Climate change is reshaping the risk landscape for natural gas pipelines, with landslides emerging as a major driver of technological accidents triggered by natural hazards (Natech events). Conventional Natech risk models rarely incorporate climate-sensitive parameters such as groundwater levels and soil moisture, limiting their capacity to capture evolving threats. This study develops a probabilistic model that explicitly links climate-driven landslide susceptibility to pipeline vulnerability, providing a quantitative basis for assessing pipeline failure probability under different emission projection scenarios. Using Monte Carlo simulations across five regions in China, the results show that under high-emission pathways (SSP5-8.5), pipeline failure probability in summer increases dramatically. For example, from 0.320 to 0.943 in Xinjiang, 0.112 to 0.220 in Sichuan, and 0.087 to 0.188 in Hainan. In cold regions, winter failure probability more than doubles, rising from 0.206 to 0.501 in Heilongjiang and from 0.235 to 0.488 in Beijing. These shifts reveal an overall increase in risk, intensification of seasonal contrasts, and, in some areas, a reconfiguration of high-risk periods. Sensitivity analysis highlights groundwater levels and soil moisture as the dominant drivers, with regional differences shaped by precipitation regimes, permafrost thaw, and typhoon impacts. Building on these insights, this study proposes an AI-based condition-monitoring framework that integrates real-time climate and geotechnical data to support adaptive early warning and safety management.

The thermal coupling between the atmosphere and the subsurface on the Qinghai-Tibetan Plateau (QTP) governs permafrost stability, surface energy balance, and ecosystem processes, yet its spatiotemporal dynamics under accelerated warming are poorly understood. This study quantifies soil-atmosphere thermal coupling ((3) at the critical 0.1 m root-zone depth using in-situ data from 99 sites (1980-2020) and a machine learning framework. Results show significantly weaker coupling in permafrost (PF) zones (mean (3 = 0.42) than in seasonal frost (SF) zones (mean (3 = 0.50), confirming the powerful thermal buffering of permafrost. Critically, we find a widespread trend of weakening coupling (decreasing (3) at 66.7 % of sites, a phenomenon most pronounced in SF zones. Our driver analysis reveals that the spatial patterns of (3 are primarily controlled by surface insulation from summer rainfall and soil moisture. The temporal trends, however, are driven by a complex and counter-intuitive interplay. Paradoxically, rapid atmospheric warming is the strongest driver of a strengthening of coupling, likely due to the loss of insulative snow cover, while trends toward wetter conditions drive a weakening of coupling by enhancing surface insulation. Spatially explicit maps derived from our models pinpoint hotspots of accelerated decoupling in the eastern and southern QTP, while also identifying high-elevation PF regions where coupling is strengthening, signaling a loss of protective insulation and increased vulnerability to degradation. These findings highlight a dynamic and non-uniform response of land-atmosphere interactions to climate change, with profound implications for the QTP's cryosphere, hydrology, and ecosystems.

Here, we present the result of different models for active layer thickness (ALT) in an area of the Italian Central Alps where a few information about the ALT is present. Looking at a particular warm year (2018), we improved PERMACLIM, a model used to calculate the Ground Surface Temperature (GST) and applied two different versions of Stefan's equation to model the ALT. PERMACLIM was updated refining the temporal basis (daily respect the monthly means) of the air temperature and the snow cover. PERMACLIM was updated also to minimize the bias of the snow cover in summer months using the PlanetScope images. Moreover, the contribution of the solar radiation was added to the air temperature to improve the summer GST. The modelled GST showed a good calibration and, among the two versions of Stefan's equation, the first (ALT1) indicates a maximum active layer thickness of 7.5 m and showed a better accuracy with R2 of 0.93 and RMSE of 0.32 m. The model underlined also the importance of better definition of the thermal conductivity of the ground that can strongly influence the ALT.

To investigate the effect of interface temperature on the soil-reinforcement interaction mechanism, a series of pullout tests were conducted considering different types of reinforcement (geogrid and non-woven geotextile), backfill (dry sand, wet sand, and clay), and six interface temperatures. The test results indicate that at interface temperatures of 0 degrees C and above, reinforcement failure didn't occur during the pullout tests, whereas it predominantly occurred at subzero temperatures. Besides, the pullout resistance for the same soil-reinforcement interface gradually decreased as the interface temperature rose. At a given positive interface temperature, the pullout resistance between wet sand and reinforcement was significantly higher than that of the clayreinforcement interface but lower than that of the dry sand-reinforcement interface. Compared with geotextile reinforcements, geogrids were more difficult to pull out under the same interface temperature and backfill conditions. In addition, the lag effect in the transfer of tensile forces within the reinforcements was significantly influenced by the type of soil-reinforcement interface and the interface temperature. Finally, the progressive deformation mechanism along the reinforcement length at different interface temperatures was analyzed based on the strain distribution in the reinforcement.

The root-knot nematode, Meloidogyne javanica, is one of the most damaging plant-parasitic nematodes, affecting chickpea and causing substantial yield losses worldwide. The damage potential and population dynamics of this nematode in chickpea in Ethiopia have yet to be investigated. In this study, six chickpea cultivars were tested using 12 ranges of initial population densities (Pi) of M. javanica second-stage juveniles (J2): 0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64 and 128 J2 (g dry soil)-1 in a controlled glasshouse pot experiment. The Seinhorst yield loss and population dynamics models were fitted to describe population development and the effect on different measured growth variables. The tolerance limit (TTFW) for total fresh weight ranged from 0.05 to 1.22 J2 (g dry soil)-1, with corresponding yield losses ranging from 31 to 64%. The minimum yield for seed weight (mSW) ranged from 0.29 to 0.61, with estimated yield losses of 71 and 39%. The 'Haberu' and 'Geletu' cultivars were considered good hosts, with maximum population densities (M) of 16.27 and 5.64 J2 (g dry soil)-1 and maximum multiplication rate (a) values of 6.25 and 9.23, respectively. All other cultivars are moderate hosts for M. javanica; therefore, it is crucial to initiate chickpea-breeding strategies to manage the tropical root-knot nematode M. javanica in Ethiopia.

Aims Human disturbances and environmental changes significantly influence riparian vegetation composition and dynamics by altering hydrological regimes. In high-altitude river systems, snowmelt-driven water-level fluctuations add further complexity to these processes. However, little is known about how riparian plant functional strategies-competitor (C), stress-tolerator (S), and ruderal (R)-respond to dam-induced water-level fluctuations. This study aimed to assess the effects of water-level fluctuations and climatic factors on riparian vegetation functional strategies along the Nyang River, Qinghai-Tibet Plateau.Location This study was conducted along the Nyang River, Qinghai-Tibet Plateau, China. A total of 33 sites were surveyed, spanning upstream, reservoir, and downstream zones, which were categorized based on water-level fluctuation gradients.Methods We classified riparian vegetation functional strategies using Grime's CSR framework based on species trait data. Hydrological and climatic variables, including water-level fluctuations, temperature, precipitation, and snow cover, were derived from the Global Surface Water Mapping Layers and the FLDAS dataset. Soil properties were measured in the field. Redundancy analysis and partial least squares path modeling were applied to identify key drivers of CSR variation across different river zones.Results Riparian vegetation exhibited significant differences in stress tolerance and ruderal strategies across the Nyang River. Plants in the reservoir and upstream zones had higher S-strategy values, whereas downstream vegetation was predominantly characterized by high competitiveness. The primary drivers of CSR variation across the catchment were temperature, precipitation, and snow cover. In reservoir zones, water-level fluctuations (e.g., retention time, river width) were the dominant influences, whereas downstream vegetation was mainly governed by climate variables. In upstream zones, precipitation, water-level fluctuations, and snow cover jointly influenced CSR strategies. Water-level fluctuations directly regulated functional strategies, whereas snow cover had both direct effects and indirect effects via soil moisture changes.Conclusions This study highlights the interactive effects of climate change and flow regulation on riparian vegetation functional strategies in high-altitude river systems. The findings provide critical insights into how water-level fluctuations and climatic factors shape riparian plant strategies, offering valuable information for ecosystem-based river management and conservation in alpine regions.

Climate change occurs more rapidly at high latitudes, making polar ecosystems highly vulnerable to environmental changes. Plants respond to these conditions by altering the fluxes of water vapor (H2O) and carbon dioxide (CO2). This study analyzed the seasonal variability of the Net Ecosystem Exchange (NEE) of CO2, as well as the sensible (H) and latent (LE) heat fluxes, in two ecosystems in north-central Siberia: a subarctic palsa mire near Igarka, and a mature larch forest near Tura. The flux responses to variations in atmospheric parameters were also assessed. Experimental data were collected from 2019 to 2023 using eddy covariance methods. The results showed that both permafrost ecosystems consistently served as net atmospheric CO2 sinks during the growing seasons, despite significant year-to-year meteorological variations. From 2019 to 2023, summer NEE ranged from -62.9 to -120.2 gC m-2 in the Igarka palsa mire and from -63.5 to -83.6 gC m-2 in the Tura larch forest. During summer periods characterized by prolonged insufficient soil moisture, higher air temperatures, and limited precipitation, the palsa mire exhibited reduced CO2 uptake (i.e., less negative NEE) and Gross Primary Production (GPP) compared to the larch forest. These results suggest that larch forests may be more resilient to climate change than palsa mires. This resilience is primarily linked to deep-rooted water access and conservative stomatal control in larch, whereas palsa mire vegetation depends strongly on surface moisture availability. H and LE fluxes exhibited significant interannual variations, primarily due to variations in incoming solar radiation and precipitation. No significant LE decrease occurred during periods of low precipitation in 2019 and 2020 when drought conditions were observed at both stations during the summer. Maximum H and LE flux rates occurred in June and July when net radiation values were at their maximum for both ecosystems. These findings underscore the urgent need for ecosystem-specific climate strategies, as differential resilience could significantly impact future carbon dynamics in the rapidly warming Arctic.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

Characterizing vertical profiles of in-situ particle properties is relevant because being only based on the surface or column-integrated measurements cannot unambiguously conclude the radiative impact on aerosol. Vertical profiles of in-situ aerosol properties on-board an unmanned aerial vehicle (UAV) were measured above El Arenosillo (37.1 N,-6.7 W) in the southwest of Spain during four flight missions. Measured properties included particle number size distribution, total particle concentration and multiwavelength absorption coefficient up to 3100 m during cold season (February 4, 2022 and December 11, 2023) and warm season (September 20, 2023 and April 2, 2024). The heterogeneity of particle properties has been shown around two types of events: a mineral particle event of desert origin during cold season and a new particle formation event during warm season. During cold season, a comparison between the flight missions with and without desert dust episodes shows that mineral particles decrease the planetary boundary layer (PBL) height. This behavior is probably related to absorber particles aloft atmosphere, which traps solar radiation and heat up the upper layer of the atmosphere and deteriorates the vertical dispersion. In the literature, this effect is called as 'dome effect'. During warm season, new particle formation was observed above PBL. This event could be related to the presence of precursor gases in the residual layer, and enhanced by a low concentration of pre-existing particles. The characteristic parameter during the observed event was the fine-to-total particle volume concentration ratio close to zero. These observations highlight the necessity to establish a long-term multi-temporal monitoring of vertical profiles for atmospheric parameters onboard UAV systems and to integrate in Earth observations networks. For example, radiative forcing is usually estimated from surface data, but the heterogeneity in the vertical profiles of atmospheric particles properties, which are used to the forcing quantification, is a result of inaccuracies.

Reclaimed coastal areas are highly susceptible to uneven subsidence caused by the consolidation of soft marine deposits, which can induce differential settlement, structural deterioration, and systemic risks to urban infrastructure. Further, engineering activities, such as construction and loadings, exacerbate subsidence, impacting infrastructure stability. Therefore, monitoring the integrity and vulnerability of linear urban infrastructure after construction on reclaimed land is critical for understanding settlement dynamics, ensuring safe and reliable operation and minimizing cascading hazards. Subsequently, in the present study, to monitor deformation of the linear infrastructure constructed over decades-old reclaimed land in Mokpo city, South Korea (where 70% of urban and port infrastructure is built on reclaimed land), we analyzed 79 Sentinel-1A SLC ascending-orbit datasets (2017-2023) using the Persistent Scatterer Interferometry (PSInSAR) technique to quantify vertical land motion (VLM). Results reveal settlement rates ranging from -12.36 to 4.44 mm/year, with an average of -1.50 mm/year across 1869 persistent scatterers located along major roads and railways. To interpret the underlying causes of this deformation, Casagrande plasticity analysis of subsurface materials revealed that deep marine clays beneath the reclaimed zones have low permeability and high compressibility, leading to slow pore-pressure dissipation and prolonged consolidation under sustained loading. This geotechnical behavior accounts for the persistent and spatially variable subsidence observed through PSInSAR. Spatial pattern analysis using Anselin Local Moran's I further identified statistically significant clusters and outliers of VLM, delineating critical infrastructure segments where concentrated settlement poses heightened risks to transportation stability. A hyperbolic settlement model was also applied to anticipate nonlinear consolidation trends at vulnerable sites, predicting persistent subsidence through 2030. Proxy-based validation, integrating long-term groundwater variations, lithostratigraphy, effective shear-wave velocity (Vs30), and geomorphological conditions, exhibited the reliability of the InSAR-derived deformation fields. The findings highlight that Mokpo's decades-old reclamation fills remain geotechnically unstable, highlighting the urgent need for proactive monitoring, targeted soil improvement, structural reinforcement, and integrated InSAR-GNSS monitoring frameworks to ensure the structural integrity of road and railway infrastructure and to support sustainable urban development in reclaimed coastal cities worldwide.