Search Results (292)

Shallow lakes are vulnerable to multiple anthropogenic stressors. However, the spatial responses of benthic ecosystems to these composite disturbances and the underlying mechanisms driving them remain poorly understood. Nansi Lake is a strategic water-regulating reservoir of the Eastern Route of the South-to-North Water Transfers. It has long been subjected to multiple human activities, and its aquatic ecological environment exhibits pronounced spatial heterogeneity. A systematic assessment is thus needed to evaluate the spatial distribution patterns of surface-sediment diatom communities and their trophic response characteristics. This study integrates the Trophic Diatom Index (TDI) with multivariate statistical approaches. It analyzes the spatial distribution and driving factors of surface-sediment diatom assemblages based on diatom and water quality data from 62 sampling sites. The results reveal three distinct community zones across the lake. The first is a high-disturbance zone dominated by hydraulic regulation and mining activities. In this zone, Stephanodiscus parvus Stoermer & Håkansson is the absolute dominant species, indicating a clear eutrophic status. The second is a hydrochemically stable zone dominated by Achnanthidium minutissimum (Kützing) Czarnecki, exhibiting relatively high community integrity. The third is a vast central open-water zone characterized by the dominance of Pseudostaurosira brevistriata (Grunow) Williams & Round, representing a mesotrophic transitional state. Partial redundancy analysis (pRDA) shows that multiple explanatory variables jointly explain 28.91% of the community variation. The independent explanatory powers of anthropogenic variables (9.12%) and environmental factors (7.94%) are both higher than that of pure spatial dispersal processes (0.35%). Redundancy Analysis (RDA) indicates that different types of human activities—such as reservoir regulation, coal mining, and estuarine inflows—may influence the spatial distribution patterns of surface-sediment diatoms. They do so by jointly driving variations in lake trophic status and the ionic environment, particularly Mg²⁺ and SO₄²⁻. This study provides a scientific basis for the water resource management of shallow lakes subject to anthropogenic impacts. Full article

Intensive human activities are reshaping inland tail-end deltas. Based on hydrological and sediment data from 1950 to 2023 and physical model experiments, this study examines the Ganjiang tail-end delta to analyze channel evolution, driving mechanisms, and management pathways. Results indicate that the Wan’an Reservoir and large-scale sand mining are the dominant drivers of flow-sediment regime shifts and channel reshaping. Sand mining has caused severe riverbed incision, with a local maximum depth of 16.5 m. During the dry season, the flow diversion ratio of the West Branch exceeds 90%, fundamentally altering the flow distribution pattern. Although riverbed incision has enhanced local flood conveyance, the overall flood discharge capacity of the tail-end delta remains limited due to backwater from Poyang Lake, introducing new flood risks. Reduced sediment supply and hydrological changes have exacerbated wetland shrinkage and eutrophication. Physical model experiments show that the comprehensive regulation project can raise dry-season water levels by approximately 5 m through sluice operation, optimize flow diversion, and increase wetland surface water area by 56%. This project integrates flood control, ecological protection, and water resource utilization, representing a proactive exploration of adaptive management for deltas and providing scientific references for understanding evolution and guiding management in similar inland tail-end deltas. Full article

Shallow groundwater in the Dongting Lake area is an important resource for domestic, agricultural, and industrial use, and its quality is essential for regional sustainable development and public health. Therefore, effective protection of this resource is urgently needed. In this paper, we integrate Positive Matrix Factorization (PMF) and Self-Organizing Map (SOM) machine-learning algorithms to conduct an in-depth analysis of the distribution, sources, and risks of toxic elements in shallow groundwater along the southern shore of Dongting Lake. The results indicate that Fe and Mn in the groundwater of the study area are at a severe pollution level, while As is at a light pollution level. The model analysis identified four pollution sources: natural sources (Fe, Mn) accounting for 31.33%, agricultural production (Zn) for 18.96%, traffic-mining mixed source (Pb, Cu, Cd) for 32.67%, and mineral dissolution-redox driven (As) for 17.04%. The average concentrations of Fe and Mn exceeded the standard limits. Although the carcinogenic metal Cd did not pose a health risk, the health risk value of As exceeded the maximum acceptable level, which requires serious attention. The PMF model quantified four potential sources of toxic elements, while SOM was used as a complementary nonlinear clustering tool to examine the consistency of the PMF-derived source contribution patterns. The integrated PMF–SOM framework, together with spatial distribution and geochemical evidence, improved the interpretability and robustness of source identification. Full article

To identify the sources and driving mechanisms of nitrate contamination in pore water around Nansi Lake, 54 pore water samples were analyzed via hydrogeochemical analysis, Gibbs diagrams, ionic ratios, and principal component analysis (PCA). The pore water is predominantly slightly alkaline, with dominant cations Ca²⁺ and Na⁺, and anions HCO₃⁻ and SO₄²⁻. Nitrate-nitrogen (NO₃⁻-N) concentrations range from 0.82 to 54.31 mg·L⁻¹, with a coefficient of variation of 1.41 and an exceedance rate of 18.52%, indicating significant external inputs. A positive correlation between NO₂⁻ and NO₃⁻ suggests denitrification in some areas. Nitrate concentrations exhibit distinct spatial heterogeneity: high concentrations occur in agricultural/aquaculture lakeside plains and urban areas, low concentrations near coal mining subsidence zones, and transitional zones showing outward diffusion. Nitrate sources are predominantly anthropogenic. High Cl⁻ and low NO₃⁻/Cl⁻ ratios indicate domestic and aquaculture wastewater infiltration, whereas low Cl⁻ and high NO₃⁻/Cl⁻ ratios indicate agricultural fertilizer input. Industrial and natural sources are minor. PCA identified three controlling factors (cumulative variance 69.81%): coal mining and industrial/domestic pollution (39.82%), carbonate rock weathering (19.44%), and agricultural activities (10.55%). Health risk assessment shows no significant risk for adults (hazard quotient (HQ) < 1), but children face localized risks at nine sites (HQs of 1.25–2.26) in intensive farming, urban, and transitional zones. Excessive fertilizer application and sewage leakage are the primary causes, posing methemoglobinemia risks to infants. This study provides a scientific basis for nitrate pollution control and sustainable water management in the Nansi Lake Basin and offers methodological insights for similar lacustrine plain regions. Full article

In recent years, unmanned aerial vehicles (UAVs) have increasingly become carrying platforms for Earth observation systems equipped with optical, microwave, and other types of sensors, primarily enabling high-resolution observations of above-ground targets. With the development of geophysical methods, bulky instruments originally designed for deep subsurface detection have been progressively miniaturized and made more lightweight, allowing their integration with civilian UAVs and opening new technological avenues for subsurface investigation. We have developed a semi-airborne transient electromagnetic system based on a UAV that is capable of simultaneously obtaining underground resistivity and polarization rate parameters. A survey was conducted over the M’sesa mining area in the Democratic Republic of the Congo. This is a mine pit that has been abandoned for over 50 years and has been flooded to form a lake, making it difficult to detect its deep mineralization potential using traditional ground-based methods. The results clearly delineate the spatial distribution of the Shangoluwe–M’sesa compressional fault and reveal a deep low-resistivity and high-chargeability zone, which provides clues for the exploration of deep deposits. This study will be of significant importance for accelerating the promotion and application of UAV-based semi-airborne electromagnetic exploration technologies. Full article

Coal-mining subsidence lakes are an expanding artificial wetland type in China, yet the relationships between waterbird diversity components and water-quality and landscape gradients remain unclear. We conducted monthly point-count surveys from January to December 2025 at 28 subsidence lakes in Huaibei, Anhui, China (lake area: 0.01–1.05 km²), and used generalized linear mixed models (GLMMs) to test relationships between waterbird diversity and water quality, lake morphology, landscape composition, and anthropogenic disturbance. Associations differed among diversity components. Species richness was positively associated with surrounding cropland and built-up area, whereas total abundance was positively associated with total nitrogen but negatively associated with total phosphorus, indicating that nutrient-related associations were not uniform across water-quality variables. Both Shannon and Margalef diversity were positively associated with surrounding cropland and also showed positive, context-dependent associations with built-up area. These findings suggest that different components of waterbird diversity were associated with different environmental gradients, with landscape context more strongly associated with richness and diversity indices, whereas water-quality gradients were more strongly associated with abundance. Conserving waterbird diversity in subsidence lakes therefore requires attention not only to nutrient conditions within lakes, but also to the surrounding wetland–farmland landscape context. Full article

The growing demand for Critical Raw Materials (CRMs) requires mining practices that align with sustainability and environmental, social, and governance (ESG) principles, while mining training increasingly benefits from advanced digital tools. Virtual Reality (VR) can provide high-resolution site representations that support both interactive learning and data-oriented analysis without operational risk. This study presents a VR-based framework for the quantitative assessment of pit lake rehabilitation using Virtual Excursions (VEs) developed from panoramic imagery and supported by machine-learning correction. High-resolution 360° panoramic images were used to extract geometric characteristics of a rehabilitated pit lake at the LARCO GMMSA Euboea mine site, Greece, including surface area, shoreline length, mean diameter, and maximum diameter. These image-derived estimates were validated against ground-truth data from field surveys and mine-closure documentation. To reduce systematic deviations associated with panoramic image measurements, a supervised multiple linear regression model was applied as a correction step. Validation based on Root Mean Square Error (RMSE) and the coefficient of determination ($R^2$) showed substantial improvement of the corrected estimates relative to the uncorrected image-based measurements. The results demonstrate that panoramic VR imagery can support site-specific quantitative environmental assessment in addition to its educational value. Although the present findings are limited to a single pit lake case study, the proposed workflow provides a structured basis for integrating immersive visualization, image-based measurement, and regression-based correction in post-mining rehabilitation assessment. Full article

With a typical floodplain in Poyang Lake selected as the study area, this paper employed the remote sensing Waterline Extraction Method (WEM) to invert its topographic changes based on 264 Landsat images from 1987 to 2024. The research systematically revealed the spatiotemporal variations in sediment accretion rates over the past 40 years and their influencing factors. By comparing different WEMs, the object-based method was identified as the most suitable for this study area. Accuracy validation of the topographic inversion showed that when using no fewer than 13 images, the average elevation error rate remained below 7.0%, indicating good reliability. The period from 1987 to 2024 was divided into 15 sub-periods, and digital elevation models of the floodplain were reconstructed for each. Results indicated that: (1) natural floodplain unaffected by sand mining experienced continuous accretion, with an average rate of approximately 3.1 ± 0.7 cm yr⁻¹ (surface elevation change) between 1987 and 2024; (2) in areas impacted by sand mining, the sediment accretion rate after mining (about 1.7 ± 0.8 cm yr⁻¹) was lower than that before mining (about 2.6 ± 2.7 cm yr⁻¹), likely due to the loss of vegetation cover reducing sediment retention capacity; (3) different vegetation types notably influenced accretion rates, with mixed Carex–T. lutarioriparia communities showing a consistently higher rate (about 3.5 ± 0.9 cm yr⁻¹) than pure Carex communities (about 1.7 ± 0.7 cm yr⁻¹), primarily attributable to differences in plant morphology, root architecture, and inundation tolerance. Further analysis revealed that riverine sediment supply was the fundamental material source for floodplain accretion. The phased decline in sediment discharge from the Ganjiang and Xiushui rivers since 1996 generally corresponds to the decreasing trend in sediment accretion rates observed after 2004. Full article

Heavy metal pollution from mining activities and urban runoff poses a serious threat to public health and aquatic ecosystems in vulnerable communities around the Bolivia–Peru transboundary Lake Titicaca basin. This study evaluates the use of two abundant wetland plants—totora (Schoenoplectus californicus) and reed (Phragmites australis)—as low-cost, locally available biosorbents for the removal of dissolved iron (Fe²⁺) from the Pallina River, a major contaminant source to Cohana Bay. Monitoring data from Bolivia’s Ministry of Environment and Water (2019–2022) revealed Fe²⁺ concentrations exceeding the national legal limit (0.3 mg/L) by more than 20 times during the dry season. Laboratory experiments using synthetic Fe²⁺ solutions (20 mg/L) optimized biosorption conditions, identifying pH 5, 4–6 g/L biomass, fine particle size (0.15–0.212 mm), and a 3 h contact time as optimal. Both plants followed pseudo-second-order kinetics and Langmuir isotherms. Totora showed superior performance, achieving a maximum capacity of 7.8 mg/g compared to reed’s 2.9 mg/g. Continuous-flow column tests removed up to 95% of Fe²⁺ from synthetic water. When applied to real Pallina River water, totora achieved 50% Fe²⁺ removal despite reduced efficiency due to competing organic matter. The findings demonstrate the potential of totora-based biosorption as a scalable, nature-based solution for transboundary water management. The policy implications of this study are profound under the national and global water and wetland governance mechanisms and transboundary frameworks like the Binational Autonomous Authority of Lake Titicaca (ALT, est. 1996) and Ramsar Convention. Full article

Resource-dependent development worldwide imposes considerable environmental costs and challenges to regional sustainability, particularly through forming coal mining subsidence areas (CMSAs). Nonetheless, villagers’ relocation intentions within the CMSA remain underexplored. Additionally, previous research on individuals’ relocation intentions has predominantly conceptualized it as a dichotomous variable, overlooking its intrinsic elements. This work aims to explore constitutive elements of relocation intention by developing a universal conceptual framework from the perspective of individuals’ subjective preferences and establishing an integrated model for empirical evaluation. This model combines the analytical hierarchy process (AHP), exploratory factor analysis (EFA), technique for order of preference by similarity to ideal solution (TOPSIS), and obstacle degree model (ODM). Data were collected from the Pan’an Lake CMSA in Xuzhou, China. Results identified core elements of villagers’ relocation intentions, including indicators about houses/farmland destruction at origin and housing quality/services at destination. Notably, we discovered a paradox: aspects expected to deter relocation garner greater attention as intention strengthens. This study advances sustainable relocation governance by exploring internal constitutive elements of individual relocation intention rather than defining it as a dichotomous variable. Additionally, it enhances the evaluation efficiency by determining objective indicator weights from the exploratory factor analysis. Full article

Rainbowfish of the genus Melanotaenia are highly endemic freshwater fishes found only in Australia and New Guinea. Although widespread, most species have narrow geographic ranges, making them particularly vulnerable to environmental change. Currently, 43 described (and many undescribed) Melanotaenia species occur in the Bird’s Head and Bird’s Neck region of Western New Guinea, 29 of which are currently classified as critically endangered, endangered, or vulnerable by the IUCN Red List, including two that may be extinct in the wild. We generated a high-spatial-resolution baseline land cover classification of rainbowfish habitats using low-cloud Planet Labs quarterly basemap mosaics and compared it with a moderate-resolution Landsat 8 OLI-derived classification to assess how spatial resolution influences land cover classification. Using the full 40-year Landsat archive, we quantified decadal land cover change around species type localities and identified localized disturbance events that may affect rainbowfish habitats. For species described from large rivers and lakes, changes in water-body extent over time were quantified. Deforestation varied widely, ranging from little or no detectable change in remote, difficult-to-access locations (e.g., M. misoolensis, M. sneideri), to landscapes heavily modified by logging, urbanization, mining, and agriculture (e.g., M. boesemani, M. arfakensis). Around the type localities, from the high-resolution imagery, we detected ~2939 ha of cleared land, whereas from the Landsat classification we identified only 31 ha of clearing, indicating that most of the fine-scale deforestation was not resolved at the Landsat scale. Time-sequence analyses indicate that over one-third of type localities experienced one or more localized disturbance events over the last 40 years. Land cover change in this region is highly dynamic and differs from commonly studied frontier deforestation patterns elsewhere. It also underscores a critical conservation challenge where rainbowfish species are being discovered in landscapes that are simultaneously undergoing rapid, spatially heterogeneous change. The same infrastructure that enables biological exploration also accelerates habitat modification. These changes threaten the persistence of highly endemic rainbowfish and underscore the value of multi-scale spatial and temporal remote sensing approaches for assessing habitat change in remote, biodiverse regions. The framework presented here is also broadly applicable to other narrowly distributed endemic taxa. Full article

Phosphorus enrichment remains a major driver of eutrophication in lake-feeding rivers, yet effective regulation is hindered by insufficient understanding of the spatiotemporal variability and dominant sources of total phosphorus (TP) at the basin scale. The Xiangjiang River, a major inflow to Dongting Lake, provides a representative system for examining TP dynamics in a human-impacted watershed. An interpretable association rule mining framework was applied to multi-source water quality, hydrological, agricultural, and socio-economic data (2020–2024) to characterize TP variation and quantify source contributions. TP concentrations exhibit pronounced seasonal and hydrological variability, with higher levels during spring and the flood season and lower levels during autumn and low-flow periods, together with a longitudinal increasing pattern from upstream to downstream. Quantitative source apportionment indicates that agricultural non-point sources dominate TP contributions at the basin scale, domestic sources provide a stable secondary contribution, and industrial sources exert localized influences. The spatial organization of source contributions closely corresponds to land-use patterns, with relatively consistent source structures among sites despite local heterogeneity. These results demonstrate the utility of an interpretable association rule mining framework for resolving TP source structures in heterogeneous river basins. The proposed framework offers a transferable approach for phosphorus source identification and supports basin-scale nutrient management and targeted control of agricultural non-point source pollution. Full article

The global lithium supply balance has been under pressure since the recent increase in demand for electric vehicles. Conventional techniques for lithium extraction from natural resources are solar evaporation and hard-rock mining, which both have their limitations in view of sustainability. The question arises whether these methods will suffice for a responsible supply to provide the necessary materials for the emerging green economy. While new technologies for the valorization of lithium from unconventional resources like geothermal brines, salt lakes and seawater are in the pipeline, they are yet to be proven on an industrial scale. Membrane technology, ion-exchange adsorption and electrochemical methods are the current focus of several players in the pilot stage of their announced lithium carbonate or hydroxide production process. These technologies have various advantages and disadvantages in terms of energy consumption, selectivity and process costs, and the optimal choice remains dependent on local factors such as brine composition, energy availability and reagent cost. There are currently several DLE projects in the pilot phase, which is a significant step towards more sustainable lithium supply. Proving the economic and technical viability of these methods for extracting lithium from unconventional sources would increase the amount of globally proven reserves while diversifying and de-risking the supply chain, which is currently heavily dominated by a small number of countries. Full article

Contamination of drinking water by potentially toxic elements (PTEs) remains a critical public-health concern in Uganda. This systematic review compiled and harmonized quantitative concentrations (mg/L) for key PTEs, lead (Pb), cadmium (Cd), arsenic (As), chromium (Cr), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), cobalt (Co), manganese (Mn), and iron (Fe), across various potable and informal water sources used for drinking, including municipal tap water, boreholes, protected and unprotected springs, wells, rainwater, packaged drinking water, rivers, lakes, and wetlands. A comprehensive search of different databases and key institutional repositories yielded 715 records; after screening and eligibility assessment, 161 studies met the inclusion criteria, and were retained for final synthesis. Reported PTE concentrations frequently exceeded WHO and UNBS drinking water guidelines, with Pb up to 8.2 mg/L, Cd up to 1.4 mg/L, As up to 25.2 mg/L, Cr up to 148 mg/L, Fe up to 67.3 mg/L, and Mn up to 3.75 mg/L, particularly in high-risk zones such as Rwakaiha Wetland, Kasese mining affected catchments, and Kampala’s urban springs and drainage corridors. These hotspots are largely influenced by mining activities, industrial discharges, agricultural runoff, and corrosion of aging water distribution infrastructure, while natural geological conditions contribute to elevated background Fe and Mn in several regions. The review highlights associated health implications, including neurological damage, renal impairment, and cancer risks from chronic exposure, and identifies gaps in regulatory enforcement and routine monitoring. It concludes with practical recommendations, including stricter effluent control, expansion of low-cost adsorption and filtration options at household and community level, and targeted upgrades to water-treatment and distribution systems to promote safe-water access and support Uganda’s progress toward Sustainable Development Goal 6. Full article

Surface water is essential for sustaining ecosystems and supporting human socio-economic development, yet pollution from urbanization increasingly threatens its ecological sustainability. The accurate prediction of dissolved oxygen (DO), as an important indicator of water quality, is crucial for water resource protection. To address the methodological gaps in current research, we propose a hybrid deep learning model (GCG) that integrates spatiotemporal correlations to enhance DO prediction accuracy through the systematic exploitation of latent data dependencies. This study proposes a three-stage modeling framework: (1) A novel adjacency matrix construction methodology based on Pearson correlation coefficients is developed to quantify spatial correlations between monitoring stations, enabling spatial feature aggregation via graph convolutional networks (GCNs); (2) the spatially enhanced features are subsequently processed through 1D convolutional neural networks (CNNs) to capture temporal local patterns; (3) model performance is comprehensively evaluated using four metrics: R², RMSE, MAE, and MAPE. The proposed model was implemented for DO prediction in Lake Taihu, China. Experimental results demonstrate that compared to conventional adjacency matrix construction methods, the Pearson correlation-based adjacency matrix confers advantages, achieving at least a 5% reduction in RMSE and over 10% improvement in MAE and MAPE. Furthermore, the GCG model outperformed the comparison model, with an R² enhancement of 8%, while reducing RMSE and MAE by over 70% and 60%, respectively. These results validate the model’s effectiveness in mining spatiotemporal correlations for regional water quality forecasting, offering a reliable tool toward sustainable water monitoring and ecosystem-based management. Full article