Search Results (513)

The karst region of Southwest China represents a typical high geological background area characterized by extensive carbonate bedrock and secondary enrichment of heavy metals, particularly cadmium (Cd), in residual soils. Under natural carbonate-buffered conditions, Cd is largely immobilized through mineral associations and surface complexation, resulting in elevated total concentrations but low bioavailability. However, intensified anthropogenic pressures–including acid deposition, mining, excessive fertilization, and improper irrigation—have accelerated soil acidification in paddy fields. Acidification disrupts carbonate geochemical equilibria, weakens buffering capacity, and drives Cd speciation shifts toward more labile forms, thereby enhancing plant uptake and accumulation. These effects are especially pronounced in paddy fields and other systems subject to hydrological and redox fluctuations that further increase Cd mobility. To evaluate these coupled geogenic and anthropogenic controls, we conducted a structured literature synthesis (2016–2026) focusing on peer-reviewed studies of Cd dynamics in Southwestern China’s karst agroecosystems. We critically examine (i) the formation mechanisms and spatial heterogeneity of high-background Cd, (ii) acidification-driven speciation transformation and soil–crop transfer pathways, and (iii) in situ remediation and precision risk assessment strategies. By integrating geological inheritance, geochemical activation, and ecological risk perspectives, this review proposes a conceptual framework to support soil quality standard refinement and adaptive risk management in high-background karst regions. Full article

This study presents a comprehensive analysis of a landslide that occurred in February 2024 in the Tau-Samal district of Almaty, Kazakhstan. Characterized by rapid onset and anthropogenic influence, this event resulted from a complex interaction of environmental and anthropogenic factors. Specifically, the landslide was triggered by seasonal temperature fluctuations leading to multiple freeze–thaw cycles, localized microseismicity (magnitude 3.5 on 4 February 2024), and a major water main break resulting in localized flooding of loess soils. The study utilizes an integrated landslide susceptibility index (LSI) model, which combines the analytic hierarchy process (AHP) for factor weighting. Validation was conducted by comparing the spatial distribution of high-susceptibility zones derived from the LSI model with the actual location of the landslide. Geotechnical studies highlight the susceptibility of Almaty loess, focusing on parameters such as cohesion, internal friction angle, and liquefaction potential. The findings highlight the need for climate-adapted urban policies and improved geotechnical monitoring in high-risk loess areas. This study contributes to a regional understanding of Tien Shan geohazards by placing the Tau-Samal event within the broader context of seismically and hydrologically driven slope processes. Full article

Hydraulic failure in levees, river embankments, and earth dams represents a critical challenge in flood risk management, particularly under increasing climate-induced hydrological stresses. This study presents a systematic literature review of numerical, probabilistic, and data-driven modeling approaches used to assess hydraulic failure mechanisms in earthen flood-protection structures. A structured search was conducted in Scopus, Web of Science, and Taylor & Francis for peer-reviewed English-language journal articles published between 2015 and 2026. Following duplicate removal, title and abstract screening, and full-text eligibility assessment, 65 studies were included in the final synthesis. Based on the synthesis, an integrated mechanism–model–uncertainty framework is developed to relate hydraulic loading conditions, soil response, dominant failure mechanisms, appropriate numerical modeling approaches, uncertainty treatment, and climate-related stressors. This study provides valuable insights for engineers, researchers, and policymakers by identifying key advances, limitations, and future research directions for improving levee resilience. Study quality was assessed using a structured quality assessment rubric. The review protocol was not registered in a public registry, and no external funding was received. Full article

Gravity Recovery and Climate Experiment (GRACE) satellites primarily monitor changes in land water storage, including groundwater, soil moisture, lake and river surface water, and canopy and snow water. However, its coarse spatial resolution of 0.25 degrees limits its ability to observe smaller basins. To assess aquifer depletion and evaluate a long-term water resource management framework, GRACE data are crucial. It remains rare for GRACE-focused studies to be conducted in great depth. A comprehensive review of 80 articles published between 2011 and 2025 was conducted using the Scopus and Web of Science databases. These articles focused on downscaling GRACE data using machine learning (ML) methods. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines were used in this review. This study highlights the attributes of ML models, the input variables used, the evaluation metrics, and the output resolution. Based on the analysis of the articles, random forest (RF) methods were used in the majority of the papers. Gradient boosting (GB), artificial neural networks (ANN), support vector machines (SVM), support vector regression (SVR), and long short-term memory (LSTM) were the most widely used ML methods. As input variables, rainfall (Pr), soil moisture (SM), and runoff (Qs) are essential. In 2011, there were very few journal articles; since 2021, the number has increased. The number of published studies from China was the highest (24), followed by the USA (12) and Iran (9). A total of 38 journals published reviewed articles. In terms of articles, Remote Sensing generates 19%, Journal of Hydrology has 10%, and Journal of Hydrology: Regional Studies has 8%. The paper also discusses limitations, challenges, recommendations, and potential future directions for improving the accuracy of the GWS change prediction model. Full article

Wildfires may significantly alter the mineralogical and microstructural characteristics of geological materials, leading to increased susceptibility to landslides, debris flows, and other related hazards. These processes may involve considerable post-fire hydrological changes that affect the infiltration rate and the surface runoff in the burned soils. In the present study, a laboratory experimental investigation is carried out focusing on the water infiltration in burned soils which were produced in a muffle furnace at accurately controlled temperatures within 400 °C∼800 °C. The original and burned soils were first subjected to a number of geotechnical tests, including grain size distribution, consistency, and hydraulic conductivity. Subsequently, their water infiltration rates were measured in a laboratory setup. Finally, numerical simulations are performed to assess the infiltration process based on the Green–Ampt model. The experimental results reveal significant differences in the hydrological behavior between burned and unburned soils. Overall, burned soils experienced quicker ponding and slower infiltration. However, as the burning temperature increased from moderate to high, the infiltration rate also rose considerably, along with delayed ponding time. This trend may be related to the microstructural change in the grain size distribution explored experimentally in the present study. The numerical results are highly consistent with the experimental data. The hydraulic conductivity is identified as the predominant parameter in the infiltration process examined and simulated in the present study. Its evolution with varied burning temperatures can also be traced to the fire-induced alteration in the grain size distribution, and primarily accounts for the differences in the infiltration of different soil specimens. The present study demonstrates the potential of laboratory experiments complemented with a quantitative modeling approach in improving our understanding of soil’s post-fire hydrological responses. Full article

Groundwater level (GWL) variations in the arid regions of Northwest China are driven by both natural processes and human activities. Identifying causal links between hydrological variables is fundamental to understanding groundwater evolution and conducting dynamic simulations. This study integrates the Mann–Kendall test, Seasonal-Trend decomposition using Loess, and the Peter and Clark Momentum-threshold and Momentary Conditional Independence (PCMCI) causal inference to analyze GWL variation characteristics and causal response processes across seven sub-basins in the Tarim Basin using multi-source remote sensing data. Results show an overall decline in GWL, primarily in the north-central part of the basin, with the Kaidu–Konqi River Basin reaching a maximum rate of 0.51 m/year. The trend components reveal localized depletion alongside broad stability, while seasonal components exhibit three types of temporal shifts in fluctuations. A mismatch exists between the prevalence of environmental influences and their causal strength. Daytime land surface temperature (LST_D), surface runoff (RO), and evapotranspiration (ET) show the highest detection frequencies, yet volumetric soil water in layers 2 (SWVL₂) and RO exhibit the largest ranges in strength and drive variations at specific sites. Response times are asymmetric. Negative effects from ET on GWL transmit quickly, while positive recovery is slow. Conversely, positive recharge from volumetric soil water in layer 1 (SWVL₁) is faster than its negative lag. At the basin scale, surface processes recharge GWL while mediating indirect influences from other variables. Climate and agricultural irrigation act as direct sinks. Depending on local conditions, three regional patterns emerge: direct climate-driven depletion, obstructed shallow water retention, and indirect compensation from agricultural water use. Causal networks indicate that RO and SWVL₁ have the highest centrality and dominate water output, whereas SWVL₂ acts as a passive receiver. Pathways from the surface to GWL are also asymmetric. The most frequent path involves step-by-step infiltration along RO → ET → SWVL₁ → SWVL₂ → GWL. In contrast, the paths with the highest cumulative strength are shorter and faster, specifically RO → ET → GWL and RO → SWVL₁ → GWL. The identified pathways and lag parameters provide a direct basis for groundwater dynamic modeling and water resource management in the basin. Full article

Coastal groundwater in monsoon-dominated regions faces compounding threats from seasonal hydrological extremes and seawater intrusion (SWI), yet the molecular-scale response of dissolved organic matter (DOM) remains poorly understood. We conducted a two-season investigation in Mannar District, Sri Lanka, integrating hydrochemistry, fluorescence spectroscopy, and Fourier-transform ion cyclotron resonance mass spectrometry to characterize DOM dynamics across shallow and deep groundwater. Dry-season chloride averaged 302 mg/L (shallow—5 to 12 m) and 505 mg/L (tube wells—20 to 30 m), then declined by 60–80% during monsoon recharge. Despite this freshening, DOM dynamics were decoupled from salinity: shallow wells showed dry-season DOC peaks (6.64 mg/L) driven by soil concentration, while tube wells exhibited wet-season enrichment (5.02 mg/L). Shallow aquifers maintained consistently high humification indices (around 0.70) and aromatic-rich DOM, indicating sustained buffering by soil-derived inputs. In contrast, wet-season recharge in tube wells appeared to stimulate microbial processing, as indicated by elevated protein-like fluorescence (C2: 26% to 36%) and a higher contribution of nitrogen-bearing formulas (CHONs: 31.4% to 37.1%). Tube wells also accumulated reduced, energy-rich DOM with correspondingly high molecular lability indices. Paradoxically, correlation networks suggested that these saturated aliphatic and halogenated structures persist due to kinetic protection under low oxygen, high-salinity conditions. These findings indicate that aquifer structure and redox conditions control DOM biogeochemistry in coastal groundwater systems. At the molecular level, DOM dynamics are influenced by aquifer depth and seasonal recharge, leading to a decoupling between salinity and organic matter transformation. Full article

Soil electrical resistivity (SER) is widely used as an indirect indicator of soil physical, chemical, and hydrological properties and plays an important role in applications such as grounding system design, geotechnical site characterization, agricultural soil monitoring, and environmental contamination assessment. However, SER is strongly influenced by environmental variables including soil moisture content, temperature, salinity, and soil texture, which makes accurate prediction challenging under heterogeneous field conditions. A systematic review was conducted following the PRISMA 2020 protocol using the Scopus database to identify peer-reviewed studies published between 2018 and 2026 related to predictive models of soil electrical resistivity based on environmental parameters. After applying defined inclusion and exclusion criteria, a set of relevant studies was selected for qualitative and comparative analysis. The reviewed studies consistently identify soil moisture content as the most frequently reported influential factor affecting SER, followed by temperature, salinity, and soil texture. This observation reflects the predominant focus of the analyzed literature within the selected time frame rather than a definitive representation of all controlling physical processes. Similarly, the reviewed literature suggests that empirical and statistical models remain valuable due to their simplicity and interpretability, whereas machine learning approaches such as artificial neural networks, support vector regression, and ensemble methods are often reported to achieve higher predictive accuracy in complex soil environments. The predictive SER modeling represents a rapidly evolving research field, and future work should focus on hybrid physics-informed machine learning models, the development of standardized datasets, and the integration of predictive algorithms with emerging sensing technologies and IoT-based monitoring systems. Full article

As a critical link between regional economic development and ecological security, understanding the dynamics of water retention is essential for sustainable water resource management in the Huaihe River Economic Belt. This study explores the spatio-temporal evolution and spatial explanatory factors of water retention across five temporal snapshots (2003, 2008, 2013, 2018, and 2023). Based on the InVEST model, we assessed water retention capacity at both grid and spatial development levels, thereby obtaining the retention characteristics of different land-use types and their responses to land-use transitions. Furthermore, a parameter-optimized geographical detector was employed to quantify the relative contributions of climatic-environmental and social-economic factors to the spatial variance of the modeled water retention index. Results indicate that the total water retention capacity exhibited significant interannual fluctuations, with the net capacity in 2023 being lower than the initial level in 2003. Retention values displayed obvious spatial heterogeneity, with high levels concentrated in the southwest and north and low levels distributed in the central area, closely mirroring precipitation distribution. While forest land exhibited the strongest unit water retention capacity, cropland contributed the most to the total volume (50.49%) due to its predominant areal proportion (73.92%). Notably, the conversion of forest to cropland was spatially associated with the most substantial loss in the modeled retention capacity. Soil saturated hydraulic conductivity and land-use type were identified as the dominant factors explaining the spatial variance of water retention. These findings underscore the methodological utility of coupling the InVEST model with a parameter-optimized geographical detector. For practical ecosystem management, the results suggest that spatial planning policies should strictly limit the conversion of ecological lands to agricultural use and prioritize targeted soil hydrological improvements in the central plains to secure long-term water resources. Full article

Ecological restoration—whether active or passive—includes forest development, forest rehabilitation, and a range of other activities that contribute to ecosystem services. To provide a formal framework, we hypothesized how does reforestation (through different forestry practices) affect the conservation of soil functionality? That is, how does reforestation/afforestation/forest restoration improve soil quality? And, specifically, how do they improve physical properties (such as structural stability, infiltration) and chemical properties (such as acidity, electrical conductivity)? For this purpose, we conducted a bibliometric analysis review of the peer-reviewed scientific literature and research reports of numerous articles in order to compile a large database of forest restoration studies, with an emphasis on the Mediterranean region. The final focus was to obtain conclusions about how it affects soil quality. Overall, our examination confirms that deforestation drives a decline in soil carbon and nitrogen, subsequently impairing microbial activity. Consequently, forest removal frequently leads to accelerated erosion, nutrient depletion, and compaction. In contrast, reforestation acts as a critical intervention, stabilizing soil structure, reestablishing fertility, and enhancing soil quality overall. Additionally, three case studies are synthetically presented concerning the short-, medium-, and long-term results of forest restoration projects carried out mainly in central and northern Spain. These cases corroborate the significant role of forest restoration in the control and enhancement of ecosystem services, particularly in relation to soil improvement, the enhancement of hydrological regulation processes within watersheds (runoff, infiltration, erosion), landscape amelioration, and the socio-economic aspects of rural environments. Ultimately, forest restoration is established as a necessary and essential practice in ecological restoration efforts to counteract the impacts of anthropogenic activities. Full article

Soil preferential flow plays a crucial role in governing hydrological cycles and soil moisture distribution in mountain forests. This makes it essential for understanding subsurface water movement and for guiding hillslope hydrological management. In this study, soil preferential flow, soil properties, and root characteristics across three slope positions on a Larix gmelinii var. principis-rupprechtii (Mayr) Pilger (larch) plantation hillslope in the Liupan Mountains were systematically observed to reveal the spatial patterns and formation mechanisms of hillslope soil preferential flow. The results showed that soil preferential flow development followed a distinct spatial pattern across the slope positions, with the mid-slope exhibiting the most developed preferential flow characteristics. The comprehensive preferential flow index further quantified this spatial variation, ranking the slope positions as mid-slope > upper slope > lower slope. Different soil structural properties exerted varying influences on preferential flow. Macropore-related properties (low bulk density and high porosity and saturated conductivity) promoted most preferential flow, whereas aggregate-related properties (high organic matter and water-stable aggregates) suppressed it. The influence of root characteristics on preferential flow was also dual. Root length density generally promoted preferential flow (e.g., DC, LI, and UniFr), whereas root surface area density primarily exerted an inhibitory effect (e.g., LI, UniFr, and total stained area TotStAr). This study clarifies how slope position modulates preferential flow through soil and root characteristics, offering insights for slope-specific hydrological understanding and targeted soil and water conservation practices. Full article

Sediment accumulation in reservoirs represents a critical challenge for sustainable water resources management in semi-arid regions. In Jordan, accelerated sedimentation threatens the operational capacity of major dams, including the King Talal Dam (KTD), which serves as a key water resource in the Amman–Zarqa Basin (AZB). This study assesses sediment yield and erosion risk at the catchment scale using the Soil and Water Assessment Tool (SWAT) integrated with the Modified Universal Soil Loss Equation (MUSLE). The AZB was subdivided into 31 sub-basins and 586 Hydrological Response Units (HRUs) based on land use, soil characteristics, topography, and slope. The model was calibrated for the period 1993–2002 and validated for 2003–2012 using hydrological and sediment observations from 17 monitoring stations. Long-term simulations covering more than two decades were conducted to quantify spatial and temporal sediment yield patterns across the basin. Results indicate a mean annual sediment yield of 2.79 t ha⁻¹ yr⁻¹, corresponding to approximately 0.59 MCM yr⁻¹ of sediment inflow to the reservoir. These estimates closely agree with bathymetric survey results reported by the Jordan Valley Authority, which indicate sedimentation rates of 2.59 t ha⁻¹ yr⁻¹ (0.55 MCM yr⁻¹). Overall, the model demonstrates strong agreement between observed and simulated sediment loads, confirming its reliability for sediment dynamics assessment. The findings are relevant to Sustainable Development Goals (SDGs) 6 (clean water and sanitation) and 15 (life on land) by informing sustainable watershed and soil erosion management practices. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article

The genus Juniperus species is widely distributed in the Northern Hemisphere of the planet Earth. These species are notable for their ability to adapt to extreme environmental conditions, playing a crucial role in ecosystem structure and function. Currently, their expansion is being driven by anthropogenic activities and climate change, posing significant challenges for both control and conservation. The objective of this review was to synthesize the available evidence regarding the ecological importance and impacts of Juniperus on ecosystems, promoting a holistic perspective that contributes to the achievement of the United Nations 2030 Agenda for Sustainable Development. A systematic literature search was conducted using the Scopus database, and only the documents published between 2001 and 2025 were considered for the investigation. The results showed that these species possess a high ecological versatility, favoring their invasive success in disturbed ecosystems, particularly under the influence of climate change and land-use changes. Conversely, Juniperus species facilitate positive ecological outcomes by providing essential ecosystem services that benefit both the human population and the flora and fauna present in these ecosystems. Nevertheless, their expansion also causes negative effects, such as the suppression of herbaceous shrubs and understory cover, alteration of the hydrological function, and accelerated soil erosion, among others. Consequently, the genus Juniperus exhibits a dual ecological role, acting as a hero to many species within these ecosystems, yet a villain to others. In this sense, given its remarkable adaptive dynamism under scenarios of climate change and continuous anthropogenic alterations, it is imperative to promote comprehensive conservation and restoration strategies. These should include ecological monitoring, invasive species control, genetic management, and habitat restoration. Such efforts must be supported by long-term interdisciplinary research to understand and mitigate the ecological, genetic, and social impacts resulting from its expansion. Furthermore, these investigations and strategies must be flexible and locally contextualized to promote genuine ecosystem resilience in the face of the ongoing environmental transformations. Full article

Using perfluorooctanoic acid (PFOA) as a representative highly mobile solute to isolate hydrological controls, we investigated how slope influences the partitioning of vertical and lateral transport pathways. While vertical percolation has been widely examined using conventional column leaching tests, lateral transport driven by topographic gradients remain insufficiently quantified under controlled conditions. Here, laboratory-scale inclined leaching experiments were conducted to resolve the distribution of solute transport among vertical leachate, lateral runoff, and solid-phase retention under systematically varied slope angles (0°, 4°, 9°, and 20°), flow regimes, and leaching volumes. Results show that solute migration shifted from vertical-dominated transport under flat conditions (91% at 0°) to lateral-dominated export at moderate slopes, with lateral pathways accounting for up to 75% of the recovered mass at 9°. This pathway shift was well described by an exponential partitioning model, f₁(α) = f_max (1 − e^−kα), where f_max = 0.80 and k = 0.34°⁻¹ (R² = 0.97), indicating a critical crossover threshold at approximately 4° slope. Flow regime interacted with slope angle to modulate lateral transport efficiency: slower flow enhanced lateral export at moderate slopes, whereas faster flow promoted peak lateral transport under steeper conditions. In contrast, solid-phase retention remained consistently low (5–9%) across all treatments, indicating that the observed redistribution patterns were primarily governed by hydrological pathway partitioning rather than sorption processes. These results demonstrate that even modest topographic gradients can fundamentally alter solute transport pathways in sloped soils. The slope-dependent pathway partitioning framework developed here provides a process-based basis for incorporating lateral transport into hillslope hydrological models and for improving assessments of contaminant redistribution in both managed and natural landscapes. Full article