Spectro-environmental factors integrated ensemble learning for urban river network water quality remote sensing.

Remote sensing water quality monitoring technology can effectively supplement the shortcomings of traditional water quality monitoring methods in spatiotemporal dynamic monitoring capabilities. At present, although the spectral feature-based remote sensing water quality inversion models have achieved many successes, there could still be a problem of insufficient generalization ability in monitoring the water quality of complex river networks in large cities. In this paper, we propose a spectro-environmental factors integrated ensemble learning model for urban river network water quality inversion. We analyzed the correlation between water quality parameters, spectral reflectance, and environmental factors based on an in-situ dataset collected in the northern part of Shanghai. Using the Hot Spot Analysis (Getis-Ord Gi*), we found that river network water quality parameters have different patterns in different urban functional zones. Furthermore, daily average temperature, total rainfall within the seven days, and several band combinations were also selected as the environmental and spectral features using factor analysis and Pearson correlation coefficient analysis. After the feature analysis, the spectro-environmental factors integrated ensemble learning model was trained. Compared with the spectral-based machine learning inversion models, the coefficients of determination R2 increased by about 0.50. Our model was also tested in three different test areas within and outside the in-situ sampling areas in Shanghai based on low-altitude multispectral remote sensing images. The R2 results for total phosphorus (TP), ammonia nitrogen (NH3-N), and chemical oxygen demand (COD) within the in-situ sampling areas were 0.52, 0.58, and 0.56 respectively. The mean absolute percentage error (MAPE) results were 53.36%, 63.95%, and 22.46% respectively. After adding the area outside the in-situ sampling areas, the R2 results for TP, NH3-N, and COD were 0.47, 0.47, and 0.53. The MAPE were 49.38%, 74.46%, and 20.49%. Our research provided a new remote sensing water quality inversion method to be utilized in complex urban river networks which exhibited solid accuracy and generalization ability.

Human activities exacerbate river network degrading in the Qinhuai River basin.

Rivers are undergoing significant changes under the pressures of natural processes and human activities. However, characterizing and understanding these changes over the long term and from a spatial perspective have proven challenging. This paper presents a novel framework featuring twelve indicators that combine geometric and spatial structures for evaluating changes in river network patterns. Through global principal component analysis, these indicators were integrated into a comprehensive river network pattern index (RNP). Employing Pearson correlation analysis, geographically weighted regression, geographic detector models, and the Shapley Value, the study quantitatively analyzed various stressors' impacts and relative contributions on river network changes from the 1960s to 2015s. The results showed a clear trend of degradation over time, particularly with frequency and density declining by 57 % and 48 %, respectively. The changes across subbasins varied temporally and spatially, with the 1980s emerging as a significant temporal hotspot and six spatial hotspots identified among twenty subbasins. The analysis showed that agriculture was significantly negatively associated with RNP, while the relationship between urbanization and RNP was inverted N-shaped. To address the negative effects of human activities, a shift from uniform management approaches is crucial. In agricultural areas, adopting more intensive farming practices could help mitigate negative impacts on RNP. For highly urbanized regions, city planning should consider the interactions between urbanization and other factors affecting RNP. Overall, incorporating an understanding of RNP's spatial-temporal dynamics and driving factors into spatial planning is critical for creating effective and sustainable management strategies for human-river interactions.

Occurrence, risk assessment and source apportionment of perfluoroalkyl acids in the river of a hill-plain intersection region: The impacts of land use and river network structure.

Studying the impacts of land use and river network structure on perfluoroalkyl acids (PFAAs) footprint in rivers is crucial for predicting the fate of PFAAs in aquatic environments. This study investigated the distribution, ecological risks, sources and influence factors of 17 PFAAs in water and sediments of rivers from hills to plain areas. The results showed that the detection frequencies were higher for short-chain PFAAs than long-chain PFAAs in water, whereas an opposite pattern was found in sediments. The concentration of ∑PFAAs ranged from 59.2 to 414 ng/L in water and from 1.4 to 60.1 ng/g in sediments. Perfluorohexanoic acid and perfluorooctanoic acid were identified as the main pollutants in the river. The average concentrations of PFAAs were higher in the aquaculture areas (water: 309.8 ng/L; sediments: 43.27 ng/g) than in residential areas (water: 206.03 ng/L; sediments: 11.7 ng/g) and farmland areas (water: 123.12 ng/L; sediments: 9.4 ng/g). Environmental risk assessment showed that PFAAs were mainly low risk or no risk in water, but were moderate risk and even high risk in sediments, especially for perfluorooctane sulfonate. Source apportionment found that PFAA sources were mostly from industry, wastewater discharge, and surface runoff. Dissolved oxygen, chemical oxygen demand, water system circularity, network connectivity and organic matter were significantly correlated to PFAA concentration, indicating that the physicochemical properties and river network might directly influence the environmental behavior of PFAAs. The built-up area was positively correlated with PFAAs. These findings indicated that a comprehensive understanding of the influences of land use and river network structure on PFAAs in rivers is essential for managers to formulate effective PFAA control strategies.

Distribution of microplastics in Lanzhou section of the Yellow River: Characteristics, ecological risk assessment, and factors analysis.

Microplastic (MP) is an emerging pollutant that has attracted attention in the environmental field, and the research of MPs in freshwater systems needs to be strengthened. To characterize the MPs in surface water and sediments of the western urban river network, water and sediment samples were collected. The results showed that the abundance of MPs in the water body of the river network ranged from 7 to 172 n/L, whereas the abundance of MPs in the sediments ranged from 7 to 144 n/kg, and the average abundance in the dry season was significantly higher than that in the rainy season. The majority of MPs (83.67 %) were < 1 mm and fibrous. The most commonly identified types of MPs were PET and PP, while the color blue was frequently observed. MPs have the potential to vertically migrate in sediments, with size, shape, density, and hydrodynamic forces being the main factors that contribute to this process. Correlation analysis results revealed that anthropogenic and meteorological factors, including precipitation, atmospheric conditions, and population density, had a discernible impact on the abundance, size, and shape of MPs. The ecological risk of MPs was assessed using the Polymer Hazardous Index (PHI), Pollution Load Index (PLI), and Potential Ecological Risk Index (PERI) methods, and the results showed that the overall ecological risk of the Lanzhou section of the Yellow River was low. This study can provide a scientific basis for monitoring and risk assessment of emerging contaminants such as MPs in the river environment.

Analysis of changes in river connectivity during the urbanization process: a case study of the southeastern plain of Yinzhou, China.

Affected by human activities, the naturally occurring river network in the southeastern plain of Yinzhou has gradually evolved into a natural-artificial composite water system, and changes in river connectivity due to changes in river network systems have caused water security problems, including urban flooding. To clarify the river connectivity change and its relationship with the urbanization process, this paper discusses an evaluation method for river connectivity based on complex networks and cellular automata (CA) from the perspective of complex systems, quantitatively analyzes the spatial-temporal characteristics of the structural and functional river connectivity in the study area during the 1990s-2020s, and reveals the impact of river nodes and chains on the connectivity level under the disturbance of natural or human factors. The results contained the following revelations: ① River connectivity showed a decreasing trend in the initial and rapid development stages of urbanization from the 1990s to the 2010s and a limited increasing trend in the optimization and upgrading stages from the 2010s to the 2020s. ② River network degradation and ongoing connectivity decline are found in the northeastern part of the study area. The highest river connectivity exists in Dongqianhukaifaqu. ③ The number of river nodes and chains should be maintained at approximately 80% for normal river connectivity. The nodes of high degree in the inflow area are listed in the key protection areas. ④ Changes in river connectivity are significantly correlated with the urbanization process. Changes in the functional connectivity level affect the magnitude of a flood. This study provides a theoretical basis for river network connectivity improvement and flood prevention in plain areas.

Meta-ecosystem Frameworks Can Enhance Control of the Biotic Transport of Microplastics.

The lack of systematic approaches and analyses to identify, quantify, and manage the biotic transport of microplastics (MPs) along cross-ecosystem landscapes prevents the current goals of sustainable environmental development from being met. This Perspective proposes a meta-ecosystem framework, which considers organismal and resource flows among ecosystems to shed light on the research and management challenges related to both abiotic and biotic MP transport at landscape levels. We discuss MP transport pathways through species movements and trophic transfers among ecosystems and sub-ecosystems, and highlight these pathways in the mitigation of MP pollution. The integration of biotic pathways across landscapes prioritizes management actions for MP transport using diverse approaches such as wastewater treatment and plastic removal policies to mitigate contamination. In addition, our framework emphasizes the potential sink enhancement of MPs through habitat conservation and enhancement of riparian vegetation. By considering the mechanisms of meta-ecosystem dynamics through the processes of biotic dispersal, accumulation, and the ultimate fate of MPs, advances in the environmental impact assessment and management of MP production can proceed more effectively.

Land use and spatial contiguity are key driven factors of antibiotic multimedia patterns in the megacity river network.

The widespread spread of antibiotics in the environment poses a growing threat to human health. This study investigated the distribution and fate of antibiotics concerning land use characteristics, hydrological conditions, and spatial contiguity within a megacity river network. Temporally, the average concentrations of twenty antibiotics in water (354 ng/L), suspended particulate matter (SPM) (46 ng/L), and sediment (151 ng/g) during dry season were notably higher than that in the corresponding environment media (water: 127 ng/L, SPM: 2 ng/L, and sediment: 49 ng/g) during the wet season. Moreover, the inter-annual variation of antibiotics in water showed a decreasing trend. Spatially, substantial antibiotic contamination was observed in a human-intensive watershed, particularly in the upstream and central city sections. The macrolides in water were most affected by land use types and hydrological processes. Antibiotic contamination in water exhibited a stronger spatial autocorrelation compared to other media. Nevertheless, the interconnectedness of antibiotic contamination in sediments during the wet season warrants attention, and relevant authorities should enhance environmental monitoring in watersheds with pollution hotspots. Certain antibiotics, such as sulfamethoxazole, enrofloxacin, and florfenicol, were transported via urban rivers to the ocean, potentially posing environmental risks to coastal water quality. Local sources accounted for the predominant portion (>50 %) of most antibiotics in various media. The correlation distances of antibiotics in waters during the wet season could screen ecological risk prioritization in aquatic environments.

Fine particulate matter as a key factor promoting the spread of antibiotics in river network.

The extensive utilization of antibiotics has resulted in their frequent detection, contributing to an increased abundance of antibiotic resistance genes in rivers and posing a significant threat to environmental health. Particulate matter plays a crucial role as the primary carrier of various pollutants in river ecosystem. Its physicochemical properties and processes of sedimentation and re-suspension can influence the migration and transformation of antibiotics, yet the mechanisms of this impact remain unclear. In this study, we investigated the distribution characteristics at the micro-scale of particles in the upstream plain river network of the Taihu basin and the adsorption behaviors of antibiotics in particulate matter. The results revealed that particles were predominantly in the size range of 30 to 150 µm in the river network and highest total antibiotic concentrations in 0 to 10 µm particle size fractions. Adsorption experiments also confirmed that the smaller the suspended particle size, the stronger the adsorption capacity for antibiotics. Spatially, both the average particle size and total antibiotic concentrations were lower downstream than upstream. The distribution mechanism of antibiotic in river network sediments was significantly influenced by frequent resuspension and settling of fine particles with a stronger capacity to adsorb antibiotics under hydrodynamic conditions. This ultimately facilitated the release of antibiotics from sediment into the water, resulting in lower antibiotic concentrations in downstream sediments relative to upstream These findings suggest that fine particles serve as the primary carriers of antibiotics, and their sorting and transport processes can significantly influence the distribution of antibiotics in water-sediment systems. This study enhances our understanding of the migration mechanisms of antibiotics in river networks and will prove beneficial for the development of management strategies aimed at controlling antibiotic dissemination.

A comprehensive spatial analysis of invertebrate diversity within intermittent stream networks: Responses to drying and land use.

Freshwater ecosystems are highly vulnerable to the impacts of climate change, which affect both diversity and ecosystem functioning. Furthermore, these ecosystems face additional threats from human activities, such as changes in land use, leading to water pollution and habitat degradation. Intermittent streams represent nearly half of all fluvial systems and support a rich diversity adapted to cope with drying. This study examines the impact of drying and different land uses on the taxonomic and functional diversity of aquatic invertebrates in a Mediterranean intermittent stream network. By sampling 16 reaches seasonally, we hypothesised that longer dry-phase duration and agriculture would both reduce α-diversity, with drying dominating impacts on ß-diversity over agricultural practices. We anticipated that drying and agriculture would alter species and trait compositions, favouring desiccation-tolerant and generalist taxa. Drying adversely affected the taxonomic and functional α-diversity of aquatic invertebrates, while it positively influenced ß-diversity. Land use only affected α-diversity. Specifically, habitat heterogeneity and increased water nutrient levels within the stream network correlated positively with invertebrate diversity. However, the negative effects of drying were less pronounced in upstream forested regions with high habitat heterogeneity compared to downstream areas influenced by agriculture. Our research highlights the importance of preserving natural and forested streams in intermittent networks, particularly in headwater regions, thus facilitating recolonization when flow is restored throughout the stream network.

Spatial heterogeneity of the effects of river network patterns on water quality in highly urbanized city.

River water quality deterioration is a serious problem in urban water environments. River network patterns affect water quality by influencing the flow, mixing, and other processes of water bodies. However, the effects of urban river network patterns on water quality remain poorly understood, thereby hindering the urban planning and management decision-making process. In this study, the geographically weighted regression (GWR) model was used to explore the spatial heterogeneity of the relationship between river network pattern and water quality. The results showed that the river network has a complex structure, high connectivity, and relatively even distribution and morphology. Important river structure indicators affecting water quality included the water surface ratio (Wp) and multifractal features (∆α, ∆f) while important river connectivity indicators included circuitry (α) and network connectivity (γ). River structure has a more complex effect on water quality than connectivity. This study recommends that the Wp should be increased in agricultural areas and appropriately reduced in urban built-up areas, and the number of river segments and nodes should be controlled within a rational configuration. Our study provides key insights for evaluating and optimizing the river network patterns to improve water quality of urban rivers. In the future, the land use intensity, hydrological processes, and human activities should be coupled with the river network pattern to deepen our understanding of urban river environment.

Hydrologic Connectivity Regulates Riverine N2O Sources and Dynamics.

Indirect nitrous oxide (N2O) emissions from streams and rivers are a poorly constrained term in the global N2O budget. Current models of riverine N2O emissions place a strong focus on denitrification in groundwater and riverine environments as a dominant source of riverine N2O, but do not explicitly consider direct N2O input from terrestrial ecosystems. Here, we combine N2O isotope measurements and spatial stream network modeling to show that terrestrial-aquatic interactions, driven by changing hydrologic connectivity, control the sources and dynamics of riverine N2O in a mesoscale river network within the U.S. Corn Belt. We find that N2O produced from nitrification constituted a substantial fraction (i.e., >30%) of riverine N2O across the entire river network. The delivery of soil-produced N2O to streams was identified as a key mechanism for the high nitrification contribution and potentially accounted for more than 40% of the total riverine emission. This revealed large terrestrial N2O input implies an important climate-N2O feedback mechanism that may enhance riverine N2O emissions under a wetter and warmer climate. Inadequate representation of hydrologic connectivity in observations and modeling of riverine N2O emissions may result in significant underestimations.

Research on the connectivity of urban river network-wetland and water quality simulation.

The connectivity of urban river networks plays an important role in cities in many aspects, such as urban water safety, water quality (WQ), and aquatic ecological balance. This study focuses on the river network and the Majiawan Wetland in the Chaoyang District of Beijing by establishing a two-dimensional hydrological WQ model employing various water allocation schemes between the river network and the wetland. Water circulation and WQ are the main indexes, and the effects of different scenarios on improving water circulation and WQ are simulated and compared. This study demonstrates that the addition of water replenishment at the intersection of river network and internal slow-water zones of the wetland (Scheme 2) has greater effectiveness in improving both hydrology and WQ compared to two other schemes. The water area of the Majiawan Wetland has expanded, and water velocity has increased. Using chemical oxygen demand, total nitrogen, and total phosphorus as the index values for determining the water class, the WQ of about 20% of the wetland area was reached Water Class II (domestic drinking water), with Water Class III (general industrial water) accounting for the other 80%. This study provides valuable evaluation and reference for similar areas of urban river network connectivity.

The length and spacing of river tributaries.

River networks are composed of a mainstem and tributaries. These tributaries dissect landscapes, regulate water and habitat availability, and transport sediment and nutrients. Despite the importance of tributaries, we currently lack theory and data describing whether and how tributary length and spacing varies within watersheds, thereby limiting our ability to accurately describe river network geometry. We address this knowledge gap by analyzing 4,696 tributaries across six landscapes with varying climate, tectonic setting, and lithology. Our results show that both tributary length and spacing systematically increase with downstream distance along the mainstem river, following a power-law scaling. This power-law scaling can be modulated by basin shape, with tributaries becoming shorter and, in some cases, more closely spaced as basin elongate. Furthermore, the power-law scaling may break down in cases where river networks have been disturbed by pervasive faulting, raising the possibility that the scaling we observe is not unique to all branching networks, and instead may be universal across undisturbed fluvial networks. These findings can be used to improve predictions of river network geometry and potentially to distinguish fluvial river networks from other branching networks.

Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore, there is an urgent need for a method that can accurately identify various types of agricultural organic pollution to prevent the water ecosystems in the region from significant organic pollution. In this study, a network model called RA-GoogLeNet is proposed for accurately identifying agricultural organic pollution in the river network area of the Jiangnan Plain. RA-GoogLeNet uses fluorescence spectral data of agricultural non-point source water quality in Changzhou Changdang Lake Basin, based on GoogLeNet architecture, and adds an efficient channel attention (ECA) mechanism to its A-Inception module, which enables the model to automatically learn the importance of independent channel features. ResNet are used to connect each A-Reception module. The experimental results show that RA-GoogLeNet performs well in fluorescence spectral classification of water quality, with an accuracy of 96.3%, which is 1.2% higher than the baseline model, and has good recall and F1 score. This study provides powerful technical support for the traceability of agricultural organic pollution.

Diversity and biogeography of bacterial community in the Ili River network varies locally and regionally.

Microorganisms in rivers indeed play a crucial role in nutrient cycling within aquatic ecosystems. Understanding the assembly mechanisms of bacterial communities in river networks is essential for predicting their special composition and functional characteristics in natural rivers. This study employed 16S rRNA gene amplicon sequence variation (ASVs) to scrutinize the bacterial community within the uniquely topographical Ili River network. The bacterial community composition varied across the three tributaries with distinct sources and the mainstream. The confluence of various sources diminished the diversity of the bacterial community and altered the functionality of within mainstream. We suggest that strong dispersal limitation predominantly shaped the community at the regional scale (46.6 %), underscoring the significant contribution of headwater sites to bacterial community composition. Contrary to expectation, the bacterial resources in the mainstream were not enriched by the higher diversity in three tributaries. Instead, confluence disturbance potentially increased the undominated processes (36.7 %) and alter the bacterial community composition at the local scale of the mainstream. The intricate coalescence at the confluence could potentially be an intriguing causative factor. Our research indicates that the composition of bacterial communities within intricate river networks exhibits biogeographic patterns, simultaneously influenced by river confluence and geographical features, necessitating multi-scale analysis.

Tracing sediment sources in a plain river network area by using optimized experimental design and reflectance spectroscopy.

Soil erosion in a plain river network area with dense rivers, fertile land, and agricultural development is easily causes river siltation, agricultural non-point source pollution, and water eutrophication. Therefore, the negative impact of the sediment on the environment cannot be underestimated. Most traditional sediment fingerprint tracing studies have focused on mountain basins and lack a scheme suitable for plain river network sediment tracing. Here, a typical plain river network in the Taihu Basin was selected as the study area. The flow structure and characteristics were analysed, and a sampling scheme for the stream segment and a two-step model of sediment tracing in a plain river network were proposed to quantitatively distinguish the types of sediment sources. The results indicated that the traditional discriminant function analysis adequately distinguishes the contribution rate of basin soil and has a good validation accuracy (R2 = 0.96, root mean square error of calibration = 5.91 %), whereas Random Forest obtains better discrimination results by mining non-linear information in the soil spectra of different land types, with R2 values of 0.89, 0.83, and 0.80 for farmland, forest, and grassland, respectively. The average proportion of soil in the sediment in the watershed was 23 %, and the proportion of soil in the watershed increased from upstream to downstream. The sediment sources of the Caoqiao, Yincun, and Shaoxiang Rivers mainly came from grassland (44 %), forest (39 %), and farmland (42 %), respectively. Land-use distribution, water conservation facilities, and soil particle size were the main factors affecting these sources. Each river adopts measures to remove the corresponding pollutants, optimise water and soil conservation measures for riverbank green belts and forest, and regularly clean up silt in water conservancy ditches and rivers, which can reduce the pollution impact caused by sediment.

Dynamics of Lotka-Volterra Competition Patch Models in Streams with Two Branches.

Streams may have many branches and form complex river networks. We investigate two competition patch models associated with two different river network modules, where one is a distributary stream with two branches at the downstream end, and the other is a tributary stream with two branches at the upstream end. Treating one species as resident species and the other one as mutant species, it is shown that, for each model, there exists a invasion curve such that the mutant species can invade when rare if and only if its dispersal strategy is below this curve, but the shapes of the invasion curves are different. Moreover, we show that the global dynamics of the two models can be similar or different depending on river networks. Especially, if the drift rates of the two species are equal, then the global dynamics are similar for small drift rate and different for large drift rate. Our results also confirm a conjecture in Jiang et al. (Bull Math Biol 82:131, 2020).

Dynamics of the sedimentary bacterial communities in a plain river network: similar coalescence patterns with bacterioplankton communities driven by distinct assembly processes.

IMPORTANCE: Microorganisms play important roles in driving the biogeochemical cycles within river ecosystems. It has been suggested that hydrologic conditions could influence microbial communities in rivers, but their specific effects on the behaviours of microbial coalescence have not been thoroughly investigated. In this study, the dynamics of sedimentary bacterial communities within a plain river network were analyzed by amplicon sequencing followed by several ecological models to uncover the underlying assembly processes. Additionally, a comparative analysis between bacterioplankton communities and sedimentary bacterial communities was performed to unveil their coalescence patterns. The results suggested that similar coalescence patterns between sedimentary bacterial and bacterioplankton communities were driven by distinct assembly processes under dynamic hydrological conditions. These findings enhanced our understanding of microbial diversity features within river ecosystems.

Pleistocene Landscape Dynamics Drives Lineage Divergence of a Temperate Freshwater Fish Gobio rivuloides in Coastal Drainages of Northern China.

Understanding historical processes underlying lineage distribution patterns is a primary goal of phylogeography. We selected Gobio rivuloides (Cypriniformes: Gobionidae) as a model to improve our knowledge about how intraspecific genetic divergence of freshwater fishes arises in coastal drainages of northern China via statistical analysis using cytochrome b gene. The time-calibrated phylogeny of G. rivuloides showed the divergence of two major lineages (I and II) at ~0.98 Ma (million years ago). Lineage I can be divided into two sub-lineages (I-A and I-B) with a divergence time of ~0.83 Ma. Sub-lineage I-A inhabits the Amur River, and sub-lineage I-B lives in the Luan River and Liao River. Lineage II is distributed in the Yellow River and Hai River, with close genetic relationships between the two drainages, and can be split into two sub-lineages (II-C and II-D) with a divergence time of ~0.60 Ma. Our findings indicate that the splitting of lineages and sub-lineages could be attributed to geographic isolation caused by the formation of the Bohai Sea, river capture, and the episodic hydrologic closing of a paleolake during the late Lower-Middle Pleistocene. It is also the first report we know of displaying a clear phylogeographic break for freshwater fishes across coastal drainages in northern China.

River connectivity determines microbial assembly processes and leads to alternative stable states in river networks.

River network is a common form of lotic ecosystems. Variances in river connection modes would form networks with significantly different structures, and further affect aquatic organisms. Microbial communities are vital organisms of river networks, they participate in numerous biogeochemical processes. Identifying associations between microbial community and structural features of river networks are essential for maintaining environmental quality. Thus, dendritic (DRN) and trellised river networks (TRN) were studied by combining molecular biological tools, ecological theory and hydrodynamic calculation. Results illustrated that river connectivity, a vital structural feature exhibiting mass transport ability of river network, increased relative importance of homogeneous selection processes in microbial assembly, which would further shape community with alternative stable states. Between the two researched river networks, DRN possessed higher connectivity, which made homogeneous selection as the driving force in community assembly. The microbial communities in DRN were consisted of species occupying similar ecological niche, and exhibited two alternative stable states, which can decrease influences of environmental disturbance on community composition. On the contrary, lower connectivity of TRN decreased proportions of homogeneous selection in community assembly, which further led to species occupying varied ecological niche. The microbial community exhibited only one stable state, and environmental disturbance would cause loss of ecological niche and significantly alter community composition. This study could provide useful information for the optimization of river connection engineering.