Search Results (863)

The Three Gorges Reservoir, serving as a crucial ecological barrier for the middle-lower Yangtze River basin, faces substantial threats to watershed ecosystems from sediment-associated heavy metal, threatening aquatic ecosystems and human health via bioaccumulation. Leveraging the legislative framework of the Yangtze River Protection Law, this study analyzed sediment cores (0–65 cm) collected from 12 representative sites in the Three Gorges Reservoir using 2020 Air–Space–Ground integrated monitoring data from the Changjiang Water Resources Commission. Concentrations of nine heavy metals (Cd, Cu, Pb, Fe, Mn, Cr, As, Hg, and Zn) were quantified to characterize spatial and vertical distribution patterns. Source apportionment was conducted through correlation analysis and principal component analysis (PCA). Contamination severity and ecological risks were assessed via geo-accumulation index (I_geo), potential ecological risk index (RI), and acute toxicity metrics. The findings indicated substantial spatial heterogeneity in sediment heavy-metal concentrations, with the coefficients of variation (CV) for Hg and Cd reaching 214.46% and 116.76%, respectively. Cu and Pb showed surface enrichment, while Cd exhibited distinct vertical accumulation. Source apportionment indicated geogenic dominance for most metals, with anthropogenic contributions specifically linked to Cd and Hg enrichment. Among the metals assessed, Cd emerged as the primary ecological risk driver, with localized strong risk levels (E_i > 320), particularly at FP and SS sites. These findings establish a scientific foundation for precision pollution control and ecological restoration strategies targeting reservoir sediments. Full article

Microplastic pollution is pervasive in marine ecosystems and poses a growing threat to marine organisms and human health. This study simultaneously investigates microplastic ingestion and phthalate exposure in Parapenaeus longirostris, a commercially valuable and ecologically relevant Mediterranean crustacean occupying an intermediate trophic position. Specimens were collected from three coastal areas in the central Tyrrhenian Sea (Western Mediterranean): near the Tiber River mouth, one of the most polluted rivers in Italy, and two additional sites to the north and south. The frequency of individuals with ingested microplastics varied among locations: 78% near the Tiber River, 64% at site S, and 38% at site N, reflecting anthropogenic pressure gradients. Analyses confirmed the lower occurrence at site N, indicating higher ingestion near land-based pollution sources. Ingested microplastic polymer types varied among sites, reflecting location-specific contamination. Phthalates were present in shrimp muscle at all sites (5–1122 ng/g w.w.) with the highest average concentration (68.26 ± 55.74 ng/g) at the site with the highest microplastic ingestion. Although no statistical correlation was found, the similar spatial distribution of microplastics and phthalates suggests a potential link influenced by local pollution and individual variability. These findings provide novel evidence of microplastic and phthalate contamination in P. longirostris, highlighting its role as a trophic connector mediating contaminant transfer through the food web. While current levels suggest no potential risk to human health, continued monitoring and further studies on exposure along trophic pathways are recommended. Full article

Coasts are critical ecological, economic and social interfaces between terrestrial and marine systems. The current upsurge in the acquisition and availability of remote sensing datasets, such as Landsat remote sensing data series, provides new opportunities for analyzing multi-decadal coastal changes and other components of coastal risk. The emergence of machine learning-based techniques represents a new trend that can support large-scale coastal monitoring and modeling using remote sensing big data. This study presents a comprehensive multi-decadal analysis of coastal changes for the period from 1990 to 2024 using Landsat remote sensing data series along the eastern and southern coasts of Peninsular Malaysia. These coastal regions include the states of Kelantan, Terengganu, Pahang, and Johor. An innovative approach combining deep learning-based shoreline extraction with the Digital Shoreline Analysis System (DSAS) was meticulously applied to the Landsat datasets. Two semantic segmentation models, U-Net and DeepLabV3+, were evaluated for automated shoreline delineation from the Landsat imagery, with U-Net demonstrating superior boundary precision and generalizability. The DSAS framework quantified shoreline change metrics—including Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), and Linear Regression Rate (LRR)—across the states of Kelantan, Terengganu, Pahang, and Johor. The results reveal distinct spatial–temporal patterns: Kelantan exhibited the highest rates of shoreline change with erosion of −64.9 m/year and accretion of up to +47.6 m/year; Terengganu showed a moderated change partly due to recent coastal protection structures; Pahang displayed both significant erosion, particularly south of the Pahang River with rates of over −50 m/year, and accretion near river mouths; Johor’s coastline predominantly exhibited accretion, with NSM values of over +1900 m, linked to extensive land reclamation activities and natural sediment deposition, although local erosion was observed along the west coast. This research highlights emerging erosion hotspots and, in some regions, the impact of engineered coastal interventions, providing critical insights for sustainable coastal zone management in Malaysia’s monsoon-influenced tropical coastal environment. The integrated deep learning and DSAS approach applied to Landsat remote sensing data series provides a scalable and reproducible framework for long-term coastal monitoring and climate adaptation planning around the world. Full article

Accurate identification of bare soil exposure and quantification of associated dust emissions are essential for understanding land degradation and air quality risks in intensively farmed regions. This study develops a monthly monitoring and modeling framework to quantify bare soil dynamics and wind erosion-induced particulate matter (PM) emissions across Shandong Province from 2017 to 2024. By integrating Sentinel-1/2 imagery, climate reanalysis, terrain and soil data, and employing a stacking ensemble classification model, we mapped bare soil areas at 10 m resolution with an overall accuracy of 93.1%. The results show distinct seasonal variation, with bare soil area peaking in winter and early spring, exceeding 25,000 km² or 15% of the total area, which is far above the 6.4% estimated by land cover products. Simulations using the CLM5.0 dust module indicate that annual PM₁₀ emissions from bare soil averaged (2.72 ± 1.09) × 10⁵ tons across 2017–2024. Emissions were highest in March and lowest in summer months, with over 80% of the total emitted during winter and spring. A notable increase in emissions was observed after 2022, likely due to more frequent extreme wind events. Spatially, emissions were concentrated in coastal lowlands such as the Yellow River Delta and surrounding saline–alkali lands. Our approach explicitly advances traditional methods by generating monthly 10 m bare soil maps and linking satellite-derived dynamics with process-based dust emission modeling, providing a robust basis for targeted dust control and land management strategies. Full article

The Niland Moving Mud Spring, located near the southeastern margin of the Salton Sea, represents a rare and evolving geotechnical hazard. Unlike the typically stationary mud pots of the Salton Trough, this spring is a CO₂-driven mud spring that has migrated southwestward since 2016, at times exceeding 3 m per month, posing threats to critical infrastructure including rail lines, highways, and pipelines. Emergency mitigation efforts initiated in 2018, including decompression wells, containment berms, and route realignments, have since slowed and recently almost halted its movement and growth. This study integrates hydrochemical, temperature, stable isotope, and tritium data to propose a refined conceptual model of the Moving Mud Spring’s origin and migration. Temperature data from the Moving Mud Spring (26.5 °C to 28.3 °C) and elevated but non-geothermal total dissolved solids (~18,000 mg/L) suggest a shallow, thermally buffered groundwater source influenced by interaction with saline lacustrine sediments. Stable water isotope data follow an evaporative trajectory consistent with imported Colorado River water, while tritium concentrations (~5 TU) confirm a modern recharge source. These findings rule out deep geothermal or residual floodwater origins from the great “1906 flood”, and instead implicate more recent irrigation seepage or canal leakage as the primary water source. A key external forcing may be the 4.1 m drop in Salton Sea water level between 2003 and 2025, which has modified regional groundwater hydraulic head gradients. This recession likely enhanced lateral groundwater flow from the Moving Mud Spring area, potentially facilitating the migration of upwelling geothermal gases and contributing to spring movement. No faults or structural features reportedly align with the spring’s trajectory, and most major fault systems trend perpendicular to its movement. The hydrologically driven model proposed in this paper, linked to Salton Sea water level decline and correlated with the direction, rate, and timing of the spring’s migration, offers a new empirical explanation for the observed movement of the Niland Moving Mud Spring. Full article

Soil erosion is a widespread problem leading to land degradation in many watersheds, including the Lato Basin, an Apulian permanent river that supplies water used for irrigation in many agricultural territories along the Ionian coast with considerable economic importance for crop production. The loss of fertile soil makes land less productive for agriculture; soil erosion decreases soil fertility, which can negatively affect crop yields. The present research aimed to determine soil loss (t/ha/year) in the Lato watershed in 2024, and then four ecosystem services—loss of carbon, habitat quality, crop productivity and sustainable tourism suitability—directly or indirectly linked to erosion, were defined and evaluated in monetary terms. These ecosystem service evaluations were made for the actual basin land use, and also for two hypothetical scenarios applying different afforestation strategies to the watershed. The first scenario envisages afforestation interventions in the areas with the highest erosion; the second scenario envisages afforestation interventions in the areas with medium erosion, cultivated with cereal crops. Each scenario was also used to evaluate the economic convenience and the effects of sustainable land management practices (e.g., reforestation) to reduce soil erosion and loss of ecosystem services. This study demonstrates that soil erosion is related to land use. It also underlines that reforestation reduces soil erosion and increases the value of ecosystem services. Furthermore, the economic analysis shows that crop productivity is the most incisive ecosystem service, as the lands with high productivity achieve higher economic values, making conversion to wooded areas economically disadvantageous if not supported with economic aid. The results of this study may help development of new management strategies for the Lato Basin, to be implemented through the distribution of community funds for rural development programs that consider the real economic productivity of each area through naturalistic engineering interventions. The reforestation measures need to be implemented over a long time frame to perform their functions; this requires relevant investments from the public sector due to cost management, requesting monetary compensation from EU funds for companies involved in forestation projects on highly productive areas that will bring benefits for the entire community. Full article

Understanding the spatiotemporal dynamics of runoff and its drivers is essential for water resources management in mid–high latitude basins. This study investigates runoff changes in the Songhua River Basin, Northeast China, during 1980–2022 using the Budyko framework, combined with Mann–Kendall trend analysis, Pettitt tests, Hurst index, and wavelet analysis. Results indicate significant climatic shifts, with basin-wide warming, heterogeneous precipitation changes, and declining relative humidity, leading to intensified cold-season drying. Temperature and evapotranspiration showed strong persistence, while precipitation exhibited high variability and periodicities linked to ENSO and East Asian monsoon anomalies. Runoff increased significantly in the mainstream Songhua and Nenjiang basins, especially in autumn, with abrupt changes clustered between 2009 and 2015. The Second Songhua Basin displayed weaker variability, largely influenced by reservoir regulation and land-use change. Attribution analysis confirmed precipitation as a primary driver, with elasticity coefficients exceeding 3 in the Nenjiang Basin during some summers, indicating extreme sensitivity. Evapotranspiration suppressed runoff under high temperatures, while freeze–thaw processes and human interventions became critical in spring and autumn. The aridity index revealed persistent winter deficits and rising spring–autumn drying trends after 2000, posing risks for snowmelt runoff and baseflow sustainability. Overall, runoff evolution reflects a shift from gradual to threshold-triggered regime changes driven by both climate variability and human regulation. These findings provide a basis for adaptive, basin-specific water management and climate resilience strategies in Northeast China. Full article

Large woody debris (LWD) in river systems serves beneficial ecological functions and poses potential hazards during flood events. Managing LWD requires a balanced understanding of its dynamics. This study employed unmanned aerial vehicles (UAVs) for high-resolution, spatiotemporal monitoring of LWD distribution and mobility along the Oshirarika River in northern Japan. UAV imagery enabled efficient LWD recruitment and transport assessments. The spatial distribution analysis revealed that >90% of LWD was deposited on bar surfaces, underscoring the role of geomorphic features in controlling LWD accumulation. Generalized linear mixed models revealed that the maximum water level and the frequency of its rise above 0.8 m were the most influential predictors of the number of recruited and transported LWD. Additionally, the topographic position—channel, lower bar, or higher bar—exhibited a significant negative association, indicating greater LWD mobility and deposition in lower elevation zones. This trend may be attributed to infrequent high-magnitude flood events, which likely result in relatively limited LWD dynamics in higher bar areas. These findings demonstrate the utility of UAV-based monitoring coupled with GLMMs for capturing the spatial and temporal dynamics of LWD. The ability to link hydrological fluctuations and LWD behavior provides a valuable framework for management and ecological restoration in steep, forested watersheds. Full article

This study investigates how landcover change between 1935 and 2020 have shaped hydrological responses in the semi-arid highlands of Tigray, Ethiopia. Focusing on the Tsili catchment (27.5 km²), it examines links between landcover change, drainage network evolution, and river channel width under conditions of population growth and climate variability. Landcover and drainage maps were derived from historical aerial photographs and satellite imagery for four time steps, and surface runoff was simulated using the SWAT model with uniform meteorological forcing to isolate landcover effects. Results show a 37.6% increase in cropland and substantial declines in shrubland (−29.3%) and forest (−10.1%). River channel width at the outlet widened from 7.5 to 10.5 m, while drainage density increased 1.5-fold. These physical changes aligned with modelled increases in surface runoff. Strong correlations were found between runoff, channel width, drainage density, and landcover types. The findings highlight that cropland expansion—at the expense of natural vegetated land—has intensified runoff and erosion risks. As climate change is expected to bring more intense rainfall to East Africa, this underscores the need for land management strategies that reduce hydrological connectivity and support sustainable agriculture in data-scarce regions. Full article

Temporal and spatial variations in water temperature were analyzed from 1998 to 2023 across two contrasting southeast Basque coast estuaries: the deeper, stratified estuary of Bilbao and the shallower, mixed estuary of Urdaibai. We assessed long-term trends, seasonality, intra- and inter-estuary differences, and links to hydro-meteorological drivers using time-series decomposition, clustering, cumulative sum, regression, and correlation analyses. The largest differences in interannual and seasonal patterns occurred between outer neritic and shallow transitional waters. Most water masses warmed overall, with increases until 2003–2006, followed by cooling until 2013–2015, and sharp warming in 2020–2023. The strongest trends (0.24–0.25 °C decade⁻¹) occurred in middle-estuary waters, while inner above-halocline waters of the stratified estuary showed no trend or slight cooling. The strongest warming occurred in spring, particularly in the easternmost mixed estuary (0.49 °C decade⁻¹), especially in May (0.88 °C decade⁻¹). Seasonal minima and maxima occurred earlier in surface transitional waters than in neritic and deep transitional waters of the stratified system. Over time, temperature maxima advanced, minima were delayed, shortening the warming phase, and springs became warmer, extending the warm season. Air temperature was the main driver of water temperature trends, while river flow modulated patterns at annual and seasonal scales, with negative correlations with temperature, mainly in spring. Full article

This paper develops a dynamic information-theoretic network framework to quantify systemic risk in China’s maritime–commodity nexus with a focus on the Yangtze River Basin using eight monthly indicators, CCFI, CBCFI, BDI, YRCFI, GAUP, MPCT, CPUS, and ASMC. We resample, impute, standardize, and difference series to achieve stationary time series. Nonlinear interdependencies are estimated via KSG mutual information (MI) within sliding windows; networks are filtered using the Planar Maximally Filtered Graph (PMFG) with bootstrap edge validation (95th percentile) and benchmarked against the MST. Average MI indicates moderate yet heterogeneous dependence (about 0.13–0.17), revealing a container/port core (CCFI–YRCFI–MPCT), a bulk/energy spine (BDI–CPUS), and commodity bridges via GAUP. Dynamic PMFG metrics show a generally resilient but episodically vulnerable structure: density and compactness decline in turbulence. Stress tests demonstrate high redundancy to diffuse link failures (connectivity largely intact until ∼70–80% edge removal) but pronounced sensitivity of diffusion capacity to targeted multi-node outages. Early-warning indicators based on entropy rate and percolation threshold Z-scores flag recurring windows of elevated fragility; change point detection evaluation of both metrics isolates clustered regime shifts (2015–2016, 2018–2019, 2021–2022, and late 2023–2024). A Systemic Importance Index (SII) combining average centrality and removal impact ranks MPCT and CCFI as most critical, followed by BDI, with GAUP/CPUS mid-peripheral and ASMC peripheral. The findings imply that safeguarding port throughput and stabilizing container freight conditions deliver the greatest resilience gains, while monitoring bulk/energy linkages is essential when macro shocks synchronize across markets. Full article

Physiographic, geographic, and environmental gradients influence the development of plant communities. This study assessed how environmental gradients affect riparian vegetation along the River Panjkora, aiming to find relationships between vegetation and abiotic factors through indicator species analysis. Vegetation was sampled using the quadrat method (1 × 1 m² for herbs, 5 × 5 m² for shrubs, 10 × 10 m² for trees), and soil samples were analyzed for edaphic variables. Indicator species and ordination analyses were performed using PCORD (version 5) and CANOCO (version 4.5) software to understand species diversity. Detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) identified species patterns and their links to environmental factors. A total of 216 plant species were recorded across seven stations, grouped into five communities. Community 01, Melia azedarach, Punica granatum, and Asparagus racemosus, are affected by Cr, p ≤ 0.03; Fe, p ≤ 0.01; Zn, p ≤ 0.04; and Mg, p = 0.03. On the other hand, Community 02, Populus alba, Debregeasia saeneb, and Youngia japonica, are controlled by Co, p = 0.01; pH, p = 0.03; Cd, p = 0.04; EC, p = 0.03; and TDSs, p = 0.03. The third community, with indicator species Pinus roxburghii, Rydingia limbata, and Cheilanthes pteridioides, is strongly influenced by Cr, p ≤ 0.05; Cu, p ≤ 0.03; TDSs, p = 0.02; and Zn, p = 0.03. Community 04, consisting of Ficus carica, Polygonum plebeium, and Avena sativa, is shaped by Na, p = 0.01; K, p ≤ 0.05; and Fe, p = 0.04. The fifth community, represented by Ficus palmata, Rosa multiflora, and Heliotropium europaeum, is influenced by pH, p ≤ 0.04 and Mn, p = 0.03. DCA displayed maximum gradient lengths of 6.443 (eigenvalue 0.742) on axis 1, 5.222 (0.662) on axis 2, 4.053 (0.600) on axis 3, and 4.791 (0.464) on axis 4. Soil pH, heavy metals (Cr, Fe, Zn, Mg, Co, Cd, Cu, Na, K, and Mn), EC, and TDSs were the main factors shaping community structure. The indicator species analysis is recommended to identify and conserve the rare species and native flora of a particular region. Full article

Microplastic (MP) contamination in riverine systems poses a growing environmental challenge, and their spatial and temporal variability complicates proper assessments. This study investigated MP concentrations (≥10 µm) across three German rivers using fluorescent staining-based detection. The results reveal highly heterogeneous distributions ranging from 4 to 1761 MP/L. The Rehbach displayed the highest mean MP concentration (540 ± 476 MP/L), whereas the Alb had the lowest (98 ± 54 MP/L). Long-term monitoring underscored pronounced temporal fluctuations linked to changing inputs, weather events, and hydrodynamics. To capture these fluctuations, monitoring campaigns must consider an appropriate temporal sampling framework. Further, to address detection challenges, the study compared 0.5 L grab sampling with 100 L pump sampling (PSU) and observed that the PSU yielded 4.7 times higher MP concentrations with improved reproducibility (27 ± 25% vs. 49 ± 33%). These results highlight the critical need for standardized protocols and scalable, cost-effective methods for reliable MP quantification and hotspot identification in freshwater environments. Full article

This study presents an assessment of hydrological diversity (hydrodiversity) in Rio Grande do Norte, Brazil, aiming to identify potential correlations between hydrodiversity and hydrological features of geoheritage. The methodology applied a quantitative approach based on mean annual precipitation, river discharge, reservoir distribution, and stream order. These variables were analyzed within a 5.5 km grid using GIS tools. The four resulting sub-indices were normalized through the Maximum Possible Value method to ensure equal weighting in the final Hydrodiversity Index, which classifies areas into four levels: low, medium, high, and very high. Results show the highest hydrodiversity values in the eastern region and along the Apodi–Mossoró River, where rainfall and drainage density are greatest. The Hydrodiversity Index map was examined alongside land use data and the distribution of 22 previously identified hydrological sites (hydrosites). A greater concentration of anthropogenic land use was noted in areas with medium to high hydrodiversity, especially in the east and along the northern coast, emphasizing the role of water resources in territorial dynamics. The findings indicate that no hydrosites are located within areas of Very High Hydrodiversity; however, more than 50% of the hydrosites correspond to areas classified as High Hydrodiversity. While further research is required to better elucidate the relationship between geodiversity and geoheritage, these results underscore both the complexity of the link between hydrodiversity and water-related geoheritage, as well as the importance of employing an index to inform conservation and management strategies. Full article

River water enters human life in various ways, with many disease outbreaks closely linked to contaminated sources. This study collected water samples from the Perak River in Malaysia, extracted environmental DNA (eDNA), and analyzed biological communities using metabarcoding and sequencing techniques to assess the local environmental health of the river. Through 16S rRNA sequencing, 4045 bacterial OTUs were identified, while 18S rRNA sequencing revealed 3422 eukaryotic OTUs, highlighting the diverse microbial and eukaryotic communities in the Perak River. The results showed certain organisms such as Serratia marcescens and Strombidium with potentially abnormal abundance, based on comparisons with other studies, suggesting possible organic and heavy metal pollution. Additionally, 35 potential pathogens, including bacteria, fungi, and parasites, were detected in the samples, all of which pose potential threats to human and animal health. While most bacterial pathogens are opportunistic, their potential risks should not be overlooked. These findings provide valuable insights into the river’s ecological status and help guide targeted conservation, surveillance and pollution management strategies. Ultimately, this study highlights environmental health issues through biodiversity analysis and identifies pathogens, contributing to the protection of human and animal health and aligning with the principles of the One Health approach. Full article