Search Results (380)

Groundwater is one of the main sources of water supply in tropical developing countries; however, its integrated management is often constrained by limited hydrogeological information and increasing anthropogenic pressures on aquifer systems. This study presents the numerical modeling of groundwater flow in the Neogene–Quaternary aquifer system of the Middle Magdalena Valley (Colombia), focusing on the rural area of Puerto Wilches, which is characterized by strong surface–groundwater interactions, particularly with the Yarirí wetland and the Magdalena River. A three-dimensional model was implemented and calibrated in FEFLOW v.8.1 under steady-state and transient conditions, integrating both primary and secondary data. The dataset included piezometric levels measured with water level meters and automatic loggers, hydrometeorological records, 21 physicochemical and microbiological parameters analyzed in 45 samples collected during three field campaigns under contrasting hydrological conditions, 79 pumping tests, detailed lithological columns from drilled wells, and complementary geological and geophysical models. The results indicate a predominant east–west groundwater flow from the Eastern Cordillera toward the Magdalena River, with seasonal recharge and discharge patterns controlled by the bimodal rainfall regime. Microbiological contamination (total coliforms in 69% of groundwater samples) and nitrate concentrations above 10 mg/L in 21% of wells were detected, mainly due to agricultural fertilizers and domestic wastewater infiltration. Particle tracking revealed predominantly horizontal flow paths, with transit times of up to 800 years in intermediate units of the Real Group and around 60 years in shallow Quaternary deposits, highlighting the differential vulnerability of the system to contamination. These findings provide scientific foundations for strengthening integrated groundwater management in tropical regions under agroindustrial and hydrocarbon pressures and emphasize the need to consolidate monitoring networks, promote sustainable agricultural practices, and establish preventive measures to protect groundwater quality. Full article

Under the ongoing trend of climate warming and increasing humidity on the Qinghai–Tibet Plateau, the Three River Source Region (TRSR) has shown strong sensitivity to global climate change. Its vegetation change is particularly worthy of attention and research. The Normalized Difference Vegetation Index (NDVI) is a key indicator for assessing the growth status of vegetation. However, the insufficiency of existing NDVI datasets in terms of spatiotemporal continuity has limited the accuracy of long-term vegetation change studies. This study proposed a machine learning-based downscaling framework that integrates the Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI and the Global Inventory Monitoring and Modeling System (GIMMS) NDVI data to reconstruct a long-term, high-resolution NDVI dataset. Unlike conventional statistical fusion approaches, the proposed framework employs machine learning-based nonlinear relationships to generate long-term, high-resolution NDVI data. Three machine learning algorithms—Random Forest (RF), LightGBM, and CatBoost—were evaluated. Their performance was validated using the MODIS NDVI as reference, with the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and Pearson’s correlation coefficient (R) as evaluation metrics. Based on model comparison, the CatBoost model was identified as the optimal algorithm for spatiotemporal data fusion (R² = 0.9014, RMSE = 0.0674, MAE = 0.0445), significantly outperforming RF and LightGBM models and demonstrating stronger capability for NDVI spatiotemporal reconstruction. Using this model, a long-term, 1 km monthly GIMMS-MODIS NDVI dataset from 1982 to 2014 was successfully reconstructed. On the basis of this dataset, the spatiotemporal variation characteristics of vegetation in the TRSR from 1982 to 2014 were systematically analyzed. The research results show that: (1) The constructed long-series high-resolution NDVI dataset has a high consistency with MODIS NDVI data; (2) From 1982 to 2014, the NDVI in the TRSR showed an increasing trend, with an average growth rate of 0.0020/10a (p < 0.05). NDVI showed obvious spatial heterogeneity, characterized by a decreasing gradient from southeast to northwest. (3) The Yellow River source exhibited the most evident vegetation recovery, the Yangtze River Source area showed a moderate improvement, whereas the Lancang River Source area displayed little noticeable change. (4) Broad-leaved forests experienced the most significant growth, while cultivated vegetation displayed a marked tendency toward degradation. This study provides both a high-accuracy long-term NDVI product for the TRSR and a methodological foundation for advancing vegetation dynamics research in other high-altitude regions. Full article

Kumamoto is a city in Japan that relies completely on groundwater for drinking water. Groundwater in the Kumamoto region divided into shallow and deep aquifers. Around Lake Ezu, where one of Kumamoto City’s largest tap-water source wells are located, groundwater from both aquifers mixes, resulting in numerous springs. The aim of this study was to identify and quantify the relative contributions of the groundwater sources that discharge into Ezu Lake. River, lake, spring, and artesian well samples were collected every month between April 2021 and March 2022, and groundwater chemistry data for the shallow and deep aquifers were obtained from previous studies. The NO₃⁻ and SO₄²⁻ concentrations indicated three end-members: (A) high NO₃⁻ from anthropogenic sources, (B) high SO₄²⁻ from Shirakawa River water, and (C) low NO₃⁻ and SO₄²⁻ from denitrification or dilution. Mixing analysis show 60–70% from A, 17–22% from B, and 7–25% from C for the lake waters. Also, the result showed that springs in the Kami-Ezu area were dominated by shallow aquifer water, whereas artesian wells in the Shimo-Ezu area reflected deep aquifer water. This is the first time that the contributions of groundwater sources in this area have been quantified using a three-component mixing approach. Furthermore, it was estimated that Shirakawa River infiltration, including the artificial recharge project from rice paddy, contributed approximately 57% to groundwater discharge into Ezu Lake in 2020. These results provide new insights into the contribution of artificial recharge from agricultural land to groundwater. Full article

Antibiotic resistance genes (ARGs) have emerged as globally concerning environmental contaminants, posing serious threats to ecosystem health and public safety. This systematic review summarizes global research trends on ARGs across three key aspects: (i) identification and distribution in river and lake ecosystems, (ii) sources and environmental behaviors, and (iii) ecological and human health risks. Concentration data of ARGs in various rivers and lakes across China were compiled to reveal their spatial distribution patterns. The analysis of ARGs sources and environmental behaviors provides essential insights for designing effective mitigation strategies. Furthermore, this review highlights the potential ecological and human health hazards of ARGs and discusses limitations and improvement directions of current risk assessment methodologies. The main findings indicate that ARGs are widely present in rivers and lakes across China; higher abundances occur in eastern and southern regions compared with central–western and northern areas, such as 4.93 × 10²–8.10 × 10³ copies/mL in Qinghai Lake and 6.7 × 10⁷–1.76 × 10⁸ copies/mL in Taihu Lake. The environmental behaviors of ARGs are highly complex, involving multiple mechanisms and influenced by climatic conditions, nutrient levels, and additional environmental factors. Based on these findings, future efforts should prioritize long-term site-specific monitoring, evaluate their prolonged impacts on aquatic ecosystems, and develop integrated risk assessment models to support evidence-based environmental management. Full article

The Wushan Loess, situated in the Yangtze Three Gorges region of China, represents the southernmost aeolian loess deposit in China and provides critical insights into Late Pleistocene paleoenvironmental conditions and East Asian monsoon dynamics. Despite its significance, the genesis and provenance of this unique loess deposit remain controversial. This study employs an integrated multi-proxy approach combining detrital zircon U-Pb geochronology, optically stimulated luminescence (OSL) dating, and detailed grain size analysis to systematically investigate the provenance and depositional mechanisms of the Wushan Loess. Three representative loess–paleosol profiles (Gaotang-GT, Badong-BD, and Zigui-ZG) were analyzed, yielding 17 OSL ages, 729 grain size measurements, and approximately 420 analyses per profile were conducted, yielding 1189 valid ages (GT 406, BD 391, ZG 402). OSL chronology constrains the deposition period to 18–103 ka (Marine Isotope Stages 2–5), coinciding with enhanced East Asian winter monsoon activity during the Last Glacial period. Grain size analysis reveals a dominant silt fraction (modal size: 20–25 μm) characteristic of aeolian transport, with coarse silt (20–63 μm) averaging 47.1% and fine silt (<20 μm) averaging 44.2% of the sediments. Detrital zircon U-Pb age spectra exhibit consistent major peaks at 200–220 Ma, 450–500 Ma, 720–780 Ma, and 1800–1850 Ma across all profiles. Kernel Density Estimation (KDE) and Multi-Dimensional Scaling (MDS) analyses indicate a mixed provenance model. Non-negative least squares (NNLS) unmixing confirms this quantitative source apportionment., dominated by proximal contributions from the upper Yangtze River basin (including the Three Gorges area and Sichuan Basin, ~65%–70%), supplemented by distal dust input from the Loess Plateau and northern Chinese deserts (~30%–35%). This study establishes for the first time a proximal-dominated provenance model for the Wushan Loess, providing new evidence for understanding southern Chinese loess formation mechanisms and Late Pleistocene East Asian monsoon evolution. Full article

This study systematically investigates settlement sites that record living patterns of ancient humans, aiming to reveal the interactive mechanisms of human–environment relationships. The core issues of landscape archeology research are the surface spatial structure, human spatial cognition, and social practice activities. This article takes the Han Dynasty settlement site in Sanyangzhuang, Neihuang County, Anyang City, Henan Province, as a typical case. It comprehensively uses ArcGIS 10.8 spatial analysis and remote sensing image interpretation techniques to construct spatial distribution models of elevation, slope, and aspect in the study area, and analyzes the process of the Yellow River’s ancient course changes. A regional historical geographic information system was constructed by integrating multiple data sources, including archeological excavation reports, excavated artifacts, and historical documents. At the same time, the sequences of temperature and dry–wet index changes in the study area during the Qin and Han dynasties were quantitatively reconstructed, and a climate evolution map for this period was created based on ancient climate proxy indicators. Drawing on three dimensions of settlement morphology, architectural spatial organization, and agricultural technology systems, this paper provides a deep analysis of the site’s spatial cognitive logic and the ecological wisdom it embodies. The results show the following: (1) The Sanyangzhuang Han Dynasty settlement site reflects the efficient utilization strategy and environmental adaptation mechanism of ancient settlements for land resources, presenting typical scattered characteristics. Its formation mechanism is closely related to the evolution of social systems in the Western Han Dynasty. (2) In terms of site selection, settlements consider practicality and ceremony, which can not only meet basic living needs, but also divide internal functional zones based on the meaning implied by the orientation of the constellations. (3) The widespread use of iron farming tools has promoted the innovation of cultivation techniques, and the implementation of the substitution method has formed an ecological regulation system to cope with seasonal climate change while ensuring agricultural yield. The above results comprehensively reflect three types of ecological wisdom: “ecological adaptation wisdom of integrating homestead and farmland”, “spatial cognitive wisdom of analogy, heaven, law, and earth”, and “agricultural technology wisdom adapted to the times”. This study not only deepens our understanding of the cultural value of the Han Dynasty settlement site in Sanyangzhuang, but also provides a new theoretical perspective, an important paradigm reference, and a methodological reference for the study of ancient settlement ecological wisdom. Full article

This study collected 820 topsoil samples from cultivated lands across Ningxia, covering the Yellow River irrigation area, the central arid zone, and the southern mountainous region. The ordinary kriging were spatially interpolated to analyze As, Hg, Cd, Cr, and Pb heavy-metal pollution spatial patterns. Pollution was evaluated using the Nemerow and geoaccumulation (I_(geo)) indices, and sources quantified via Pearson correlations, PCA (Principal Component Analysis), and PMF (Positive Matrix Factorization). The results indicated that Hg and Cd posed the highest ecological risks. The overall mean concentrations (mg.kg⁻¹) of Hg, Cd, As, Pb, and Cr were 0.04, 0.27, 9.91,23.81, and 57.34, respectively. Compared with the background values, they were 1.90, 2.41, 0.83, 1.14, 2.74 times higher, respectively. Geospatially, regions with higher pollution probabilities for Cd, Cr, Pb, Hg, and As were concentrated in the northern and central parts of Ningxia, whereas the southern region exhibited lower pollution probabilities. pH significantly influenced the accumulation and spatial distribution of heavy metals in soil. Source apportionment identified three primary contributors: transportation and natural parent materials (As, Pb, Cr), industrial activities (Hg), and agricultural practices (Cd). Hg and Cd were identified as the key risk elements requiring prioritized management. These results enhance understanding of the pollution levers of heavy metals in Ningxia cultivated soils, and also provide foundation for developing more scientific and precise soil risk control policies, offering significant practical value for environmental risk management. Full article

PM_2.5 is the primary source of urban atmospheric pollution, as it not only damages the ecological environment but also poses a threat to human health. Taking the Yangtze River Economic Belt as the research object, this study analyzes the spatiotemporal variation characteristics of PM_2.5 concentrations in the region from 2005 to 2020. Furthermore, by combining the Geodetector model with Geographically and Temporally Weighted Regression (GTWR) model, the spatiotemporal heterogeneity of its influencing factors is revealed at three scales: municipal, watershed, and grid. The results show that, from 2005 to 2020, the annual average PM_2.5 concentration in the Yangtze River Economic Belt exhibited an inverted U-shaped trend with 2013 as the inflection point, showing distinct spatial clustering characteristics. Overall, the spatiotemporal variation in annual average PM_2.5 concentration demonstrated a significant downward trend during this period, with slower decline rates in the western region and faster rates in the central and eastern regions. Spatial differentiation of annual average PM_2.5 concentrations within the region was primarily influenced by three factors: PFA, PISA, and PD. NDVI and PWA exerted their effects mainly at large scales, while MAT and SDE primarily acted at small scales. Within the region, NDVI and CVO predominantly suppressed PM_2.5 concentrations, whereas MAT, PFA, PD, and SDE primarily promoted PM_2.5 pollution. The spatial distribution of effects for factors within the same category is broadly consistent across the three scales, though details vary. This study overcomes previous limitations of administrative-scale research, yielding more refined results. It provides new methodologies and insights for future research while offering more precise scientific support for regional PM_2.5 governance. Full article

This research examines the otolith microchemical characteristics of the critically endangered kunming snout trout (Schizothorax grahami) collected from the sources section endemic to the Chishui River, China, a tributary of the upper Yangtze River, and the metal concentrations in the water of fish habitats. Among the analyzed elements, strontium (Sr) exhibited consistent distribution patterns across otolith rings, as observed through face-scan imagery (scanning the polished surface of the otolith cut), with a relatively low coefficient of variation. Statistical analysis using a paired two-tailed t-test revealed significant differences in Sr:Ca ratios among samples from the three river sections. Notably, magnesium (Mg) levels in the otolith core during the early life stages of the fish were notably higher compared to non-core regions. Similarly, Mg concentrations of water were elevated in the spawning grounds relative to non-spawning areas. This suggests that otolith Mg content may be influenced by the specific water conditions of the spawning grounds. Furthermore, Mg:Ca ratios in the otolith core displayed significant variation among samples from U3, L2, and other sites, implying that the fish in these samples originated from distinct spawning locations. These findings demonstrate that strontium and magnesium in otoliths can serve as effective markers for reconstructing the life history of S. grahami in the Chishui River and can contribute to the management of different fish stocks. Full article

Understanding the interactions among ecosystem services (ESs) and their spatiotemporal dynamics is pivotal for sustainable ecosystem management, particularly in arid regions where water scarcity imposes significant constraints. This study focuses on the Ili River Valley, a representative arid region, to investigate the evolution of ESs, their trade-offs and synergies, and the underlying driving mechanisms from a water-resource-constrained perspective. We assessed five key ESs—soil retention (SR), habitat quality (HQ), water purification (WP), carbon sequestration (CS), and water yield (WY)—utilizing multi-source remote sensing and statistical data spanning 2000 to 2020. Employing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, Spearman correlation analysis, Geographically Weighted Regression (GWR), and the Geodetector method, we conducted a comprehensive analysis at both sub-watershed and 500 m grid scales. Our findings reveal that, except for SR and WP, the remaining three ESs exhibited an overall increasing trend over the two-decade period. Trade-off relationships predominantly characterize the ESs in the Ili River Valley; however, these interactions vary temporally and across spatial scales. Natural factors, including precipitation, temperature, and soil moisture, primarily drive WY, CS, and SR, whereas anthropogenic factors significantly influence HQ and WP. Moreover, the impact of these driving factors exhibits notable differences across spatial scales. The study underscores the necessity for ES management strategies tailored to specific regional characteristics, accounting for scale-dependent variations and the dual influences of natural and human factors. Such strategies are essential for formulating region-specific conservation and restoration policies, providing a scientific foundation for sustainable development in ecologically vulnerable arid regions. Full article

River water quality is a direct determinant of both drinking water security and regional economic vitality. However, the hydrochemical trajectories and solute provenance of agricultural streams remain only fragmentarily understood. Here, we examine the Jinqian River—a representative agricultural tributary of the Danjiangkou Reservoir source area for the South-to-North Water Diversion Project—by coupling hydrochemistry with multivariate statistics techniques. The results revealed that the pH values of the river water ranged from 7.55 to 8.30, indicating a weakly alkaline condition. During all three hydrological periods, the concentrations of total nitrogen (TN) exceeded the limits set by the Class Ⅲ surface water quality standards in China, suggesting that the agricultural river has been significantly impacted by human activities. Solute dynamics followed three rainfall-modulated patterns: (i) dilution-driven decreases in the flood season (e.g., Na⁺), (ii) concentration via flushing or evaporative concentration (e.g., SO₄²⁻), and (iii) reservoir-induced damping of seasonal contrasts (e.g., TN), the latter attributable to nitrogen retention behind upstream dams. Geochemical fingerprints reveal that Cl⁻ and Na⁺ originate predominantly from halite dissolution; Ca²⁺, Mg²⁺ and HCO₃⁻ from coupled carbonate–silicate weathering; and SO₄²⁻ from evaporite dissolution. Principal component analysis distills four dominant quality controlling factors: agricultural fertilizers, halite weathering, evaporite dissolution, and domestic effluent. These findings provide a quantitative basis for managing nutrient and salt fluxes in agricultural rivers and for safeguarding water sustainability within water-diversion source regions. Full article

Constructing ecological security patterns (ESPs) from an ecosystem services perspective is critical for sustaining regional ecological stability. However, existing research often overlooks the complex trade-offs among multiple ecosystem services. This study focuses on the Shiyang River Basin, assessing four key ecosystem services in 2021: habitat quality, water yield, soil retention, and carbon sequestration. Ecological sources were identified using the Ordered Weighted Averaging (OWA) method. Subsequently, the minimum cumulative resistance model in conjunction with circuit theory was employed to delineate ecological corridors, identify pinch points, and detect barrier points. Spatial syntax analysis was employed to assess the network’s structural characteristics. The results revealed 46 ecological sources covering 12,336.34 km² (29.7% of the study area), along with 94 corridors, 80 pinch points, and 39 barrier points. Based on these findings, a regional ecological framework—“Three Zones, Three Corridors, One Belt, and Multiple Points”—is proposed to guide ecosystem service optimization. Full article

Investigating how China’s most extensive grassland conservation program, the Grazing Withdrawal Project, impacts herders’ resilience and welfare levels is crucial for promoting sustainable grassland protection and enabling herders to withstand external shocks. However, few empirical studies have linked policy measures, economic resilience, and subjective well-being. Based on 266 questionnaires from the Yellow River Source Region, we constructed an indicator system for evaluating economic resilience and employed multiple linear regression to explore the key variables affecting herders’ economic resilience and subjective well-being under the context of the project and to clarify the mediating effect of resilience in translating government interventions into enhanced welfare. The results reveal that households in the Yellow River Source Region were characterized by “low economic resilience yet high subjective well-being.” Among the three resilience dimensions, recovery capacity and reorganization capacities were comparatively weak. Economic resilience had a significant positive impact on herders’ well-being, partially mediating the relationship between policy variables and subjective well-being. Compared with other policy measures, subsidy adequacy and emergency support remained the primary drivers of subjective well-being. Future policy should innovate a diversified subsidy regime that maintains herders’ subjective well-being while making up for the shortcomings of reorganization capacity, thereby securing the sustainability of livelihoods alongside ecological conservation. Full article

Model-based simulation of farmland evapotranspiration and crop growth facilitates precise monitoring of crop and farmland dynamics with high efficiency, real-time responsiveness, and continuity. However, there are still significant limitations in using crop models to simulate the dynamic process of evapotranspiration and cotton growth in mulched drip-irrigated cotton fields under different irrigation gradients. The SWAP crop growth model effectively simulates crop growth. However, the original SWAP model lacks a dedicated module to consider the impact of mulching on cotton field evapotranspiration and cotton dry matter mass. Therefore, in this study, the source codes of the soil moisture, evapotranspiration, and crop growth modules of the SWAP model were improved. The evapotranspiration and cotton growth data of the mulched drip-irrigated cotton fields under three irrigation treatments (W1 = 3360 m³·hm⁻², W2 = 4200 m³·hm⁻², and W3 = 5040 m³·hm⁻²) in 2023 and 2024 at the Xinjiang Modern Water-saving Irrigation Key Experimental Station of the Corps were used to verify the simulation accuracy of the improved SWAP model. Research shows the following: (1) The average relative errors of the simulated evapotranspiration, leaf area index, and dry matter weight of cotton in the improved SWAP crop growth model are all <20% compared with the measured values. The root means square errors of the three treatments (W1, W2, and W3) ranged from 0.85 to 1.38 mm, from 0.03 to 0.18 kg·hm⁻², and 55.01 to 69 kg·hm⁻², respectively. The accuracy of the improved model in simulating evapotranspiration and cotton growth in the mulched cotton field increased by 37.49% and 68.25%, respectively. (2) The evapotranspiration rate of cotton fields is positively correlated with the irrigation water volume and is most influenced by meteorological factors such as temperature and solar radiation. During the flowering stage, evapotranspiration accounted for 62.83%, 62.09%, 61.21%, 26.46%, 40.01%, and 38.8% of the total evapotranspiration. Therefore, the improved SWAP model can effectively simulate the evaporation and transpiration of the mulched drip-irrigated cotton fields in the Manas River Basin. This study provides a scientific basis for the digital simulation of mulched farmland in the arid regions of Northwest China. Full article

The Puebla Metropolitan Area, one of the most industrialized regions in Mexico, shows severe contamination of both surface and groundwater. In this study a multi-tracer approach combining hydrochemistry with environmental isotopes (δ²H, δ¹⁸O, ³H) was applied to evaluate groundwater–surface water (GW–SW) interactions and their role in water quality degradation. Elevated concentrations of aluminum, iron, zinc, and lead were detected in the Alseseca and Atoyac Rivers, exceeding national standards, while arsenic, manganese, and lead in groundwater surpassed Mexican and WHO drinking water limits. The main sources of contamination include volcanic inputs from Popocatepetl activity (e.g., arsenic) and untreated discharges from industrial parks (e.g., lead), which together introduce significant loads of Potentially Toxic Elements (PTEs) into surface and groundwater. Isotopic analysis identified three sources for aquifer recharge: (1) recharge from high-altitude meteoric water, (2) mixed GW–SW water recharged at intermediate elevations with heavy metal presence, and (3) recharge from lower altitudes (evaporate water). Tritium confirmed both modern and old recharge, while isotope-based mixing models indicated surface water contributions to groundwater ranging from 18% to 72%. These interpretations were derived from the integrated analysis of hydrochemical and isotopic data, allowing the quantification of recharge sources, residence times, and mixing processes. The results demonstrate that hydraulic connectivity, enhanced by fractures and faults, facilitates contaminant transfer from polluted rivers into the aquifer. Full article