Flash floods are often responsible for deaths and damage to infrastructure. The objective of this work is to create a data-driven model to understand how predisposing factors influence the spatial variation of the triggering factor (rainfall intensity) in the case of flash floods in the continental area of Portugal. Flash floods occurrences were extracted from the DISASTER database. We extracted the accumulated precipitation from the Copernicus database by considering two days of duration. The analysed predisposing factors for flooding were extracted considering the whole basin where each occurrence is located. These factors include the basin area, the predominant lithology, drainage density, and the mean or median values of elevation, slope, stream power index (SPI), topographic wetness index (TWI), roughness, and four soil properties. The Random Forest algorithm was used to build the models and obtained mean absolute percentage error (MAPE) around 19%, an acceptable value for the objectives of the work. The median of SPI, mean elevation and the area of the basin are the top three most relevant predisposing factors interpreted by the model for defining the rainfall input for flash flooding in mainland Portugal.

Tree destruction induced by heavy rainfall, an overlooked type of forest degradation, has been exacerbated along with global climate change. On the Chinese Loess Plateau, especially in afforested gully catchments dominated by Robinia pseudoacacia, destructive rainfall events have increasingly led to widespread forest damage. Previous study has manifested the severity of heavy rainfall-induced tree destruction and its association with topographic change, yet the contributions of tree structure and forest structure remain poorly understood. In this study, we quantified the destroyed trees induced by heavy rainfall using light detection and ranging (LiDAR) techniques. We assessed the influence of tree structure (tree height, crown diameter, and crown area), forest structure (tree density, gap fraction, leaf area index, and canopy cover), and terrain parameters (elevation, slope, and terrain relief) using machine learning models (random forest and logistic regression). Based on these, we aimed to clarify the respective and combined contributions of structural and topographic factors to rainfall-induced tree destruction. Key findings revealed that when considered in isolation, greater tree height, crown diameter, crown area, leaf area index (LAI), and canopy cover suppressed tree destruction, whereas higher gap fractions increased the probability of tree destruction. However, the synergistic increases of tree structural factors (tree height, crown diameter, and crown area) and forest structural factors (LAI and canopy cover) significantly promoted tree destruction, which can counteract the inhibitory effect of terrain on destruction. In addition, increases in tree structure or canopy density (LAI and canopy cover) also increased the probability of tree destruction at the same elevation. Our findings challenge conventional assumptions in forest management by demonstrating the interaction of tree structure and canopy density can significantly promote tree destruction during heavy rainfall. This highlights the need to avoid overly dense afforestation in vulnerable landscapes and supports more adaptive, climate-resilient restoration strategies.

The practice of widening levees to mitigate frequent river flooding is globally prevalent. This paper addresses the pressing issue of sand-filled widened levee failures under the combined effect of heavy rainfall and high riverine water levels, as commonly observed in practice. The primary objective is to illuminate the triggering mechanism and characteristics of such levee failures using the well-designed physical model experiment and Material Point Method (MPM), thus guiding practical implementations. Experimentally, the macro-instability of the levee, manifested as slope failure within the sand-filled widened section, is primarily triggered by changes in the stress regime near the levee toe and continuous creep deformation. Upon failure initiation, the levee slope experiences a progressive failure mode, starting with local sliding, followed by global sliding, and ultimately transitioning into a flow-like behaviour, which characterises the slide-to-flow failure pattern. The slope failure along the interface between the original and new levees is the result of shear deformation rather than the cause. Parametric studies conducted using the calibrated MPM model reveal a critical threshold for the widening width, beyond which the volume of sliding mass and travel angle exhibit no further variation. Increasing the cohesion of the river sand used for levee widening demonstrates the most pronounced improvement in levee stability in the face of the combined effect of intense rainfall and elevated river levels. The MPM-based evaluation of common slope protection measures demonstrates the superior protective benefits of grouting reinforcement and impervious armour layer protection, providing valuable insights for reinforcement strategies in levee engineering applications.

Predicting cumulative surface slope displacements induced by rainfall infiltration is crucial for accurately assessing the risks to potentially affected infrastructure. In this paper the numerical modelling of the case history of Miscano slope is presented. Plaxis 2D code has been used adopting two constitutive laws: the linear elastoplastic model (Mohr-Coulomb, MC) and the Hardening Soil with small strain stiffness (HSsmall). The aim is to test the suitability of these constitutive laws in predicting the hydro-mechanical behaviour of clayey soil slope. Based on long-term field measurements, the parameters of MC and HSsmall have been determined by back analysing the first-year field measurements in terms of cumulative surficial horizontal displacements and pore water pressure. Subsequently, the numerical models have been validated against the analogous field measurements collected from the second year. The numerical models predict with a good agreement the field measurements for both years. In terms of cumulative surficial horizontal displacements, the HSsmall underestimates the field measurements by 21.2% at the end of the first year, while that based on MC exhibits a 32.8% overestimation. Moreover, the initialization procedure clearly affects the cumulative surficial horizontal displacements results obtained with both the HSsmall and MC models for the second year. In fact, the best results have been achieved when the second-year net rainfall have been applied starting from the initial phase used to generate the lithostatic stress state.

The sulphated gravel embankment in seasonal frozen soil regions may experience deformation problems such as salt expansion, frost heave, and settlement under rainfall percolation conditions and changes in environmental temperature, affecting considerably its normal use. In response to these issues, relying on the renovation and expansion project of an international airport in northwest China, this paper used a self-designed temperature control testing device and conducted indoor constant temperature tests and freeze-thaw cycle tests using on-site natural embankment filling, and conducted numerical simulation tests using the COMSOL Multiphysics software programme. This paper investigated the characteristics of temperature variation, moisture, salt migration, and deformation of sulphated gravel in seasonal frozen soil regions under rainfall percolation conditions. The results indicated that under environmental temperature changes in the range of- 10-25 degrees C, the temperature at which sulphated gravel salt expansion and frost heave occur was approximately-8 degrees C, and the deformation sensitive depth range from 0 to 200 mm. The moisture and salt contents of soil samples would experience a sudden increase due to rainfall percolation, with the sudden increase in moisture in the soil sample with a salt content of 0.9 % lagging that of the soil sample with a salt content of 0.5 % by one freeze-thaw cycle. Rainfall percolation significantly enhanced the settlement deformation of sulphated gravel during freeze-thaw cycles. The primary causes of soil deformation include the upward migration of water vapour, the downward percolation of moisture, and rainfall. These factors contribute to the destruction of the soil structure and alter the contact modes between soil particles, resulting in soil loosening and settlement deformation.

Extreme rainfall causes the collapse of rammed earth city walls. Understanding the depth of rainwater infiltration and the distribution of internal moisture content is crucial for analyzing the impact of rainfall on the safety and stability of these walls. This study focuses on the rammed earth city wall at the Mall site in Zhengzhou. Based on Richards' equation, the water motion equation of rammed earth wall is deduced and established. The change of moisture content of rammed earth wall and the development of wetting front under rainfall condition are studied. The stability of the rammed earth city wall under rainfall infiltration is analyzed by finite element methods. The results show that the water motion equation can effectively describe the moisture distribution inside the rammed earth city wall during rainfall. As the rainfall continues, the wetting front deepens, and the depth of the saturated zone increases. Just below the wetting front, the moisture content decreases rapidly and eventually returns to its initial value. the water motion equation provides a theoretical basis for analyzing water-related damage in rammed earth walls. Factors such as the initial soil moisture content, rainfall duration, and rainfall intensity significantly influence the distribution of the wetting front and moisture content. The saturation of the upper soil layers reduces the shear strength of the shallow soil, leading to a decrease in the safety factor, which can result in shallow landslides and collapse of the rammed earth wall. The research results can provide theoretical support for the analysis of water infiltration law of rammed earth city walls under rainfall conditions, and provide reference for revealing the instability mechanism of rammed earth city walls induced by rainfall. (c) 2025 Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The interface between geotextile and geomaterials plays a crucial role in the performance of various geotechnical structures. Soil-geotextile interfaces often suffer reduced performance under environmental stressors such as rainfall and cyclic loading, limiting the reliability of geotechnical structures. This study examines the influence of gravel content (Gc), compaction degree (Cd), and rainfall duration (Rd) on the mobilized shear strength at the silty clay-gravel mixture (SCGM)- geotextile interface through a comprehensive series of direct shear tests under both static and cyclic loadings. A novel approach using Polyurethane Foam Adhesive (PFA) injection is introduced to enhance the interface behavior. The results reveal that increasing Gc from 0 % to 70 % leads to a 35-70 % improvement in mobilized shear strength and friction angle, while cohesion decreases by 15 %-60 %, depending on Cd. A higher Cd further boosts shear strength by 6 %- 70 %, influenced by Gc and normal stress levels. Under cyclic loading, increasing displacement amplitude reduces shear stiffness (K), while having minimal impact on the damping ratio (D); K and D appear unaffected by the number of cycles in non-injected samples. Rainfall reduces mobilized shear strength by 8 %-25 %, depending on the normal stress, with a 47 % drop in friction angle and a 24 % increase in cohesion after 120 minutes of rainfall exposure. In contrast, PFA-injected samples exhibit a marked increase in mobilized shear strength under both dry and wet conditions, primarily attributed to enhanced cohesion. Notably, PFA treatment proves particularly effective in maintaining higher shear strength and stiffness in rainfall-affected interfaces, demonstrating its potential in improving geotextile-soil interaction under challenging environmental conditions.

From July 26 to July 28, 2024, a rare heavy rainfall associated with Typhoon Gaemi triggered widespread clustered landslides in Zixing City, Hunan Province, China. The severe disaster caused 50 fatalities and 15 missing persons across 26 villages, damaging 11,869 houses and affecting a total of 128,000 individuals. Timely and accurate event analysis is essential for deepening our understanding of landslide clustering mechanisms and guiding future disaster prevention efforts. To achieve this, remote sensing analysis using satellite and unmanned aerial vehicle (UAV) aerial images was conducted to assess the distribution pattern of landslide clusters and explore their relationship with environmental factors. Field investigations were subsequently carried out to identify the failure mechanisms of representative landslides. The results identified three main landslide clustering areas in the eastern mountainous forest region of Zixing City. The landslides are predominantly shallow soil slides, with their distribution closely linked to rainfall thresholds and lithology. The clustering areas typically received cumulative precipitation exceeding 400 mm during the extreme rainfall event. Lithology significantly influences the composition and thickness of slope soils, which in turn controls sliding patterns and affects landslide distribution density and individual landslide size. Granite residual soils contributed to the highest landslide density, with many large individual landslides. Topography and vegetation also play important roles in landslide formation and movement. This study provides preliminary insights into the clustered landslide event, aiding researchers in quickly understanding its key features.

Wildfires are increasingly recognized as a critical driver of ecosystem degradation, with post-fire hydrological and soil impacts posing significant threats to biodiversity, water quality, and long-term land productivity. In fire-prone regions, understanding how varying fire intensities exacerbate runoff and erosion is essential for guiding post-fire recovery and sustainable land management. The loss of vegetation and changes in soil properties following fire events can significantly increase surface runoff and soil erosion. This study investigates the effects of varying fire intensities on runoff and sediment yield in the Kheyrud Educational Forest. Controlled burns were conducted at low, moderate, and high intensities, along with an unburned plot serving as the control. For each treatment, three replicate plots of 2 m2 were established. Runoff and sediments were measured over the course of 1 year under natural rainfall. In addition, key soil physical properties, including bulk density, penetration resistance, and particle size distribution (sand, silt, and clay fractions), were assessed to better understand the underlying mechanisms driving hydrological responses. The results revealed that bulk density and penetration resistance were lowest in the control and highest for the high-intensity fire treatment. A significant correlation was observed between bulk density, penetration resistance, and both runoff and sediment production. However, no significant correlation was found between runoff and soil texture (sand, silt, and clay content). Fire intensity had a pronounced effect on runoff and sediment, with the lowest levels recorded in the control and low-intensity fire treatment, and the highest in the high-intensity fire treatment. The total annual erosion rates were 0.88, 1.10, 1.57, and 2.24 tons/ha/year for the control, low-, moderate-, and high-intensity treatments, respectively. The study demonstrates that high-intensity fires induce substantial changes in soil structure and vegetation cover, exacerbating runoff and sediment loss. To mitigate post-fire soil degradation, proactive forest management strategies are essential. Preventive measures-such as reducing fuel loads (e.g., removing uprooted trees in beech stands), minimizing soil compaction and vegetation damage during logging operations, can help reduce the ecological impact of wildfires. These findings provide a scientific basis for adaptive management in fire-prone forests, addressing urgent needs to balance ecological resilience and human activities in wildfire-vulnerable landscapes.

With the continued development of water resources in Southwest China, fluctuations in water levels and rainfall have triggered numerous landslides. The potential hazards posed by these events have garnered considerable attention from the academic community, making it imperative to elucidate the landslide mechanisms under the combined influence of multiple factors. This study integrates laboratory tests and numerical simulations to explore the instability mechanisms of landslides under the combined effects of rainfall and fluctuating water levels, as well as to compare the impacts of different factors. Results indicate that the sensitivity of landslide deformation decreases as the number of water level fluctuations increases, exhibiting a gradually stabilizing tendency. However, the occurrence of a heavy rainfall event can reactivate previously stabilized landslides by increasing pore water pressure and establishing a positive feedback loop with rainfall infiltration. This process reduces boundary constraints at the toe of the slope, promotes the development of an overhanging surface, and ultimately leads to overall instability and landslide disaster. Under the same rainfall intensities, the presence of water level fluctuations prior to rainfall significantly shortens the time for the landslide to reach a critical state. The key mechanisms contributing to landslide failure include terrain modification, fine particle erosion, and outward water pressure, all of which generates substantial destabilizing forces. This research offers valuable insights for the monitoring, early warning, and risk mitigation of landslides that have already experienced some degree of deformation in hydropower reservoir areas.