Search Results (934)

Groundwater-potential assessment in karst aquifers is complicated by pronounced spatial heterogeneity driven by structural permeability, lithological variability, recharge redistribution, and unresolved subsurface conduit connectivity. Although machine-learning approaches have improved regional groundwater mapping, most existing models provide only deterministic predictions and offer limited information on predictive uncertainty and hydrogeological reliability. To address this limitation, we propose CT-TreeFlow. This probabilistic groundwater assessment framework goes beyond conventional machine-learning models by explicitly learning the full conditional probability distribution of groundwater favourability rather than a single deterministic estimate. The framework integrates sparse probabilistic environmental routing, conditional density estimation, hydrogeologically constrained pseudo-absence generation, geographically structured spatial validation, and explainability-driven interpretation within a unified modelling architecture, enabling simultaneous groundwater prediction, uncertainty quantification, and hydrogeological interpretation. The framework was applied to the Zagros karst system in Khuzestan Province, Iran, using remote-sensing-derived environmental predictors, Copernicus DEM-based morphometric variables, geological–structural datasets, and hydroclimatic indicators. Performance was evaluated against LightGBM and XGBoost using GroupKFold spatial cross-validation. CT-TreeFlow achieved a mean RMSE of 2.737 and a mean R² of 0.852, while also providing spatially explicit uncertainty estimates and probabilistic prediction intervals. Explainability analyses identified fracture density, lithology, drainage organisation, and terrain-controlled recharge conditions as the dominant controls on groundwater favourability. Predicted high-favourability zones showed strong spatial correspondence with major carbonate formations and independent spring–cave inventories, supporting the hydrogeological plausibility of the mapped patterns. These results demonstrate that probabilistic modelling can provide more reliable and physically interpretable groundwater assessments than deterministic approaches in structurally complex karst environments. CT-TreeFlow offers a transferable framework for uncertainty-aware groundwater exploration and regional hydrogeological decision support in heterogeneous aquifer systems. Full article

The dynamics of methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) in groundwater have rarely been investigated. As dissolved gases they may be transported to distant sites and, hence, to the atmosphere. Crumps Cave (CC) is located on a perched aquifer in south-central Kentucky. Water was sampled at a waterfall within the cave located 15 m below the surface, at two adjacent surface wells 15 m and 50 m deep, providing samples from the epikarst and regional aquifer, respectively. Dissolved gases and geochemistry parameters were analyzed for seasonal changes across three years of weekly monitoring (2015–2017) using Kruskal–Wallis H tests and Bonferroni-corrected pairwise comparisons. Dissolved CO₂ concentrations are mainly controlled by percolation through the epikarst, influenced by soil respiration, and vary with rainfall and seasonal temperature fluctuations. CH₄ showed a site-dependent pattern: concentrations were significantly elevated in warm seasons at the shallow and deep wells, where anaerobic conditions and agriculturally derived organic matter promote methanogenesis; no seasonal variation was detected at the cave site, where oxic conditions limit CH₄ year-round. N₂O was significantly elevated in cold seasons at all three sites, driven by cold-season denitrification of agriculturally derived nitrates. N₂O did not differ between sites, indicating seasonal temperature-driven denitrification as the primary control rather than site hydrology, with cold-season denitrification of agriculturally derived nitrates from fertilizer application. Indirect gas emissions are characteristic of karst systems and may be transported or stored in aquifers through complex interactions of groundwater recharge, microbial activity, and seasonal land-use variability. Full article

Machine learning (ML) is increasingly applied to geochemical baseline estimation and anomaly detection in soils and sediments, yet the methodological conditions under which machine learning outperforms traditional approaches—and which preprocessing and validation decisions most consequentially determine that advantage—remain incompletely characterized across environmental and mineral exploration domains. A structured systematic scoping review of 146 records from the Web of Science Core Collection applied sequential filtering to yield 78 thematically eligible studies, from which 20 were prioritized through a composite index integrating age-adjusted citation impact, platform usage, and semantic relevance. Four cross-cutting findings emerge. First, performance gains in environmental applications were driven primarily by spatial model structure rather than algorithm selection: incorporating a spatial covariate derived from geographically weighted regression raised test-set explained variance from $R^2=0.80$ to $R^2=0.96$ for cadmium mobility prediction in a geochemically heterogeneous karst setting, a gain the source study supported with a held-out test set and a Monte Carlo analysis of sensitivity to data size. Second, isometric or centered log-ratio preprocessing was applied in the majority of mineral exploration studies (three of five classical and hybrid studies and four of five deep-learning studies) but in none of the seven environmental studies, representing a systematic methodological gap with direct consequences for covariate importance estimates under compositional closure. Third, Shapley additive explanations and accumulated local effects functioned as instruments of operational value, enabling element-specific anomaly threshold derivation, training sample diagnosis, and grid-cell anomaly type classification; this evidence demonstrates that the accuracy–interpretability trade-off commonly assumed in the machine learning literature is not fundamental in geochemical applications but contingent on algorithm selection. Fourth, 90% of the 20 synthesized studies (18 of 20 by study-area location—13 in China and five in Iran) were evaluated under within-domain validation designs, and the consistently high performance metrics reported should be interpreted as interpolation estimates rather than evidence of transferable predictive capability. Geographic diversification of training datasets and spatially explicit cross-regional validation are identified as structural prerequisites for regulatory-grade applicability. Full article

Agricultural karst watersheds are highly vulnerable to nutrient loss because strong surface water–groundwater (SW–GW) connectivity can rapidly transfer nitrogen and sulfur species from soils, agricultural activities, and human settlements into aquatic systems. However, the coupled behavior and contrasting controls of nitrate (NO₃⁻) and sulfate (SO₄²⁻) in such agroecosystems remain insufficiently understood, limiting effective nutrient and groundwater-quality management. In this study, a typical karst agricultural watershed in Southwest China was selected to investigate the sources, transformation processes, and transport pathways of NO₃⁻ and SO₄²⁻ under strong SW–GW interactions. During the rainy season, 44 groundwater and 40 surface water samples were collected for major hydrochemical and nitrate–sulfate stable isotope analyses. An integrated framework combining hydrochemical analysis, self-organizing maps (SOM), positive matrix factorization (PMF), and MixSIAR were used to identify dominant sources, quantify source contributions, and clarify controlling processes. The results showed that groundwater was mainly characterized by carbonate-controlled Ca-HCO₃ facies, whereas surface water exhibited higher mineralization and a shift toward Ca-SO₄ facies, indicating stronger external inputs and rapid hydrological responses. Nitrate was primarily controlled by external nitrogen inputs, with manure and sewage and soil nitrogen contributing 39–62% and 16–33%, respectively. Nitrate was also regulated by nitrification under oxic conditions, while denitrification was negligible. In contrast, sulfate was predominantly governed by geogenic processes, with sulfide oxidation contributing 63–83%, while other sources were minor. These contrasting controls resulted in distinct spatial and process behaviors: nitrate showed source-driven variability associated with agricultural and domestic inputs, whereas sulfate displayed process-driven accumulation mainly controlled by water–rock interactions. Strong SW–GW connectivity enhanced the transfer of anthropogenic nutrient signals, while subsurface mixing and buffering regulated their expression in groundwater and surface water. These findings demonstrate a clear decoupling between nitrate and sulfate controls in agricultural karst systems and provide a scientific basis for nutrient pollution control, groundwater protection, and sustainable agricultural water management in vulnerable karst regions. Full article

Vegetation net primary productivity (NPP) is a key indicator of terrestrial carbon sequestration and ecological restoration effectiveness. The karst mountainous region of Southwest China is characterized by fragmented terrain and high ecological vulnerability, making quantification of NPP dynamics and drivers essential for regional management. Using MOD17A3 NPP data (2000–2020), this study applied trend analysis, Hurst exponent analysis, partial correlation analysis, residual trend analysis, and Geodetector to investigate NPP spatiotemporal patterns and driving mechanisms in Guizhou Province. Results show a significant increasing trend in NPP (3.653 gC·m⁻²·a⁻¹, p < 0.01), with 78.61% of the area exhibiting growth and a spatial pattern of higher values in the south and lower values in the north. NPP shows persistence, indicating a continued increasing tendency. Along elevation gradients, NPP exhibits a unimodal pattern, peaking at 1000–1200 m, while growth rates increase with elevation and slope, with greater variability at higher altitudes. Temperature exerts a stronger and more extensive influence on NPP than precipitation, with significant correlations over 34.35% and 10.16% of the study area, respectively (p < 0.05). Residual trend analysis indicates that non-climatic factors accounted for a larger share of NPP variation (64.49%) than climatic factors (35.51%), with ecological restoration likely the leading non-climatic driver. Geomorphological type is the primary driver of spatial heterogeneity (q = 0.220), followed by precipitation, temperature, and land use, with interaction effects mainly showing nonlinear enhancement. These findings provide insights for ecological restoration and vegetation management in karst regions. Full article

Understanding how landscape patterns affect habitat quality in fragile karst regions is critical for biodiversity conservation, yet the driving mechanisms remain poorly understood, particularly regarding karst geomorphic heterogeneity. Taking Guizhou Province, a typical karst area of southwestern China, this study integrated land-use and natural geographic data (DEM, karst landforms, soil types, slope, soil thickness, vegetation cover, bedrock exposure, and rocky desertification) from 2000 to 2020. We quantified landscape pattern indices and habitat quality using Fragstats and InVEST, then explored spatial relationships via bivariate spatial autocorrelation and geographically weighted regression (GWR). Results show that land-use intensity increased and landscape structure stabilized, while fragmentation slightly decreased, but connectivity weakened. Habitat quality declined 4.4% over two decades. Globally, habitat quality was positively correlated with aggregation, cohesion, contagion, and largest patch index, and negatively correlated with shape complexity, patch density, diversity, and splitting indices. Locally, six karst zones exhibited distinct clustering patterns, revealing nonlinear interactions between natural vulnerability (e.g., bedrock exposure, thin soil) and human activities. After 2010, the dominant driver shifted from natural conditions to human–land interactions, with human activities contributing approximately 60% of habitat quality degradation. These findings provide a quantitative, spatially explicit basis for ecological zoning and differentiated policy making in Guizhou and similar fragile regions. Full article

The traditional urbanization path based on scale expansion is unsustainable in karst mountainous regions due to fragmented topography and ecological fragility. Taking Guiyang City as a case study, this paper constructs two evaluation indicator systems for urban–rural development and environmental support. Employing the entropy method, coupled coordination degree model, Grey relational analysis, Geodetector, and multi-source spatial analysis methods to examine the evolutionary trajectory, driving mechanisms, and spatial responses of the human–land system from 2000 to 2024. The results show three main findings. First, the comprehensive score of Guiyang’s urban–rural human–land system increased from 0.054 to 0.826, and the coupling coordination degree rose from 0.223 (relative imbalance) in 2000 to 0.903 (high-quality coordination) in 2024, while the environmental support system deviated from the classic environmental Kuznets curve. Second, the driving force has shifted from economic scale to green well-being. The interaction analysis using Geodetector shows that all interaction types fall under the category of two-factor enhancement, among which the interaction coefficient between the number of broadband internet subscribers and other driving factors has the highest explanatory power, with a q-value of 0.949. Third, spatially, the light center distribution stabilized after 2015, and the land use ecological transition index dropped from 0.162 to 0.050 while the D-value continued rising, showing a significant negative correlation (r = −0.89, p < 0.05). Construction land was concentrated in low-slope (0–6°) and mid-elevation (1000–1400 m) basin areas, overlapping with high-quality farmland, and the synchronization rate between economically active areas and construction expansion was 50%. These findings reveal a digital–ecological co-evolution path in karst regions and provide an empirical basis for urban–rural integration governance. Full article

Karst desertification is a major ecological and environmental issue that threatens regional ecological security and sustainable development; its dynamic monitoring is of great significance for evaluating the effectiveness of ecological restoration and promoting regional sustainable development. Based on the Web of Science database, this paper offers a bibliometric-informed narrative review of the evolution of remote sensing monitoring and information extraction technologies for karst desertification from 1987 to 2025. It focuses on analyzing research progress in methods such as multi-source remote sensing data fusion, deep learning models, and integrated GIS analysis, with regard to improving the accuracy of information extraction and the ability to identify spatiotemporal dynamics of karst desertification. This paper also compares the advantages and limitations of different technologies in terms of high-resolution identification and long-term dynamic monitoring. Building on this foundation and drawing on relevant domestic and international research findings, this study examines the development trends and major challenges facing karst desertification monitoring technologies. It further outlines the direction for establishing a long-term, standardized dynamic monitoring system, with the aim of providing a scientific basis for ecological governance and sustainable development in the karst regions of Southwest China. Full article

Karst terrains hold vital global groundwater reserves, underpinning regional water security and ecological stability. To elucidate groundwater hydrochemical patterns and formation mechanisms in Wuhan’s karst zone, this study adopted the Gibbs model, correlation analysis, principal component analysis and positive matrix factorization to explore water–rock interactions, hydrochemical origins, element migration, hydrogeochemical facies and genetic processes. The results show that water in both confined porous loose rock aquifers (CPLRAs) and karst fissure carbonate rock aquifers (KFCRAs) is mainly of HCO₃–Ca and HCO₃·SO₄–Ca types. Carbonate dissolution dominates hydrochemical evolution, with Ca²⁺, Mg²⁺, and HCO₃⁻ as major ions. Natural water–rock interactions control the ionic characteristics of both groundwater types. Silicate weathering exerts a greater influence on water in the KFCRA, while water in the CPLRA has more complex ion sources. Anthropogenic activities contribute 17.52% and 17.61% to their hydrochemical variations, suggesting moderate human influence. Water in the CPLRA is mainly affected by domestic sewage and soil organic nitrogen, locally superimposed with industrial and mining disturbances. Water in the KFCRA is primarily influenced by agricultural pollution, with minor domestic sewage input. These findings provide a scientific basis for sustainable development, protection, and targeted pollution control of groundwater resources in the Wuhan karst area, and offer a reference for hydrochemical studies in comparable karst regions. Full article

Acid mine drainage (AMD) pollution from closed coal mines in karst regions represents a major environmental challenge in the global mining industry. The complexity of hydrogeological conditions in such regions leads to significant challenges in both predictability and controllability of pollution. Taking the Yudong River Basin in Guizhou Province, Southwest China, as the study area, and based on six years (2017–2023) of systematic remediation practices and monitoring data, this study systematically evaluates the effectiveness and applicable conditions of three types of treatment technologies: centralized treatment stations, source control combined with end-of-pipe treatment, and water-sealing ecological plugging. On this basis, governance models applicable to karst regions are distilled. The results show that after six years of remediation, the number of pollution points in the Yudong River Basin decreased from 27 to 12. At the outflow section, the total Fe reduction rate reached 88.3%, the total Mn reduction rate reached 62.3%, and the proportion of contaminated river length was reduced by 78.5%. Each of the three technologies has its own applicable conditions. Centralized treatment stations, characterized by mature technology but high operational costs, are suitable for emergency transition periods. Source control combined with end-of-pipe treatment addresses both symptoms and root causes, making it applicable to complex pollution points. Water-sealing ecological plugging, although cost-controllable, carries a risk of secondary pollution in karst-developed areas. The failure of water-sealing ecological plugging technology is mainly attributed to two mechanisms: bypass flow through karst conduits and overflow induced by water level rise. Based on the six-year remediation practice, this study proposes a source control model for karst conduits centered on the core concepts of “filling, isolating, plugging, intercepting, draining, and controlling”. The implementation process consists of four stages: detailed investigation, graded optimization, stepwise implementation, and long-term monitoring. The core innovation lies in the cross-disciplinary application of coal mine water control techniques to environmental remediation, achieving a shift from passive end-of-pipe treatment to active source control. This model can provide theoretical reference and practical guidance for karst mining areas in Southwest China and other regions with similar geological conditions. Full article

Research on the river-groundwater cross-contamination of per- and polyfluoroalkyl substances (PFAS) in karst regions is limited. We therefore investigated the PFAS occurrence, spatial distribution, sources and ecological risks in the Lijiang River basin, a typical karst area. PFAS concentrations were relatively low (0.08–74.0 ng/L, mean 4.13 ng/L). PFBA, PFHxA, PFNA and 6:2 FTS were widely detected. Short-chain PFAS concentrations (0.08–74.0, mean 4.75 ng/L) were higher than long-chain ones (0.02–3.31, mean 0.72 ng/L). Unusually, groundwater PFAS concentrations (0.08–74.0, mean 7.97 ng/L) exceeded those in rivers (0.08–11.7, mean 2.31 ng/L). Positive matrix factorization (PMF) combined with spatial distribution identified five main sources: sewage treatment plants (24.0%), gas station leaks/wastewater discharges (21.3%), untreated domestic sewage (18.1%), small-scale industrial wastewater (16.7%), and agricultural/aquaculture wastewater (20.2%). The ecological risk assessment showed that, except for PFUnDA posing a low risk to algae, the other PFASs presented no significant risk to algae, daphnia or fish. The human health risk assessment indicated minimal direct health risks. Our findings indicate that some PFASs in groundwater and river water may share common sources, highlighting the complex PFAS migration between rivers and groundwater in karst regions. Full article

Rice (Oryza sativa L.) production is constantly threatened by devastating diseases such as rice blast, bacterial blight, and brown planthopper infestation. The AP2-type transcription factor OsHTR (also known as SMOS1/SHB/RAL1/NGR5/GR5) has been previously implicated in hormonal signaling networks and nitrogen use efficiency; however, its role in disease resistance remains largely unexplored. In this study, we functionally characterized OsHTR in disease resistance using knockout (KO) and overexpression (OE) transgenic lines in the ZH11 background. Transcriptome analysis revealed that differentially expressed genes in the htr mutant were significantly enriched in plant–pathogen interaction pathways, with multiple NBS-LRR and NB-ARC resistance-related genes upregulated. Real-time PCR validation confirmed the upregulation of 15 candidate resistance genes in the htr mutant. Comprehensive resistance evaluations suggested that HTR-KO lines exhibited enhanced resistance to rice blast and bacterial blight compared to wild-type ZH11 and HTR-OE lines, which displayed moderate susceptibility. In contrast, all lines remained highly susceptible to brown planthopper, indicating a disease-specific regulatory function of OsHTR. Furthermore, targeted knockout of individual upregulated resistance-related genes (LOC_Os10g04090, LOC_Os12g29690, LOC_Os02g11980, and LOC_Os11g11770) and OsHTR-interacting gene LOC_Os06g03710 confirmed their distinct contributions to blast and bacterial blight resistance but did not establish them as direct targets of OsHTR. Collectively, our results indicate that OsHTR functions as a negative regulator of disease resistance in rice, likely acting through transcriptional repression of defense-related genes, although direct binding remains to be demonstrated. This study uncovers a novel regulatory module connecting AP2-type transcription factors to disease resistance and provides valuable genetic resources for molecular breeding of broad-spectrum-resistant rice cultivars. Full article

Flexible casing piles can form locally enlarged sections by expanding flexible casings during concrete casting, thereby filling karst cavities and improving the adaptability and bearing capacity of pile foundations in karst areas. However, the damage evolution and failure mechanism of the enlarged section under vertical loading remain insufficiently understood. In this study, a three-dimensional finite element model of a flexible casing pile was established using the Concrete Damaged Plasticity (CDP) model. The stress transfer, plastic strain development, and tensile–compressive damage evolution of the enlarged section under vertical static loading were investigated. The effects of karst cavity spacing, cavity number, and cavity diameter on the vertical bearing behavior were further analyzed. The results show that damage localization is governed by the transition zone between the pile shaft and the enlarged section, where plastic strain, tensile damage localization, and compressive damage accumulation develop in a coupled manner. Increasing the number and diameter of enlarged sections improves the ultimate bearing capacity, whereas cavity spacing mainly controls the interaction and synchronization of damage zones between adjacent enlarged sections. These findings establish a damage-based interpretation for identifying the failure-control region of flexible casing piles in karst cavities and provide a basis for bearing-capacity assessment and structural optimization. Full article

Reservoirs in karst regions exhibit significant carbon sink potential; however, how different reservoir types influence carbon sequestration remains poorly understood. In this study, dual carbon isotopes (δ¹³C–Δ¹⁴C) were applied to trace dissolved organic carbon (DOC) sources in an open reservoir (Aha Reservoir, AHR) and a closed reservoir (Guanshan Lake, GSL) in southwestern China, and to evaluate their carbon sequestration potential. DOC concentrations in GSL were significantly higher than those in AHR (4.14 ± 0.28 mg/L > 3.37 ± 0.30 mg/L) (p < 0.01), along with lower δ¹³C values (−30.34 ± 0.51‰ < −28.18 ± 0.31‰) and more enriched Δ¹⁴C values (−6.94 ± 11.07‰ > −93.74 ± 6.76‰). The δ¹³C–Δ¹⁴C tracing revealed that plants were the primary DOC source for AHR (61 ± 2%), whereas algae dominated DOC sources in GSL (70 ± 2%). Inflow rivers and water retention time (WRT) likely drive differences in DOC sources and concentrations between the two reservoirs. The absence of inflow rivers and the longer WRT in GSL created favorable conditions for algal growth, resulting in substantially higher chlorophyll a (Chl.a) concentrations (103.00 ± 29.87 μg/L > 13.10 ± 3.29 μg/L) and enhanced production of autochthonous DOC through a stronger biological carbon pump (BCP) effect. These conditions further facilitate the formation and accumulation of recalcitrant DOC (RDOC), ultimately increasing DOC concentrations in GSL. Our findings highlight that closed karst reservoirs may represent important yet underappreciated carbon sinks and should receive greater attention in future carbon-sink assessments. Full article

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