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Water Quality Variation Patterns in Storm Sewers under Impact of Exogenous Pollutants
HUANG Biao, YU Fu-hui, LÜ Jia-chun, TANG Yang-bo, HE Wen-feng
Journal of Changjiang River Scientific Research Institute ›› 2025, Vol. 42 ›› Issue (12) : 170-179.
PDF(2808 KB)
PDF(2808 KB)
Water Quality Variation Patterns in Storm Sewers under Impact of Exogenous Pollutants
[Objective] Storm sewers face challenges from both hydraulic pressures and pollutant accumulation. Exogenous inflows carry substantial pollutant loads into storm sewers, and during rainfall events, these pollutants are rapidly mobilized and discharged at outfalls, sharply degrading receiving water quality and presenting a critical environmental management challenge. This study systematically investigates the sources, dynamics, and impacts of storm sewer pollution in a representative urban drainage area with known exogenous pollution inputs. Specifically, it aims to identify dominant pollution sources, analyze the spatiotemporal evolution of pollutant accumulation during dry and rainy seasons, and evaluate the effectiveness of outlet-based control strategies through scenario simulation. The novelty of this study lies in its integration of long-term, high-frequency monitoring with multivariate statistical analysis and rainfall scenario modeling, providing mechanistic insights into storm sewer pollution processes and their mitigation. [Methods] The study was conducted in a storm sewer drainage catchment located in a densely urbanized district, characterized by frequent illicit sewer connections and adjacent industrial facilities. Comprehensive monitoring was carried out in a full hydrological year, covering both dry and rainy seasons to capture seasonal variations. The measured parameters included flow rate, COD, NH3-N, total phosphorus (TP), and conductivity, while event-based sampling during rainfall events captured the dynamics of pollutant wash-off and resuspension. To separate the contributions of different sources, principal component analysis (PCA) was applied to the monitoring dataset to identify dominant pollution signatures. Stepwise statistical methods were employed to evaluate temporal accumulation patterns. Hydrological and water quality models were developed to reproduce rainfall-runoff processes under typical storms, incorporating outlet-based control measures like initial flow detention and sedimentation. By integrating real-time data collection, multivariate source apportionment, and scenario simulations, this approach established a robust framework to analyze the interactions between exogenous pollution sources and in-pipe pollutant dynamics. [Results] The results revealed interactions between continuous exogenous inflows, internal accumulation, and rainfall-induced pollutant mobilization. PCA distinguished three dominant sources: illicit sanitary sewage connections that caused continuous baseflow contamination during dry seasons; rainfall-driven surface wash-off that produced sharp concentration spikes at the onset of storms; and industrial discharges, typically episodic with specific COD fractions and heavy metal signatures. During dry seasons, a stepwise increase in pollutant concentrations was observed, as COD and NH3-N accumulated in the sewer network due to ongoing illicit inflows and limited hydraulic flushing, creating latent pollution risks, abruptly released during subsequent rainfall events. High-frequency monitoring during storms confirmed a pronounced first-flush effect, with pollutant concentrations peaking within the first 20-30 minutes of rainfall due to both surface wash-off and the resuspension of in-pipe deposits. Scenario-based modeling demonstrated that targeted outlet control measures could significantly mitigate these impacts. The simulations showed that detaining approximately the initial 30% of stormwater outflow reduced COD and NH3-N loads by 40%-60%, highlighting the effectiveness of simple, targeted interventions. Furthermore, detention measures delayed pollutant peaks, reducing acute stress on receiving waters and improving the resilience of the urban drainage system to pollution shocks. These results underscored the importance of addressing both continuous exogenous inflows and event-based flushing dynamics for effective pollution control. [Conclusion] This study provides new evidence on the mechanisms and management of storm sewer pollution, demonstrating that internal sewer pollution results from the combination of continuous accumulation during dry seasons and sudden mobilization during rainfall events. Unlike previous studies focusing on rainfall-runoff wash-off as the primary driver, this study highlights the critical role of illicit sanitary connections and industrial discharges in maintaining persistent internal pollutant loads. By combining long-term, high-frequency monitoring with PCA-based source apportionment and rainfall scenario simulations, the study presents an innovative framework applicable to other urban areas for revealing hidden pollution dynamics. The practical implications are significant. Localized outlet control measures, particularly initial stormwater detention, provide a cost-effective and technically feasible way to reduce pollutant loads in receiving waters. On a broader scale, the findings emphasize the necessity of integrating internal storm sewer pollution management into urban water quality strategies. This study advances the understanding of pollutant accumulation and mobilization in storm sewers while providing guidance for sustainable urban drainage planning.
urban stormwater drainage network / exogenous pollutants / rainfall events / water quality evolution patterns / control facilities
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Urban black blooms that are primarily caused by organic carbon are deleterious environmental problems. However, detailed studies on the microbial characteristics that form urban black blooms are lacking. In this study, we observed the composition, diversity, and function of bacterial community in the overlying water and sediments during the occurrence and remediation of urban black blooms using high-throughput 16S rRNA gene amplicon sequencing analysis. First, we found that pivotal consortia in the overlying water increased significantly during the formation of black blooms, including the genera Acidovorax, Brevundimonas, Pusillimonas, and Burkholderiales involved in the degradation of refractory organics, as well as the genera Desulfovibrio, Dechloromonas, and Rhizobium related to the production of black and odorous substances. An RDA analysis revealed that chemical oxygen demand, dissolved oxygen, and oxidation reduction potential were related to the changes in microbial community composition. Furthermore, aeration was found to accelerate the removal of ammonia nitrogen and enhance the function of microbial community by stimulating the growth of order Planktomycetes during the remediation of black blooms, but aeration substantially damaged the microbial diversity and richness. Therefore, the health of the aquatic ecosystem should be comprehensively considered when aeration is applied to restore polluted waterbodies. Notably, we observed a large number of pathogenic bacteria in urban black blooms, which emphasizes the importance of treating domestic sewage so that it is harmless. Together, these findings provide new insights and a basis to prevent and manage urban black blooms.Copyright © 2021. Published by Elsevier B.V.
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Stormwater quality modeling remains one of the most challenging issues in urban hydrology today. The processes involved in contaminant generation and transport are very complex, with many associated uncertainties, including uncertainty arising from process variability. In this study, the spatio-temporal variability of build-up/wash-off processes in a heterogeneous urban catchment within the Parisian region is assessed based on three stochastic modeling approaches integrated into the physically based distributed hydrological model, the Urban Runoff Branching Structure (URBS) model. Results demonstrate that accounting for process variability at the scale of a hydrological element is important for analyzing the contamination recorded at the catchment outlet. The intra-event dynamics of total suspended solids (TSS) were most accurately selected for the stochastic exponential SWMM model, as this model succeeded not only in simulating the general trend of TSS concentrations fluctuations but also in replicating multiple peaks observed in pollutographs. The advantage of this approach is that it captures the stochastic nature of the processes with minimal prior knowledge and without extensive calibration, though further enhancement is necessary for it to become a useful tool to support decision making.
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Diffuse pollution caused by rainfall events potentially affects water quality in rivers and, therefore, must be investigated in order to improve water quality planning and management recovery strategies. For these, a quali-quantitative approach was used to monitor the water quality parameters in a river located in a semi-urban watershed area based upon automatic sampling. Thirteen water quality parameters were measured during five rainfall events. Events ranged from 2.3 to 56.8 mm and water peak flows from 3.3 to 4.5 m/s. The pollutographs measured showed a standard pattern for total suspended solids (TSS). However, for the other chemical parameters, as total phosphorous (TP) and dissolved organic carbon (DOC), the dilution effects were more evident. It was possible to observe the rainfall influence mainly for physical parameters indicating a mass transport pattern for diffuse pollutants, which increased, for example, the amount of TSS in the river. Furthermore, hydrological characteristics were relevant considering the pollutant behavior. Antecedent dry periods, ranging from 1.3 days to 21.4 days, and critical time, from 2.0 to 10.4 h, are determinants to evaluate non-traditional water quality impacts in the river. In general, each rainfall episode has its own characteristics, which produces distinct mass contribution and temporal behavior, being challenging in making generalization. Therefore, the results indicate that diffuse pollution has to be considered to establish future decision-making strategies to water resources management.
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The magnitude of pollution in Lake Hawassa has been exacerbated by population growth and economic development in the city of Hawassa, which is hydrologically closed and retains pollutants entering it. This study was therefore aimed at examining seasonal and spatial variations in the water quality of Lake Hawassa Watershed (LHW) and identifying possible sources of pollution using multivariate statistical techniques. Water and effluent samples from LHW were collected monthly for analysis of 19 physicochemical parameters during dry and wet seasons at 19 monitoring stations. Multivariate statistical techniques (MVST) were used to investigate the influences of an anthropogenic intervention on the physicochemical characteristics of water quality at monitoring stations. Through cluster analysis (CA), all 19 monitoring stations were spatially grouped into two statistically significant clusters for the dry and wet seasons based on pollution index, which were designated as moderately polluted (MP) and highly polluted (HP). According to the study results, rivers and Lake Hawassa were moderately polluted (MP), while point sources (industry, hospitals and hotels) were found to be highly polluted (HP). Discriminant analysis (DA) was used to identify the most critical parameters to study the spatial variations, and seven significant parameters were extracted (electrical conductivity (EC), dissolved oxygen (DO), chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), sodium ion (Na+), and potassium ion (K+) with the spatial variance to distinguish the pollution condition of the groups obtained using CA. Principal component analysis (PCA) was used to qualitatively determine the potential sources contributing to LHW pollution. In addition, three factors determining pollution levels during the dry and wet season were identified to explain 70.5% and 72.5% of the total variance, respectively. Various sources of pollution are prevalent in the LHW, including urban runoff, industrial discharges, diffused sources from agricultural land use, and livestock. A correlation matrix with seasonal variations was prepared for both seasons using physicochemical parameters. In conclusion, effective management of point and non-point source pollution is imperative to improve domestic, industrial, livestock, and agricultural runoff to reduce pollutants entering the Lake. In this regard, proper municipal and industrial wastewater treatment should be complemented, especially, by stringent management that requires a comprehensive application of technologies such as fertilizer management, ecological ditches, constructed wetlands, and buffer strips. Furthermore, application of indigenous aeration practices such as the use of drop structures at critical locations would help improve water quality in the lake watershed.
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Water resources are scarce in the Northeastern Loess Plateau, and water cellar water (WCW) is a vital water resource available in the vast rural areas of the region. The quality of WCW was assessed by principal component analysis (PCA) and Nemerow’s pollution index (NPI) for different rainfall catchment areas, depths, and storage times. Eleven indicators were measured, including pH, electrical conductivity (EC), F−, Cl−, NO3−, SO42−, Na+, NH4+, Ca2+, Mg2+, and K+. The results show that the tap water quality in the rural areas of the Northeastern Loess Plateau is above the second level and meets the drinking water standard (DWS), which is similar to the tap water quality in the region. The main component score of water quality from tile roof + cement ground (I) is 0.32, and the Nemero index is 0.41; the principal component score of water quality from cement ground (I) is 0.45, and the Nemero index is 0.29; the principal component score of water quality from trampled land (I) is 0.59, and the Nemero index is 0.44; the principal component score of water quality from tile roof + trampled land (II) is 1.87, and the Nemero index is 1.10. The rainwater harvesting catchment area of tile roof + cement ground (I) ensured the highest water quality, followed by cement ground (I), trampled ground (I), and tile roof + trampled ground (II). The water quality of the catchment area for artificially collected rainwater (roof tile surface, cement ground, etc.) was better than that of the original soil (trampled ground). The highest water quality was found at a storage time of 1 year (I), followed by 2.5 years (I), and 2 months (II). A depth of 4 m (I) contributed to the highest water quality, followed by 2 m (II), 3 m (II), and 1 m (II). Water quality improved with the increasing depth of WCW. The rainfall and WCW in the area were weakly alkaline, and the groundwater was contaminated with NO3−. PCA’s water quality assessment results were similar to the NPI method, indicating that both methods can be used in combination for unconventional water quality assessment.
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The water environment of plain river networks can be self-cleaning to a certain extent, but if the wastewater load exceeds a certain threshold, it can disturb the natural balance and cause water pollution. This underlines the importance of water pollution control measures. However, the development of water pollution control measures requires a large number of hydrological and hydrodynamic parameters and the establishment of corresponding relationships through modelling. Therefore, this study mainly used the Infoworks ICM model to construct a detailed hydrological–hydrodynamic water environment analysis model for the Yundong area of Baoying County, Yangzhou City, China, screened the main pollution source areas and pollution time periods of the typical rivers in the study area, and proposed effective improvement measures according to the actual situation of the study area. The results show that after the synergistic effect of multiple measures, the water quality can reach the Class III standard (GB3838-2002). This study can provide a reference for the water environment management and improvement of the plain river network and has good application prospects.
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Rainfall events induce water quality transformation in river systems influenced by the watershed land use and hydrology dynamics. In this context, an adaptive monitoring approach (AMA) is used to assess non-point sources (NPS) of pollution events, through dissolved organic matter (DOM) contribution. The case study is a monitoring site in a semi-urban watershed characterized by NPS contribution. An integrated quali-quantitative method for DOM based on dissolved organic carbon (DOC) content, spectroscopic techniques of excitation-emission fluorescence (EEF), and UV-visible absorbance is proposed. The results indicate a mix of allochthonous and autochthonous DOM characteristics from NPS sources associated to vegetation area influence (A/DOC of 15.43 L (g cm) and SUVA of 2.11 L (mg m)). The EEF signals showed more humic-like than protein-like characteristics with peaks A and C (approximately 5.72 r.u.) more intense than peaks B, T, and T (approximately 4.33 r.u.), indicating NPS from the soil leachate. The absorbance ratio values indicate a mix of organic compounds with greater proportion of refractory characteristics with high aromaticity and molecular weight (approximately A/A of 4.15 and A/A of 4.48), associated with the surface wash-off of accumulated residual and subsurface soil erosion, which contribute to complex organic matter structures. The fluorescence indexes, overall, indicated allochthonous sources with intermediate humic characteristics (FI ≈ 1.43, BIX ≈ 0.65, and HIX ≈ 7.98). The proposed integrated optical property strategy represents an opportunity for better understanding of DOM dynamic assessment for identifying potential mitigation techniques for organic pollution control and improving water quality conditions.
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This paper presents one of the largest databases on the quality of urban wet weather discharges measured since the development of continuous in-sewer water quality sensors in the late 1990s. Five years of continuous turbidity measurements enabled the validation of 263 and 239 rainfall events, respectively on two experimental catchments in Lyon (France), Chassieu (185 ha separate sewer) and Ecully (245 ha combined sewer). Except for high rainfall events of summer and second half of winter, analysis of database representativeness showed that all seasons were relatively well represented. As a first analysis of the database, traditional tools used in the urban drainage field were applied to assess: i) statistics and analysis of distributions of TSS and COD events loads and event mean concentrations (EMCs) and ii) the correlations between these statistics and events characteristics and iii) M(V) curves describing the intra-event mass distribution. Results showed that: i) EMCs and loads were approximately log-normally distributed, with a clear impact from wastewater contribution in Ecully, ii) EMCs are not correlated with storm event characteristics, whereas loads have shown significant correlation with key storm event variables such as total event volume, rainfall depth, maximum rainfall intensity and discharge and iii) M(V) curves dynamic could be classified in three categories, however with no clear correlation with storm event characteristics. The visual analysis of continuous time series of TSS and COD pollutographs, derived from turbidity time series showed that event pollutographs were highly variable, due to complex interacting processes during and between events, and suggests that further progress in knowledge and modelling of urban wet weather pollutant loads and pollutographs should be based on more detailed analyses of continuous time series rather, than on the traditional single event approach.Copyright © 2011 Elsevier Ltd. All rights reserved.
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DB11/T2074—2022,城镇排水防涝系统数学模型构建与应用技术规程[S]. 北京: 北京市城市规划设计研究院.北京市规划和自然资源委员会、北京市市场监督管理局, 2022.
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