple case studies demonstrating that it is a powerful tool for: (1) efficiently detecting and monitoring fires, whether isolated sources or extended plumes; (2) handling both clear and cloudy conditions; (3) detecting dust plumes predominantly associated with calcite; (4) identifying pollution sources; and (5) detecting volcanic events. The consistency of our results with those obtained with the EUMETSAT Principal Component Compression (PCC) is also illustrated through the processing of a representative study period. Full article

This paper introduces the Sensor Traffic Generator (STGen), a lightweight, pure-software testbed for evaluating IoT application- and transport-layer protocols at scale. Relative to existing software-based IoT evaluation platforms, STGen combines three design decisions that, to the best of our knowledge, no prior testbed offers together. Every emulated sensor node runs as an independent operating-system process using a real transport stack rather than a discrete-event model or a container. Sensor workloads are generated using physically grounded stochastic models calibrated against real deployment data. Experiments are specified in three independent tiers, IoT Protocols (N), Scenarios (M), and Networks (L), reducing configuration effort from a combinatorial $N\times M\times L$ problem to a linear $N+M+L$ workflow, with new protocols integrated by overriding a four-method abstract interface. STGen operates above OSI Layer 4 and therefore does not model PHY- or MAC-layer behavior, such as RF interference, CSMA/CA collision avoidance, or duty cycling. The sensor models are calibrated using 1,826,223 real-world readings from the Intel Berkeley Research Laboratory; for temperature, the synthetic stream matches the 37-day measurements of 54 Mica2Dot motes with a Kolmogorov–Smirnov D of 0.071 and a Jensen–Shannon divergence of 0.018, showing that STGen reproduces the statistical structure of real sensor data rather than only plausible values. By inverting these calibrated models, STGen also synthesizes labeled false-data-injection anomalies that are separable from normal traffic, with a receiver operating characteristic AUC of 0.898 for stealthy drift and 1.0 for hard physical range violations. In our experiments, STGen instantiates 6000 concurrently emulated sensor nodes on a commodity workstation in 1.02 s using 0.62 GB of memory (approximately 99 KB per node), which is more than two orders of magnitude below the per-node memory costs of container- and VM-based testbeds. STGen also exposes deployment-relevant behavior that controlled emulation alone may hide. Under live wide-area jitter, MQTT and CoAP exhibit different loss and latency patterns than those observed under uniformly degraded NetEm conditions, including MQTT reconnection storms. These results show that STGen provides a scalable and reproducible bridge between lightweight protocol emulation and practical deployment-oriented IoT protocol evaluation. Full article

Compound coastal hazards such as flooding, land subsidence, storm surge, and salinity intrusion impose accelerating risks on deltaic communities. This study presents a unified multi-hazard susceptibility mapping framework for Terrebonne Parish, Louisiana, modeling all four hazards from a common 30 m predictor stack, with per-hazard exclusion of label-related predictors. Eight Machine Learning and Deep Learning algorithms were benchmarked per hazard against an ensemble meta-learner. Generalizability was assessed under three designs of increasing spatial rigor: blocked holdout, interleaved block cross-validation, and a strict contiguous-zone design with a 5 km buffer. Best holdout F1-macro ranged from 0.644 (salinity) to 0.923 (flood). Interleaved-block cross-validation was statistically indistinguishable from holdout; only the buffered contiguous-zone design revealed genuine transfer limits, with F1-macro declining 12–54 percentage points by hazard. Ensemble stacking did not improve upon cross-validation-guided single-model selection despite roughly five times the training cost. Salinity labels were derived from 21 kriged monitoring stations (RMSE = 3.40 PSU; R² = 0.82). A composite Multi-Hazard Susceptibility Index (mean = 0.675 parish-wide; 0.674 land-masked) identifies southern coastal Terrebonne as the priority zone for risk reduction, robust to reweighting of any single hazard. To our knowledge, this is the first framework to jointly map these four hazards while quantifying how validation design governs apparent model transferability. Full article

Accurate retrieval of high-resolution three-dimensional (3D) wind fields from Doppler radar observations is essential for understanding the dynamical structure of convective storms and the turbulent processes that govern their evolution. This study develops and evaluates a ground-based dual and multi-Doppler radar wind retrieval framework designed to reconstruct turbulent wind structures within severe convective environments, including a squall-line event and a hurricane, using an advanced phased-array radar configuration at our facility. The retrieval algorithm combines a weighted least-squares initialization followed by a three-dimensional variational (3DVAR) refinement constrained by the anelastic mass continuity equation. To rigorously evaluate retrieval performance, we develop an LES-based radar wind retrieval framework in which turbulence-resolving LES wind fields are used to generate synthetic radial velocity observations, enabling direct comparison between the retrieved winds and the LES truth. The experiments are idealized and focus on radar geometry, sampling, filtering, and retrieval behavior, rather than representing a full radar instrument simulator. Statistical evaluation shows that the multi-Doppler configuration retrieves the horizontal wind components with high accuracy when sufficient radar viewing-angle diversity is available, whereas the dual-Doppler configuration shows degraded performance, particularly for the $v$-wind component, due to limited viewing geometry. Vertical velocity remains more difficult to retrieve, particularly at low levels, although the idealized hurricane experiment shows improved skill aloft, with correlations reaching ~0.8. Radar-geometry diagnostics show that the multi-Doppler configuration increases effective azimuth diversity across the retrieval swath, improves the conditioning of the local retrieval matrix, and reduces pointwise 3D wind-vector errors relative to the dual-Doppler configuration. Turbulence diagnostics, including velocity variance, turbulent kinetic energy, and kinetic energy spectra, indicate that the retrieval framework preserves the dominant storm-scale and radar-resolvable energy-containing turbulent structures while partially smoothing smaller-scale (<1–2 km) fluctuations by radar sampling, influence-radius filtering, and Gaussian distance weighting. These results emphasize that accurate 3D wind retrieval requires not only sufficient observational coverage but also a well-conditioned radar viewing geometry and highlight the utility of the LES-based radar wind retrieval framework for designing advanced ground-based radar systems for observing turbulent wind structures within convective storms. Full article

This paper addresses the real-time trajectory tracking problem for the Twin Rotor MIMO System (TRMS), a nonlinear, strongly coupled, open-loop unstable aerodynamic laboratory benchmark whose six-dimensional state space is only partially observable through pitch and yaw angle encoders. A High-Gain Observer (HGO) is designed to reconstruct the four unmeasured states, comprising angular velocities and rotor torques, from encoder measurements alone. Three observer-based backstepping control architectures are proposed and experimentally validated on the physical TRMS platform at a 1 kHz embedded sampling rate: (i) adaptive backstepping with tuning functions, which eliminates the over-parametrization inherent in conventional adaptive formulations through a single unified parameter update law; (ii) backstepping with online Brain Storm Optimization (BSO) of the design gains; and (iii) backstepping with online Artificial Bee Colony (ABC) gain optimization. All three architectures achieve stable 100 s trajectory tracking, whereas the conventional non-adaptive backstepping baseline diverges after 42 s due to progressive yaw-channel instability exceeding 4 rad. The BSO- and ABC-optimized controllers achieve the highest pitch-axis tracking precision (reducing pitch root-mean-square errors by 68% relative to the baseline), while the adaptive tuning functions architecture yields the best yaw-axis stability (0.2244 rad RMSE, a 91% reduction). The tuning functions architecture primarily resolves the yaw-channel instability caused by parametric over-parametrization, while the metaheuristic optimizers primarily improve pitch tracking precision through online gain refinement. Closed-loop stability is rigorously established via Lyapunov analysis and the nonlinear separation principle. The High-Gain Observer is directly validated on the two measured states through comparison of its pitch and yaw angle estimates against the incremental encoder signals over the full 100 s trial; the angular velocity and rotor torque estimates are only indirectly supported by the sustained stability of the closed loop, since no velocity or torque sensor is available on the rig. Comprehensive simulation and real-time experimental comparisons quantify the performance, robustness, and computational feasibility of each architecture under identical operating conditions. Full article

Storm Kristin affected central Portugal on 28 January 2026, producing exceptional wind gusts and widespread disruption across the natural, infrastructural and built environments. This paper presents the results of a post-disaster reconnaissance mission carried out in the municipalities of Leiria and Marinha Grande, two of the most affected areas. The methodology combined ground-based visual inspection, photographic records, unmanned aerial vehicle surveys, terrestrial laser scanning, and information provided by local authorities and infrastructure managers. The results show that the spatial distribution and severity of the damage were consistent with the occurrence of very intense localised gusts associated with a sting jet mechanism. Extensive damage was observed in vegetation, transport networks, electrical and telecommunications infrastructure, public spaces and different building typologies. Across the building stock, roofing systems were the most vulnerable components, particularly lightweight panels, ceramic tiles, ridge elements and poorly anchored envelope systems. Industrial and public buildings showed the most severe failures, including extensive roof loss, deformation of structural and envelope components, and local collapse, while residential buildings generally presented minor-to-moderate damage. Heritage buildings showed specific vulnerabilities related to cumulative degradation, exposed architectural elements and the consequences of local damage for historic fabric. The findings highlight the need for improved wind-risk preparedness, systematic post-event documentation, enhanced roof and cladding anchorage, preventive maintenance, and further investigation of the relationship between recorded wind speeds, observed damage patterns and current wind-design assumptions. Full article

Urban stormwater drainage networks in old urban districts often suffer from insufficient drainage capacity, adverse pipe slopes, and outdated design standards, which increase the risk of urban waterlogging during heavy rainfall events. To address these issues, this study proposes a multi-objective hydraulic optimization framework for the rehabilitation of urban stormwater drainage networks by coupling SWMM hydrodynamic simulation, an improved bottleneck index method, and the NSGA-III algorithm. The proposed bottleneck index integrates the ratio of actual hydraulic gradient to pipe slope with pipe filling ratio (h/D), enabling the identification of pipes with insufficient drainage capacity and unreasonable construction conditions. The Sanjie River catchment in Fuzhou, China, was selected as the study area. The results indicated that the maximum proportion of bottleneck pipes increased from 33.28% to 41.62% as the design storm return period increased from 1 to 30 years, while the rate of increase gradually diminished under larger return periods. Multi-objective optimization results showed that increasing the maximum allowable rehabilitated pipe diameter from 1.2 m to 1.5 m yielded only limited additional improvement in drainage performance, ranging from 2.06% to 4.11%, whereas the rehabilitation cost increased by 3.10% to 4.41%. Therefore, 1.2 m was identified as the more cost-effective maximum allowable diameter. Under this condition, the rehabilitation schemes for the 3-, 5-, 10-, and 20-year design storms reduced nodal overflow volume by 36.56%, 33.67%, 31.24%, and 27.24%, respectively. The proposed framework provides a systematic and practical approach for diagnosing and rehabilitating existing urban stormwater drainage networks. Full article