River Water Quality Improvement Research Articles

Unveiling industrial emissions in a large European river: Insights from data mining of high-frequency measurements

Despite the tremendous efforts to improve river water quality, chemical contamination remains a significant issue. Besides well-known contaminants, in recent years, pollutants of industrial origin received increasing attention because of the huge knowledge gap regarding their occurrence, fate and environmental risks. Moreover, such pollutants often exhibit high concentration fluctuations over time, which makes them less predictable and measurable with classical short-time campaigns.This study provides insights into the different sources of chemical contamination of the Rhine River based on temporal high-frequency LC-HRMS monitoring data from a single location. A newly developed prioritization strategy selected nearly 3000 substances as potentially major contaminants. A novel classification analysis based on temporal behavior identified 53% of these compounds (accounting for 62% of the time-integrated intensity recorded in the dataset) as originating from irregular emission sources. Irregular emissions can originate from industrial production cycles. After delimiting other potential irregular sources, we have strong evidence indicating that a considerable share of the irregular emissions likely comes from industrial activities. This finding is supported by the structural elucidation of sixteen irregularly emitted substances, for which the industrial origin was successfully confirmed. Those compounds include 3-chloro-5-(trifluoromethyl)pyridine-2-carboxylic acid and 4-(dimethylamino)-2,2-diphenylpentanenitrile. In addition, 40 other compounds exhibited temporal emission patterns similar to the sixteen industrial compounds, which strongly suggests a common contamination source. Finally, 100 top-ranking compounds were selected for further structural elucidation and emission reduction measures. The computational approach outlined within this study can be effectively applied in other large river catchments to identify unknown contaminants stemming from industrial sources.

Impact of COVID-19 lockdown on water quality of major rivers in Sri Lanka

ABSTRACT The COVID-19 lockdown resulted in a reduction in human activities, lowering pollution levels in these rivers. Nevertheless, limited research can be found on the impact of COVID-19 on river water quality in Sri Lankan rivers. Therefore, this research was carried out to investigate the water quality index (WQI) of four major rivers (Mahaweli, Nilwala, Kelani, and Kalu) in Sri Lanka in three consecutive time slots spanning from 2019 to 2022 (before, during, and after the lockdown). In-depth WQI analysis has unveiled nuanced dynamics in river health. While the lockdown period contributed to positive alterations in key parameters, subsequent periods demonstrated declining water quality post-lockdown. This decline underscores the direct correlation between human activity and river water quality deterioration. Several parameters showed positive changes during the lockdown, indicating an improvement in river water quality. When comparing the periods before, during, and after the lockdown, pH, colour, turbidity, total iron, sulphate, chloride, total coliform, and E. coli all showed a significant positive impact. However, some parameters, such as fluoride and electrical conductivity (EC), had a neutral effect. This study sheds light on the positive effects of the COVID-19 lockdown on reducing river pollution in Sri Lanka.

Model of environmental management due to coal mining on the Separi River in Tenggarong Seberang District, Kutai Kartanegara Regency, East Kalimantan Province

Coal mining has a significant impact on reducing river water quality. The decline in river water quality causes problems for human life and the environment. Therefore, this research aimed to evaluate river water quality and develop strategies for improving river water quality due to open pit coal mining activities in Tenggarong Seberang District and develop environmental improvement strategies. Several chemical parameters, including pH, TSS, Fe, and Mn, were observed through laboratory tests to determine water quality in the Separi River used in coal mining. The next step was determining environmental improvement strategies using the ISM approach. Twenty stakeholders from related agencies and institutions using FGD were involved in developing a policy strategy. The results of the analysis showed that there has been a decrease in river water quality standards due to mining activities in the research area, and the quality is still below the standard quality. Therefore, two significant strategies must be a priority for the environmental management of the Separi River. First, Conducting an environmental audit of the factors causing the decline in river water quality is necessary. Second, there must be warnings and legal sanctions for negligence in oil spills and oil used from coal mining.

Improving river water quality prediction with hybrid machine learning and temporal analysis

River systems provide multiple ecosystem services to society globally, but these are already degraded or threatened in many areas of the world due to water quality issues linked to diffuse and point-source pollutant inputs. Water quality evaluation is essential to develop remediation and management strategies. Computational tools such as machine learning based predictive models have been developed to improve monitoring network capabilities. The model's performance is reduced when datasets composed of reductant information are used for training, on the other hand, the selection of most representative and variable water quality scenarios could result in higher precision. This study analyzed historical water quality behavior in the Santiago River, Mexico, to identify the most variable and representative data available to train machine learning models (Adaptive Neuro Fuzzy Inference System – ANFIS, Artificial Neural Network – ANN, and Support Vector Machine - SVM). Thirteen monitoring sites were clustered according to their water quality variability from 2009 to 2022. Subsequently, a Time Series Analysis (TSA) was used to select the most representative monitoring station from each cluster. Data for 6/13 monitoring sites were retained for the Best Training Subset (BTS) used to train restricted models that performed with similar (ANN and SMV) or higher (ANFIS) prediction accuracy (in terms of RMSE, MAE, MSE and R2) for both training and testing. This study provides evidence of water quality data containing redundant information that is not useful to improve machine learning model performance, in turn leading to overtraining. Combined analytical approaches can maximize the representativeness and variability of data selected for machine learning applications, leading to improved prediction.

Design of Non-Structural Practices for Sustainable Water Quality Improvement in an Urban River: A Case Study of South Korea

Urban rivers exhibit characteristics of low flow and significant water quality fluctuations, making them susceptible to pollution from various sources such as untreated sewage, non-point pollution within the urban area, and unknown inflows. To address water quality management in urban rivers, precise investigations into background water quality, pollution levels, and the characteristics of pollution sources are essential. Following the identification of pollution sources, sustainable river management strategies, incorporating both structural and non-structural measures, are crucial. This study aims to develop continuous and long-term river management strategies, considering the characteristics of urban river basins, through citizen participation governance and non-structural approaches. Citizen networks were formed for each target urban river, and activities for water quality improvement were proposed and implemented. This study provides phased approaches to citizen participation governance, and activities include citizen-led water quality monitoring, the purification and monitoring of riverbank pollution sources, and water-related education. It emphasizes the importance of local residents’ interest in urban river water quality improvement and underscores the need for sustained activities through local citizen networks. Additionally, active participation and investments from the local government, government agencies, and various experts are deemed essential.

Payments for environmental services with ecological thresholds: farmers’ preferences for a sponsorship bonus

Designing incentives for agri-environmental public good provision with threshold effects calls for payment mechanisms favouring critical mass participation and continuity of commitments at the landscape scale. We conducted a choice experiment to test the acceptability of a bonus in a scheme for improving river water quality in France. We introduce a sponsorship bonus each time the farmer convinces a peer into entering the scheme, which can be combined with a collective result bonus per hectare if the river reaches a higher step on the water quality scale. We consider the involvement of local financers could increase the willingness to pay beyond opportunity costs and income foregone and propose higher levels of payment than agri-environmental schemes. Results suggest a sponsorship bonus on its own is cost-effective. We characterize respondents’ heterogeneity and identify three groups based on choice patterns: (i) “pro-environment individualists”, (ii) “management change averse” farmers, and (iii) “pro-incentive” farmers.

Assessing Heavy Metals in the Sele River Estuary: An Overview of Pollution Indices in Southern Italy.

Rapid industrialization, coupled with a historical lack of understanding in toxicology, has led in an increase in estuary pollution, frequently resulting in unexpected environmental situations. Therefore, the occurrence of heavy metals (HMs) constitutes a major environmental issue, posing a serious risk both to aquatic ecosystems and public health. This study aimed to evaluate the levels of eight HMs (As, Hg, Cd, Cr, Cu, Ni, Pb, and Zn) in water, suspended particles, and sediment near the Sele River estuary (Italy) in order to assess their environmental impacts on the sea and health risks for humans. The results revealed an increasing order of HM concentration according to the scheme suspended particulate matter (SPM) > sediment (SED) > dissolved phase (DP) and a moderate contamination status in sediment. The health risk assessment indicated that the non-carcinogenic risk was negligible. Carcinogenic risk, expressed as the incremental lifetime cancer risk (ILCR), was negligible for Cd and Ni and within tolerable limits for As, Pb, and Cr. The findings suggested that, even if there are currently no specific limits for chemical parameters in the transitional waters of Italy, monitoring systems should be implemented to determine pollution levels and implement effective steps to improve river water quality and reduce human health risks.

The Effect of Weir Opening on Physiochemical Properties in the Geum Estuary of Republic of Korea

Deteriorated river water quality affects estuarine environments due to river and estuary linkages. Thus, river water quality improvement could play a pivotal role in the maintenance of estuarine ecosystem functions. The South Korean administration opened river weirs to restore river ecosystems and announced that this helped restore habitats and improve water quality. Despite these reported positive results in the rivers, little research has been conducted on the effects of weir opening on estuaries linking to rivers. We investigated the physicochemical properties of the Geum Estuary during the initial weir opening (2018) and stabilization (2021) periods. The results indicated that the NO3− inputs from rivers to estuaries decreased from 2018 to 2021 by 19~68%; however, the trends of [NO3−] in estuarine water columns in nearby estuary dams fluctuated between 2018 and 2021. No change in NO3− pollutant sources was observed from 2018 to 2021. Unlike [NO3−], [PO4−] and [SiO2] were higher in 2021; thus, large amounts of previously accumulated PO4− and SiO2 within the weirs might have been released from the river into the estuary. This supply of PO4− could enhance estuarine phytoplankton growth, where PO4− is a limiting factor for primary production due to excessive inputs of NO3− from rivers. Therefore, dredging the accumulated sediment within weirs should be considered prior to opening them to prevent the release of PO4− and SiO2 into estuaries.

Analisis Partisipasi Masyarakat dalam Program Pengelolaan Sampah Sungai Semangir Kecamatan Mangli Kabupaten Jember

Rivers are an important element that connects urban and rural environments which are used by humans and other living creatures. Any action taken on a river will have the effect of changing its nature and condition as an adjustment to the treatment it receives. Community participation can be divided into several forms, namely community participation in planning development programs, community participation in realizing the results of plans made, community participation in utilizing the results of development that has been implemented, and community participation in evaluation which is realized by assessing and supervising development activities and the results. Community participation is influenced by two main factors, namely internal factors and external factors. Internal factors are the social and economic conditions of the community. External factors that influence participation include communication, community leaders, and opportunities to participate. The research was conducted using a deductive approach which uses logic to draw conclusions based on the observations made. The type of research used is qualitative research. Community participation is influenced by 2 main factors, namely internal factors and external factors. Internal factors are the social and economic conditions of the community. External factors that influence participation include communication, community leaders, and opportunities to participate. The River Management Program in the Semanggir River, Jember Regency is to create a clean river program. The Clean River Program (PROKASIH) was formed to control river water pollution and improve river water quality. To support the realization of the program, a River Working Group was formed which will take part in protecting rivers as well as developing the values ??of mutual cooperation and community as well as increasing community participation in river protection and conservation. To increase community participation and the active role of safeguarding related interests, an approach needs to be taken to provide an understanding that waste is the responsibility of all elements. There is a need for synergy between the elements of the pentahelix, namely the government, private sector, academics, media and society, to jointly address the waste issue in the area considering that this area provides quite a large economic contribution to the local community

Reflecting on changes in the drinking and irrigation water quality of rivers Beas, Satluj and confluence waters.

Prevention and control of water pollution for maintaining and restoring the wholesomeness of rivers are unavoidable. The current water quality approach of designated best use has some limitations such as it is non-integrative and inflexible with regard to the consideration of variables and does not provide a separate rating scale for a given designated use. We thus used water quality index approach proposed by the Canadian Council of Ministers of the Environment (CCME WQI) to evaluate and develop a separate rating system for drinking and irrigation purposes of rivers Beas, Satluj and their confluence water of the Indian Punjab using information collected over 4 years (2016 to 2019). River Beas exhibited better water quality compared to river Satluj for irrigation as well as for drinking. The overall drinking water quality index (DWQI) for Beas was marginal (45.5), whereas it was poor for Satluj (37.7) and confluence waters (40.1). The spatial variation in DWQI was greater for Satluj compared to Beas and confluence waters reflecting the effect of dumping of untreated industrial and domestic waste waters. Variables such as Total coliform (T. coli), dissolved oxygen (DO), turbidity and biological oxygen demand (BOD) contributed to the deterioration of DWQI. The irrigation water quality index (IWQI) was good for Beas (86), marginal for Satluj (60.1) and fair for confluence waters (71.2). Faecal coliform (F. coli), Kelly ratio (KR) and %Na contributed to the deterioration of IWQI. Calcium-magnesium-bicarbonate (Ca-Mg-HCO3) was the dominant water type in Beas and confluence waters, whereas for Satluj, in addition to Ca-Mg-HCO3, sodium-potassium-chloride-sulphate and mixed water types were also prevalent. The river waters witnessed salinity hazard but did not pose sodicity hazard except at a few locations of Satluj. The study indicates the need to take location specific measures for improving river water quality for drinking as well as irrigation purposes. The current status of water quality calls for an urgent need to formulate stringent policy regulations to maintain the surface water quality.

A coupled model to improve river water quality prediction towards addressing non-stationarity and data limitation

Accurate predictions of river water quality are vital for sustainable water management. However, even the powerful deep learning model, i.e., long short-term memory (LSTM), has difficulty in accurately predicting water quality dynamics owing to the high non-stationarity and data limitation in a changing environment. To wiggle out of quagmires, wavelet analysis (WA) and transfer learning (TL) techniques were introduced in this study to assist LSTM modeling, termed WA-LSTM-TL. Total phosphorus, total nitrogen, ammonia nitrogen, and permanganate index were predicted in a 4 h step within 49 water quality monitoring sites in a coastal province of China. We selected suitable source domains for each target domain using an innovatively proposed regionalization approach that included 20 attributes to improve the prediction efficiency of WA-LSTM-TL. The coupled WA-LSTM facilitated capturing non-stationary patterns of water quality dynamics and improved the performance by 53 % during testing phase compared to conventional LSTM. The WA-LSTM-TL, aided by the knowledge of source domain, obtained a 17 % higher performance compared to locally trained WA-LSTM, and such improvement was more impressive when local data was limited (+66 %). The benefit of TL-based modeling diminished as data quantity increased; however, it outperformed locally direct modeling regardless of whether target domain data was limited or sufficient. This study demonstrates the reasoning for coupling WA and TL techniques with LSTM models and provides a newly coupled modeling approach for improving short-term prediction of river water quality from the perspectives of non-stationarity and data limitation.

Integrated prediction of water pollution and risk assessment of water system connectivity based on dynamic model average and model selection criteria.

In recent years, with the rapid development of economy and society, river water environmental pollution incidents occur frequently, which seriously threaten the ecological health of the river and the safety of water supply. Water pollution prediction is an important basis for understanding development trends of the aquatic environment, preventing water pollution incidents and improving river water quality. However, due to the large uncertainty of hydrological, meteorological and water environment systems, it is challenging to accurately predict water environment quality using single model. In order to improve the accuracy and stability of water pollution prediction, this study proposed an integrated learning criterion that integrated dynamic model average and model selection (DMA-MS) and used this criterion to construct the integrated learning model for water pollution prediction. Finally, based on the prediction results of the integrated learning model, the connectivity risk of the connectivity project was evaluated. The results demonstrate that the integrated model based on the DMA-MS criterion effectively integrated the characteristics of a single model and could provide more accurate and stable predictions. The mean absolute percentage error (MAPE) of the integrated model was only 11.1%, which was 24.5%-45% lower than that of the single model. In addition, this study indicates that the nearest station was the most important factor affecting the performance of the prediction station, and managers should pay increased attention to the water environment of the control section that is close to their area. The results of the connectivity risk assessment indicate that although the water environment risks were not obvious, the connectivity project may still bring some risks to the crossed water system, especially in the non-flood season.

Water quality improvement project for initial rainwater pollution and its performance evaluation

Efficiently addressing initial rainwater pollution is crucial for mitigating urban water pollution. However, the performance evaluation of initial rainwater pollution control project is rarely introduced. In this study, the architecture of effective comprehensive engineering measures for improving the water quality of initial rainwater in Anhui Province, China, was described. Three water quality indicators, ammonia nitrogen (NH3–N), chemical oxygen demand (COD), and total phosphorus (TP), were selected to explore the severity of urban pollution caused by initial rainwater under various rainfall scenarios. A single-factor evaluation method was used to contrast and assess the benefits of the initial rainfall interception project in terms of water quality enhancement. Results showed that initial rainfall pollution was gentler under light rainfall conditions but more prominent under moderate and heavy conditions. The percentages of NH3–N, COD, and TP in Lotus Pond that met the tertiary drinking water standard were 100%, 74.91%, and 100% with great improvement, and the average concentrations of NH3–N, COD, and TP in Fushan Road Drainage have decreased by 91.43%, 10.49%, and 57.33% respectively, after the construction of the interception project. These indicated that the nitrogen and phosphorus pollution were successfully controlled by the control techniques in both locations, but COD concentration has to be addressed with more specialized strategies. Overall, the water quality improvement project for initial rainwater pollution plays a great role in effectively governing initial rainwater pollution and improving river water quality, and provides an effective technical reference for urban water ecological environment management.

Assessing Water Sustainability in Northwest China: Analysis of Water Quantity, Water Quality, Socio-Economic Development and Policy Impacts

Northwest China (NWC) is one of the driest areas of the world. Over the past decades, NWC has experienced rapid socio-economic development, further stressing its freshwater quantity and quality. However, there is little knowledge on the long-term status of NWC’s water resources and the anthropogenic impacts—positive (environmental policies) or negative (uncontrolled development). We present a holistic spatiotemporal assessment of NWC’s water quantity, water scarcity, and water quality based on water use intensity (WUI), water scarcity index (WSI), and statistical analyses and tests, combining multiple datasets spanning the past two decades. Moreover, we analyze the impacts of socio-economic development on water resources and mention the relevant governmental efforts and policies to preserve NWC’s water resources. NWC’s water use was found to be unsustainable, having significantly increased by 10% over the past two decades, but without being able to adequately cover the needs of most sectors. Our results also reveal water scarcity inequalities among NWC’s provinces; perennial water scarcity exists in Xinjiang and Ningxia Provinces, and there is no water stress in Qinghai. A remarkable wastewater treatment rate (from 27.3% in 2003 to 97.1% in 2020) and river water quality improvement have been achieved under continuous efforts, huge restoration and water pollution control investments. However, water shortages are a persistent issue. Balancing the water availability and demand will be crucial to achieve a truly sustainable development.

Analisis Kualitas Air di Sungai Marbau

This study aims to analyze the quality of river water and the water quality status of the Marbau watershed in North Labuhanbatu Regency based on water quality criteria and to formulate a pollution control strategy that needs to be implemented. The method used is a quantitative descriptive method by analyzing the status of river water quality based on the pollution index. The results showed that the P1 value of Marbau river water ranged from 0.94 to 1.82. The recommended pollution control strategies are: 1) maintaining river protection zones involving environmental cadres and green communities in monitoring; 2) monitoring and controlling water pollution along the river; 3) improve river water quality monitoring; 5) supervision of the discharge of waste water into rivers; 4) granting permits for disposal of wastewater (IPLC) into rivers must pay attention to the condition of the capacity to accommodate river pollution loads and enforce environmental law against business actors who violate established environmental quality standards. In conclusion, the quality of the Marbau river has decreased with the water quality status being slightly polluted. The recommendations for water pollution control strategies that need to be implemented are progressive strategies.
 Keywords: Water Quality, North Labuhanbatu, Marbau

Historical Trends and Driving Forces of River Water Quality Improvement in the Megacity Shenzhen, China

The water quality of urban rivers in China has undergone significant improvement since the 13th Five-Year Plan period (2016–2020). Among these, urban rivers in Shenzhen are the most representative. Assessing historical trends and analyzing the driving forces of river water quality improvement is of great importance and provides valuable insights. This study selects two typical watersheds, Maozhou River and Longgang River, to explore how water quality trends link with water control projects in Shenzhen from 2003 to 2020. The historical trends were evaluated using a recently developed index called WQI-DET, which considers DO, COD, NH3-N, TP, and anionic surfactants. Results showed that both rivers were seriously polluted before 2010 and gradually improved during the 12th Five-Year Plan period. After 2010, the water quality improved rapidly thanks to the environmental remediation of the mainstream, especially the interception project of Longgang River around 2010, and the Maozhou River interception project in 2015. The rainwater and sewage diversion renovation project mainly contributed to meeting the standards for Class IV water bodies during the 13th Five-Year Plan period. This study reveals the semi-quantitative link between comprehensive water quality improvement and pollution control engineering measures. It is a helpful review for Shenzhen and provides a useful reference for other cities.

Assessment of river water quality improvement due to riverbank filtration (RBF) mechanism

Riverbank filtration (RBF) is a natural process where river water is induced to flow through riverbed soils to pumping wells located on the banks. It is a well-established and proven natural water treatment technology by having a series of physical and chemical processes during subsurface passage. This paper aims at the measurement of physical and chemical characteristics of river water and groundwater from riverbank filtration wells at Kg. Jenderam Hilir, Selangor and to assess the effectiveness of riverbank filtration through Water Quality Index (WQI) for both river water and groundwater. The riverbank filtration is able to improve quality of water such as reducing the turbidity to 0 NTU, Chemical Oxygen Demand (COD) to 3.67 mg/l, Suspended Solids (SS) to 6.33 mg/l and several other contents that existed in the river. In addition, the effectiveness of RBF is also proven based on the improvement of Water Quality Index (WQI) for Langat river from Class IV to Class III.

Simulation Study on the Impact of South–North Water Transfer Central Line Recharge on the Water Environment of Bai River

To effectively improve the water quality of the Bai River, this paper proposes the use of the ecological replenishment of the South–North Water Transfer as a measure for the integrated allocation of water resources, addressing the impact of complex topography, climate, and human disturbances on the river’s water environment. This measure can alleviate the problem of water shortage and significantly enhance the quality of the Bai River’s water environment. Using the MIKE21 coupled hydrodynamic and water-quality model, this paper analyzes the impact of ecological recharge on river hydrodynamics and simulates the evolution of various water-quality indicators, including dissolved oxygen (DO), permanganate index (CODMn), chemical oxygen demand (COD), ammonia nitrogen (NH3-N), and total phosphorus (TP) under different scenarios. The aim of this paper is to investigate the impact mechanism of ecological recharge on the river’s water environment. The results show that the most significant improvement in river water quality is achieved when the recharge flow is 2Q and the recharge duration is 1/2T (scenario 1), with the river improving from a grade IV water-quality standard to a grade III water-quality standard, and COD and TP indicators improving to a grade II water standard, with the largest improvement rate of 94.67% seen in DO, with the best improvement rate of 94.67% in DO indicators and the best reduction rate of 66.67% in TP indicators. Overall, ecological replenishment can significantly improve the Bai River’s water quality, with scenario 1 being the most effective approach. The results of this study may provide theoretical and technical support for the future management of river water environments.

Influence of urban green space landscape pattern on river water quality in a highly urbanized river network of Hangzhou city

Optimizing urban green space landscape patterns is a key goal for improving river water quality. However, little is known about the spatial heterogeneity of the impact of urban green spatial patterns on river-water environments. This study investigated the influence of urban green space patterns on the spatiotemporal heterogeneity of river water quality in the Hangzhou section of the Beijing-Hangzhou Canal through exploratory regression analysis and a combination of geographically weighted regression analysis (GWR) and spatial interpolation. The results show that (1) total nitrogen (TN) and nitrate nitrogen (NO3–-N) are the leading indicators of river pollution in the study area, (2) green space configuration is more crucial for improving water quality than composition, and (3) GWR can effectively explain the impact of urban green space on river water quality. For example, landscape shape and edge indices have a great impact on ammonia nitrogen (NH4+-N), TN and total phosphorus (TP); the more complex the shape and edge of the green space, the more beneficial it is for water purification. The interpretation of NO3–-N is complex and mainly influenced by the largest patch index (LPI) and landscape composition. Given the limited land availability in urban area, the spatial configuration of urban green space should be optimized without additional land use to minimize the non-point source (NPS) pollution with the smallest possible green space area. The proposed approach provides a new understanding of the interaction between spatial patterns of green space and the urban water environment, and valuable information for developing green space planning policies for local sites.

Water quality management at a critical checkpoint by coordinated multi-catchment urban-rural load allocation

Improving river water quality at critical checkpoints, defined as locations with significant impacts on water use, to satisfy regulation standards is an important goal of sustainable catchment management. Challenges remain in investigating pollution hotspots, designing efficient target reduction, and evaluating management performance. To address these challenges, we develop a systems approach for water quality management that integrates natural physical processes with human activities and their environmental impacts. In this approach, we firstly expand the concepts of headroom (amount under a permitted value) and excess (amount exceeding a permit) onto the source, spatial, and temporal domains for water quality management. We evaluate system-wide pollution contributions by simulating physical processes in a semi-distributed integrated representation using the CatchWat-SD model. We apply the model to the Upper Thames River basin and validate it using available monitoring data. We then incorporate the evaluated headroom-excess into a coordinated load allocation to enhance the efficiency and feasibility of interventions. Load allocation scenarios where headroom-excess is coordinated at different domains are generated and simulated. Finally, we evaluate the performance of these scenarios using multi-criteria metrics to demonstrate the advantages of headroom-excess coordination. Results show that urban sources, downstream sub-catchments, and dry season flows are associated with excess, thus, enabling managers to identify which cases (pollution sources, locations, and times) to focus load reductions towards. The more a load allocation strategy coordinates headroom-excess across domains, the more target reduction is allocated to the cases with excess, and the better performance it obtains in all the criteria. The study emphasises the need to incorporate headroom-excess in load allocation, which helps to improve systems-level water quality performance more efficiently. The approach can be further expanded to water quality management at multiple checkpoints for sustainable management of regional water systems.