Flash floods are often responsible for deaths and damage to infrastructure. The objective of this work is to create a data-driven model to understand how predisposing factors influence the spatial variation of the triggering factor (rainfall intensity) in the case of flash floods in the continental area of Portugal. Flash floods occurrences were extracted from the DISASTER database. We extracted the accumulated precipitation from the Copernicus database by considering two days of duration. The analysed predisposing factors for flooding were extracted considering the whole basin where each occurrence is located. These factors include the basin area, the predominant lithology, drainage density, and the mean or median values of elevation, slope, stream power index (SPI), topographic wetness index (TWI), roughness, and four soil properties. The Random Forest algorithm was used to build the models and obtained mean absolute percentage error (MAPE) around 19%, an acceptable value for the objectives of the work. The median of SPI, mean elevation and the area of the basin are the top three most relevant predisposing factors interpreted by the model for defining the rainfall input for flash flooding in mainland Portugal.

The aerosol scattering phase function (ASPF), a crucial element of aerosol optical properties, is pivotal for radiative forcing calculations and aerosol remote sensing detection. Current detection methods for the ASPF include multi-sensor detection, single-sensor rotational detection and imaging detection. However, these methods face challenges in achieving high-resolution full-angle measurement, particularly for small forward (i.e., less than 10 degrees) or backward (i.e., more than 170 degrees) scattering angles in open path. In this work, a full-angle ASPF detection system based on the multi-field-of-view Scheimpflug lidar technique has been proposed and demonstrated. A 450 nm continuous-wave semiconductor laser was utilized as the light source and four CMOS image sensors were employed as detectors. To detect the full-angle ASPF, four receiving units capture angular scattering signals across different angle ranges, namely 0 degrees-20 degrees, 10 degrees-96 degrees, 84 degrees-170 degrees, 160 degrees-180 degrees, respectively. The influence of the relative illumination and angular response of the used image sensors have been corrected, and a signal stitching algorithm was developed to obtain a complete 0-180 degrees angular scattering signal. Atmospheric measurements have been conducted by employing the full-angle ASPF detection system in open path. The experimental results of the ASPF have been compared with the AERONET data from the Socheongcho station and simulated ASPF based on the typical aerosol models in mainland China, showing excellent agreement. The promising results demonstrated in this work have shown a great potential for detecting the full-angle ASPF in open path.

Global warming results in more field soil suffering freeze-thaw cycles (FTCs). The environmental risk of microplastics-recognized as a global emerging contaminant-in soils undergoing FTCs remains unclear. In this study, the combined effects of FTCs and poly(butylene adipate-co-terephthalate) (PBAT) microplastics on microbial degradation of atrazine in Mollisols were investigated. Freeze-thaw cycles, rather than microplastics, significantly inhibited the biodegradation of atrazine in soil, with average inhibition ratios of 33.69% and 4.99% for FTCs and microplastics, respectively. Thawing temperature was the main factor driving the changes in soil microbial community structures and the degradation of atrazine. The degradable microplastics with an amendment level of 0.2% had different and limited effects on the dissipation of atrazine under different modes of FTCs. Among the four modes, microplastics only showed a trend toward promoting atrazine degradation under high-frequency and high-thawing-temperature FTCs. Across all modes, microplastics altered microbial interactions and ecological niches that included affecting specific bacterial abundance, module keystone species, microbial network complexity, and functional genes in soil. There's no synergistic effect between microplastics and FTCs on the degradation of atrazine in soil within a short-term period. This study provides critical insights into the ecological effects of the new biodegradable mulch film-derived microplastics in soil under FTCs.

The development of thermokarst lakes on the Qinghai-Tibetan Plateau (QTP) serves as a prominent indicator of permafrost degradation driven by climate warming and increased humidity. However, quantitative observations of surface change and relationships between lakes and permafrost during thermokarst development remain inadequate. This study utilized long-term terrestrial laser scanning (TLS) to capture high-resolution data on the surface contour changes of the lake in the Beiluhe Basin over 3 years. Between June 2021 and September 2023, the area of BLH-B Lake increased by 19.23% to 6634 m2, with a maximum shoreline retreat distance of 14.37 m. Lake expansion exhibited pronounced seasonal characteristics, closely correlated with temperature and precipitation variations, with the most significant changes occurring during thawing periods. Notably, the lake expanded by up to 505 m2 during extreme rainfall events in the 2022 thawing period, accounting for 47.20% of the total expansion observed over 3 years. Integrated geophysical methods, including electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), revealed substantial permafrost degradation, particularly along the northwestern and western shores, where talik formation occurred within 40 m of the lakeshore. Heat from groundwater flow within the active layer and direct solar radiation contributes to accelerated permafrost degradation around the lake. The integration of TLS with geophysical methods revealed both surface contour changes and subsurface permafrost conditions, providing a comprehensive view of the dynamics of thermokarst lakes. This integrated monitoring approach proves effective for studying thermokarst lake evolution, offering critical quantitative insights into permafrost degradation processes on the QTP and providing essential baselines for climate change impact assessment.

Accurately modeling soil-fluid coupling under large deformations is critical for understanding and predicting phenomena such as slope failures, embankment collapses, and other geotechnical hazards. This topic has been studied for decades and remains challenging due to the nonlinear responses of geotechnical structures, which typically result from plastic yielding and finite deformation of the soil skeleton. In this work, we comprehensively summarize the theory involved in the soil-fluid coupling problem. Within a finite strain framework, we employ an elasto-plastic constitutive model with linear hardening to represent the solid skeleton and a nearly incompressible model for water. The water content influences the behavior of the solid skeleton by affecting its cohesion. The governing equations are discretized by material point method and two sets of material points are employed to independently represent solid skeleton and fluid, respectively. The proposed method is validated by comparing simulation results with experimental results for the impact of water on dry soil and wet soil. The capability of the method is further demonstrated through two cases: (1) the impact of a rigid body on saturated soil, causing water seepage, and (2) the filling of a ditch, which considers the erosion of the foundation. This work may provide a versatile tool for analyzing the dynamic responses of fluid and solid interactions, considering both mixing and separation phenomena.

The Arctic has been warming much faster than the global average, known as Arctic amplification. The active layer is seasonally frozen in winter and thaws in summer. In the 2017 Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign, airborne L- and P- band synthetic aperture radar (SAR) was used to acquire a dataset of active layer thickness (ALT) and vertical soil moisture profile, at 30 m resolution for 51 swaths across the ABoVE domain. Using a thawing degree day (TDD) model, ALT=K root TDD, we estimated ALT along the ABoVE swaths employing the 2-m air temperature from ERA5. The coefficient (K) calibrated has an R2=0.9783. We also obtained an excellent fit between ALT and K root(TDD/theta) where theta is the soil moisture from ERA5 (R2=0.9719). Output based on shared-social economic pathway (SSP) climate scenarios SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 from seven global climate models (GCMs), statistically downscaled to 25-km resolution, was used to project the impacts of climate warming on ALT. Assuming ALT=K root TDD, the projections of UKESM1-0-LL GCM resulted in the largest projected ALT, up to about 0.7 m in 2080s under SSP5-8.5. Given that the mean observed ALT of the study sites is about 0.482 m, this implies that ALT will increase by 0.074 to 0.217 m (15% and 45%) in 2080s. This will have substantial impacts on Arctic infrastructure. The projected settlement Iset (cm) of 1 to 7 cm will also impact the infrastructure, especially by differential settlement due to the high spatial variability of ALT and soil moisture, given at local scale the actual thawing will partly depend on thaw sensitivity of the material and potential thaw strain, which could vary widely from location to location.

Researchers have tried hard to study the toxic effects of single pollutants like certain antibiotics and nanoplastic particles on plants. But we still know little about how these pollutants interact when they're together in the environment, and what combined toxic effects they have on plants. This study assessed the toxic effects of polystyrene nanoplastics (PS-NPs) and ciprofloxacin (CIP), both individually and in combination, on soybean (Glycine max L.) seedlings by various concentration gradients treatments of PS-NPs (0, 10, 100 mg/L) and CIP (0, 10 mg/L). The results indicated that high concentrations of PS-NPs significantly impeded soybean seedling growth, as evidenced by reductions in root length, plant height, and leaf area. CIP predominantly affected the physiological functions of leaves, resulting in a decrease in chlorophyll content. The combined exposure demonstrated synergistic effects, further intensifying the adverse impacts on the growth and physiological functions of soybean seedlings. Metabolomic analyses indicated that single and combined exposures markedly altered the metabolite expression profiles in soybean leaves, particularly related to amino acid and antioxidant defense metabolic pathways. These results indicate the comprehensive effects of NPs with antibiotics on plants and provide novel insights into toxic mechanisms.

Nanoplastics (NPs) and zinc (Zn), both widespread in soil environments, present considerable risks to soil biota. While NPs persist environmentally and act as vectors for heavy metals like Zn, their combined toxicity, especially in soil invertebrates, remains poorly understood. This study evaluates the individual and combined effects of Zn and NPs on earthworm coelomocytes and explores their interactions with Cu/Zn-superoxide dismutase (SOD), an antioxidant enzyme. Molecular docking revealed that NPs bind near the active site of SOD through pi-cation interactions with lysine residues, further stabilized by neighboring hydrophobic amino acids. Viability assays indicated that NPs alone (20 mg/L) had negligible impact (94.54 %, p > 0.05), Zn alone (300 mg/L) reduced viability to 80.02 %, while co-exposure reduced it further to 73.16 %. Elevated levels of reactive oxygen species (ROS) and malondialdehyde (MDA) levels were elevated to 186 % and 173 % under co-exposure, alongside greater antioxidant enzyme disruption, point to synergistic toxicity. Dynamic light scattering and zeta potential (From -13 to -7 mV) analyses revealed larger particle sizes in the combined system, indicative of enhanced protein interactions. Conformational changes in SOD, such as alpha-helix loss and altered fluorescence, further support structural disruption. These findings demonstrate that co-exposure to NPs and Zn intensifies cellular and protein-level toxicity via integrated physical and biochemical mechanisms, providing critical insight into the ecological risks posed by such co-contaminants in soil environments.

Seismic risk assessment of code-noncompliant reinforced concrete (RC) frames faces significant challenges due to structural heterogeneity and the complex interplay of site-specific hazard conditions. This study aims to introduce a novel framework that integrates three key concepts specifically targeting these challenges. Central to the methodology are fragility fuses, which employ a triplet of curves-lower bound, median, and upper bound-to rigorously quantify within-class variability in seismic performance, offering a more nuanced representation of code-noncompliant building behavior compared to conventional single-curve approaches. Complementing this, spectrum-consistent transformations dynamically adjust fragility curves to account for regional spectral shapes and soil categories, ensuring site-specific accuracy by reconciling hazard intensity with local geotechnical conditions. Further enhancing precision, the framework adopts a nonlinear hazard model that captures the curvature of hazard curves in log-log space, overcoming the oversimplifications of linear approximations and significantly improving risk estimates for rare, high-intensity events. Applied to four RC frame typologies (2-5 stories) with diverse geometries and material properties, the framework demonstrates a 15-40 % reduction in risk estimation errors through nonlinear hazard modeling, while spectrum-consistent adjustments show up to 30 % variability in exceedance probabilities across soil classes. Fragility fuses further highlight the impact of structural heterogeneity, with older, non-ductile frames exhibiting 25 % wider confidence intervals in performance. Finally, risk maps are presented for the four frame typologies, making use of non-linear hazard curves and spectrumconsistent fragility fuses accounting for both local effects and within-typology variability.

Constitutive models of sands play an essential role in analysing the foundation responses to cyclic loads, such as seismic, traffic and wave loads. In general, sands exhibit distinctly different mechanical behaviours under monotonic, regular and irregular cyclic loads. To describe these complex mechanical behaviours of sands, it is necessary to establish appropriate constitutive models. This study first analyses the features of hysteretic stressstrain relation of sands in some detail. It is found that there exists a largest hysteretic loop when sands are sufficiently sheared in two opposite directions, and the shear stiffness at a stress-reversal point primarily depends on the degree of stiffness degradation in the last loading or unloading process. Secondly, a stress-reversal method is proposed to effectively reproduce these features. This method provides a new formulation of the hysteretic stress-strain curves, and employs a newly defined scalar quantity, called the small strain stiffness factor, to determine the shear stiffness at an arbitrary stress-reversal state. Thirdly, within the frameworks of elastoplastic theory and the critical state soil mechanics, an elastoplastic stress-reversal surface model is developed for sands. For a monotonic loading process, a double-parameter hardening rule is proposed to account for the coupled compression-shear hardening mechanism. For a cyclic loading process, a new kinematic hardening rule of the loading surface is elaborately designed in stress space, which can be conveniently incorporated with the stressreversal method. Finally, the stress-reversal surface model is used to simulate some laboratory triaxial tests on two sands, including monotonic loading tests along conventional and special stress paths, as well as drained cyclic tests with regular and irregular shearing amplitudes. A more systematic comparison between the model simulations and relevant test data validates the rationality and capability of the model, demonstrating its distinctive performance under irregular cyclic loading condition.