Search Results (65)

Mountain flood susceptibility in complex mountainous basins is strongly influenced by terrain–climate interactions; however, the linkage between spatial susceptibility patterns and hydrological processes remains poorly understood. This study proposes a process-oriented framework that explicitly links flood susceptibility patterns with hydrological processes, moving beyond conventional approaches that rely on independent model integration. The Baishuijiang River Basin, located in Wenxian County, southern Gansu Province, China, is selected as a representative mountainous watershed for this analysis. The specific conclusions are as follows: (1) Flood susceptibility was mapped using a Particle Swarm Optimization (PSO)-enhanced Maximum Entropy (MaxEnt) model based on multi-source environmental variables, including climatic, terrain, soil, land cover, and vegetation factors. The model achieved high predictive accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.912), identifying precipitation of the driest month (bio14), elevation, and land use as dominant controlling factors. Medium-to-high-susceptibility areas account for approximately 22% of the basin and are mainly distributed along river valleys and flow convergence areas. These patterns are strongly associated with reduced infiltration capacity under dry antecedent conditions and enhanced flow concentration in steep terrain, and they exhibit clear nonlinear responses and threshold effects. (2) Hydrological simulations using Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) show good agreement with observed runoff (Nash–Sutcliffe Efficiency (NSE) = 0.74−0.85). Sensitivity analysis indicates that runoff dynamics are primarily controlled by the Curve Number (CN), recession constant, and ratio to peak, corresponding to infiltration capacity, recession processes, and peak discharge amplification. The spatial consistency between high-susceptibility areas and areas of strong runoff response demonstrates that susceptibility patterns can be physically explained through hydrological processes, providing a process-based interpretation rather than a purely statistical prediction. (3) Future projections indicate that medium–high-susceptibility areas remain generally stable but show a gradual expansion (+5.2% ± 0.8%) and increasing concentration along river corridors under climate change scenarios. This reflects intensified precipitation variability and enhanced runoff concentration processes, suggesting a climate-driven amplification of flood risk in hydrologically connected areas. Overall, this study goes beyond conventional susceptibility assessment by establishing a physically interpretable framework that provides a consistent linkage between environmental controls, susceptibility patterns, and hydrological responses. The proposed approach is transferable to similar mountainous basins with strong terrain–climate interactions, although uncertainties related to data limitations and single-basin application remain and require further investigation. Full article

Against the backdrop of global climate warming and rapid urbanization, urban thermal environments exhibit strong spatiotemporal heterogeneity and diurnal contrasts. Based on the high-resolution, seamless land surface temperature dataset (GSHTD), this study systematically evaluates the evolution of extreme urban thermal environments across 107 cities in the Yangtze River Basin (YRB) from 2001 to 2020. Urban cores were delineated using high-density impervious surface area (ISA ≥ 50%), and rural background temperatures were elevation-corrected. To quantify the asynchrony between extreme heat intensification and seasonal background warming, we propose “Risk Amplification Index (Ri)”. The results reveal that: (1) The surface urban heat island intensity (SUHII) intensified across the entire basin, with daytime increases being significantly stronger and more spatially consistent than nighttime ones. (2) The intra-annual SUHII cycle exhibits a unimodal pattern peaking in August, with widening inter-city disparities during the warm season. (3) The intensification of extreme heat is often asynchronous with background warming. Combined with land-use change intensity (ΔISA), our analysis indicates that small and medium-sized cities undergoing rapid expansion (high ΔISA) exhibit a stronger heat-risk amplification effect (higher Ri), whereas mature megacities (high total ISA but low ΔISA) show relatively synchronous thermal evolution. The results suggest that an ISA density of around 70% may act as a threshold beyond which extreme-heat amplification is more likely to intensify. These findings suggest that future heat-risk governance should be time- and region-specific, shifting the focus of climate-adaptive planning from solely megacities to mitigating extreme-heat risk amplification during the rapid urbanization of small and medium-sized cities. Full article

This study quantifies how confinement changes the orientational phase space of proteins by comparing hanging-drop (HD) with Langmuir–Blodgett (LB) conditions within a unified probabilistic framework grounded in structural data from the Protein Data Bank (PDB). For each protein, principal moments of inertia are computed from atomic coordinates, trace-normalized, and used to define a geometry-based benchmark for the probability of occupying a predefined productive-orientation set. In parallel, a Hamiltonian-weighted probability is obtained within a classical statistical–mechanical treatment by reconstructing the orientational distribution over the polar–azimuthal domain under a fixed global confinement protocol. The analysis is carried out on a ten-protein panel spanning diverse sizes and anisotropies, and the HD→LB contrast is characterized through probability gains, distributional distances, and an energy-basin decomposition that distinguishes basin depth from basin measure. Under identical parameterization, LB globally produces higher productive-orientation probabilities than HD across all proteins, establishing a uniform direction of the confinement effect while preserving protein-dependent magnitudes. The inertia-based benchmark exhibits broader dispersion in LB/HD amplification, whereas the Hamiltonian construction yields a more regular cross-protein gain, consistent with LB acting as a global reweighting of orientational phase space rather than a protein-specific re-tuning. By integrating PDB-derived structural descriptors with a statistical–mechanical operator, the framework provides a transparent bridge between molecular geometry and confinement-driven ordering and offers a compact basis for comparing crystallization-relevant confinement protocols across structurally heterogeneous proteins. Full article

Environmental DNA (eDNA) metabarcoding has become a powerful, non-invasive method for detecting aquatic organisms. However, optimal sampling strategies for benthic taxa in lentic ecosystems remain unclear. This study evaluated the effectiveness of eDNA metabarcoding in detecting freshwater Unionidae mussels in lake water columns and examined their spatial and seasonal distribution patterns. We validated a mini-barcode primer targeting the mitochondrial 16S rDNA of unionid mussels through controlled laboratory experiments and field tests, confirming reliable amplification and accurate taxonomic assignment of freshwater bivalve DNA. Field surveys were conducted in four lakes within the Nakdong River basin, where eDNA samples were collected from littoral zones and from surface, mid-, and bottom layers of central lake areas during autumn and winter. Metabarcoding analysis identified 79 amplicon sequence variants (ASVs) representing four unionid taxa, with Cristaria plicata and Sinanodonta lauta comprising the majority of reads and ASVs. Overall, the number of Unionidae eDNA reads showed no significant seasonal differences, but there was notable spatial variation among sampling locations. Read numbers were significantly lower in littoral zones compared to central lake areas, with no significant differences detected among depth layers within the central zones. Species-specific analyses revealed contrasting spatial patterns: C. plicata had higher read abundance in mid- and bottom layers, while S. lauta was more frequently detected in surface and littoral samples. These findings suggest that the distribution of freshwater mussel eDNA in lakes is primarily influenced by spatial factors related to habitat preference and hydrodynamic mixing, rather than by seasonal variation during stable periods. This study offers practical insights for designing effective eDNA sampling strategies for benthic invertebrates in lentic ecosystems. Full article

This study presents an integrated framework that couples three-dimensional geotechnical ground modeling with a HAZUS-based urban seismic vulnerability assessment for Seoul, Korea. Over 63,000 boreholes, in situ seismic tests, and building inventory records were compiled into a unified relational database following rigorous multi-stage quality control. A multi-parameter N–Vs regression model was calibrated to supplement missing shear-wave velocity (Vs) data, reducing prediction errors by more than 20% relative to conventional empirical equations. Based on the quality-controlled Vs dataset, a high-resolution three-dimensional Vs–ground model was constructed to represent subsurface heterogeneity and associated uncertainty across the metropolitan area. The building inventory, comprising approximately 700,000 structures, was standardized according to the HAZUS structural taxonomy and mapped to Korean seismic design eras, enabling a Seoul-adapted vulnerability assessment in which exposure characterization and seismic demand are localized. Site-specific ground-motion amplification and response spectra derived from the 3D ground model were used to modify the spectral acceleration input to the HAZUS fragility functions. Results reveal pronounced spatial variability in site conditions, with northern mountainous zones corresponding primarily to NEHRP Site Class B, central districts to Class C, and southern alluvial basins to Classes D–E, producing amplification differences of up to 1.7 under identical input spectral accelerations. High-risk zones such as Gangnam, Songpa, and Yeouido exhibit concentrated expected damage where thick alluvial deposits coincide with dense stocks of mid-rise reinforced-concrete buildings. Overall, the study demonstrates that integrating high-resolution 3D geotechnical ground models with HAZUS-based fragility analysis provides a physically consistent and data-driven basis for urban-scale seismic risk assessment and resilience planning. Full article

The southern Korean Peninsula faces complex seismic challenges due to the concentration of critical infrastructure and the region’s unique intraplate tectonic environment. In this study, over 300 strong-motion records from 10 moderate-magnitude earthquakes were analyzed using data from 10 representative seismic stations. Acceleration response spectra, normalized by peak ground acceleration, were generated and systematically compared with international and domestic seismic design standards, including USNRC Regulatory Guide 1.60 and KBC 2016. The observed spectra frequently exceeded existing code requirements in the mid-to-high-frequency range critical for local infrastructure, indicating potential vulnerabilities in applying generic global standards to Korean conditions. Analysis of vertical-to-horizontal spectral ratios further revealed pronounced frequency dependence and amplification effects, especially in sedimentary basin sites. These findings underscore the importance of accounting for site-specific geological and seismic characteristics in the seismic design of critical infrastructure in Korea. The results advocate for the development of regionally calibrated, risk-informed seismic design frameworks and provide essential empirical data to support safer, more resilient infrastructure amid moderate but potentially hazardous earthquake activity. Full article

Ground settlement is a multifaceted geological phenomenon driven by natural and man-made forces, posing a significant impediment to sustainable urban development. Thus, ground settlement susceptibility (GSS) mapping has emerged as a critical tool for understanding and mitigating cascading hazards in seismically active and anthropogenically modified sedimentary basins. Here, we develop an integrated framework for assessing GSS in the Pohang region, South Korea, by integrating Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR)-derived vertical land motion (VLM) data with seismological, geotechnical, and topographic parameters (i.e., peak ground acceleration (PGA), effective shear-wave velocity (V_s³⁰), site period (T_s), general amplification factor (A_F), seismic vulnerability index (K_g), soil depth, topographic slope, and landform classes) through ensemble machine learning models such as Random Forest (RF), XGBoost, and Decision Tree (DT). Analysis of 56 Sentinel-1 SLC images (2017–2023) revealed persistent subsidence concentrated in Quaternary alluvium, reclaimed coastal plains, and basin-fill deposits. Among the tested models, RF achieved the best performance and strongly agreed with field evidence of sand boils, liquefaction, and structural damage from the 2017 Pohang earthquake. The very-high-susceptibility zones exhibited mean subsidence rates of −3.21 mm/year, primarily within soft sediments (V_s³⁰ < 360 m/s) and areas of thick alluvium deposits. Integration of the optimal RF-based GSS index with regional building inventories revealed that nearly 65% of existing buildings fell within high- to very-high-susceptibility zones. The proposed framework demonstrates that integrating PSInSAR and ensemble learning provides a robust and transferable approach for quantifying ground settlement hazards and supporting risk-informed urban planning in seismically active and complex geological coastal environments. Full article

Background: Monkeypox (MPX), caused by the Monkeypox virus (MPOX) of the Orthopoxvirus genus, has re-emerged as a significant global health threat. Once confined to Central and West Africa, the 2022–2025 multi-country outbreaks, predominantly caused by Clade IIb, demonstrated sustained human-to-human transmission and global spread. Objective: This review summarizes current knowledge on MPX virology, epidemiology, clinical presentation, and diagnostic technologies, with a focus on innovations supporting rapid and field-deployable detection in resource-limited settings. Methods: The recent literature (2019–2025), including peer-reviewed studies, WHO and Africa CDC reports, and clinical guidelines, was critically reviewed. Data were synthesized to outline key developments in diagnostic methodologies and surveillance approaches. Results: MPX comprises two genetic clades: Clade I (Congo Basin) and Clade II (West African), which differ in virulence and transmission. Clade IIb is associated with sexual and close-contact transmission during recent outbreaks. Clinical manifestations have shifted from classic disseminated rash to localized anogenital lesions and atypical or subclinical infections. RT-PCR remains the diagnostic gold standard, while emerging assays such as loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), and CRISPR/Cas-based platforms show promise for rapid point-of-care (POC) testing. Complementary serological tools, including ELISA and lateral flow assays, enhance surveillance and immune profiling. Conclusions: The resurgence of MPX highlights the urgent need for accessible, sensitive, and specific diagnostic platforms to strengthen surveillance and outbreak control, especially in endemic and resource-constrained regions. Full article

Landslide impacts into water generate impulse waves that, in confined basins and along steep coasts, escalate swiftly into hazardous near-shore surges. In this study, we present a scenario-aware workflow using gradient boosting and k-means clustering, and explain them using Shapley additive explanations (SHAPs). Two cases are addressed: forecasting at water entry (Scenario I) with predictors Froude number $Fr$, relative effective mass M, and relative thickness S; and pre-event assessment (Scenario II) with predictors Bingham number $Bi$, relative moving length L, and relative initial mass $Mi$. Using 270 controlled physical-model experiments, we benchmark six learning algorithms under 5-fold cross-validation. Gradient boosting delivers the best overall accuracy and cross-scenario robustness, with XGBoost close behind. Scenario I attains a coefficient of determination $R^2$ of 0.941, while Scenario II achieves $R^2=0.865$. Residual analyses indicate narrower spreads and lighter tails for the top models. SHAP reveals physics-consistent controls: M and $Fr$ dominate Scenario I, whereas initial mass and the $Bi$ dominate Scenario II; interactions $Fr\times S$ and $Mi\times Bi$ clarify non-linear amplification of wave amplitude and height. The cluster–predict–explain framework couples predictive skill with physical transparency and is directly applicable to coastal hazard screening and integration into shoreline early-warning workflows. Full article

Estimating the impacts of climate change on streamflow in the Xiaoxingkai Lake Basin is vital for ensuring sustainable water resource management and transboundary cooperation across the entire Xingkai Lake Basin, a transboundary lake system shared between China and Russia. In this study, 11 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used to drive the Soil and Water Assessment Tool Plus (SWAT+) model. Streamflow projections were made for two future periods: the 2040s (2021–2060) and the 2080s (2061–2100). To correct for systematic biases in the GCM outputs, we applied the Delta Change method, which significantly reduced root mean square error (RMSE) in both precipitation and temperature by 3–35%, thereby improving the accuracy of SWAT+ simulations. To better capture inter-model variability and enhance the robustness of streamflow projections, we used the Bayesian Model Averaging (BMA) technique to generate a weighted ensemble, which outperformed the simple arithmetic mean by reducing uncertainty across models. Our results indicated that under SSP245, greater increases were projected in annual streamflow as well as in wet and normal-flow seasons (e.g., streamflow in normal-flow season in the 2080s increased by 13.0% under SSP245, compared to 7.0% under SSP585). However, SSP585 produced a much larger relative amplification in the dry season, with percentage changes relative to the historical baseline reaching up to +171.7% in the 2080s, although the corresponding absolute increases remained limited due to the low baseline flow. These findings quantify climate-driven hydrological changes in a cool temperate lake basin by integrating climate projections, hydrological modeling, and ensemble techniques, and highlight their implications for understanding hydrological sustainability under future climate scenarios, providing a critical scientific foundation for developing adaptive, cross-border water management strategies, and for further studies on water resource resilience in transboundary basins. Full article

On 22 May 2012, a magnitude Mw 5.6 earthquake struck the Pernik region of western Bulgaria, causing structural damage in nearby cities, including Sofia. This study assesses the seismic response of a six-story reinforced concrete building in central Sofia, utilizing real accelerogram data recorded at the basement (SGL1) and sixth floor (SGL2) levels during the earthquake. Using the Kanai–Yoshizawa (KY) model, the study estimates inter-story motion and assesses amplification effects across the structure. Analysis of peak ground acceleration (PGA), velocity (PGV), displacement (PGD), and spectral ratios reveals significant dynamic amplification of peak ground acceleration and displacement on the sixth floor, indicating flexible and dynamic behavior, as well as potential resonance effects. The analysis combines three spectral techniques—Horizontal-to-Vertical Spectral Ratio (H/V), Floor Spectral Ratio (FSR), and the Random Decrement Method (RDM)—to determine the building’s dynamic characteristics, including natural frequency and damping ratio. The results indicate a dominant vibration frequency of approximately 2.2 Hz and damping ratios ranging from 3.6% to 6.5%, which is consistent with the typical damping ratios of mid-rise concrete buildings. The findings underscore the significance of soil–structure interaction (SSI), particularly in sedimentary basins like the Sofia Graben, where localized geological effects influence seismic amplification. By integrating accelerometric data with advanced spectral techniques, this research can enhance ongoing site-specific monitoring and seismic design practices, contributing to the refinement of earthquake engineering methodologies for mitigating seismic risk in earthquake-prone urban areas. Full article

Flash floods, typically triggered by natural events such as heavy rainfall, snowmelt, and dam failures, are characterized by abrupt onset, destructive power, unpredictability, and challenges in mitigation. This study investigates the spatial distribution patterns and driving mechanisms of rainstorm-induced flash flood disasters in the Yarlung Tsangpo River Basin (YTRB) by integrating topography, hydrometeorology, human activity data, and historical disaster records. Through a multi-method spatial analysis framework—including kernel density estimation, standard deviation ellipse, spatial autocorrelation (Moran’s I and Getis–Ord Gi*), and the optimal parameter geographic detector (OPGD) model (integrating univariate analysis and interaction detection)—we reveal multiscale disaster dynamics across county, township, and small catchment levels. Key findings indicate that finer spatial resolution (e.g., small catchment scale) enhances precision when identifying high-risk zones. Temporally, the number of rainstorm-induced flash floods increased significantly and disaster-affected areas expanded significantly from the 1980s to the 2010s, with a peak spatial dispersion observed during 2010–2019, reflecting a westward shift in disaster distribution. Spatial aggregation of flash floods persisted throughout the study period, concentrated in the central basin. Village density (TD) was identified as the predominant human activity factor, exhibiting nonlinear amplification through interactions with short-duration heavy rainfall (particularly 3 h [P3] and 6 h [P6] maximum precipitations) and GDP. These precipitation durations demonstrated compounding risk effects, where sustained rainfall intensity progressively heightened disaster potential. Topographic and ecological interactions, particularly between elevation (DEM) and vegetation type (VT), further modulate disaster intensity. These findings provide critical insights for risk zonation and targeted prevention strategies in high-altitude river basins. Full article

Global and regional climate change and their water-related impacts are a key component in future development scenarios to guide sustainable water management. Climatic changes may lead to an undesirable redistribution of water supplies and potentially harmful extremities in river flows throughout the year. If we add to this the uneven spatial distribution of water resources in Kazakhstan, the importance of assessment of the intra-annual distribution of river flows under historical and present climatic conditions becomes evident. The presented scientific study analyzes decadal regional trends from 1985 to 2022 in the intra-annual distribution of river runoff in selected catchments in Kazakhstan, including Buktyrma River, Zhabay River, and Ulken-Kobda River. The river basins were selected to cover diverse regions in terms of geographical features and hydrological conditions, significantly affected by climate change. We applied statistical analysis methods using multiyear values of mean monthly and mean annual river flows, mean monthly air temperatures, and mean monthly precipitation. To analyze the intra-annual distribution of annual river flow in the context of climate change, a computational method was used, in which the actual current river flow (modern river flow taking into account non-stationarity of climatic changes) was compared with the conditionally natural flow obtained by modeling and corresponding to the natural regime of the river. The long-term dynamics of flow-forming factors and runoff parameters with regard to phases of different water content (25%, 50%, and 75%) were considered. Statistical analysis of seasonal changes in water content of modeled and actual river flow, taking into account climatic non-stationarity, allowed us to identify significant trends of flow redistribution within the year: indicating a decrease in the volume of spring floods, an increase in winter flow and increase in seasonal variability, especially for the Ulken Kobda River. It appears that atmospheric circulation significantly affects annual and seasonal variations of water availability. The shift in western circulation type (W) contributes to increased average annual river flow, while the shift in eastern circulation type (E) is associated with amplification of extreme flood-type events. The results obtained are important for adapting sustainable water management practices under a changing climate, helping to anticipate the availability of water resources and allowing pro-active measures to mitigate hydrological extremes. Full article

Prediction of the intensity of earthquake-induced motions at the ground surface attracts extensive attention from the geoscience community due to the significant threat it poses to humans and the built environment. Several factors are involved, including earthquake magnitude, epicentral distance, and local soil conditions. The local site effects, such as resonance amplification, topographic focusing, and basin-edge interactions, can significantly influence the amplitude–frequency content and duration of the incoming seismic waves. They are commonly predicted using site effect proxies or applying more sophisticated analytical and numerical models with advanced constitutive stress–strain relationships. The seismic excitation in numerical simulations consists of a set of input ground motions compatible with the seismo-tectonic settings at the studied location and the probability of exceedance of a specific level of ground shaking over a given period. These motions are applied at the base of the considered soil profiles, and their vertical propagation is simulated using linear and nonlinear approaches in time or frequency domains. This paper provides a comprehensive literature review of the major input parameters for site response analyses, evaluates the efficiency of site response proxies, and discusses the significance of accurate modeling approaches for predicting bedrock motion amplification. The important dynamic soil parameters include shear-wave velocity, shear modulus reduction, and damping ratio curves, along with the selection and scaling of earthquake ground motions, the evaluation of site effects through site response proxies, and experimental and numerical analysis, all of which are described in this article. Full article

This study examined atmospheric mechanisms affecting the East Bay Hills Fire (1991) in Oakland, California, using the Advanced Weather Research and Forecasting (WRF) model and North American Regional Reanalysis (NARR) dataset. High-resolution WRF simulations, initially at 16 km, were downscaled to 4 km and 1 km for analyzing primary and secondary circulations at synoptic and meso-α/meso-β scales, respectively, before the fire. Additionally, the interaction between the synoptic-scale and mesoscale environments was examined using backward trajectories derived from NARR data. The findings reveal that a strong pressure gradient created by a ridge over the Great Basin and a trough off the Pacific coast generated favorable meso-α conditions for the hot, dry northeasterly winds, known as “Diablo winds”, which initiated the wildfire in northern California. Mountain waves, enhanced by jet stream dynamics, contributed to sinking air on the Sierra Nevada’s western slopes. The main conclusion is that jet circulation did not directly transport warm, dry air to the fire but established a vertical atmospheric structure conducive to wave amplification and breaking and downward dry air fluxes leading to the necessary warm and dry low-level air for the fire. The hot–dry–windy (HDW) fire weather index further confirmed the highly favorable fire weather conditions. Full article