Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity (Vs) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to Vs data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and Vs respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and Vs correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

With polar amplification warming the northern high latitudes at an unprecedented rate, understanding the future dynamics of vegetation and the associated carbon-nitrogen cycle is increasingly critical. This study uses the dynamic vegetation model LPJ-GUESS 4.1 to simulate vegetation changes for a future climate scenario, generated by the EC-Earth3.3.1 Earth System model, with the forcing of a 560 ppm CO2 level. Using climate output from an earth system model without coupled dynamic vegetation, to run a higher resolution dynamic vegetation standalone model, allows for a more in depth exploration of vegetation changes. Plus, with this approach, the drivers of high latitude vegetation changes are isolated, but there is still a complete understanding of the climate system and the feedback mechanisms that contributed to it. Our simulations reveal an uneven greening response. The already vegetated Southern Scandinavia and western Russia undergo a shift in species composition as boreal species decline and temperate species expand. This is accompanied by a shift to a carbon sink, despite higher litterfall, root turnover and soil respiration rates, suggesting productivity increases are outpacing decomposition. The previously barren or marginal landscapes of Siberia and interior Alaska/Western Canada, undergo significant vegetation expansion, transitioning towards more stable, forested systems with enhanced carbon uptake. Yet, in the previously sparsely vegetated northern Scandinavia, under elevated CO2 temperate species quickly establish, bypassing the expected boreal progression due to surpassed climate thresholds. Here, despite rising productivity, there is a shift to a carbon source. The deeply frozen soils in central Siberia resist colonisation, underscoring the role of continuous permafrost in buffering ecological change. Together, these results highlight that CO2 induced greening does not always equate to enhanced carbon sequestration. The interplay of warming, nutrient constraints, permafrost dynamics and disturbance regimes creates divergent ecosystem trajectories across the northern high latitudes. These findings illustrate a strong need for regional differentiation in climate projections and carbon budget assessments, as the Arctic's role as a carbon sink may be more heterogeneous and vulnerable than previously assumed.

Land surface temperature (LST) plays an important role in Earth energy balance and water/carbon cycle processes and is recognized as an Essential Climate Variable (ECV) and an Essential Agricultural Variable (EAV). LST products that are issued from satellite observations mostly depict landscape-scale temperature due to their generally large footprint. This means that a pixel-based temperature integrates over various components, whereas temperature individual components are better suited for the purpose of evapotranspiration estimation, crop growth assessment, drought monitoring, etc. Thus, disentangling soil and vegetation temperatures is a real matter of concern. Moreover, most satellite-based LSTs are contaminated by directional effects due to the inherent anisotropy properties of most terrestrial targets. The characteristics of directional effects are closely linked to the properties of the target and controlled by the view and solar geometry. A singular angular signature is obtained in the hotspot geometry, i.e., when the sun, the satellite and the target are aligned. The hotspot phenomenon highlights the temperature differences between sunlit and shaded areas. However, due to the lack of adequate multi-angle observations and inaccurate portrayal or neglect of solar influence, the hotspot effect is often overlooked and has become a barrier for better inversion results at satellite scale. Therefore, hotspot effect needs to be better characterized, which here is achieved with a three-component model that distinguishes vegetation, sunlit and shaded soil temperature components and accounts for vegetation structure. Our work combines thermal infrared (TIR) observations from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the LEO (Low Earth Orbit) Sentinel-3, and two sensors onboard GEO (geostationary) satellites, i.e. the Advanced Himawari Imager (AHI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI). Based on inversion with a Bayesian method and prior information associated with component temperature differences as constrained, the findings include: 1) Satellite observations throughout East Asia around noon indicate that for every 10 degrees change in angular distance from the sun, LST will on average vary by 0.6 K; 2) As a better constraint, the hotspot effect can benefit from multi-angle TIR observations to improve the retrieval of LST components, thereby reducing the root mean squared error (RMSE) from approximately 3.5 K, 5.8 K, and 4.1 K to 2.8 K, 3.5 K, and 3.1 K, at DM, EVO and KAL sites, respectively; 3) Based on a dataset simulated with a threedimensional radiative transfer model, a significant inversion error may result if the hotspot is ignored for an angular distance between the viewing and solar directions that is smaller than 30 degrees. Overall, considering the hotspot effect has the potential to reduce inversion noise and to separate the temperature difference between sunlit and shaded areas in a pixel, paving the way for producing stable temperature component products.

Study region: Indus Basin Study focus: Meteorological droughts can result in hydrological and soil moisture droughts with severe consequences for food production. In the Indus basin there are strong upstream-downstream linkages and upstream droughts may have strong downstream impacts. This study identifies periods of meteorological, hydrological and soil moisture drought in the Indus Basin for the period 1981-2010, analyses drought propagation and evaluates the role of meltwater in mitigating drought. We used outputs from a cryosphere-hydrology model (SPHY) and a crop-hydrology model (LPJmL), analysed the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Streamflow Index (SSI), Soil Moisture Anomaly Index (SMAI) and crop yield, which are used as drought indicators to identify periods of drought, analyse drought propagation and its impacts. New hydrological insights for the region: Propagation of meteorological drought to hydrological drought and hydrological drought to soil moisture drought shows varied patterns and lag times. There were slightly more periods of soil moisture drought when meltwater was not available than when meltwater was available for irrigation. Our results show that identifying the link between soil moisture drought and yield anomaly remains challenging due to differences in temporal resolution of the data. Nevertheless, the results highlight the critical role of meltwater in mitigating yield variability, especially in the more downstream areas. This provides insight into the potential consequences of future cryosphere degradation for food production in the future.

The time-dependent behaviour of soft and clayey soils treated with Deep Cement Mixing (DCM) columns is important for analyzing the long-term performance of civil engineering infrastructures. Previous studies on DCMinstalled composite soil (CS) have primarily focused on examining the soil strength and stiffness characteristics. The limited focus on the time-dependent settlement and stress-strain distribution of CS underscores the need for a more comprehensive understanding of this complex phenomenon. In this study, a lab-scale physical ground model is designed and developed to investigate the time-dependent settlement profile of the composite Montmorillonitic Clay soil (MMC). The settlement behaviour of the ground model is assessed using Creep Hypothesis B and the results are further validated with the Power Law Model. Additionally, a FEM-based numerical simulation is performed to examine the time-dependent settlement and the stress distribution between the column and surrounding clay soil at different depths. The results from the physical model test show that the time-dependent parameter of the ground model (i.e., DCM column installed in MMC) is proportionate to the loading rate until the failure of the DCM column is reached. However, the time-dependent parameter was found to be decreased by 59.04 % in the post-failure phase of the DCM column. This reduction indicates that the DCM column was the primary load-bearing component before its failure. The numerical study shows that the pore water pressure dissipation in the clay soil and DCM column interface was similar at various depths. The top and bottom sections of the DCM column possess higher stress levels, which demonstrates its susceptibility for failure in the DCM column.

Solidified soil (SS) is widely applied for resource utilization of excavated soil (ES), however the waste solidified soil (WSS) may pose environmental hazards in future because of its high pH (>10). WSS is unsuitable for landfill but can be raw materials for preparing recycled solidified soil (RSS) with better mechanical properties than SS. This investigation used OPC and alkali-activated slag (AAS) as binders to solidify ES and WSS and prepare RSS. The mechanical properties of RSS were experimentally verified to be better than SS, increased by over 76 %. The mechanism is that the clay particles in WSS have been solidified to form sand-like particles or adhere to natural sand, resulting in increasing content of sand-sized particles, and the residual clay particles undergo cation exchange under the high pH and Ca2 + content, resulting in a decrease in zeta potential, reducing diffusion layer thickness. As a result, the flowability of RSS increases under the same liquid to solid ratio. The residual unreacted binder particles and high pH in WSS are beneficial for the early and final compressive strength increase of RSS, which allows preparing RSS with lower cost and carbon emission. Finally, the utilization of WSS has significant environmental benefits.

Evaluating the stability of coral islands and reefs in dynamic marine environments, such as waves, tsunamis, storm surges, and earthquakes, is a critical scientific issue in the field of marine geotechnical engineering. Nansha coral sand was used as the study object, and stress-controlled drained and undrained cyclic-loading tests were conducted. The undrained excess pore-water pressure and the drained cumulative volumetric strain of saturated coral sand were determined at various non-plastic fine contents (FC), relative density (D-r), and cyclic stress ratio (CSR). The results indicated that cumulative volumetric strain (epsilon(vp)) developed in coral sand via two modes: cyclic stabilisation and cyclic creep. Analyses revealed that when the potential damage coefficient (DP) x CSR 0.05, epsilon(vp) transitioned into the cyclic creep mode. Utilising cumulative dissipation energy as a linking factor showed an arctangent function relationship between the excess pore water pressure ratio (R-u) and epsilon(vp) values of saturated coral sand with different FC, D-r, and CSR. This relationship was applicable to both stress- and strain-controlled cyclic-loading tests. Parameters m and n of the R-u-epsilon(vp) function model increased with an increasing CSR. Additionally, an increase in the D-r or FC resulted in a decrease in m and an increase in n. Multiple regression analysis further revealed that model parameters corrected for compactness and cyclic stress levels exhibited distinct trends as the void ratio (e) increased. Specifically, CSR alpha x m(D)(R) decreased, and CSR1-alpha x n(D)(R) increased. Both parameters displayed a single power function relationship with e. Based on these findings, a coupled incremental model for the cyclic pore pressure and volumetric strain of saturated coral sand, based on energy conversion, was developed.

Although silicon nutrition in crops has been reported to improve growth and herbicide tolerance, the response of crop-associated weeds has not been studied. To support or reject the hypothesis that silicon nutrition can affect the tolerance of velvetleaf to pyrithiobac-sodium, affecting crop-weed competition, this study was conducted as a dose-response study in which cotton and velvetleaf grown in soil with or without K2SiO3 + silicate-solubilizing bacteria (SSB) were sprayed with pyrithiobac-sodium. Some enzymes involved in lignin biosynthesis, antioxidant, and herbicide metabolism were measured to find physiological changes. The findings accept the hypothesis above for the first time. Silicon nutrition could disrupt pyrithiobac-sodium selectivity for controlling velvetleaf in cotton. Regardless of treatments, velvetleaf accumulated more silicon and lignin than cotton. Unlike phenylalanine ammonia-lyase, the activity of cytochrome P450 reductase (1.3 vs. 0.7 U/g), glutathione S-transferase (1.7 vs. 1.2 U/g), superoxide dismutase (21.7 vs. 12.5 U/mg), and catalase (443.9 vs. 342.5 U/mg) was higher in cotton than in velvetleaf, grown in soil without silicon nutrition. All enzymes became more active with silicon nutrition, but the increase was higher in velvetleaf. In field studies, velvetleaf benefited from silicon nutrition more than cotton, enhancing the competitive ability of velvetleaf in cotton and reducing further crop yield. K2SiO3 + SSB caused a 29.7 % increase in velvetleaf biomass, which caused the greatest damage to cotton seed (80.9 %) and lint (69.2 %) yields. It is recommended to avoid soil nutrition with K2SiO3 + SSB in velvetleafinfested cotton fields, where velvetleaf control with pyrithiobac-sodium is intended.

This study investigates the physicochemical properties of Soil-Like Material (SLM) recovered from aged Municipal Solid Waste (MSW) dumps in Anantapur, Andhra Pradesh, India, and assesses its potential for reuse. The SLM, which constitutes 68%-75% of the excavated waste, was analyzed for key parameters including total dissolved solids (TDS), chemical oxygen demand (COD), electrical conductivity (EC), and heavy metal concentrations. Results revealed that the organic content of SLM ranged from 6% to 20%, significantly higher than that of local soils (1.5%). The leachate produced from SLM showed elevated levels of TDS (500-1,200 mg l-1), COD (150-270 mg l-1), and heavy metals such as copper (Cu), lead (Pb), chromium (Cr), and zinc (Zn). Cu and Pb concentrations were found to be 27 and 26 times higher than those in local soil extracts, posing substantial risks to groundwater and soil quality. Other metals, including nickel (Ni), arsenic (As), and cadmium (Cd), also exceeded permissible limits. These findings suggest that while SLM has potential for reuse, its high contamination levels require treatment methods such as soil washing, heating, or stabilization with additives like lime or fly ash to reduce environmental risks. Without proper treatment, the direct use of SLM could result in substantial ecological damage. The study highlights the importance of sustainable landfill site rehabilitation and the development of safe strategies for the reuse of SLM to mitigate potential environmental impacts.

Dollar spot, caused by Clarireedia jacksonii, is a chronic fungal disease of creeping bentgrass in cool, humid environments in the United States. In closely mown golf playing surfaces, symptoms include small, circular, sunken spots of blighted turf that eventually coalesce if left untreated. This report evaluates the efficacy of preventative fungicide programs to suppress dollar spot in golf greens. Programs contained broad spectrum fungicides mixed with Appear II, a systemic potassium phosphite fungicide that is formulated with a green pigment. A study was conducted on an 'L-93' plus 'Providence' creeping bentgrass (Agrostis stolonifera) push-up constructed nursery green originally seeded in 2000 at the North Shore Country Club in Glenview, IL. Results indicated fungicide programs that contained Appear II can provide complete control of dollar spot and can also significantly reduce localized dry spot, an abiotic disorder of turfgrass caused by hydrophobic soils, which commonly occurs in sand-based putting greens.