As a relatively new method, vacuum preloading combined with prefabricated horizontal drains (PHDs) has increasingly been used for the improvement of dredged soil. However, the consolidation process of soil during vacuum preloading, in particular the deformation process of soil around PHDs, has not been fully understood. In this study, particle image velocimetry technology was used to capture the displacement field of dredged soil during vacuum preloading for the first time, to the best of our knowledge. Using the displacement data, strain paths in soil were established to enable a better understanding of the consolidation behavior of soil and the related pore water pressure changes. The effect of clogging on the deformation behavior and the growth of a clogging column around PHD were studied. Finite element analysis was also conducted to further evaluate the effects of the compression index (lambda) and permeability index (ck) on the soil deformation and clogging column. Empirical equations were proposed to characterize the clogging column and to estimate the consolidation time, serving as references for the analytical model that incorporates time-dependent variations in the clogging column for soil consolidation under vacuum preloading using PHDs.

Background and AimsGlobal climate change is intensifying the co-occurrence of abiotic stresses, particularly combined waterlogging/submergence and salinity, posing severe and escalating threats to woody plant ecosystems critical for biodiversity, carbon storage, and soil stabilization. Despite extensive research on herbaceous species, understanding of woody plant responses remains fragmented and disproportionately focused on specific groups like mangroves and halophytes. This review aims to synthesize and critically evaluate the current state of knowledge on the integrated physiological, morphological, and molecular responses of diverse woody plants to this challenging combined stress scenario.MethodsA comprehensive synthesis and analysis of existing scientific literature was conducted. This involved systematically examining empirical studies, comparative analyses, and theoretical frameworks related to the responses of various woody plant species to the concurrent application of waterlogging/submergence and salinity stress, drawing comparisons to single-stress effects and herbaceous model systems.ResultsThe majority of woody plants exhibit synergistic, more detrimental effects under combined stress compared to either stress alone. Key manifestations include significantly heightened inhibition of photosynthesis, severe disruption of ion (particularly Na+ and Cl-) homeostasis leading to toxicity, and exacerbated oxidative damage. Woody plants utilize core stress tolerance mechanisms analogous to herbaceous species, such as ion exclusion/compartmentalization, activation of enzymatic and non-enzymatic antioxidant systems, and osmotic adjustment via compatible solute accumulation. Crucially, they also deploy distinctive structural and long-term adaptive strategies, including the development of specialized organs (pneumatophores, hypertrophic lenticels), deep root systems for accessing less saline groundwater, and physiological acclimation processes leveraging their perennial nature. Nevertheless, critical knowledge gaps persist, particularly concerning the underlying molecular signaling networks, the mechanisms of long-term adaptation over years/decades, and the specific responses of mature trees in natural ecosystems.ConclusionSignificant gaps hinder a comprehensive understanding of how woody plants cope with combined waterlogging/submergence and salinity stress. To advance fundamental knowledge and inform effective ecological restoration strategies for climate-resilient landscapes, future research must prioritize the application of integrated multi-omics approaches (genomics, transcriptomics, proteomics, metabolomics), the development of high-efficiency genetic transformation techniques for recalcitrant woody species, the deployment of advanced high-throughput phenotyping platforms, and crucially, long-term field-based studies simulating realistic future stress scenarios.

Forest logging activities negatively affect various soil properties. In this study, we focus on the logging effects on soil water retention and associated pore size distribution. We measured the soil-water characteristic curves (SWCCs) on 21 undisturbed samples from three research plots: a reference area, a clear-cut area and a forest track. A total of 12 SWCC points between saturation and wilting point were determined for each sample with a sand box and pressure plate apparatus. The trimodal behaviour is highlighted by the dependence between soil moisture and suction. Therefore, we proposed a revised model by combining two exponential expressions with the van Genuchten model. The exponential terms describe the influence of macro-and-structural porosities, and the latter is used to calculate textural porosity. This new model with eight independent parameters was suitable to fit trimodal SWCCs in all samples. Results revealed that logging had the most destructive effect on large pores, and the soil on the forest track was the most affected. Both soil-air and available water capacity were reduced and the permanent wilting point increased as a result of damage to the soil structure and pore system. Observed increased organic carbon content in compacted soils can be attributed to slowed decomposition due to reduced air capacity and increased waterlogging susceptibility of damaged soils.

Aims The effects of a tropical forest logging road on soil C and N, and the compositions of Actinobacteria, Acidobacteria, and wood rot/lignin-degrading fungal (WRT/LD) decomposer communities were evaluated.Methods and results Soils from a healthy Costa Rican old growth forest before Hurricane Otto and from an adjacent, recently formed logging road built after Hurricane Otto were collected over 4 years and assessed for C and N metrics, and characteristics of the three decomposer communities determined by Illumina amplicon sequencing methods. The Logging Road negatively impacted the soil total organic C, respiration, biomass C, qCO2, and total N, while the Actinobacterial and Acidobacterial communities changed from stable compositions of copiotrophic taxa in the rich forest soil to stable compositions of oligotrophic taxa in the poor logging road soil, and the WRT/LD community changed from stable compositions of copiotrophic taxa in the forest soils to an unstable community of oligotrophic taxa with almost no overlap in genera between logging road soils.Conclusions The logging road negatively influenced 3 decomposer communities and associated C and N metrics, with the two bacterial communities taxonomically stabilizing, but the fungal community taxonomically diverging into an unstable composition over time. Monitoring efforts are on-going to provide local forest land managers with potential indicators of soil ecosystem damage and recovery.

The clogging of porous media with solid particle suspension flow is modeled using two empirical parameters of filtration coefficient (7) and formation damage coefficient (/3). These parameters are typically determined through coreflood tests. This study employs machine learning techniques to predict 7 and /3 using experimental data from open literature. The prediction of /3 is based on critical porosity fraction (gamma) data and a power law equation relating /3 and gamma. Collected data were randomly partitioned into training (80 %) and testing (20 %) subsets. Four regression algorithms were employed, treating 7 or gamma as the target variable, with injection velocity (um), particle concentration (Cin), and ratio of mean pore size (Dpore) to mean particle size (Dp) as features. The extreme gradient boosting (XGBoost) algorithm showed the best performance. The feature Cin had the highest influence on 7 and gamma, revealing a significant finding previously overlooked. Postmortem analyses revealed qualitative consistencies in 7 results, supporting the existence of critical velocities. Furthermore, 7 results showed a power law relation between 7 and all three features used. An equation was formulated to estimate 7 as a function of these three features. A direct prediction of /3 using these features was established by applying the XGBoost model to predict gamma and then employing an existing power law relationship between /3 and gamma. This study demonstrated that machine learning offers an alternative approach for predicting 7 and /3, which is particularly useful for initial evaluations of clogging potentials and identification of experimental conditions to focus on.

Waterlogging, or excessive accumulation of water in the soil, poses significant stress to riparian ecosystems and agroforestry, especially with increasing global rainfall. Cenchrus fungigraminus is a vital agricultural resource, biomaterial, and super-energy plant with high resistance and adaptability. This study examined its morphological and physiological responses under root and above-ground waterlogging for up to 30 days. Results showed that waterlogging significantly inhibited growth, reducing membrane permeability, and root activity, and accelerating leaf senescence (P < 0.05). Despite this, C. fungigraminus achieved 100 % survival after 30 days of waterlogging. The plant adapted to the hypoxic environment by enhancing oxygen channels through cortex cell loosening, lysigenous tissue formation, and adventitious root development. It also activated defense mechanisms, increasing the activities of antioxidant enzymes (SOD, POD, and CAT), levels of non-enzymatic antioxidants (AsA and GSH), osmotic regulators (SS, SP, and Pro), and anaerobic respiratory enzymes (PDC, ADH, and LDH), and hormones (ABA, IAA, GA, and ETH). Under two levels of waterlogging depth, the plant initially adopted the LowO2 escape strategy (LOES), but over time, it transitioned to the Low-O2 quiescence strategy (LOQS), while still retaining some features of the LOES. Our results revealed that C. fungigraminus demonstrates strong adaptability to waterlogging, especially in response to root waterlogging. By employing anatomical adjustments and exceptional cellular defense mechanisms, the species effectively mitigates damage, establishing itself as an excellent forage grass for slope protection under waterlogged conditions. These results offer valuable guidance for selecting waterlogging-tolerant species to restore and rehabilitate degraded riparian ecosystems in the Yellow River Basin, optimize land use in waterlogging-prone areas, and advance the genetic improvement of waterlogging tolerance in other forage varieties.

Global warming-induced abiotic stresses, such as waterlogging, significantly threaten crop yields. Increased rainfall intensity in recent years has exacerbated waterlogging severity, especially in lowlands and heavy soils. Its intensity is projected to increase by 14-35% in the future, posing a serious risk to crop production and the achievement of sustainable development goals. Soybean, a major global commercial crop cultivated across diverse climates, is highly sensitive to waterlogging, with yield losses of up to 83% due to impaired root morphology and growth. Therefore, understanding the stage-specific response of soybean to varying intensities of waterlogging under different climate regimes is crucial to mitigate the impact of climate change. This study evaluated two climate regimes (Summer: C-S and Rainy: C-R), four growth stages (S-15: 15 days after emergence, S-30, S-45, and S-60), and five waterlogging durations (D-2: 2 days, D-4, D-6, D-8, and D-10) using a randomized complete block design (RCBD) with seven replications in 2023. Results revealed that waterlogging adversely affected soybean root morphology (reducing root volume by 8.6% and dry weight by 5.3%) and growth (decreasing leaf area by similar to 6% and dry matter by 48.2%), with more severe effects observed during the summer compared to the rainy season. Among growth stages, soybean was most sensitive at S-45, showing greater reductions in growth attributes and seed yield (similar to 64.9%) across climate regimes. Prolonged waterlogging (2-10 days) had a pronounced negative impact on root and shoot parameters, resulting in yield reductions of 25.4-47.8% during summer and 47.0-68.2% during the rainy season, compared to the control. Yield stability was highest at D-2 (yield stability index: 0.53) with minimal yield reductions, while D-10 caused the greatest yield loss (similar to 58%). Interestingly, the summer climate regime, characterized by bright sunshine hours and higher temperatures, supported better post-stress recovery, leading to higher grain yields. In conclusion, waterlogging during C-R x S-45 x D-10 caused the most substantial yield reduction (similar to 91%).

This paper puts forward a vibrable prefabricated vertical drain (V-PVD) that combines vibrators on PVD to alleviate the clogging on PVD and enhances the reinforcement effect of vacuum preloading method. To validate the reinforcement effect of V-PVD, a full-scale on-site test was conducted including four zones with different V-PVD installations. The ground surface settlement and pore water pressure in each zone were monitored. In addition, a comparative analysis was conducted on vane shear strength and water content before and after soil reinforcement. The test results indicates that the vibrable prefabricated vertical drain in vacuum preloading method can effectively improve the soil reinforcement effect. The ground surface settlement increased by 20.9% to 43.8% compared to conventional vacuum preloading method, and the dissipation value of pore water pressure increased by 17.1% to 58.6%, and vane shear strength increases by 5.9% to 24.5%. The activation of the vibrator helps to remove clogging around PVD, and the more vibrators installed on PVD surface, the better the soil reinforcement effect is achieved. However more vibrators installed on PVD, the drainage area on the PVD surface was influenced and drainage efficiency reduced initially, which implies that a reasonable installation of vibrator should be considered in practice.

Waterlogging is a significant concern in urban areas and can result in severe disruptions and damage and it's an urban problem. This study is conducted in Thoothukudi and Tamil Nadu, which are particularly sensitive to waterlogging because of their geographical and meteorological circumstances. Using synthetic aperture radar (SAR) images from 2015 to 2022, topographical analysis, land use/land cover (LULC) data, and geological insights, this research intends to identify and assess areas prone to water logging. The data source for this study comprises rainfall records from the Indian Meteorological Department (IMD), Sentinel-1 SAR imagery, Sentinel-2 multispectral images from the European Space Agency (ESA), and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM).Terrain analysis was undertaken using DEM to generate elevation, slope, and aspect maps, while SAR data were processed to extract water pixels, which included the extraction of water pixels from SAR data for each year and overlaying them. The overlaid image was correlated with topographic maps to identify the high-risk regions. Key places such as Muthayapuram, Milavittan, Bryant Nagar, and Thalamuthunagar were constantly highlighted as prone to floods. Additionally, the saltpan regions, defined by low-lying water table levels, endure continuous flooding, demonstrating the usefulness of combining SAR imaging with topographic analysis for urban water management. These findings provide useful insights for urban planners and policymakers, underlining the need for deliberate steps to reduce waterlogging, maintain public health, and minimize infrastructure damage, thus enabling sustainable development in Thoothukudi.

The traditional vacuum preloading method of prefabricated vertical drain (PVDs) has been widely used in practical engineering. However, the serious clogging effect around PVDs in the process of vacuum-preloading reinforcement can easily lead to a series of problems such as uneven settlement and large lateral displacement of soil after reinforcement, which seriously affects the application of PVDs in marine clay foundation treatment. In this paper, the effect of combined treatment of marine clay by geotextiles and PVDs on reducing the clogging effect around PVDs was studied by laboratory model experiment. The effects of geotextiles with different diameters and spacings on the surface settlement, excess pore water pressure and lateral displacement of the reinforced soil were analysed. The experimental results show that this method has obvious help on alleviating the above problems, thus providing a reference for the application of geotextile combined with vacuum preloading method to treat marine clay foundation in engineering practice.