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Article

Quantitative Assessment of Seasonal and Land-Use Impacts on Coastal Urban Sewage Systems with Seawater Intrusion Vulnerability Analysis

by
Yanhong Ge
1,2,†,
Jiachong Lin
3,†,
Qidong Yin
3,4,
Sheng Huang
3,
Yingchao Lin
5 and
Kai He
3,*
1
Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
2
Guangdong Infore Technology Co., Ltd., Foshan 528300, China
3
School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China
4
Guangdong Provincial Key Laboratory of Marine Civil Engineering, Shenzhen 518060, China
5
College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Water 2025, 17(13), 1939; https://doi.org/10.3390/w17131939 (registering DOI)
Submission received: 29 March 2025 / Revised: 30 May 2025 / Accepted: 13 June 2025 / Published: 28 June 2025
(This article belongs to the Special Issue Sewage Disposal, Biological Processes and Resource Utilization of Sewage Sludge)
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Versions Notes

Abstract

Based on the sewage pipe network system in the service area of Qianshan-Gongbei Plant in Zhuhai City, the characteristics of water quality and quantity were analyzed, and the common problems were diagnosed. Through the establishment of a hydraulic-water quality model, the flow state of sewage in the pipe network is simulated, and the actual data is checked. It is found that there are significant differences in the quantity and quality of sewage pipe network systems in different seasons and land use types, and there is an obvious seawater backflow phenomenon in coastal areas. To solve these problems, this paper puts forward a series of optimization suggestions to improve the operation efficiency of sewage treatment plants and the reliability of urban drainage systems.

1. Introduction

Urban drainage systems constitute critical infrastructure in modern cities, serving as vital conduits for the collection and conveyance of wastewater to treatment facilities. In recent years, rapid economic growth and substantial investments in infrastructure have spurred significant expansion of urban drainage networks across China. By the end of 2022, the cumulative length of urban drainage pipelines reached an impressive 914,000 km [1]. Despite these expansions and the concurrent increases in Wastewater Treatment Plant (WWTP) capacities, persistent challenges remain. In particular, external water intrusion and the interconnection of stormwater and sewage systems often lead to unexpectedly low pollutant concentrations in WWTP influents—a phenomenon especially pronounced in southern China, where abundant rainfall exacerbates the issue compared to northern regions [2]. These diluted influents disrupt the carbon-to-nitrogen-phosphorus Ratio (C:N:P) balance critical for biological treatment, potentially increasing chemical usage for nutrient removal while reducing biogas production in anaerobic processes—outcomes that vary by technology but consistently elevate operational costs per cubic meter treated [3].
This discrepancy between anticipated and observed influent quality suggests inefficiencies within the collection system that hinder optimal WWTP performance and compromise treatment efficacy [4]. The root causes are multifaceted, stemming largely from a historical prioritization of network expansion over proactive management and maintenance. Consequently, issues such as pipeline misconnections, structural defects (e.g., cracks and corrosion), and unauthorized direct sewage discharges have become widespread [5,6]. These deficiencies contribute not only to significant extraneous water intrusion, including groundwater and stormwater, but also to combined sewer overflows that dilute the wastewater stream and reduce treatment efficiency [7,8]. Moreover, such operational shortcomings pose direct risks to environmental quality through sewage overflows and the contamination of surrounding soils and water bodies [9,10]. The resulting fluctuations in influent water quantity and quality present substantial challenges for maintaining stable, compliant WWTP operations, ultimately hindering the achievement of consistent effluent standards [11,12]. Thus, enhancing system performance requires a comprehensive understanding of the factors influencing both the volume and composition of wastewater entering treatment facilities.
Prior studies have explored various approaches to address these challenges, notably through the development and application of pipe network models and numerical simulations. These tools enable detailed analyses of sewage flow patterns, the identification of hydraulic bottlenecks, and the prediction of water quality variations along pipelines [13]. By simulating multiple scenarios, researchers can pinpoint areas affected by leakage, damage, or misconnections, thereby reducing reliance on extensive manual inspections. In addition to modeling, diagnostic methodologies that partition urban drainage networks into discrete management zones have been investigated [14,15,16]. For instance, a diagnostic framework that integrates localized water quality monitoring with chemical mass balance models has been proposed to assess sewage collection efficiency within these partitions [17,18]. Furthermore, comparing theoretical sewage generation volumes—derived from population and water consumption data—with actual monitored flows at WWTPs can reveal discrepancies indicative of significant inflow and infiltration(I/I) issues [19,20]. These partition-based diagnostic techniques offer valuable insights for targeted inspection and rehabilitation, ultimately enhancing network performance and guiding facility upgrades. However, despite these advancements, there remains a notable gap in the focused investigation of coastal urban drainage systems. Coastal cities face unique challenges due to tidal influences, seawater intrusion, and often higher population densities, all of which necessitate tailored assessment and management strategies. Critically, the development of an integrated modeling framework incorporating these interdependent variables (tidal dynamics, water quality gradients, and hydraulic loading rates) could significantly improve WWTP adaptability. Recent advances in sewer system modeling (e.g., coupled hydrodynamic-water quality simulations) have demonstrated particular utility for:
(i)
Predicting seawater intrusion impacts on influent quality and WWTP operational efficiency.
(ii)
Optimizing pump scheduling to mitigate tidal back-flow effects.
(iii)
Forecasting contaminant load variations under compound rainfall-tide scenarios.
Such numerical approaches enable scenario testing of coastal-specific conditions that are impractical to study through physical monitoring alone, providing a powerful tool for operational decision-support and infrastructure planning. The models can specifically address:
(i)
Dynamic correlations between tidal cycles and influent salinity fluctuations.
(ii)
Nonlinear responses of biological treatment units to variable water quality gradients.
(iii)
Capacity allocation strategies under hydraulic and pollution load shocks.
This study addresses the aforementioned gap by focusing on Zhuhai City, a coastal metropolis in southern China that faces significant challenges in sewage pipe network treatment capacity and operational efficiency. Leveraging a comprehensive dataset of monthly water quantity and quality measurements from 2021—collected from WWTPs and associated sewage pumping stations—this research examines the interplay among seasonality, land use, and seawater intrusion on influent characteristics. The objectives are to (1) characterize the temporal and spatial patterns of water quantity and quality within the WWTP service area; (2) identify the key factors contributing to observed variations, including rainfall patterns, land-use characteristics, and seawater intrusion; and (3) pinpoint specific areas within the network exhibiting performance deficiencies. The insights gained are expected to inform strategies for optimizing the management and operation of coastal urban drainage systems, ultimately contributing to enhanced water quality and environmental protection.

2. Materials and Methods

2.1. Study Area

Zhuhai City, a coastal urban area in Guangdong Province, exhibits a subtropical maritime monsoon climate with abundant precipitation, creating significant operational challenges for its sewage pipe network system. The service area of the Qianshan-Gongbei Wastewater Treatment Plant (WWTP) encompasses several distinct drainage zones, including Shangchong, Qianshan, Gongbei, and the Nanping Science and Technology Industrial Park. This area, with a developed land footprint of approximately 42.7 km2, accommodates a resident population of around 620,000. Within this region, the sewage collection system is supported by two operational Wastewater Treatment Plants—the Qianshan WWTP and the Gongbei WWTP—complemented by a network of established sewage pumping stations (see Figure 1).

2.2. Data Sources

To analyze the temporal variations in water quantity and quality at sewage pumping stations within the drainage network, seven specific pumping stations were selected as study subjects: Guangzhu, Daishan, Paizi, Shangchong, Shuiwantou, Yuehaidong and the Cross-Border Industrial Park pumping stations (Kuajinggongyeyuan Pump Station). Hydraulic analysis revealed that the Pingdongsilu and Guangzhu pumping stations shared nearly identical operational profiles—both serving as terminal collection nodes (receiving exclusively local residential sewage without contributions from upstream stations) in their respective sewer subsystems. Given this functional equivalence, the Guangzhu station was chosen as the representative case for systematic evaluation. Data were collected from these stations, encompassing measured inflow water volume, inflow Chemical Oxygen Demand (COD) concentration, inflow ammonia nitrogen (NH3-N) concentration, and inflow chloride concentration over the period from 2021 to 2023. These data were utilized to investigate the characteristics of temporal changes in water quantity and quality and to assess the influence of land use types on these variations.

2.3. Water Quality Analysis

Water quality parameters were analyzed using standard methods [21]. Specifically, the concentration of COD was determined by the rapid digestion spectrophotometric method, utilizing potassium dichromate solution as the oxidizing agent [22]. The 5-day Biochemical Oxygen Demand (BOD5) was measured using the dilution and seeding method [23]. Suspended Solids (SS) were quantified via the gravimetric method [24]. Total Nitrogen (TN) was determined using the alkaline potassium persulfate digestion UV spectrophotometric method [25]. Total Phosphorus (TP) was measured employing the continuous flow ammonium molybdate spectrophotometric method, with analysis performed on a continuous flow analyzer [26]. Ammonia nitrogen (NH3-N) was determined using the Nessler’s reagent spectrophotometric method, with measurements taken on a visible spectrophotometer [27]. Chlorine concentration was analyzed using the N,N-diethyl-p-phenylenediamine (DPD) spectrophotometric method [28]. This method is suitable for water samples with a chlorine concentration range of 0.05–1.5 mg/L. The procedure involves the addition of a DPD reagent to the sample, which reacts with chlorine to form a red-colored complex. The absorbance of the resulting solution is then measured at a wavelength of 515 nm using a spectrophotometer, and the chlorine concentration is calculated based on a calibration curve prepared with standard chlorine solutions [29]. This method is applicable for monitoring various water sources, including drinking water, medical wastewater, and dye wastewater, and is particularly useful for assessing the impact of water treatment processes on chlorine levels.

3. Results

3.1. Seasonal Variations in Influent Quantity and Quality at the Qianshan WWTP

Analysis of influent characteristics at the Qianshan WWTP in Zhuhai City revealed pronounced seasonal variations in both water quantity and quality that are directly correlated with the region’s distinct wet (April–October) and dry (November–March) seasons (see Figure 2). During the wet season, influent flow rates increased significantly, generally ranging from 2–3 × 106 m3 per month, with peak flows in August and September approaching 3 × 106 m3. This surge is attributable to increased precipitation and subsequent runoff entering the combined sewer system. Conversely, during the dry season, influent volumes decreased considerably, ranging from 1–2 × 106 m3 per month, with the lowest values recorded in January and February (approximately 1 million m3).
Key water quality parameters exhibited inverse trends relative to the flow rates. In the dry season, when influent flows were reduced, concentrations of COD, BOD, and SS were elevated. Specifically, dry season COD concentrations ranged from 200 to 300 mg/L, BOD from 100 to 150 mg/L, and SS from 100 to 150 mg/L—particularly in December and January. In contrast, during the wet season, the increased influent volume resulted in a significant dilution effect, with COD decreasing to 100–200 mg/L, BOD to 50–100 mg/L, and SS to 50–100 mg/L. Nutrient concentrations also displayed notable seasonal fluctuations; NH3-N and TN levels were higher in the dry season (NH3-N: 15–25 mg/L; TN: 30–40 mg/L) compared to the wet season (NH3-N: 10–20 mg/L; TN: 20–30 mg/L). TP exhibited less pronounced seasonal variation, although slightly higher concentrations were observed during the dry season (3–5 mg/L) relative to the wet season (2–4 mg/L).
Overall, the Qianshan WWTP demonstrates significant seasonal fluctuations in both influent quantity and quality. During the rainy season, increased precipitation leads to higher influent volumes but lower pollutant concentrations due to dilution. The dry season is characterized by reduced flows and elevated pollutant levels, indicating that the sewage system faces distinct challenges and treatment pressures across different seasons.

3.2. Seasonal Variations in Influent Quantity and Quality at the Gongbei WWTP

Similar to the Qianshan WWTP, the Gongbei WWTP exhibits analogous seasonal patterns in influent quantity and quality (see Figure 3). During the wet season (April–October), influent flow rates increase markedly, ranging from 4–6 × 106 m3 per month and peaking in August at nearly 7 × 106 m3. This surge is directly attributed to enhanced rainfall and increased stormwater inflow into the sewer network. Conversely, during the dry season, influent volumes decreased considerably, ranging from 1–2 × 106 m3 per month, with the lowest values recorded in January and February (approximately 1 × 106 m3).
Water quality parameters at the Gongbei WWTP are similar to those observed at Qianshan. In the dry season, reduced influent flow coincides with significantly higher concentrations of key pollutants: COD levels range from 250 to 350 mg/L and BOD from 150 to 200 mg/L. In contrast, during the wet season, dilution effects lower COD concentrations to 150–250 mg/L and BOD to 100–150 mg/L. SS also exhibits a seasonal pattern, with values of 100–150 mg/L, particularly from December to February—in the dry season and 50–100 mg/L during the wet season. Nutrient concentrations show similar seasonal variations; NH3-N and TN peak in the dry season at 20–30 mg/L and 30–40 mg/L, respectively, compared to 10–20 mg/L (NH3-N) and 20–30 mg/L (TN) in the wet season. Although TP displays less variation overall, its concentration is slightly elevated during the dry season (4–5 mg/L in January–February) relative to the wet season (3–4 mg/L).
Overall, the Gongbei WWTP is clearly influenced by seasonal precipitation patterns. During the rainy season, increased rainfall leads to higher influent volumes and a corresponding dilution of pollutants. In contrast, the dry season is characterized by reduced flow and elevated pollutant concentrations, underscoring the critical role of seasonal dynamics and, in coastal regions, the potential contribution of seawater intrusion in shaping influent characteristics.

3.3. Impact of Land Use Types on Water Quality and Quantity

The spatial analysis of influent characteristics from six representative pumping stations (Figure 4 and Figure 5) reveals that the interplay between land use and seasonal variations significantly influences the water quality and quantity within the coastal urban sewage pipe network system. For instance, the Cross-Border Industrial Park pumping station, serving an industrial zone, consistently exhibited higher NH3-N concentrations (10–42 mg/L), reflecting the impact of industrial discharges. In contrast, the Shangchong station, located in a densely populated residential area, showed consistently high influent flow rates and correspondingly elevated total COD and NH3-N loads, attributable to increased domestic wastewater discharge. Notably, the Shuiwantou pumping station, situated in a coastal area with lower population density, recorded the lowest pollutant concentrations (COD < 120 mg/L, NH3-N < 20 mg/L, excluding March 2021), likely due to reduced anthropogenic inputs and potential dilution effects from seawater intrusion, a factor not quantitatively assessed. Additionally, the Daishan pumping station, also serving a residential area, demonstrated elevated total COD and NH3-N levels; pandemic-related lockdowns before October 2022 resulted in increased pollutant loads, whereas the subsequent easing of restrictions led to a reduction in these levels.
Temporal analysis further underscores pronounced seasonal fluctuations in both water quantity and pollutant concentrations. At the Guangzhu pumping station, an inverse relationship was evident: peak flows during the rainy season (observed in August 2021 and 2022 and October 2023) corresponded with minima in pollutant levels. The Paizi pumping station, influenced by its coastal setting, exhibited considerable flow variability while generally maintaining lower pollutant concentrations. In contrast, the Daishan pumping station displayed milder seasonal variations, with instances where dry season flows occasionally exceeded those of the rainy season. At the Cross-Border Industrial Park pumping station, although influent flows remained relatively stable over time, pollutant loads exhibited notable temporal trends, suggesting that the magnitude of industrial discharge varied with operational activity. Moreover, the temporal dynamics of pollutant loads were clearly influenced by external factors such as industrial activity. Reduced industrial output during the 2021 COVID-19 pandemic correlated with lower pollutant loads, while the subsequent recovery in industrial production during 2022 and 2023 resulted in substantial increases in both flow rates and pollutant concentrations. Additionally, the Shangchong pumping station consistently experienced peak flows during the summer months, and at the Guangzhu pumping station, the trends for COD and NH3-N concentrations were closely aligned, each exhibiting an inverse relationship with water quantity. These observations underscore the critical roles of both land use and temporal variability in shaping the performance and operational challenges of coastal urban sewage systems.

3.4. Analysis of Factors Influencing Wastewater Quality in Coastal Pumping Stations

To further investigate the impact of seawater intrusion on influent water quality at coastal pumping stations, chloride (Cl−) concentrations were analyzed at three representative sites within the study area: Shuiwantou, Yuehaidong, and Paizi (Figure 6). Across all three stations, Cl− levels were significantly elevated, providing clear evidence of seawater mixing with the wastewater system. These elevated chloride concentrations serve as a reliable indicator of saline intrusion and highlight the vulnerability of coastal urban sewage networks to seawater contamination. The analysis focused on variations in Cl− concentrations under differing tidal and rainfall conditions, which facilitated a comprehensive interpretation of intrusion patterns. By comparing data across multiple stations, the study assessed spatial variability in saline influence and yielded valuable insights into the complex interplay between natural seawater intrusion and sewage systems.
At the Shuiwantou pumping station, instances of exceptionally high Cl− concentrations were recorded, highlighting the significant influence of tidal dynamics and stormwater influx. On 6 and 14 May 2020, as well as on 9 August 2020, chloride levels reached 6873.05 mg/L, 6489.4 mg/L, and 7118.5 mg/L, respectively. Notably, these episodes of heightened Cl− were accompanied by markedly reduced COD and NH3-N concentrations, elevated tide levels, and increased influent flow rates. This inverse relationship strongly indicates that seawater is actively mixing with the incoming wastewater, resulting in a dilution of organic pollutants and a direct impact on overall influent quality.
In contrast, there were occasions when elevated Cl− concentrations coincided with high levels of other pollutants. For example, on 8 May 2020 (Cl−: 7462.93 mg/L, COD: 720 mg/L), 3 September 2020 (Cl−: 7668 mg/L, COD: 720 mg/L), 12 November 2020 (Cl−: 8008.8 mg/L, COD: 1010 mg/L), and 8 March 2021 (Cl−: 8264.4 mg/L, COD: 590 mg/L), both chloride and COD concentrations were markedly elevated. Water samples collected during these events were turbid, exhibited a yellowish-brown hue, and emitted a distinct odor, suggesting that upstream pollution exceeded permissible limits. Additionally, periods of rainfall were associated with increased influent flow rates and higher turbidity at Shuiwantou, further complicating the influence of seawater intrusion on the overall water quality of coastal pumping stations.
Statistical analyses (Figure 7) and principal component analysis (PCA, Figure 8) of NH3-N, COD, and chloride concentrations at the three coastal pumping stations (Shuiwantou, Yuehaidong, and Paizi) revealed the presence of outliers in both COD and chloride concentration datasets. Further analysis integrating weather and water quality records demonstrated distinct patterns:
First, low COD and Chloride Concentrations: Typically occurred during the rainy season or periods of exceptionally high water inflow, likely due to dilution effects from stormwater. Second, high Chloride Concentrations: Strongly correlated with elevated tidal levels, confirming seawater intrusion as a key influencing factor. Third, High COD Concentrations: Frequently accompanied by the presence of black sludge in the water, suggesting possible industrial discharges or sediment resuspension events.
These findings highlight the complex interplay between hydrological conditions (rainfall and tides) and anthropogenic factors (wastewater inputs and sludge accumulation) in shaping influent quality at coastal pumping stations. The PCA further supported these observations, with principal components clearly separating samples based on tidal influence (chloride-dominated) versus contamination events (COD-dominated).

4. Discussion

4.1. Implications of Seasonal Variability

The pronounced seasonal variations observed in both influent quantity and quality at the Qianshan and Gongbei WWTPs highlight the significant influence of hydrological regimes on coastal urban sewage systems. The wet season, characterized by increased precipitation and runoff, leads to a substantial increase in influent flow rates. This, in turn, results in a dilution effect, lowering the concentrations of key pollutants such as COD, BOD, SS, NH3-N, and TN. Conversely, the dry season witnesses reduced influent volumes and a concomitant increase in pollutant concentrations. This inverse relationship between flow and pollutant concentration is a well-documented phenomenon in wastewater treatment and management [30,31], and underscores the fundamental impact of rainfall-derived inflow and infiltration (I/I) on the characteristics of wastewater entering treatment facilities [32,33,34]. The magnitude of these seasonal fluctuations, with flow rates varying by factors ranging between two and three and pollutant concentrations showing similar inverse trends, demonstrates the considerable challenge that I/I poses to consistent and efficient wastewater treatment in coastal urban environments, such as Zhuhai City. The slight but consistent elevation of TP in the dry season, even with less pronounced variation than other parameters, may indicate contributions from groundwater I/I or other non-rainfall-dependent sources that become more prominent when dilution is minimized [35,36,37,38].
A critical aspect revealed by this study is the compounding effect of coastal proximity on these seasonal variations. While dilution during high-flow periods generally reduces pollutant concentrations, it concurrently increases the hydraulic load on the WWTPs, potentially exceeding design capacities and compromising treatment efficiency [39]. Furthermore, the potential for seawater intrusion, common in coastal sewage networks during dry periods [40,41,42,43], introduces additional complexity. Seawater intrusion can alter the ionic composition of the wastewater, potentially inhibiting biological treatment processes and impacting the removal of organic matter and nutrients [44,45]. The observed data, particularly the consistently higher pollutant concentrations during the dry season, suggest that seawater intrusion, combined with reduced freshwater input, might be a non-negligible factor influencing the influent characteristics. This highlights the need for a nuanced understanding of not only the quantity but also the source of influent variations, recognizing that coastal systems experience a unique interplay of freshwater and saline inputs.
The findings presented here strongly advocate for adaptive management strategies and advanced process control in coastal WWTPs to address the challenges posed by seasonal influent variability. Real-time monitoring of influent flow and quality, coupled with predictive modeling incorporating rainfall forecasts and tidal data (to account for potential seawater intrusion), can inform operational adjustments to optimize treatment performance [46,47]. For instance, during high-flow events, strategies might include adjusting sludge retention times or chemical dosages to maintain treatment efficacy despite dilution. During low-flow, high-concentration periods, process intensification, such as enhanced biological nutrient removal or the addition of supplemental carbon sources, may be necessary. Furthermore, long-term infrastructure planning should consider the implications of climate change, which is projected to exacerbate both extreme rainfall events and sea-level rise, potentially increasing the frequency and severity of both I/I and seawater intrusion. Ultimately, a holistic approach that integrates wastewater treatment with broader urban water management, including stormwater management and sewer system rehabilitation [48,49], is crucial for ensuring the resilience and sustainability of coastal urban sanitation systems.

4.2. Influence of Land Use on Sewage Characteristics

The observed variations in influent characteristics across the six pumping stations demonstrably link land use patterns to the quantity and quality of wastewater within the coastal urban sewage network. The influence of distinct land use categories, residential, industrial, and coastal, manifests as specific pollutant signatures and flow regimes. Densely populated residential areas, exemplified by the Shangchong and Daishan pumping stations, contribute significantly higher hydraulic loads and organic matter (represented by COD) and NH3-N, consistent with the predominance of domestic wastewater sources [50]. Conversely, the Cross-Border Industrial Park pumping station, serving a primarily industrial zone, exhibits elevated NH3-N concentrations, indicative of industrial effluents with a higher nitrogen content [51]. The Shuiwantou pumping station, located in a less densely populated coastal area, consistently shows lower pollutant concentrations. While this could be partly attributed to lower anthropogenic input, the potential influence of seawater intrusion, leading to dilution, cannot be disregarded and warrants further investigation, as noted in Section 4.1. These findings align with established principles of urban hydrology and wastewater engineering, where land use is a primary determinant of non-point source pollution and wastewater generation rates [52,53].
The interaction between land use and temporal dynamics, including both seasonal variations and episodic events like the pandemic, adds further complexity to the sewage system’s response. The observed increase in pollutant loads at the Daishan pumping station during pandemic-related lockdowns directly illustrates the impact of human activity patterns on wastewater characteristics. This “anthropogenic pulse” highlights the sensitivity of urban sewage systems to changes in population behavior and activity levels [54,55]. Furthermore, the seasonal variations, with peak flows typically occurring during the wet season (as discussed in previous sections, and cross-referencing is crucial), are modulated by land use. For example, the Guangzhu pumping station’s inverse relationship between flow and pollutant concentration is characteristic of systems heavily influenced by rainfall-derived I/I, a phenomenon that may be amplified in areas with specific land cover characteristics (e.g., impervious surfaces) [56,57]. The contrasting behavior of the Paizi pumping station, with its coastal influence and flow variability, again points to the complex interplay of factors requiring site-specific analysis.
These findings underscore the imperative for integrating land use planning and wastewater management in coastal urban environments. Accurate characterization of wastewater streams based on contributing land use types is essential for optimizing treatment processes and infrastructure design. For instance, source control measures, such as pre-treatment of industrial effluents at the Cross-Border Industrial Park pumping station, could significantly reduce the NH3-N load entering the municipal system. Similarly, implementing green infrastructure in residential areas to reduce stormwater runoff and I/I could mitigate the peak flows and associated dilution effects observed at pumping stations like Shangchong. Furthermore, incorporating land use projections into future infrastructure planning is crucial, particularly in rapidly urbanizing coastal regions where population growth and land use change are expected to intensify the challenges of wastewater management. Real-time monitoring, coupled with advanced data analytics and geospatial modeling, can provide the necessary tools for adaptive management [58], allowing operators to anticipate and respond effectively to the dynamic interplay of land use, seasonal variations, and episodic events. The aim is a move towards a more resilient system.

4.3. Managing Seawater Intrusion

The consistently elevated chloride (Cl−) concentrations observed at the Shuiwantou, Yuehaidong, and Paizi pumping stations provide compelling evidence of significant seawater intrusion into the coastal urban sewage network. This intrusion is not merely a passive mixing process; it actively shapes the influent characteristics, impacting both the quantity and quality of wastewater entering the treatment system [59,60]. The observed inverse relationship between Cl− and conventional pollutants (COD and NH3-N) during certain periods, particularly at Shuiwantou, exemplifies the dilution effect of seawater ingress. However, the concurrent occurrence of high Cl− and high COD during other events, associated with visual and olfactory indicators of pollution, demonstrates that seawater intrusion can also coincide with and potentially exacerbate upstream pollution events. This complex interplay highlights that seawater intrusion is not a singular phenomenon but rather a dynamic process influenced by tidal cycles, rainfall-driven runoff, and, potentially, the operational status of the sewer network itself (e.g., pipe leaks and illegal connections) [61,62]. The fact that intrusion occurs at multiple points and varies in its impact reinforces the systemic vulnerability of coastal sewage infrastructure.
The implications of seawater intrusion extend beyond simple dilution or concentration effects; it fundamentally alters the physicochemical properties of the wastewater, posing significant challenges for treatment processes. High salinity can inhibit the activity of microbial communities responsible for organic matter degradation and nutrient removal in biological treatment systems [63,64]. Specifically, elevated Cl- concentrations can disrupt the osmotic balance in microorganisms, leading to reduced metabolic rates and treatment efficiency [65,66]. The intermittent and variable nature of seawater intrusion, driven by tidal fluctuations and episodic rainfall events, creates a constantly shifting operational environment for WWTPs. This necessitates a move away from steady-state design assumptions towards a more dynamic and adaptive operational paradigm. Furthermore, the spatial variability in intrusion, as evidenced by the differences between the three pumping stations, underscores the need for localized monitoring and control strategies rather than a “one-size-fits-all” approach.

5. Conclusions

This study demonstrates that coastal urban sewage systems in Zhuhai City experience significant variations in influent characteristics driven by seasonal hydrological patterns, land use, and seawater intrusion. At the Qianshan and Gongbei WWTPs, wet season flows increased by factors of 2–3 compared to the dry season, with corresponding decreases in COD (from 200–350 mg/L to 100–250 mg/L) and NH3-N (from 15–30 mg/L to 10–20 mg/L) due to dilution. Land use significantly impacted pollutant loads; the industrial area (the Cross-Border Industrial Park pumping station) consistently showed higher NH3-N (10–42 mg/L) than the residential (Shangchong pumping station) or coastal (Shuiwantou pumping station) areas.
Seawater intrusion, evidenced by elevated Cl− concentrations (reaching over 8000 mg/L at Shuiwantou during specific events), presents a complex challenge. While sometimes associated with pollutant dilution, intrusion also coincided with high COD levels (up to 1010 mg/L), indicating interactions with other pollution sources.
These findings highlight the need for adaptive, site-specific management of coastal wastewater systems. Integrating real-time monitoring, predictive modeling, and infrastructure improvements is critical for mitigating the impacts of I/I, land use variations, and seawater intrusion, ensuring consistent treatment performance and protecting coastal water quality under the pressure of climate change.

Author Contributions

Methodology, Q.Y.; Validation, S.H.; Investigation, J.L.; Resources, Y.L.; Writing—review & editing, Y.G. and K.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Guangdong Basic and Applied Basic Research Foundation, grant number 2024A1515011909 and 2023B1515040028, Foshan Shunde District Core Technology Breakthrough Project, grant number 2230218004273 and Science and Technology Plan Project of Zhuhai in the Field of Social Development, grant number 2320004000067 and 2420004000307.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to express their sincere gratitude to Zhuhai Water Environment Holding Group Ltd. for providing the water samples essential to this research. We are also deeply grateful to Guan Yuntao at Tsinghua Shenzhen International Graduate School for his invaluable guidance, insightful suggestions, and continuous support throughout this study. His expertise and mentorship have been instrumental in the successful completion of this work.

Conflicts of Interest

Author Yanhong Ge was employed by the company Guangdong Infore Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BOD5The 5-day Biochemical Oxygen Demand
Cl−Chloride Ion
C:N:PCarbon-to-Nitrogen-Phosphorus Ratio
CODChemical Oxygen Demand
DPDN,N-Diethyl-p-Phenylenediamine
I/IInflow and Infiltration
IQRInterquartile Ranges
MDPIMultidisciplinary Digital Publishing Institute
NH3-NAmmonia Nitrogen
PCAPrincipal Component Analysis
SSSuspended Solids
TNTotal Nitrogen
TPTotal Phosphorus
WWTPWastewater Treatment Plant

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Figure 1. Location of sewage pumping station and sewage plant in the study area.
Figure 1. Location of sewage pumping station and sewage plant in the study area.
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Figure 2. Change of water quantity and quality in Qianshan WWTP. (a) shows the monthly variations in influent flow and concentrations of BOD, COD, and suspended solids at Qianshan WWTP from 2020 to 2023. (b) shows the monthly variations in influent flow and concentrations of total nitrogen, total phosphorus, and ammonia nitrogen at Qianshan WWTP from 2020 to 2023.
Figure 2. Change of water quantity and quality in Qianshan WWTP. (a) shows the monthly variations in influent flow and concentrations of BOD, COD, and suspended solids at Qianshan WWTP from 2020 to 2023. (b) shows the monthly variations in influent flow and concentrations of total nitrogen, total phosphorus, and ammonia nitrogen at Qianshan WWTP from 2020 to 2023.
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Figure 3. Change of water quantity and quality in Gongbei WWTP. (a) shows the monthly variations in influent flow and concentrations of BOD, COD, and suspended solids at Gongbei WWTP from 2020 to 2023. (b) shows the monthly variations in influent flow and concentrations of total nitrogen, total phosphorus, and ammonia nitrogen at Gongbei WWTP from 2020 to 2023.
Figure 3. Change of water quantity and quality in Gongbei WWTP. (a) shows the monthly variations in influent flow and concentrations of BOD, COD, and suspended solids at Gongbei WWTP from 2020 to 2023. (b) shows the monthly variations in influent flow and concentrations of total nitrogen, total phosphorus, and ammonia nitrogen at Gongbei WWTP from 2020 to 2023.
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Figure 4. Monthly changes in water quantity and quality in Shangchong pumping station, Shuiwantou pumping station, and the Cross-Border Industrial Park pumping station. (a) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at Shangchong pump station from 2021 to 2023. (b) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Shuiwantou pumping station from 2021 to 2023. (c) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Cross-Border Industrial Park pumping station from 2021 to 2023.
Figure 4. Monthly changes in water quantity and quality in Shangchong pumping station, Shuiwantou pumping station, and the Cross-Border Industrial Park pumping station. (a) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at Shangchong pump station from 2021 to 2023. (b) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Shuiwantou pumping station from 2021 to 2023. (c) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Cross-Border Industrial Park pumping station from 2021 to 2023.
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Figure 5. Monthly variation of water quantity and quality in Guangzhu pumping station, Daishan pumping station, and Paizi pumping station. (a) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at Guangzhu pumping station from 2021 to 2023. (b) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Daishan pumping station from 2021 to 2023. (c) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Paizi pumping station from 2021 to 2023.
Figure 5. Monthly variation of water quantity and quality in Guangzhu pumping station, Daishan pumping station, and Paizi pumping station. (a) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at Guangzhu pumping station from 2021 to 2023. (b) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Daishan pumping station from 2021 to 2023. (c) shows the monthly variations in influent flow and concentrations of COD and ammonia nitrogen at the Paizi pumping station from 2021 to 2023.
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Figure 6. Interannual trends (2020–2023) in chloride, Chemical Oxygen Demand (COD), and ammonia nitrogen (NH3-N) concentrations at: (a) Paizi, (b) Shuiwantou, and (c) Yuehaidong coastal pumping stations.
Figure 6. Interannual trends (2020–2023) in chloride, Chemical Oxygen Demand (COD), and ammonia nitrogen (NH3-N) concentrations at: (a) Paizi, (b) Shuiwantou, and (c) Yuehaidong coastal pumping stations.
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Figure 7. Spatial distribution of wastewater quality parameters: Box plots of (a) Paizi, (b) Shuiwantou, and (c) Yuehaidong pumping stations showing NH3-N, COD, and chloride concentration ranges (2020–2023 data). The boxes represent interquartile ranges (IQR), with solid light gray lines indicating medians and dashed light gray lines showing means.
Figure 7. Spatial distribution of wastewater quality parameters: Box plots of (a) Paizi, (b) Shuiwantou, and (c) Yuehaidong pumping stations showing NH3-N, COD, and chloride concentration ranges (2020–2023 data). The boxes represent interquartile ranges (IQR), with solid light gray lines indicating medians and dashed light gray lines showing means.
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Figure 8. Principal component analysis of coastal pollution patterns: (a) Paizi, (b) Shuiwantou, (c) Yuehaidong stations. Arrows show loading directions for NH3-N (ammonia nitrogen), COD (chemical oxygen demand), and Cl− (chloride) concentrations. Individual samples are colored by collection year (2020: black, 2021: red, 2022: green, 2023: blue), with ellipses encompassing 95% confidence regions for annual groupings. Percentage values on axes indicate explained variances.
Figure 8. Principal component analysis of coastal pollution patterns: (a) Paizi, (b) Shuiwantou, (c) Yuehaidong stations. Arrows show loading directions for NH3-N (ammonia nitrogen), COD (chemical oxygen demand), and Cl− (chloride) concentrations. Individual samples are colored by collection year (2020: black, 2021: red, 2022: green, 2023: blue), with ellipses encompassing 95% confidence regions for annual groupings. Percentage values on axes indicate explained variances.
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Ge, Y.; Lin, J.; Yin, Q.; Huang, S.; Lin, Y.; He, K. Quantitative Assessment of Seasonal and Land-Use Impacts on Coastal Urban Sewage Systems with Seawater Intrusion Vulnerability Analysis. Water 2025, 17, 1939. https://doi.org/10.3390/w17131939

AMA Style

Ge Y, Lin J, Yin Q, Huang S, Lin Y, He K. Quantitative Assessment of Seasonal and Land-Use Impacts on Coastal Urban Sewage Systems with Seawater Intrusion Vulnerability Analysis. Water. 2025; 17(13):1939. https://doi.org/10.3390/w17131939

Chicago/Turabian Style

Ge, Yanhong, Jiachong Lin, Qidong Yin, Sheng Huang, Yingchao Lin, and Kai He. 2025. "Quantitative Assessment of Seasonal and Land-Use Impacts on Coastal Urban Sewage Systems with Seawater Intrusion Vulnerability Analysis" Water 17, no. 13: 1939. https://doi.org/10.3390/w17131939

APA Style

Ge, Y., Lin, J., Yin, Q., Huang, S., Lin, Y., & He, K. (2025). Quantitative Assessment of Seasonal and Land-Use Impacts on Coastal Urban Sewage Systems with Seawater Intrusion Vulnerability Analysis. Water, 17(13), 1939. https://doi.org/10.3390/w17131939

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