The risk of sudden water pollution is one of the biggest obstacles to ensuring the safety of river basin water environments. While external pressure factors such as illegal discharge have been extensively studied with regard to their impact on the risk of sudden pollution, the influence of the river network topology has received limited attention. To fill this gap, extensive computational experiments were conducted in this study to investigate the effects of river network topology on the potential risk of sudden pollution. Based on the real-world characteristics of dendritic river networks, we used optimal channel networks to generate various river network topologies, represented by seven indicators that encompass morphology, connectivity, and structure. The water quality model simulated the spatial and temporal responses of the samples to a wide range of sudden pollution scenarios, and quantified the associated risk of sudden pollution using three proxy indicators: the maximum standard-exceeding multiple, proportion of standard-exceeding river length, and duration of exceedance. The results showed that among the seven indicators, the average outlet path (Do) and geometric fractal dimension (Dg) had a significant impact on risk. This is because network topology alters hydrological signatures such as discharge, velocity, and travel time. Moreover, multi-group analysis of structural equations revealed that the aspect ratio influences the impact of structural and connectivity indicators on risk by modulating pollution range and concentration. This study revealed the topological factors of the risk of sudden water pollution in dendritic river networks, emphasizing the regulatory role of topology in potential sudden water pollution risk and providing valuable insights for river management and planning. © 2024 Elsevier B.V.

Despite their widespread occurrence and significant environmental implications, the influence of sluice operations on the mobility of perfluoroalkyl acid (PFAA) in riverine sediments remains largely unexplored. To address this gap, a series of flume experiments were conducted to simulate the sedimentary migration of PFAA under the turbulent conditions generated by opening a sluice. Our study provides novel insights into the mechanisms by which plunging turbulence modulates the transfer of sedimentary PFAAs across the sediment‒water interface. Significant transient release effects were observed in the dissolved and suspended particulate matter (SPM) phases of PFAA, with total concentrations maintaining relative stability over extended periods following disturbance. The fluviraption of plunging turbulence increased PFAA concentrations in the surface sedimentary and porewater phases but weakened the adsorption performance of resuspended particles for the chemicals in the lower reach of the sluice. The instantaneous release of PFAA from sediment, fueled by turbulence, was identified as the primary driver of total mass transfer across the interface, increasing exponentially with the Reynolds number (Rex, R2=0.99, p© 2025 Elsevier Ltd

As the discharge of exogenous perfluoroalkyl acids (PFAAs) is gradually controlled, the secondary release of endogenous PFAAs is poised to become a major challenge. However, the effects of complex hydrodynamic conditions, such as disturbance from ship propeller jets, on PFAA release, are still poorly understood. In the present study, a propeller jet disturbance simulation experiment was carried out using an indoor flume to investigate the responses and mechanisms of PFAA release to the cumulative effects of jet force over time. Although an increase in jet action time (t) increased the total amount of dissolved PFAAs in the overlying water, PFAA dissolution intensity decreased. Conversely, increase in t induced a rise in both total PFAA amount adsorbed and adsorption intensity in suspended particulate matter (SPM). Moreover, differences in functional groups and carbon-fluorine chain lengths resulted in different types of PFAAs exhibiting different sensitivities to changes in t during dissolution and adsorption. During the jet disturbance, there were distinct shear zoning and pressure gradients in the flow field, contributing to the tendency of PFAAs to be distributed in the overlying water. However, after the disturbance, PFAAs tended to distribute in the SPM. Changes in t consistently affected the partition behavior of long-chain PFAAs (C ≥ 7), whereas the effect on the partition behavior of short-chain PFAAs (C © 2024 Elsevier B.V.

Heavy metal pollution is a critical issue affecting the safety of drinking water sources. However, the impact of human activities on heavy metal risk levels in water-carrying lakes remains unclear. This study aims to explore the risk mechanisms of heavy metals in Luoma Lake, an important water-carrying lake for the South-to-North Water Diversion Project. We explored the spatial and temporal differences in the distribution of heavy metals in Lake Luoma using methods such as the heavy metal pollution index (HPI) and assessed the risk variations using a health assessment model. The results indicated that heavy metal concentrations in water-carrying lakes generally decreased during the dry season, with Mn and Zn levels decreasing by 89.3% and 56.2%, respectively. The comprehensive score of HPI decreased by 13.16% following the retreating polder compared to the control area (Non-retreating polder area). Furthermore, the HPI at the drinking water intake was lower, which is closely associated with the elevated dissolved oxygen (DO) and oxidation–reduction potential (ORP) resulting from water diversion. The annual average health risk across the entire lake was not significant, with higher levels observed in the control area. The annual non-carcinogenic risk levels of Mn, Ni, Cu, Zn, and Pb range from 10−13 to 10−9, which are considered negligible risk levels. Notably, the carcinogenic risk posed by arsenic (As) through the drinking pathway reached 10−5 a−1, exceeding the maximum levels recommended by certain organizations. These findings provide a critical foundation for managing heavy metals in water-carrying drinking water sources. © 2024 by the authors.

Reticular river networks, essential for ecosystems and hydrology, pose challenges in assessing longitudinal connectivity due to complex multi-path structures and variable flows, exacerbated by human-made infrastructures like sluices. Existing tools inadequately track water flow's spatiotemporal changes, highlighting the need for targeted methods to gauge connectivity within complex river network systems. The Hydraulic Capacity Connectivity Index (HCCI) was developed adopting complex network theory. This involves river networks mapping, nodes and edges construstion, weight factor definition, maximum flow and resistance distance calculation. The connectivity between nodes is represented by the product of the maximum flow and the inverse of the resistance distance. The mean connectivity of each node with all other nodes, denoted as the node connectivity capacity Ci, and the HCCI of the whole river network is defined as the mean of the Ci for all nodes. The HCCI was firstly applied to a symmetrical virtual river network to investigate the factors influencing the HCCI. The results revealed that Ci showed a radial decreasing pattern from the obstructed river reach outwards, and the boundary rivers play the most significant role in regulating the flow dynamics. Subsequently, the HCCI was applied to a real river network in the Yandu district, followed by spatiotemporal statistical analysis comparing with 1D hydraulic model's simulated river discharge. Results showed a high correlation (Pearson coefficient of 0.89) between the HCCI and monthly average river discharge at the global scale. At the local scale, the geographically weighted regression model demonstrated the strong explanatory power of Ci in predicting the distribution of river reach discharge. This suggests that the HCCI addresses multi-path connectivity assessment challenge in reticular river networks, precisely characterizing spatiotemporal flow dynamics. Furthermore, since HCCI is based on a complex network model that can calculate the connectivity between all river node pairs, it is theoretically applicable to other types of river networks, such as dendritic river networks. By identifying low-connectivity areas, HCCI can guide managers in developing scientifically sound and effective strategies for restoring river network hydrodynamics. This can help prevent water stagnation and degradation of water quality, which is beneficial for environmental protection and water resource management. © 2024 Elsevier Ltd

Calculating pollution load contribution rate is an effective way to identify pollution sources, which is important in improving water quality management. Reticular river networks pose unique challenges in pollution load contribution rates calculation, as current methods are not applicable to river networks with uncertain flow direction or exhibit low computational efficiency. This study addresses this challenge by offering a new method that transforms the calculation of water quantity constituents in assessment sections into a conserved substance concentration problem. Applied to a typical reticular river network, Suzhou River Network in the Tai Lake Basin, China, total phosphorus pollution load contribution rates demonstrate significant spatial and temporal variations, and are closely associated with factors such as pollution load, rainfall, and water diversion. The developed method stands out for its simplicity and improved computational efficiency, making it particularly suitable for regions with indeterminate flow directions. Quantifying the contribution of pollution sources in reticular river networks to identify sources of pollution helps to improve the precision and pertinence of water pollution management programs. © 2024 The Author(s)

Short-chained perfluoroalkyl acids (PFAAs, CnF2n+1–R, n ≤ 6) have merged as global concerns due to their extensive application and considerable toxicity. However, long-chained PFAAs (n ≥ 7) featured with high persistence are still ubiquitously observed in aquatic environment. To understand the uptake behavior of short-chained PFAAs in aquatic macrophytes, the uptake kinetics, bioconcentration, and translocation of short-chained PFAAs (3 ≤n ≤ 6) in two typical free-floating macrophytes (Eichhornia crassipes and Ceratophyllum demersum) were investigated in the treatments with and without long-chained PFAAs (7 ≤n ≤ 11). Results showed that short-chained PFAAs can be readily accumulated in both E. crassipes and C. demersum, and the uptake of short-chained PFAAs fit the two-compartment kinetic model well (p © 2024 Elsevier B.V.

eticular river networks, characterized by a dense pattern of rivers and loop structures, are primarily found in lower river delta plains and are being modified due to rapid population growth and urbanization. This change impacts the distribution of water resources and could result in more frequent and severe floods. Therefore, accurately characterizing the structure of river networks is crucial. In this study, the structure and its changes of a typical plain reticular river network in the Lixia River hinterland area (LRHA), China, were evaluated in the 1960s, 1970s, 1980s, 2009, and 2016 using complex network theory tools at global and local scales. First, we constructed a complex network model by generalizing river sources, outlets, and confluences as nodes and channels as edges. By comparing with the equivalent random networks, it is found that the river networks of LRHA have large clustering coefficients and short characteristic path lengths. These characteristics classify it as a small-world network within complex networks, which is notably efficient for water and material transportation. Second, at the global scale, the global efficiency in complex network theory considers the interconnectivity between nodes and assesses the potential paths between them, effectively reflecting the connectivity status of the river network. At the local scale, the betweenness centrality of a complex network can reflect the control ability of water and material transportation at river nodes. After the 1970s, constructing several new mainstem rivers gradually shifted nodes with high betweenness centrality towards the north–south flowing rivers. In addition, we used Moran's I to quantify the spatial clustering of the network's indicators and found that degree and betweenness centrality exhibited higher spatial clustering, with mean Moran's I values of 0.398 and 0.300, respectively. Finally, we compared the structure of river networks in urban versus rural areas and the mainstem versus tributary streams. We found that urban river networks and mainstem rivers exhibit a higher degree of betweenness centrality, resulting in a greater capacity to regulate water and material cycles within the river network. According to the research findings, complex network theory has been proven to effectively evaluate the structure of reticular river networks at various scales. It enhances our comprehension of the river network's structure and assists managers in gaining a deeper understanding of how the river network structure influences the distribution of water resources. © 2024 Elsevier B.V.

The significant threat of antibiotic resistance genes (ARGs) to aquatic environments health has been widely acknowledged. To date, several studies have focused on the distribution and diversity of ARGs in a single river while their profiles in complex river networks are largely known. Here, the spatiotemporal dynamics of ARG profiles in a canal network were examined using high-throughput quantitative PCR, and the underlying assembly processes and its main environmental influencing factors were elucidated using multiple statistical analyses. The results demonstrated significant seasonal dynamics with greater richness and relative abundance of ARGs observed during the dry season compared to the wet season. ARG profiles exhibited a pronounced distance-decay pattern in the dry season, whereas no such pattern was evident in the wet season. Null model analysis indicated that deterministic processes, in contrast to stochastic processes, had a significant impact on shaping the ARG profiles. Furthermore, it was found that Firmicutes and pH emerged as the foremost factors influencing these profiles. This study enhanced our comprehension of the variations in ARG profiles within canal networks, which may contribute to the design of efficient management approaches aimed at restraining the propagation of ARGs. © 2024 Elsevier Inc.

Both cyanobacterial blooms and antibiotic resistance have aggravated worldwide and posed a great threat to public health in recent years. As a significant source and reservoir of water environmental resistome, cyanobacteria exhibit confusing discrepancy between their reduced susceptibility and their chronic exposure to antibiotic mixtures at sub-inhibitory concentrations. How the increasing temperature affects the adaptive evolution of cyanobacteria-associated antibiotic resistance in response to low-level antibiotic combinations under climate change remains unclear. Here we profiled the antibiotic interaction and collateral susceptibility networks among 33 commonly detected antibiotics in 600 cyanobacterial strains isolated from 50 sites across four eutrophicated lakes in China. Cyanobacteria-associated antibiotic resistance level was found positively correlated to antibiotic heterogeneity across all sites. Among 528 antibiotic combinations, antagonism was observed for 62 % interactions and highly conserved within cyanobacterial species. Collateral resistance was detected in 78.5 % of pairwise antibiotic interaction, leading to a widened or shifted upwards mutant selection window for increased opportunity of acquiring second-step mutations. We quantified the interactive promoting effect of collateral resistance and increasing temperature on the evolution of both phenotypic and genotypic cyanobacteria-associated resistance under chronic exposure to environmental level of antibiotic combinations. With temperature increasing from 16 °C to 36 °C, the evolvability index and genotypic resistance level increased by 1.25 – 2.5 folds and 3 – 295 folds in the collateral-resistance-informed lineages, respectively. Emergence of resistance mutation pioneered by tolerance, which was jointly driven by mutation rate and persister fraction, was found to be accelerated by increased temperature and antibiotic switching rate. Our findings provided mechanic insights into the boosting effect of climate warming on the emergence and development of cyanobacteria-associated resistance against collateral antibiotic phenotypes. © 2024 Elsevier Ltd