The changing Arctic climate is affecting groundwater flow and storage in supra-permafrost aquifers due to groundwater recharge changes and thaw-driven alterations to aquifer properties and connectivity. Changes to shallow subsurface hydrological processes can drive extensive ecological and biogeochemical changes in addition to potential surface hydrologic regime shifts. This study uses a pan-Arctic geospatial approach to classify shallow, unconfined Arctic aquifers (supra-permafrost aquifers) as topography-limited (TL) (characterized by low permeability, wet climate, and/or low slopes) or recharge-limited (high permeability, dry climate and/or steep slopes) based on the water table ratio framework. Under current conditions, the continuous and discontinuous permafrost zones were determined to be predominantly (65%) TL, with an average net decrease of 5.6% by the year 2100 under RCP2.6 and RCP8.5 conditions. This apparent stability masks local-scale heterogeneity, with change in aquifer function projected at dispersed locations throughout the Arctic, and in clustered hot spots in Siberia and the central Canadian Arctic. Coastal zones around the Arctic are more TL (94%) compared to the overall average, leaving them especially vulnerable to ocean-driven impacts on groundwater such as subsurface seawater intrusion or groundwater flooding. Arctic coasts in Siberia and eastern Canada are also particularly susceptible to water table rise due to high relative sea-level rise which may exceed the active layer thickness and result in substantive changes to saturation. Classification results are sensitive to input values, particularly hydraulic conductivity, which remains a source of uncertainty in the analysis. Despite the sparsity of Arctic data, the available open-source datasets provide valuable insight into broad spatiotemporal trends in aquifer function and highlight particularly vulnerable regions and geographic areas where uncertainty should drive additional data collection and study. These results provide new context for conceptualizing changes to shallow Arctic aquifers as the climate evolves in the 21st century.

Conventional materials necessitate a layer-by-layer rolling or tamping process for subgrade backfill projects, which hampers their utility in confined spaces and environments where compaction is challenging. To address this issue, a self-compacting poured solidified mucky soil was prepared. To assess the suitability of this innovative material for subgrade, a suite of performance including flowability, bleeding rate, setting time, unconfined compressive strength (UCS), and deformation modulus were employed as evaluation criteria. The workability and mechanical properties of poured solidified mucky soil were compared. The durability and solidification mechanism were investigated. The results demonstrate that the 28-day UCS of poured solidified mucky soil with 20% curing agent content reaches 2.54 MPa. The increase of organic matter content is not conducive to the solidification process. When the curing temperature is 20 degrees C, the 28-day UCS of the poured solidified mucky soil with curing agent content not less than 12% is greater than 0.8 MPa. The three-dimensional network structure formed with calcium silicate hydrate, calcium aluminate hydrate, and ettringite is the main source of strength formation. The recommended mud moisture content is not exceed 85%, the curing agent content is 16%, and the curing temperature should not be lower than 20 degrees C.

Aim Alaska's boreal forest is experiencing increasingly severe fires, droughts, and pest attacks that may destabilize carbon sequestration. Our aim was to understand boreal forest resilience to changing wildfire regimes using remote-sensed datasets validated with ground-truthing (GT).Location Five recently burned boreal forest sites (2010-2019) near Fairbanks, Alaska.Methods We used four AVIRIS-NG hyperspectral image datasets (425 spectral bands at 5-nm intervals; 3.5 x 43 km average swath) imaged by NASA in 2017-2018 during the Arctic-Boreal Vulnerability Experiment (ABoVE). Spectral analysis included fire fuel loads and random forest (RF) models constructed from key bands to describe common pre- and postburned vegetation classes. Models were validated with 89 GT plots inside the AVIRIS scenes. GT included tree stem densities, understory cover, soil characteristics, radial growth of 51 spruce trees from cores, and visual damage assays of 668 conifers and deciduous trees.Results Spectral evidence of high fuel loads in 2017 pre-dated a 2019 wildfire. Post-GT local models described vegetation more accurately than pre-GT, but accuracy decreased when spectral rulesets were broadened to increase overall classification. Soil temperature, basal area, slope, elevation, and tree density varied widely; thaw depth, soil moisture, moss cover, and canopy height varied mainly by vegetation class. Invasive species and thermokarst were insignificant. Deciduous seedlings were abundant in postburned sites; however, conifer seedling densities were similar to unburned forest. Upland spruce radial growth showed earlier drought sensitivity than lowland spruce.Conclusion Spectral analysis revealed fire vulnerability in some areas; however, local and temporal spectral variation presented challenges to accurately classify vegetation in AVIRIS scenes. GT suggests that recovering forests near Fairbanks may lack sufficient conifer recruitment to replace existing stands. Sites with stable seasonal thaw may offset drought stress under global warming.

Earthquakes are common geological disasters, and slopes under seismic loading can trigger coseismic landslides, while also becoming unstable due to accumulated damage caused by the seismic activity. Reinforced soil slopes are widely used as seismic-resistant geotechnical systems. However, traditional geosynthetics cannot sense internal damage in reinforced soil systems, and existing in-situ distributed monitoring technologies are not suitable for seismic conditions, thus limiting accurate post-earthquake stability assessments of slopes. This study presents, for the first time, the use of a batch molding process to fabricate self-sensing piezoelectric geogrids (SPGG) for distributed monitoring of soil behavior under seismic conditions. The SPGG's reinforcement and damage sensing abilities were verified through model experiments. Results show that SPGG significantly enhances soil seismic resistance and can detect soil failure locations through voltage distortions. Additionally, the tensile deformation of the reinforcement material can be quantified with sub-centimeter precision by tracking impedance changes, enabling high-precision distributed monitoring of reinforced soil under seismic conditions. Notably, when integrated with wireless transmission technology, the SPGG-based monitoring system offers a promising solution for real-time monitoring and early warning in road infrastructure, where rapid detection and response to seismic hazards are critical for mitigating catastrophic outcomes.

Gunung Bromo Education Forest is a forest that functions as a buffer area to maintain the balance of the surrounding area. However, the undulating to hilly topography, the presence of rivers, and land management for annual crops can make the area vulnerable to erosion-induced degradation. This research aims to analyze and classify the erosion hazard level in Gunung Bromo Education Forest and analyze the relationship between research parameters and erosion in Gunung Bromo Education Forest. Erosion was predicted using the MUSLE method. This research used an explorative-descriptive method incorporating a survey and laboratory analysis. Furthermore, data analysis used was Analysis of Variance (ANOVA), Duncan's Multiple Range Test (DMRT) at a 5% significance level, and Pearson correlation test. The results showed that Gunung Bromo Education Forest erosion ranged from 0.025 to 78.36 t ha(-1)y(-1). The erosion hazard level in Gunung Bromo Education Forest is in the very light to heavy class and is dominated by the light class. The factors of erosivity (R), erodibility (K), slope (LS), and crop management (C) are positively correlated with erosion values. The conservation factor (P) is negatively correlated with erosion values. Making remedial efforts according to the erosion hazard level is important to avoid greater damage.

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.

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.

Bioindication is a key tool for monitoring habitat quality and ecosystem dynamics under increasing anthropogenic pressure. Among model organisms, ground beetles (Coleoptera: Carabidae) play a particularly important role, and one of the widely applied functional indicators describing their assemblage structure is the Mean Individual Biomass (MIB). Introduced in the 1980s, this index reflects the average body mass of Carabidae and allows assessment of successional stages. Its computational simplicity and intuitive interpretation have led to its application in forests, agricultural landscapes, post-industrial areas, and glacier forelands. This paper synthesizes the development and applications of the MIB, highlighting both its advantages and methodological limitations (including variability of length-mass models, seasonal activity patterns, and dependence on sampling methods). Particular attention is given to the potential of the MIB in the context of global environmental change, including its role as an indicator of ecosystem responses to climate change and processes related to soil carbon sequestration. Based on a literature review, future research directions are identified, encompassing methodological standardization, integration of MIB with other ecological and molecular indicators, and expansion of analyses to regions beyond Europe. By linking classical bioindication with ecosystem functioning studies, the MIB may serve as a universal tool for environmental monitoring and the assessment of ecosystem services under accelerated global change.

Accurately reproducing the measured scattering matrix of black carbon (BC) through numerical simulations remains a challenge. Researchers have developed various morphological models of BC and computed their scattering matrices in attempts to replicate experimental measurements. However, prior simulation endeavors frequently encountered issues such as significant discrepancies with observational data, implausible particle shapes, or unsuitable computational parameters. In this study, we developed a fractal-based overlapping and necking model to represent the morphology of bare BC particles. We computed the scattering matrices for both individual particles and particle population using these models and compared the results with the previously reported measurements. Our findings revealed that the overlapping model reproduces the measured scattering matrix elements more accurately, whereas the necking model fails to achieve similar consistency. At a wavelength of 532 nm, the overlapping model yields F 22(pi)/F 11(pi) ranging from 0.80 to 0.99 for single particles and from 0.86 to 0.99 for particle population, both of which are much closer to the experimental observations than those of the necking model. In contrast, only a small subset of results from the necking model falls within the measured range. The overlapping model outperforms the necking model in reproducing the scattering matrix and should be preferred for representing bare BC particles. The established understanding provides useful guidance for retrieving microphysical parameters of BC from polarization features and for diminishing the uncertainties associated with its radiative forcing estimates.

The application of prefabricated assembly technology in underground structures has increasingly garnered attention due to its potential for urban low-carbon development. However, given the vulnerability of such structures subjected to unexpected seismic events, a resilient prefabricated underground structure is deemed preferable for mitigating seismic responses and facilitating rapid recovery. This study proposes a resilient slip-friction connection-enhanced self-centering column (RSFC-SCC) for prefabricated underground structures to promote the multi-level self-centering benefits against multi-intensity earthquakes. The RSFC-SCC is composed of an SCC with two sub-columns and a series of multi-arranged replaceable RSFCs, intended to substitute the fragile central column. The mechanical model and practical manufacturing approach are elucidated, emphasizing its potential multi-level self-centering benefits and working mechanism. Given the established simulation model of RSFC-SCC-equipped prefabricated underground structures, the seismic response characteristics and mitigation capacity are investigated for a typical underground structure, involving robustness against various earthquakes. A multi-level self-centering capacity-oriented design with suggested parameter selection criteria is proposed for the RSFC-SCC to ensure that prefabricated underground structures achieve the desired vibration mitigation performance. The results show that the SCC with multi-arranged replaceable RSFCs exhibits a significant vibration isolating effect and enhanced self-centering capacity for the entire prefabricated underground structure. Benefiting from the multi-level self-centering process, the RSFC-SCC illustrates a robust capacity that adapts to varying intensities of earthquakes. The multi-level self-centering capacity-oriented design effectively facilitates the target seismic response control for the prefabricated underground structures. The energy dissipation burden and residual deformation of primary structures are mitigated within the target performance framework. Given the replacement ease of RSFCs and SCC, a rapid recovery of the prefabricated underground structure after an earthquake is ensured.