Frequent road collapses caused by water leakages from pipelines pose a severe threat to urban safety and the wellbeing of city residents. Limited research has been conducted on the relationship between pipeline leakage and soil settlement, thus resulting in a lack of mathematical models that accurately describe the soil settlement process resulting from water erosion. In this study, we developed an equation for pipeline leakage, conducted physical model experiments on road collapses induced by drainage pipeline leakage, investigated the functional relationship between drainage pipeline leakage and soil settlement, and validated this relationship through physical experiments with pipelines of various sizes. The results indicated that drainage pipeline leakage triggered internal erosion and damaged the soil layers in four stages: soil particle detachment, seepage channel formation, void development, and road collapse. When the pipeline size was increased by a factor of 1.14, the total duration of road collapse induced by pipeline leakage increased by 20.78%, and the total leakage water volume increased by 33.5%. The Pearson correlation coefficient between the theoretical and actual settlement exceeded 0.9, thus demonstrating the reasonableness and effectiveness of the proposed settlement calculation method. The findings of this study serve as a basis for monitoring soil settlement and issuing early road collapse warnings.

The European rabbit (Oryctolagus cuniculus) is a keystone species in Mediterranean ecosystems but also considered a pest in some agricultural areas. Despite its threatened status due to diseases and habitat loss, rabbit populations thrive in motorway verges, causing conflicts with human activities. In this study we examine the factors affecting rabbit warren abundance in motorway verges in central Spain, with implications for conservation and management. The research aimed to assess the importance of infrastructure (e.g. motorway slopes) and landscape (e.g. land use, soil depth) factors on rabbit warren abundance along 1631 km of motorway verges and to develop an index for broader-scale abundance and risk assessment. Using generalized linear mixed models, the study revealed that both infrastructure (slope) and landscape factors (soil depth, vegetation structure and land cover gradients) significantly influenced warren abundance. Rabbit warrens were more abundant in agricultural landscapes with deep soils and in intermediate slope ranges. The findings suggest that rabbit abundance in motorway verges is driven by a combination of factors involving both infrastructure features but also land use in surrounding areas. The derived model predictions were able to correctly discriminate between crop damaged and non-damaged areas, highlighting its potential as a tool for conflict mitigation and conservation planning. The study underscores the need to integrate landscape and infrastructure features into wildlife management strategies to address human-wildlife conflicts effectively. Future work should include direct population monitoring and explore broader ecological impacts, such as predator dynamics and wildlife-vehicle collisions.

The leakage of drainage pipes is the primary cause of underground cavity formation, and the cavity diameter-to-depth ratio significantly affects the overall stability of roads. However, studies on the quantitative calculation for road comprehensive bearing capacity considering the cavity diameter-to-depth ratio have not been extensively explored. This study employed physical model tests to examine the influence of the cavity diameter-to-depth ratio on road collapse and soil erosion characteristics. Based on limit analysis theorems, a mechanical model between the road comprehensive bearing capacity and the cavity diameter-to-depth ratio (FB-L model) was established, and damage parameters of the pavement and soil layers were introduced to modify the FB-L model. The effectiveness of the FB-L model was validated by the data derived from eight physical model tests, with an average deviation of 14.0%. The results indicate a nonlinear increase in both the maximum diameter and fracture thickness of the collapse pit as the cavity diameter-to-depth ratio increased. The pavement and soil layers adjusted the diameter and fracture thickness of the collapse pit to maintain their load-bearing capacity when the cavity diameter-to-depth ratio changed. The fluid erosion range increased continuously with increasing depth of buried soil and was influenced predominantly by gravity and seepage duration. Conversely, the cavity diameter decreased as the buried depth increased, which is associated with the rheological repose angle of the soil. Furthermore, the damage parameters of the pavement and soil layers decrease as the distance from the collapse pit diminishes, with the pavement exhibiting more severe damage than the soil layer. This study provides a theoretical basis for preventing road collapses.

Polypropylene fiber and cement were used to modify iron tailings and applying it to roadbed engineering is an important way to promote the sustainable development of the mining industry. However, the existing studies are mostly concerned with the static mechanical properties, and lack the deformation characteristics of cyclic loading under different loading modes. The effects of fiber content, dynamic-static ratio (Rcr) and curing age on the deformation characteristics of fiber cement modified iron tailing (FCIT) under different cyclic loading modes were explored through dynamic triaxial tests. The research results show that: (1) Polypropylene fibers significantly reduced the cumulative strain of FCIT. Under intermittent loading, the cumulative strain decreased by 36 similar to 43 %, and under continuous loading, the cumulative strain decreased by 48 similar to 55 %. (2) The deformation behavior of FCIT under both intermittent and progressive loading was in a plastic steady state with cumulative strain <= 1 %. (3) The cumulative strain variation of FCIT with intermittent loading of 0.316 % was significantly lower than that with continuous loading of 0.417 %, and the resilience modulus was higher with intermittent loading. (4) The stress history effect of step-by-step loading can be eliminated by the translational superposition method, and the strain evolution law under continuous loading is predicted based on the progressive loading data, and the minimum error between the expected and actual results is 6.5 % when Rcr is 0.1.

The frequent occurrence of extreme rainfall events often triggers levee slope failure (LSF), which, due to the levee effect, significantly damages the roads behind the levee. This paper presents a novel framework for the quantitative risk assessment of roads posed by LSF. Within the framework, the innovative integration of Monte Carlo simulation (MCS) and Material point method (MPM) provides a unique solution for simulating the complicated dynamic relationship between LSF and road destruction. MCS generates precise failure scenarios for MPM simulations, overcoming the limitations of traditional approaches in addressing uncertainty in complex scenario systems. With its technical superiority in capturing post-failure deformations, MPM offers critical insights for assessing road exposure and vulnerability. The framework also accounts for indirect losses from road disruptions, which have long been overlooked. The application of the framework to the risk assessment of the road behind the Shijiao Levee in the Pearl River Basin fully demonstrates its practicality and robustness. Compared to traditional risk assessment methods, the proposed framework provides a more refined dynamic evaluation, facilitating the formulation of more effective disaster mitigation strategies.

Purpose of ReviewForest roads, which are important for accessing and managing forest areas, are particularly vulnerable to damaging impacts of severe climatic events. Understanding how weather changes affect forest roads is important for their efficient management and to ensure their reliability in supporting forest products supply chains. This paper reviews research conducted on the impact of climate factors on forest roads over the past two decades. The aim of our study was to develop a conceptual framework to support adaptation and mitigation strategies in forest road network management, ensuring sustainable wood flow despite a changing climate.Recent FindingsThrough a review of scientific articles and their results, we provided insights and recommendations to increase the resiliency of forest road infrastructures against the effects of climate change. Framed within the principles of climate-smart forestry, this study also offers practical suggestions to maintain the efficiency and safety of wood transportation networks under changing weather conditions, supporting sustainable forest operations and climate adaptation.SummaryThis review highlights how changes in precipitation and temperature patterns caused by climate change can impact forest road infrastructure and wood transportation. Based on the analysis of the reviewed articles, we identified key consequences such as increased erosion, road deformation, and reduced frozen periods. The research provides dedicated actions to ensure sustainability of forest resources and their infrastructure. This review is a key step towards more resilient and adaptive forest road management practices, helping to reduce the impacts of climate change on forest transportation and ecological systems.

Salinization of road base aggregates poses a critical challenge to the performance of coastal roads, as the intrusion of chlorine salts adversely affects the stability and durability of pavement structures. To investigate the cyclic behavior of salinized road base aggregates under controlled solution concentration, c, and crystallization degree, omega, a series of unsaturated cyclic tests were conducted with a large-scale triaxial apparatus. The results showed that variations in solution concentration had a negligible influence on the resilient modulus of road base aggregates, and no significant differences were observed in their shakedown behavior. However, the long-term deformational response of the aggregates was affected by the precipitation of crystalline salt. At low crystallization degrees, a significant increase in accumulated axial strain and a decrease in resilient modulus were observed with increasing omega. Once the crystallization degree exceeded a critical threshold (omega(c)), there was a reduction in accumulated strain and an increase in resilient modulus. The precipitation of crystalline salt also disrupted the shakedown behavior of road base aggregates. During the nascent stages of crystallization (omega < 0.33), the presence of fine crystalline powders and clusters in the saltwater mixture destabilized the soil skeleton, resulting in a transition from the plastic shakedown stage to the plastic creep stage. This poses potential risks to the long-term characteristics and durability of the road base courses.

Assessing environmental impacts and prioritizing projects that minimize ecological harm is essential, especially in regions characterized by diverse climates and geographical features. This study presents a two-phase methodology aimed at optimizing environmental parameter coefficients for asphalt paving projects undertaken by municipalities in Iran. In the first phase, the Genetic Optimization Algorithm is employed to identify, categorize, and cluster coefficients associated with key environmental parameters. The second phase involves the development of a comprehensive environmental index that ranks proposed projects based on the derived coefficients, providing a systematic approach to environmentally conscious decision-making. The results indicate that water resource pollution is the most critical concern prior to project implementation, with a coefficient of 3.59. During the implementation phase, noise pollution emerges as the most significant factor (coefficient 5.89), while ecosystem damage is most pronounced during land use changes (coefficient 5.25). Soil pollution (coefficient 5.81) and local climate damage (coefficient 5.67) are dominant during the maintenance and operational phases, respectively. These findings provide practical insights for prioritizing road infrastructure projects, benefiting both urban and rural planning efforts.

Freeze-thaw cycles significantly affect soil behavior, leading to pavement failures and infrastructure damage, especially in seasonally freezing regions. The application of road salt for deicing operations introduces high salt concentrations into soils, which can alter their physical properties. Salt in soils affects their freezing point, moisture migration, and overall freeze-thaw behavior. This study investigates the effects of varying sodium chloride (NaCl) concentrations on sandy soil using both the ASTM and low-temperature-gradient methods to simulate different freezing protocols. The methodology involved subjecting soil specimens with 0%, 0.2%, 1%, and 5% salt concentrations to freeze-thaw cycles and measuring parameters such as heave rate, maximum heave, water intake, moisture content, and salt migration. The results revealed that increasing salt concentration leads to a reduction in the freezing point, with the 5% NaCl concentration showing the most significant depression at 2.96 degrees C. The heave rate and maximum heave decreased with higher salt concentrations: the 5% NaCl concentration reduced the heave rate to 11.3 mm/day (ASTM method) and 1.5 mm/day (low-temperature-gradient method) from 22.5 mm/day (ASTM method) and 17.2 mm/day (low-temperature-gradient method) in control. Salt migration analysis indicated more variability in salt distribution within the soil profile under the low-temperature-gradient method, especially at higher salt concentrations. This variability is linked to osmotic suction effects, which retain more water within the soil matrix during freeze-thaw cycles. The study highlights the importance of considering both salinity and freezing protocols in understanding soil behavior under freeze-thaw conditions.

The leaching of excessive heavy metals (HMs) from lithium slag (LS) presents a significant challenge for its use in road engineering, necessitating the development of safe treatment methods. This study employed solidification/ stabilization (S/S) technology to develop a magnesium slag-lithium slag composite solidified material (MS-LS). The deformation and displacement characteristics of MS-LS during destruction were analyzed using digital image correlation (DIC). Various microscopic analytical techniques were used to analyze the stabilization mechanisms of MS-LS towards HMs. Results indicated that adding MS significantly improved the compressive strength and resistance to cracking of MS-LS. The minimum strength of the 8 %-MS group reached 2.7 MPa, meeting the strength requirements for subgrade stabilized soil in a first-class highway under heavy traffic load conditions. The development of strength is attributed to improved structural compactness from particle micro-gradation effects and the cementitious hardening action of C-S-H gel. HMs immobilization was achieved through directional adsorption at active sites within the calcium-rich mineral phase and interlayer adsorption within the C-S-H gel, complemented by a physical encapsulation mechanism that reduces HMs leaching. The immobilization rates of Be(II) and Pb(II) in the 8 %-MS group exceeded 95 %, demonstrating the effectiveness of MS in stabilizing these HMs in LS.