Search Results (76)

Global river water quality degradation severely impairs aquatic ecosystem stability and human health, highlighting the urgency of spatiotemporal analysis for management guidance. Based on 2014–2024 monitoring data from the Quzhou Section of Qiantang River Basin, this study adopted the Water Quality Index (WQI) and statistical methods (PCA, Mann–Kendall test) to explore the spatiotemporal characteristics of water quality across the basin. Results showed an overall mean WQI of 79.26 (classified as “Good”), with general stability, localized fluctuations, and a stable-then-declining trend, mirroring an imbalance between governance effects and emerging pollution pressures. It identifies a critical governance phase focused on securing the current good water quality and curbing the trend of further deterioration. Water quality exhibited distinct variations: upper reaches > lower reaches, tributaries > mainstreams, with priority required for the Wuxi River’s declining WQI and the Qu River’s persistently low WQI. TN, TP, and NH₃-N were identified as key factors coupled with land use patterns. A differentiated strategy prioritizing nitrogen control, synergizing phosphorus–oxygen management, and reducing organics is thus proposed. This study provides scientific references for water quality assessment and targeted aquatic ecological governance in the basin and similar river networks. Full article

Ecosystem vulnerability assessment is paramount for local environmental stability and lasting economic progress. This study selects Hubei Province as the research area, applying multi-source spatiotemporal datasets spanning the period 2000–2023. A pressure–state–response (PSR) framework, incorporating 14 distinct indicators, was developed. The selection criteria for these indicators adhered to principles of scientific rigor, all-encompassing scope, statistical representativeness, and practical applicability. The chosen indicators effectively encompass natural, anthropogenic, and socio-economic drivers, aligning with the specific ecological attributes and key vulnerability factors pertinent to Hubei Province. The analytic network process (ANP) method and entropy weighting (EW) method were integrated to ascertain comprehensive weights, thereby computing the ecological vulnerability index (EVI). In the meantime, we analyzed temporal and spatial EVI shifts. Spatial autocorrelation analysis, the geodetic detector, the Theil–Sen median, the Mann–Kendall trend test, and the Grey–Markov model were employed to elucidate spatial distribution, driving factors, and future trends. Results indicate that Hubei Province exhibited mild ecological vulnerability from 2000 to 2023, but with a notable deteriorating trend: extreme vulnerability areas expanded from 0.34% to 0.94%, while moderate and severe vulnerability zones also increased. Eastern regions demonstrate elevated vulnerability, but they were lower in the west, correlating with human activity intensity. The global Moran’s I index ranged from 0.8579 to 0.8725, signifying a significant positive spatial correlation of ecological vulnerability, with the highly vulnerable areas concentrated in regions with intense human activities, while the less vulnerable areas are located in ecologically intact areas. Habitat quality index and carbon sinks emerged as key drivers, possibly stemming from the forest–wetland composite ecosystem’s high dependence on water conservation, biodiversity maintenance, and carbon storage functions. Future projections based on Grey–Markov models indicate that ecological fragility in Hubei Province will exhibit an upward trend, with ecological conservation pressures continuing to intensify. This research offers a preliminary reference basis of grounds for ecological zoning, as well as sustainable regional development in Hubei Province, while also providing a theoretical and practical framework for constructing an ecological security pattern within the Yangtze River Economic Belt (YREB) and facilitating ecological governance in analogous river basins globally, thereby contributing to regional sustainable development goals. Full article

The widespread occurrence of fluoride pollution in water bodies and its toxic effects on aquatic organisms have raised significant environmental concerns; however, studies on water quality criteria for fluoride remain relatively limited. This study aimed to derive such criteria and assess the ecological risks of fluoride in China’s surface waters, for the reference of readers. Acute and chronic toxicity data were collected globally, covering 34 species (14 families, 4 phyla) and 7 species (5 families, 3 phyla), respectively. Using species sensitivity distribution (SSD) methods, the short-term water quality criterion (SWQC) and long-term water quality criterion (LWQC) were derived as 17.47 mg/L and 3.334 mg/L. Ecological risk assessment based on the risk quotient (RQ) identified several high-risk areas among 32 major river and lake basins, with RQ values of 6.326 (Xihe River), 1.953 (Ebinur Lake), 1.368 (Chagan Lake), and 1.158 (Shahe River). At the provincial level, Guangxi Zhuang Autonomous Region showed as no risk (RQ = 0.0001140), while other regions were classified as moderate or low risk. This study achieved its objectives of deriving water quality criteria for fluoride and conducting an ecological risk assessment for surface waters in China. It also highlights current limitations, including insufficient fluoride toxicity data and the frequent oversight of key indicators in existing assessments. Future research could focus on improving water quality criteria derivation and risk assessment methods through integrated predictive modeling and expanded toxicity datasets. Full article

The Songhua River, as the third-largest river in China, has garnered increasing attention for its ecological health. This study established a water ecological health assessment system for the Songhua River Basin based on the BD-IBI. Through a comprehensive analysis, including distribution range analysis, discriminant ability analysis, and correlation analysis, 97 candidate indicators were evaluated. Among these, IDSE Leclercq (IDSE), Indice Diatomique Artois Picardie (IDAP), RA. motile individuals, RA. ß-mesosaprobic, and RA. polysaprobe were selected as the core indicators for BD-IBI construction in the Songhua River Basin. The water ecological health status of the Songhua River Basin was categorized into five levels. Furthermore, environmental factors influencing BD-IBI and water quality were analyzed using box plot analysis, redundancy analysis (RDA), and multiple linear regression model. The results indicated that while the Songhua River Basin exhibits an overall “Good” water ecological health, marked heterogeneity exists across sub-reaches. Specifically, the Tangwang River exhibited the highest BD-IBI score, while the Woken River showed the lowest score. Key water quality factors driving BD-IBI changes include DO, EC, NN, TN, TP and QHEI. These findings provide a valuable reference for the assessment and restoration of water ecological environment quality in the Songhua River Basin, promoting the sustainable development of aquatic ecosystems. Full article

Urban rivers provide vital ecosystem services, benefiting both nature and people, yet they are heavily impacted worldwide, exhibiting similar symptoms collectively known as the Urban Stream Syndrome (USS). This study assessed the ecological status of the Someșul Mic River, located in Cluj-Napoca, Romania’s second-largest and rapidly developing city, through the lens of benthic invertebrate communities, recognized for their strong bioindicator value. Six sites along the main river course, four adjacent sites on tributaries, and an artificial canal were analyzed. Our findings revealed the presence of USS at all sites; however, contrary to expectations, the mainstem sites showed higher water quality and greater taxonomic and functional diversity of zoobenthos. The primary drivers of this pattern were the proportion of coarse sediments and flow velocity, with river width playing a lesser role. Based on these results, eight mitigation strategies were proposed, aligned with the river ecosystem services. Their implementation could improve the ecological condition across the river, floodplain, and catchment levels, involving both scientists and the general public. Overall, the study provides a management-oriented framework for future river restoration initiatives in a growing city and a comparative reference for urban river assessments. Full article

Chlorophyll-a (Chl-a) and chemical oxygen demand (COD) are key indicators for water quality evaluation. In previous research on the inversion of Chl-a and COD concentrations using hyperspectral data, disparities in hyperspectral data types have constrained the universality of the inversion models. To solve this problem, in this study, synchronous in situ hyperspectral data and water samples were collected from 308 stations within the river networks of Zhongshan City. Four inversion models, support vector regression (SVR), random forest (RF), backpropagation neural network (BPNN), and one-dimensional convolutional neural network (1D-CNN), were established using the original reflectance (R), remote sensing reflectance (Rrs), and their normalized forms as inputs. To evaluate the robustness of the models, their performance was assessed via cross-reflectance type validation. For example, a model was trained using R data and then tested with Rrs data. The results show that using the normalized hyperspectral data for modeling not only improves the accuracy of the inversion results of Chl-a and COD concentrations, but also effectively unifies different types of hyperspectral data, thereby improving the versatility of the inversion model. This study provides a reference for constructing a general water quality inversion model based on hyperspectral data. Full article

This study presents the first investigation into the distribution of microplastics (MPs) in Sasebo City, Japan, using principal component analysis (PCA) in conjunction with water flow velocity and salinity variables. The mean MP abundance was 82.4 ± 47.7 items/m³ (SSB1–SSB4), showing no significant difference among sampling points. The fragment-to-fiber ratio was 76:24, and polypropylene and polyethylene (each 41%) were the main polymers. Fragment abundance increased with decreasing particle size, while fibers were rare below 700 μm. PCA indicated distinct MP polymer and shape distributions corresponding to stagnant water (SSB1), high-flow conditions (SSB2 and SSB3), and seawater (SSB4). Based on the literature, the study area represents a case of a small-scale aquatic system with limited anthropogenic influence due to moderate population, short river length, efficient effluent discharge, minimal industry, good water quality, and the absence of significant spatial variation in MP abundance. The infrequent precipitation during the sampling event supports the findings of the present study as a reliable baseline for objectively assessing MP contamination. Compared to aquatic systems of varying scales and anthropogenic influence, this baseline is applicable to both small-scale and large-scale aquatic systems with significant influences. This will serve as a valuable reference for future MP studies across diverse freshwater environments. Full article

Understanding the structural concordance between taxonomic and functional diversity (FD) metrics is essential for improving the ecological interpretation of community patterns in biomonitoring programs. This study evaluated the concordance between taxonomic and FD metrics of benthic macroinvertebrates along a fluvial habitat quality gradient in the Paute River Basin, Ecuador. Macroinvertebrate communities were sampled over six years at twelve sampling points and assessed using four taxonomic metrics: Shannon diversity (H), the Margalef index (D_Mg), family richness (N), and the Andean Biotic Index (ABI). Functional diversity was evaluated using four metrics: weighted functional dendrogram-based diversity (wFDc), Rao’s quadratic entropy (Rao), functional dispersion (FDis), and functional richness (FRic). The fluvial habitat index (FHI) was used as an environmental reference to evaluate diversity metric responses. K-means clustering was independently applied to each metric, and pairwise concordance was quantified using the Measure of Concordance (MoC) and overlap in sampling points groupings across replicates. Most metrics (except FRic and N) showed clear responsiveness to the FHI gradient, confirming their ecological relevance. Strong structural concordance was observed between H and D_Mg and the FD metrics Rao, FDis, and wFDc, showing that these metrics captured similar yet complementary aspects of community organization. In contrast, ABI showed marked sensitivity to the FHI gradient but low concordance with functional metrics, suggesting distinct dimensions of biological integrity not encompassed by trait-based metrics. These findings highlight the value of combining taxonomic and functional metrics to detect both broad and subtle ecological changes. Integrating metrics with differing structural properties and environmental sensitivities can enhance the robustness of freshwater biomonitoring frameworks, especially in systems undergoing ecological transition or habitat degradation. Full article

Rapid economic development has exacerbated environmental degradation, particularly because of carbon dioxide emissions. To address these issues, China has proposed economic transformation from high-speed to high-quality development to achieve carbon peak and neutrality. Regional collaborative carbon emission reduction is critical for sustainability. Therefore, measuring regional carbon emission reduction capacity and the collaborative development level is imperative. This study employed provincial- and city-level data (2014–2023) from the Yangtze River Delta to assess regional collaborative carbon emission reduction capacity. Evaluation model of carbon emission reduction capacity was constructed based on five perspectives: economic development, carbon emission, carbon transfer, carbon sink, and industrial development. The entropy weighting method was employed to assign index weights, which was then integrated with a composite system synergy degree model. The subsystem order parameters and the composite system’s order degree were utilized to assess carbon emission reduction and collaborative trends. Results revealed that (1) overall carbon emission reduction capacity in the Yangtze River Delta constantly improved; (2) provincial economic development strengthened while carbon emissions declined; (3) carbon transfer fluctuations decreased; (4) technology and carbon sinks improved; (5) industrial development fluctuated or declined; and (6) interregional carbon emission reduction cooperation remained stable and improved. This research offers a theoretical and scientific reference for formulating low-carbon development strategies in similar regions. Full article

Understanding the coupling mechanisms and coordinated development dynamics of the water–energy–food (WEF) system is crucial for sustainable river basin development. This study focuses on the Yellow River Basin, conducting a comprehensive analysis of the system’s coupling mechanisms and influencing factors. A structured evaluation framework is established, integrating the entropy weight–TOPSIS method, the coupling coordination degree model, and spatial correlation analysis. Empirical analysis is conducted using data from nine provinces (regions) along the Yellow River from 2003 to 2022 to assess the spatiotemporal evolution of the coupling coordination level. The Tobit regression model is employed to quantify the impact of various factors on the system’s coupling coordination degree. Results indicate that the comprehensive evaluation index of the WEF system in the Yellow River Basin exhibits an overall upward trend, with the system coupling degree remaining at a high level for an extended period, up from 0.231 to 0.375. The interdependence among the three major systems is strong (0.881–0.939), and while the coupling coordination degree has increased over time despite fluctuations, a qualitative leap has not yet been achieved. The evaluation index follows a spatial distribution pattern of midstream > downstream > upstream, characterized by a predominantly high coupling degree. However, the coordination degree frequently remains at a forced coordination level or below, with a general trend of midstream > downstream > upstream. From 2003 to 2008, a positive spatial autocorrelation was observed in the coupling and coordinated development of the WEF system across provinces, indicating a strong spatial agglomeration effect. By 2022, most provinces were clustered in “high-high” and “low-low” areas, reflecting a positive spatial correlation with minimal regional differences. Key factors positively influencing coordination include economic development levels, industrial structure upgrading, urbanization, and transportation networks, while technological innovation negatively affects the system’s coordination. Based on these findings, it is recommended to strengthen balanced economic development, optimize the layout of industrial structures, improve the inter-regional resource circulation mechanism, and promote the deep integration of technological innovation and production practices to address the bottlenecks hindering the coordinated development of the water–energy–food system. Policy recommendations are proposed to provide strategic references for the sustainable socioeconomic development of the Yellow River Basin, thereby achieving the high-quality coordinated growth of the water–energy–food system in the region. Full article

Urban non-point source (NPS) pollution is an important risk factor that leads to the deterioration of urban water quality, affects human health, and destroys the ecological balance of the water environment. Reasonable risk prevention and control of urban NPS pollution are conducive to reducing the cost of pollution management. Therefore, based on the theory of “source–sink” in landscape ecology, combined with the minimum cumulative resistance (MCR) model, this study considered the influence of geographic-environment factors in Shenyang’s built-up area on pollutants in the process of entering the water body under the action of surface runoff, and evaluated its risk. The results indicated that the highest pollution loads are generated by road surfaces. High-density residential zones and industrial zones are the main sources of urban NPS pollution. Impervious surface ratios and patch density were the dominant environmental factors affecting pollutant transport, with contributions of 56% and 40%, respectively. The minimum cumulative resistance to urban NPS pollution transport is significantly and positively correlated with the distance from water bodies and roads. Higher risk areas are mainly concentrated in the center of built-up areas and roads near the Hun River. Green spaces, business zones, public service zones, development zones, and educational zones demonstrate the highest average risk index values, exceeding 29. In contrast, preservation zones showed the lowest risk index (7.3). Compared with the traditional risk index method, the method proposed in this study could accurately estimate the risk of urban NPS pollution and provide a new reference for risk assessments of urban NPS pollution. Full article

Chaohu Lake, as an important freshwater lake in China, mainly relies on surface runoff for water replenishment, and the environmental quality of the surrounding towns directly impacts the environment of Chaohu Lake. Given the characteristics of rich water resources and extensive river networks in the lake area, this paper utilizes the GEE platform and selects Landsat data from 1992 to 2022, taking Feidong County, one of the lake’s inlets, as the study area. We used the water benefit-based ecological index (WBEI) to monitor and evaluate the ecological quality of the study area and employ the Sen+MK trend analysis method to analyze the spatial-temporal characteristics of ecological quality changes. To explore the driving forces behind the spatial-temporal changes in the WBEI, this study selects land use type, elevation, slope, aspect, potential evapotranspiration, annual average precipitation, annual average temperature, and five characteristic factors used in the construction of the WBEI as influencing factors. Using the geo-detector method, the study analyzes the driving forces behind the spatial-temporal changes in the WBEI in the study area. Results show that the WBEI, considering water efficiency, integrates waterbody information into regional environmental quality assessments, comprehensively reflecting the ecological environment of lakeside cities. From 1992 to 2022, the WBEI of the study region shows an increasing trend, with an improved area accounting for 1110.42 km², or 51.21% of the total area. Among these, the significantly improved area covers 372.9789 km² or 17.2% of the total area, while the slightly improved area covers 737.4411 km², corresponding to 34.01% of the total area. Interaction types of influencing factors include bivariate enhancement and nonlinear enhancement, with the primary interactive factors affecting the ecological environment quality change in Feidong County being CLCD∩RVI; changes in land use and vegetation cover are the main driving forces behind the changes in ecological and environmental quality in Feidong County. From 1992 to 2022, the main land type transformations in the study area were from arable land to other land types, with a significant conversion of arable land to construction land, which is the main reason for the degradation of local ecological and environmental quality. The results of this study can provide practical references and theoretical support for ecological environment assessment, governance, and improvement in areas with abundant water resources. Full article

The current urban development in cities along the Lower Yellow River is in tension regarding human–land relations. To achieve the goals of ecological protection and high-quality development (HQD), it is urgent to scientifically measure and analyse the region’s function development and development coordination (DC). This study focuses on cities along the Lower Yellow River, constructs a three-dimensional HQD assessment framework based on urban functions through multiple remote sensing data, and evaluates DCs by feature classification. The results show the following: (1) The HQD of the study area shows a trend of decreasing and then increasing during 2000–2020 and reaches its highest level at the end. HQD shows a spatial trend of decreasing from south to north and from east to west. (2) The overall agricultural function of the study area declined slightly; the ecological function declined first and then increased, with the highest value occurring in 2000; and the urban function increased steadily and improved significantly after 2015. (3) DCs under different administrative levels are polarised, with high-level DCs exhibiting a spatial leader effect. (4) Urban development preferences in the study area are divergent, and the functional type with the highest share under different administrative scales is agro-ecological, which is mainly influenced by differences in natural base. This study reveals the characteristics of HQD and functional changes in cities along the Lower Yellow River, combined with a hierarchical classification of DCs and the types of development preferences, providing a reference for the formulation of spatial governance strategies. Full article

Identifying the main sources of risk for different types of waterways helps to develop targeted risk control strategies for different river segments. To improve the level of risk management in inland waterways for sustainable development, a two-stage risk evaluation model is proposed in this study by integrating a fuzzy rule base and Bayesian networks. The model evaluates risk sources from the following four dimensions: probability of occurrence, visibility, probability of causing accidents, and consequences. Typical river sections in the upper, middle, and lower reaches of the Yangtze River were selected as cases, and 19 risk sources were identified and comparatively analyzed from the perspectives of humans, ships, the environment, and management. The fuzzy rule base is employed to compare expert opinions, yielding three key risk sources for each section based on their risk values. The findings reveal certain commonalities in the principal risk sources across sections. For example, natural disasters (landslides, earthquakes, and extreme hydrological conditions) are present in both the middle and lower reaches, and an insufficient channel width is common in the upper and middle reaches. However, the key risk sources differ among the sections. The upper reaches are primarily threatened by the improper management of affiliated vessels and adverse weather, while the middle reaches suffer from insufficient channel width surplus, and the lower reaches are mainly threatened by high vessel traffic density and low-quality crews. The results of the study show that the key risk sources in each section of the Yangtze River have obvious differences and need to be assessed according to the characteristics of different sections. This study can provide a reference for decision-making in inland waterway risk management by maritime safety authorities. Full article

Water resources, energy, and food are essential for the development of society, and they are strongly interdependent. The coupling and coordination relationships of the water–energy–food (WEF) system are important for regional resource security and high-quality development. The Yellow River Irrigation Area in Shandong Province, China, is a grain production base and has a substantial impact on national food security. To examine the water, energy, and food subsystem dynamics in this area, an evaluation system for the WEF system was established. A comprehensive weighting method based on game theory was employed to determine index weights. TOPSIS was used to assess the development level of the WEF system. A coupling coordination degree model was used to analyze the evolution of the coupling coordination degree of the WEF system from 2000 to 2020, and a GWR model was constructed to explore the spatial heterogeneity of its driving factors. The findings indicated that the development level of the WEF system in the study area was moderate, with a gradual upward trend. The coupling coordination degree fluctuated between 0.62 and 0.739. The GWR model revealed that temperature had an overall negative effect on the coupling coordination degree, with the greatest impact on the central irrigation area; the slope and NDVI had a negative effect, with increasing intensity from the southwest to the northeast; and rainfall had an overall positive effect, with the greatest impact on the irrigation area near the estuary in the northeast. Overall, the building area ratio had a negative effect on the coupling coordination degree, with exceptions in some areas. These research outcomes provide theoretical support for sustainable agricultural development in the Yellow River irrigation areas of Shandong Province and methodological reference data for studying collaborative resource utilization in irrigation regions. Full article