Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

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.

Loose sandy soil layers are prone to liquefaction under strong earthquakes, causing damage to civil engineering structures inside or upon the liquefied ground. According to the present Japanese design guideline on liquefaction countermeasures for river levees, the entire depth of the liquefiable subsoil below river embankments should be improved. However, this approach is not economical against deep liquefiable subsoil. To rationalize the design approach, this contribution investigated the performance of a floating-type cement treatment method, in which only the shallower part of the liquefiable subsoil is reinforced. A series of centrifuge shaking table model tests was conducted under a 50g environment. The depth of improvement (cement treatment) was varied systematically, and the effect of the sloping ground was examined. The experimental results revealed that the settlements of river embankments can be reduced linearly by increasing the depth of improvement. Moreover, the acceleration of embankments can be reduced drastically by the vibration-isolation effect between the cement-treated soil and the liquefiable soil. These effects contribute to the safe retention of the embankment shape even when the liquefied sloping ground causes lateral flows. Towards practical implementation, discussions on the effect of permeability on cement-treated soil were expanded. Furthermore, the stress acting on cement-treated soil during shaking was measured using an acrylic block to explain the occurrence of cracks in the soil. (c) 2025 Japanese Geotechnical Society. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

The socio-economic growth of a nation depends heavily on the availability of adequate infrastructure, which relies on essential materials like river sand (RS) and cement. However, the rising demand for RS, combined with its excessive extraction causing ecological damage, and its increasing cost, has raised significant concerns. At the same time, the production of cement contributes significantly to environmental damage, especially through CO2 emissions. In this scenario geopolymer technology has emerged as a sustainable alternative to cement, offering environmental benefits and reducing the carbon footprint of construction materials. This study investigates the impact of replacing RS with copper slag (CS) and laterite soil (LS) in geopolymer mortar (GM) on key properties such as setting time, flowability, compressive strength, and microstructure. The results showed that as LS content increased, setting time and flowability decreased considerably, while increasing CS content caused a reduction in these values. Unlike the other observed parameters, the compressive strength values showed no distinct upward or downward trend. Moreover, the microstructural analysis, including SEM, EDS, XRD, FTIR, TGA and BET, provided valuable insights to support the observed results across various mix designs. Overall, the findings highlight that optimised binary blends of CS, LS and RS not only improved the compressive strength but also enhanced the microstructural characteristics of geopolymer mortar, reinforcing their potential as sustainable and high-performance alternatives to conventional fine aggregates.

This study analyzes the effects of Hurricane Eta on the Chiriqui Viejo River basin, revealing the significant impact of extreme weather events on the hydrological dynamics of the region. The maximum rainfall recorded on November 4, 2020, reached 223.8 mm, while the flow in Paso Canoa reached 638.03 m3/s, demonstrating the magnitude of the event and the inability of the basin to handle such high volumes of water. Through a detailed analysis, it was observed that soil saturation resulted in direct runoff of up to 70.0 mm that same day, which shows that the infiltration capacity of the soil was quickly exceeded. Despite the damage observed, there are currently no advanced hydrological studies on extreme events in critical basins such as the Chiriqui Viejo River. This lack of research reflects a serious lack of planning and assessment of the risks associated with phenomena of this magnitude. One of the most critical problems found is the lack of specialized hydrology professionals, who are essential to carry out detailed studies and ensure sustainable management of water resources. In a context where climate change increases the frequency and intensity of extreme events, the absence of hydrologists in the region puts the resilience of the basin to future disasters at risk. The basin's hydraulic system demonstrated its inability to handle high flows, underscoring the need to improve flood control and water retention infrastructure. In addition, the lack of effective hydrological planning and coordination in the management of hydraulic infrastructures compromises both the safety of downstream communities and the sustainability of hydroelectric reservoirs, vital for the region.

In this paper, the Huangtupo Riverside Slump 1#, a reservoir landslide with double sliding zones in the Three Gorges Reservoir Area of China, is selected as the prototype for a scaled physical model test subjected to water level fluctuation and rainfall. The spatial-temporal characteristics of the multi-physical monitoring data are thus obtained, including the pore water pressure, earth pressure, surface deformation, and deep deformation. Subsequently, the failure mechanism and evolution process of the landslide model are discussed. The results indicate that the rise and fall of reservoir water correspondingly increase and decrease the pore water pressure and earth pressure at the front edge of the model, while having almost no effect on the trailing edge. The rainfall increases the pore water pressure and soil pressure of the entire model, and the increase is proportional to its duration and intensity but limited by the height of overlying soil. Both the surface deformation and deep deformation increase with the fall of reservoir water and rainfall. Except for the weakening effect of the soil caused by the first rise of reservoir water, which results in a certain surface deformation and deep deformation, the surface deformation has almost no response with the subsequent rises, while the deep deformation decreases with the rises. The Riverside Slump 1-1# exhibits the characteristics of retrogressive failure with whole evolution phases, while the Riverside Slump 1-2# exhibits a composite evolution, in which its middle front belongs to the retrogressive failure within the initial deformation, and the trailing edge belongs to the progressive failure within the accelerated deformation.

The large deep-seated deposit landslides are well-developed and exhibit significant deformation activity in the upper Jinsha River, Tibetan Plateau. However, the understanding of their complex deformation mechanism remains limited. As a representative case, the Xiaomojiu landslide is selected to reveal the deformation mechanism of large deep-seated deposit landslides in the upper Jinsha River. The landslide volume is estimated to be approximately 5.04-7.56 x 107 m3, and it can be divided into four distinct zones in plane: source zone, right flank scarp, accumulation zone, and front collapse zone. The buried depth of the deep sliding surface in the middle and front of the landslide is approximately 40-50 m, with several secondary sliding surfaces developed within the landslide deposits. The long-term surface deformation predominantly occurs in the middle and left front of the landslide, which is still in the stage with constant-rate deformation at present. The longitudinal gradient, erosion rate, and steepness index of the Jinsha River are significant factors that contribute to long-term intense river erosion, which is an important factor for the long-term creep deformation of the landslide. Following the Baige landslide in 2018, both the deformation range and rate of the Xiaomojiu landslide increased significantly, indicating that the short-term extreme river erosion events, including barrier lakes and outburst floods, are critical factors contributing to the exacerbated short-term landslide deformation. The free faces of the deeply incised gullies have altered the development directions of tensile fissures and fall scarps on both sides, indicating that these deeply incised gullies caused by precipitation-induced surface erosion have exacerbated the deformation and failure of rock and soil masses. In summary, it can be inferred that the potential instability mode of the Xiaomojiu landslide is characterized as a front-traction and rear-tension type under the combined action of long-term intense river erosion, short-term extreme river erosion, and precipitation-induced surface erosion. The research findings provide new insights into the deformation mechanism of large deep-seated deposit landslide in alpine canyon areas.

Climate change has led to increased frequency, duration, and severity of meteorological drought (MD) events worldwide, causing significant and irreversible damage to terrestrial ecosystems. Understanding the impact of MD on diverse vegetation types is essential for ecological security and restoration. This study investigated vegetation responses to MD through a drought propagation framework, focusing on the Yangtze River Basin in China, which has been stricken by drought frequently in recent decades. By analyzing propagation characteristics, we assessed the sensitivity and vulnerability of different vegetation types to drought. Using Copula modeling, the occurrence probability of vegetation loss (VL) under varying MD conditions was estimated. Key findings include: (1) The majority of the Yangtze River Basin showed a high rate of MD to VL propagation. (2) Different vegetation types exhibited varied responses: woodlands had relatively low sensitivity and vulnerability, grasslands showed medium sensitivity with high vulnerability, while croplands demonstrated high sensitivity and moderate vulnerability. (3) The risk of extreme VL increased sharply with rising MD intensity. This framework and its findings could provide valuable insights for understanding vegetation responses to drought and inform strategies for managing vegetation loss.

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0 degrees C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation-factors associated with energy balance-were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

Study region: The study focuses on the Indus River Basin and southern Pakistan, severely affected by flooding in 2022. Study focus: This study assessed how land surface temperature, snow cover, soil moisture, and precipitation contributed to the deluge of 2022. This study mainly investigated MODIS-AIRS land surface temperature, MODIS snow cover (NDSI), SMAP soil moisture, and GPM IMERG precipitation accumulation. Furthermore, different flood visualization and mapping techniques were applied to delineate the flood extent map using Landsat 8-9, Sentinel-2 MSI, and Sentinel-1 SAR data. New hydrological insights for the region: The region experienced some of the most anomalous climatic events in 2022, such as prolonged heatwaves as observed with higher-than-average land surface temperatures and subsequent rapid decline in snow cover extent during the spring, increased soil moisture followed by an abnormal amount of extreme monsoon precipitation in the summer. The upper subbasins experienced more than 8 degrees C in positive temperature anomaly, indicating a warmer climate in spring. Subsequently, the snow cover declined by more than 25 % in the upper subbasins. Further, higher surface soil moisture values (> 0.3 m3/m3) were observed in the basin during the spring due to the rapid snow and ice melt. Furthermore, the basin received more than 200 mm of rainfall compared to the long-term average rainfall of about 98 mm, translating to about 300 % more rainfall than usual in July and August. The analysis helps understand the spatial and temporal variability within the basin and facilitates the understanding of factors and their intricate connections contributing to flooding.