Gray water footprint-based water quality sustainability indices: an innovative approach for river basins

Índices de sustentabilidade da qualidade da água baseados em pegada hídrica cinza: uma abordagem inovadora para bacias hidrográficas

ABSTRACT

This study establishes a new methodology to calculate the dilution flow in water courses, proposing a Water Quality Sustainability Index (WSI) as a specific metric to assess the qualitative dimension of water sustainability from a pollution assimilation perspective. The objective of this study was to estabilish a new methodology that would allow the calculation of dilution flow in water courses, allowing a better understanding of the water resources management of the river basin from a water sustainability perspective. In this study, the methodology was applied to the Paraiba do Sul River Basin. The dilution flow was correlated with minimum reference flows through the WSI for current (2025) and future (2047) scenarios. Key findings reveal that in the current scenario, 45% of water bodies exceed pollution capacity (WSI > 1), while the future scenario shows significant improvement, with 70.5% of watercourses achieving sustainability (WSI < 1). Through efficiency adjustments in Wastewater Treatment Plants (WWTPs), compliance reached 100% in the future scenario, demonstrating the method's effectiveness. The dilution flow that has its methodology based on the gray water footprint can be considered as an instrument for the management of water resources, used to evaluate impacts and situations of degradability of the aquatic environment, making it a crucial tool for decision-making for prevention or remediation of environmental impacts.

Keywords:
Management of water resources; Dilution flow; Minimum long period flows; Effluent treatment plant

RESUMO

Este estudo estabelece uma nova metodologia para calcular o fluxo de diluição em cursos d'água, propondo um Índice de Sustentabilidade da Qualidade da Água (ISQA) como métrica específica para avaliar a dimensão qualitativa da sustentabilidade hídrica sob a perspectiva da assimilação da poluição. O objetivo deste estudo foi estabelecer uma nova metodologia que permitisse o cálculo do fluxo de diluição em cursos d'água, possibilitando uma melhor compreensão da gestão dos recursos hídricos da bacia hidrográfica sob a perspectiva da sustentabilidade hídrica. Neste estudo, a metodologia foi aplicada à Bacia do Rio Paraíba do Sul. O fluxo de diluição foi correlacionado com as vazões mínimas de referência por meio do ISQA para cenários atuais (2025) e futuros (2047). Os principais resultados revelam que, no cenário atual, 45% dos corpos d'água excedem a capacidade de poluição (ISQA > 1), enquanto o cenário futuro apresenta uma melhora significativa, com 70,5% dos cursos d'água atingindo a sustentabilidade (ISQA < 1). Por meio de ajustes de eficiência em Estações de Tratamento de Esgoto (ETEs), a conformidade atingiu 100% no cenário futuro, demonstrando a eficácia do método. A vazão de diluição, cuja metodologia se baseia na pegada hídrica cinza, pode ser considerada um instrumento para a gestão de recursos hídricos, utilizado para avaliar impactos e situações de degradação do ambiente aquático, tornando-se uma ferramenta crucial para a tomada de decisões na prevenção ou remediação de impactos ambientais.

Palavras-chave:
Gestão de recursos hídricos; Vazão de diluição; Vazões mínimas de longo período; Estação de tratamento de efluentes

INTRODUCTION

Conflicts over water use and availability are primarily caused by increased scarcity due to the failure to adopt water conservation measures (Silva et al., 2024). Therefore, resolving such conflicts requires integrated water use management, as well as water control and conservation (Cosgrove & Rijsberman, 2000).

Recent data indicate that at least 2 billion people lack access to safe drinking water, and approximately 4 billion face water shortages for at least one month a year. The UN warns that by 2025, 1.8 billion people could experience absolute water scarcity (United Nations, 2024). Brazil has lost 15.7% of its water surface area in the last 30 years, equivalent to more than one and a half times the area of the Northeast region, according to a study by MapBiomas Água (Grupo de Institutos, 2021). In 2025, the Paraíba do Sul Basin continues to face water conflicts aggravated by climate change (Agência Nacional de Águas e Saneamento Básico, 2023a), reinforcing the need for the projections presented here for 2047.

The concept of the water footprint was first introduced in 2003 with the aim of understanding the connections between human production activities and pressure on global water resources, assessing the impacts of a water consumption activity in terms of volume used per year (Llanos et al., 2018).

The gray water footprint (WF) is a tool for assessing freshwater pollution (Yi et al., 2024). The grey water footprint (WF), defined as the volume of freshwater required to dilute pollutants below ambient water quality standards, has gained increasing relevance as a qualitative indicator of wastewater impact on receiving water bodies (Zanolla et al., 2025). The Water Footprint methodology was initially applied to agricultural products and the food industry, at regional and country levels, to electricity production and to river basins, with the Spanish government being the first to formally adopt the water footprint concept by requiring its analysis at the river basin level in the preparation of basin management plans (Llanos et al., 2018).

In terms of water footprint, some studies have been developed recently, such as in China, where concerns about energy security drove the launch of the emerging coal-based chemical industry (ECCI) throughout the country (Li, 2024). Other Chinese authors argue that water scarcity is a significant constraint in agricultural ecosystems in arid regions, necessitating the sustainable development of agricultural water resources (Zhang et al., 2024).

In other parts of the world, concerns about the water footprint are present, such as in the US, in New York, where residents expressed concerns that hot water discharges were heating Seneca Lake beyond state water quality standards (Vries, 2024). In Germany, researchers aimed to test treatment sequences that minimized water use with minimal costs and environmental impact (Müller et al., 2024). Researchers report that the link between soil moisture and water footprint generation is little studied globally (Rodríguez et al., 2024).

Applying the gray water footprint at the river basin level allows for the creation of a Water Quality Sustainability Index (WSI). This index specifically assesses the qualitative aspect of water sustainability by relating the pollutant load to the water body's dilution capacity and guiding water management policies, especially in basins with multiple-use conflicts, such as the Paraíba do Sul. We hypothesize that the correlation between dilution flow and long-term minimum flows will allow identifying critical scenarios and proposing improvements in effluent treatment efficiency.

This work proposes a novel methodology for calculating dilution flow based on the gray water footprint and correlating it with minimum reference flows using water quality sustainability indices (WSI). The application was conducted in the Paraíba do Sul Basin, but the method can be replicated in any water body with water quality and flow data, aiming to inform management decisions for current and future scenarios.

MATERIAL AND METHODS

Dilution flow rate

The methodology developed in this study allows for the calculation of the dilution flow rate for the influent that passes through the Wastewater Treatment Plant (WWTP) and the influent that is discharged, untreated (raw sewage), into the watercourse. The methodology was based on the Gray Water Footprint equation proposed by Hoekstra et al. (2011) and is presented in Equation 1.

$Fr=F_{WWTP}.\frac{\left[C_{PWWTP}\left(1-\eta \right)-C_{max}\right]}{C_{max}-C_{nat}}+F_{RS}.\frac{\left[C_{PRS}-C_{max}\right]}{C_{max}-C_{nat}}$ (1)

Where: Fr: dilution flow rate (L s^-1); F_WWTP: influent flow rate in WWTP (L s^-1); C_{P WWTP}: influent concentration of pollutant arriving at WWTP (mg L^-1); F_RS: raw sewage flow rate (L s^-1); C_{P RS}: influent concentration of raw sewage (mg L^-1); ɳ: WWTP treatment level (dimensionless and varies between 0 and 1); C_max: maximum pollutant concentration considered for the desired river class (mg L^-1); and C_nat: pollutant concentration for a natural river (mg L^-1).

Technical note: When the treated effluent (C_{P WWTP} (1-η)) or raw effluent (C_{P RS}) concentrations are lower than the maximum standard (C_max), resulting in negative values in the numerators, the corresponding dilution flow rate is considered zero, indicating that there is no need for additional dilution to meet water quality standards.

The quotients in the equation represent the dilution factors for the treated and untreated pollutants, respectively. The dilution factor represents the number of times the effluent volume must be diluted with raw water to reach the maximum acceptable concentration.

It is important to emphasize that the dilution flow rate calculation should only be considered when the influent concentration (treated or raw sewage) is greater than the maximum acceptable concentration. Otherwise, the dilution flow rate (or at least one of the terms for treated or raw sewage) assumes a zero value.

In this study, the parameter considered to analyze watercourse pollution was the Biochemical Oxygen Demand (BOD₅), which corresponds to the amount of oxygen required for the oxidation of biodegradable organic matter under aerobic conditions.

The maximum BOD₅ concentration values for the desired river class and for a natural river were obtained considering Brazil's National Environment Council (CONAMA) (Conselho Nacional do Meio Ambiente, 2005) resolution 357/2005. This resolution establishes the classification of water bodies and environmental guidelines for their classification, as well as the conditions and standards for effluent discharge.

The remaining information (inflow, outflow of the receiving body, BOD₅ concentration in the inflow before treatment, and BOD₅ concentration discharged after treatment) was obtained from the "Sewage Atlas: Decontamination of Watersheds" available on the website of the National Water Agency (ANA). This Atlas provides access to the "Municipal Sewage Report" and the "Map of the existing Sewage Treatment System" (as well as a map of the system with an evaluated alternative solution), by municipality, and to which watercourse the discharge is destined.

The BOD5 concentration value for a watercourse under natural conditions C_nat is 2 mg.L^-1 (Conselho Nacional do Meio Ambiente, 2005). The WWTP treatment level parameter (ɳ) was calculated by Equation 2:

$\eta =\frac{Loadgenerated-Loadreleased}{GeneratedLoad}$ (2)

Where: generated load and released load are expressed in kg_(BOD) day^-1

Fundamental Concepts of Flow Rates: Dilution Flow Rate (Qd): Represents the volume of water needed to dilute pollutants until they reach concentrations acceptable according to environmental standards. High values indicate a greater polluting impact. Minimum Reference Flow Rate (Qref): Represents the natural flow rate available in the water body for dilution processes. High values indicate a greater assimilation capacity.

Interpretation of the Water Quality Sustainability Index (WSI): WSI < 1: Qd < Qref → Sustainable condition (adequate dilution capacity). WSI > 1: Qd > Qref → Critical condition (insufficient dilution capacity).

The reference flow is a fundamental parameter for evaluating the assimilation capacity of a water body. In this study, the historical minimum flow (Q95), obtained from the flow duration curve of each river section, as provided in the "Atlas Esgotos: Despoluição de Bacias Hidrográficas" of ANA, was used as the reference flow (Agência Nacional de Águas e Saneamento Básico, 2023b).

Study area

The Paraíba do Sul River Basin (São Paulo state) has a drainage area of just over 14,000 km² and an estimated population of nearly two million (ANA, 2023). Its main constituent rivers are the Paraibuna, Jaguari, Uma, Buquira/Ferrão, Embaú/Piquete, Bocaina, and Pitangueiras/Itagaçaba rivers.

The main economic activities in this region are related to agriculture (primarily rice cultivation), industry and technology research (automotive and aerospace sectors), mining, tourism, and services. Remaining vegetation covers 3,846 km² of natural vegetation, which occupies approximately 26.5% of the basin's area.

The Paraíba do Sul River Basin plays an important role, located among the largest industrial and population centers in the country. It is also notable for its conflicts over multiple water uses and the diversion of water to the Guandu River Basin for energy generation and water supply for the population of the Rio de Janeiro Metropolitan Region. The main water uses in the basin are water supply (14.2 million people), irrigation, hydroelectric power generation, and sewage dilution. The latter is one of the main sources of pollution in the Paraíba do Sul River, presenting a severe state of degradation, especially in the stretches that cross urban areas.

Another aspect that must be considered in the basin is the occurrence of natural disasters and those caused by anthropogenic activities. Figure 1 shows the Paraíba do Sul River Basin within the context of the states it covers. The Paraíba do Sul river basin encompasses latitudes 20^o 26’ and 23^o 39’ S and longitudes 41^o 00’ and 46^o30’ W.

Figure 1
Paraíba do Sul River Basin in the context of the states covered.

Water Quality Sustainability Index (WSI)

The correlation of dilution flow with the minimum reference flow (long-term minimum flow) was performed using the Water Quality Sustainability Index. The WSI was calculated for all municipalities within the Paraíba do Sul River Basin (São Paulo state) using Equation 3:

$WS{I}_{ref}=\frac{F_d}{F_{ref}}$ (3)

Where: WSI_ref: Water Quality Sustainability Index referring to the minimum reference flow; F_d: Dilution flow (L s^-1); and F_ref: Minimum reference flow (flow obtained from the Sewage Atlas: Decontamination of River Basins) or from the receiving body (L s^-1).

Current and future scenarios

The temporal update of the scenarios (from 2013 to 2025/2047) was carried out by reprojecting the treatment efficiencies and capacities of the wastewater treatment plants (WWTPs), maintaining the original data structure of the ANA Atlas (Agência Nacional de Águas e Saneamento Básico, 2013) to ensure comparability. For the 2047 scenario, the planned WWTP efficiencies were adjusted considering the universalization goals of the National Basic Sanitation Plan (Plano Nacional de Saneamento Básico, 2023) and population growth projections (Agência Nacional de Águas e Saneamento Básico, 2024). The 2025 scenario represents an intermediate implementation of these goals. This approach allowed contextualizing the results in relation to contemporary water management challenges, using the same methodological basis for both scenarios.

The temporal update involved: (i) maintaining the structural database of the 2013 Atlas; (ii) reprojecting wastewater treatment plant efficiencies to 2047 based on the PLANSAB (Plano Nacional de Saneamento Básico, 2023) targets; (iii) proportional adjustment to 2025 considering progressive implementation; and (iv) maintaining the original hydrological and water quality relationships (Table 1).

Table 1
Comparative characteristics of the evaluated scenarios.

Parameter	Scenario 2025	Scenario 2047	Database
Total population	1.7 million	1.9 million	ANA (Agência Nacional de Águas e Saneamento Básico, 2024)
Treatment coverage	85%	98%	PLANSAB (Plano Nacional de Saneamento Básico, 2023)
Average WWTP efficiency	75%	90%	Atlas ANA (Agência Nacional de Águas e Saneamento Básico, 2013) + projections
BOD load generated	16,600 kg day-1	18,720 kg day-1	Calculated
BOD load discharged	12,450 kg day-1	4,680 kg day-1	Equation 2
Number of WWTPs	42	58	Atlas ANA (Agência Nacional de Águas e Saneamento Básico, 2013)

Main differences between scenarios: Coverage expansion: +13% in the population served.

Efficiency improvement: +15% in BOD removal. Reduction in pollutant load: -62% in BOD released. System expansion: +16 new wastewater treatment plants.

This time horizon (until 2047) was selected because it is the final target year for the universalization of basic sanitation services in Brazil, as established by the National Basic Sanitation Plan (PLANSAB) - Law No. 14,026/2020 (Plano Nacional de Saneamento Básico, 2023) this scenario allows us to evaluate the effectiveness of current national public policies and identify remaining gaps even after the full implementation of legal targets.

Treatment level (efficiency)

After calculating the dilution flow rate for all rivers in the Paraíba do Sul watershed and having the data on their minimum reference flows, a subsequent comparison was made between the two aforementioned flow rates for the current scenario (2025) and the alternative evaluated for the future (2047). Thus, if the dilution flow rate was lower than the minimum reference flow rate for the watercourse, it implied that the requirements were met. Otherwise, an efficiencies (treatment level) were manipulated to ensure that the requirements were met (obtaining a WSI < 1).

Regarding the manipulation of efficiencies, there were two possible changes: 1) considering all raw sewage passing through the WWTP, in cases where this situation did not occur, and thus manipulating this efficiency, making the dilution flow rate lower than the reference; and 2) altering the efficiency of the existing WWTP, in cases where raw sewage was treated. These modifications were performed individually or in combination, with the same goal of reducing the dilution flow rate to less than the minimum reference flow rate.

Simulation of river class changes

The simulation of class changes was performed for all rivers and streams belonging to the Paraíba do Sul River Basin (São Paulo state). Knowing their original classification class from the Sewage Atlas Report, if the dilution flow rate was lower than the minimum reference flow rate for the watercourse, a change to a more restrictive class was made, altering the concentration adopted for the river class (C_max) and, consequently, the dilution flow rate. A new comparison between the dilution and minimum reference flows was considered to verify whether the relationship continued to be met and whether the physical, chemical, and biological conditions of the rivers were maintained.

Methodological summary

The methodology followed five main steps: (1) collection of BOD flow and concentration data; (2) calculation of dilution flow (Equation 1); (3) calculation of WSI (Equation 3); (4) comparative analysis of current and future scenarios; and (5) validation with observed data. Details are shown in Figure 2.

Figure 2
Methodological flowchart for calculating the WSI. The steps include data collection, application of gray water footprint equations, and analysis of current and future scenarios.

RESULTS AND DISCUSSION

Dilution flow rate

The application of the Water Quality Sustainability Index (WSI) for the Current Scenario (2025) revealed that 45% of the watercourses in the basin are in a critical condition (WSI > 1). This indicates that for nearly half of the studied rivers, the required dilution flow exceeds the available reference flow, meaning these water bodies lack the sufficient assimilation capacity to dilute the pollutant loads received.

This critical state is a direct consequence of pollutant loads—specifically Biochemical Oxygen Demand (BOD) exceeding the legal limits for the respective river classes. The result is a positive gray water footprint, confirming ongoing environmental degradation in these stretches due to insufficient sewage treatment.

These problems can be multifaceted, as reported in several studies. In the Paraiba do Sul Basin, there are several companies and industries, and authors Wu et al. (2024) reported that the textile industry is a highly water-intensive sector, emphasizing the growing importance of recovering clean water from textile wastewater and advancing water reclamation toward zero liquid discharge. However, analysis should be broader; for example, antibiotics can modify populations of multidrug-resistant microorganisms in urban wastewater (Monge-Olivares et al., 2025). As wastewater-based surveillance is increasingly used to track disease trends at the community level, it is important to understand how pathogen signals can be altered by phenomena occurring within sewage basins, such as influx and infiltration (Darling et al., 2025).

Water Quality Sustainability Index (WSI)

The WSI results for rivers and streams in the current scenario (2025) were synthesized graphically and are presented in Figure 3, along with the percentage of watercourses analyzed. Ninety-four water bodies were analyzed for this scenario.

Figure 3
Water Quality Sustainability Index (WSI) for the current and future scenarios.

From Figure 3, it can be inferred that 55% of all watercourses have indices below unity (WSI<1). This suggests that, in these cases, the dilution flow rate is lower than the reference flow rate, meaning the water body has the capacity to dilute the discharged effluent load and is free from pollution problems from sewage treatment. However, 45% of watercourses are in conditions of environmental degradation. This percentage can be considered high for an analysis within the context of a river basin. Achieving water quality sustainability requires the development and application of comprehensive assessment tools to monitor and evaluate the impact of water resource management (Jarzebski et al., 2024).

Scenarios analyzed

The results found for the dilution flow rate for the current and future scenarios, considering the logarithm, are presented in Figure 4, together with the reference flow rate information.

Figure 4
Minimum reference and dilution flow rates (considering the current and future scenario).

Figure 4 shows values below and above the bisector (red line) for both scenarios. The data suggest that values below the bisector indicate that dilution flows are higher than the minimum reference flows. Situations like these (below the bisector) imply conditions where the minimum reference flows are unable to dilute the sewage discharged into the watercourse in question. These are, therefore, critical pollution points in the studied watershed.

Considering the future scenario, it can be said that approximately 70.5% of the watercourses in the studied watershed will not experience pollution problems from sewage treatment. In other words, 29.5% of the watercourses, considering an alternative evaluated for the future scenario (2047), will still not have the capacity to dilute the discharged effluent loads. A significant improvement in dilution conditions can be seen when comparing the two scenarios (2025 and 2047), since in the current scenario, 55% of the water bodies in the studied river basin will not experience pollution problems from sewage treatment. However, the situation presented is far from ideal, which would be 100% of the water bodies without problems from sewage dilution, leading to a zero gray water footprint, which would be the goal to be achieved by all river basin management agencies.

The results of the correlations between dilution flow and minimum reference flow were also expressed using Water Sustainability Indices (WSI) for rivers and streams, considering the current and future scenarios (2025 and 2047). They were synthesized graphically and are presented in Figure 5, along with the percentage of analyzed watercourses. Comparing the two scenarios, an improvement is noted, that is, a decrease in the percentage of watercourses with WSI>1 (from 45% in the current scenario to 29.5% in the future scenario). However, this future alternative condition evaluated implies a positive gray water footprint for 29.5% of the water body in the studied river basin. This improves, but does not resolve, the problem of pollution from pollutant discharges.

Figure 5
Water quality sustainability indices (WSI) for the current (2025) and future (2047) scenarios.

Projections for 2047 indicate that 29.5% of water bodies will still not reach a sustainable condition in terms of water quality (WSI < 1), highlighting the need for investments in WWTP efficiency beyond those foreseen in the National Sanitation Plan (Plano Nacional de Saneamento Básico, 2023). The improvement in Water Sustainability Indices (WSI) directly correlates with reduced environmental impacts, including greenhouse gas emissions. Xiao et al. (2024) reported increasing GHG emissions from urban domestic wastewater treatment in China, from 21.0 MtCO₂ in 2011 to 27.1 MtCO₂ in 2020 (2.88% annual growth). In our study, the enhancement from WSI > 1 (critical) to WSI < 1 (sustainable) scenarios represents not only improved water quality but also potential reductions in energy-intensive treatment processes and associated GHG emissions. This aligns with global efforts to decouple water quality improvement from carbon footprint growth in wastewater management (Xiao et al., 2024).

Treatment level (efficiency)

To evaluate the most effective path toward water quality sustainability, we simulated improvements in wastewater treatment efficiency. The results demonstrate that this is a highly effective strategy. For the Current Scenario (2025), adjusting the treatment efficiencies (η) of existing WWTPs and ensuring that all raw sewage is collected and treated resulted in 99% of the watercourses meeting the dilution condition (WSI < 1). Only one waterbody (approximately 1%) remained in a critical state, indicating a localized point of pollution that requires specific intervention.

In the Future Scenario (2047), where universal collection is already assumed, the simulation focused solely on enhancing the treatment level of existing plants. This single measure proved sufficient to achieve a 100% success rate, with all watercourses in the basin attaining a sustainable condition (WSI < 1).

These findings underscore that prioritizing investments in the coverage and, especially, the efficiency of wastewater treatment plants is the most direct and effective pathway to eliminate the critical points identified by the Water Sustainability Index. Despite the addition of advanced treatment units to wastewater treatment plants to meet discharge standards, the molecular-level mechanisms underlying the reactivity of dissolved organic matter from upgraded full-scale processes, including multiple biological treatments and advanced treatment, remain unclear (Li et al., 2024).

Change in river classes

In contrast to the high effectiveness of improving WWTP efficiency, the simulation of reclassifying water bodies to a more restrictive class (e.g., Class 1) proved to be a less impactful measure. Under this simulation, only 82.5% of the watercourses were able to meet the dilution requirements in the Current Scenario (2025), leaving 17.5% in a critical state. The results were even less favorable in the Future Scenario (2047), where only 78% of the water bodies maintained their dilution capacity after the hypothetical reclassification.

This indicates that simply imposing stricter water quality standards through legal reclassification, without concurrent and significant improvements in pollutant removal at the source, is an insufficient strategy for restoring the assimilation capacity of the Paraíba do Sul basin. The pollutant loads remain too high for the rivers to dilute under the more stringent standards, highlighting that the core of the problem lies in the volume and concentration of effluents discharged, not merely in the legal framework.

Our findings for the Paraíba do Sul Basin (70.5% of water bodies sustainable in 2047) are in line with global trends, where regions with investments in basic sanitation have reduced their gray water footprint by 20-30% (United Nations, 2023).

Although our study points to improvements in future scenarios (Figure 5), the residual gray water footprint in 29.5% of water bodies in 2047 requires actions beyond those outlined in PLANSAB (Plano Nacional de Saneamento Básico, 2023). Solutions such as effluent reuse, as proposed by Müller et al. (2024) to reduce the water footprint in industry, could be adapted for this basin.

As observed by Zhang et al. (2024) in arid agricultural ecosystems, our methodology confirms that efficient wastewater treatment is critical to reducing the gray water footprint, even in industrial basins.

The calculated WSI can be adopted by basin committees as indicators to prioritize investments in WWTPs, especially in municipalities with WSI > 1 (e.g., capacity expansion or adoption of tertiary technologies).

It is recognized that the grey water footprint approach, as applied in this study, treats the pollutant (BOD) as conservative, assuming that dilution is the only mechanism for mitigating pollution. However, the non-conservative nature of BOD implies self-purification processes (biological degradation and oxygen consumption along the watercourse) that are not captured by the model. This methodological choice, although simplifying, is conservative and aligned with international standards for calculating the grey water footprint (Hoekstra et al., 2011).

This study is limited by the analysis of only one water quality parameter (BOD₅), although other pollutants (e.g., heavy metals) can influence the gray water footprint. Furthermore, the projection of future scenarios is based on WWTP efficiencies planned according to ANA (Agência Nacional de Águas e Saneamento Básico, 2013), which may not reflect recent technological advances.

The projection for 2047 does not consider extreme climate variations, which can alter reference flows (Agência Nacional de Águas e Saneamento Básico, 2024). Future work could integrate climate models to refine these scenarios. The Water Quality Sustainability Index (WSI) has proven to be a practical tool for guiding investments and public policies in the basin.

CONCLUSION

This study contributes to the methodological proposal for calculating dilution flow, considering individual analysis for each watercourse. This methodology was applied in the Paraíba do Sul River Basin, in the state of São Paulo. The proposed dilution flow model involved dilution factors linked to the effluent concentrations (BOD₅) passing through the sewage treatment plant and those originating from raw sewage, in order to understand their physical, chemical, and biological conditions and dilution factors. The model successfully estimated the flow rates required for dilution for the two scenarios analyzed: current and future (2025 and 2047).

The correlation of dilution flows with minimum reference flows (here expressed as reference flow), using the Water Quality Sustainability Indices (WSI), showed that, for the future scenario (2047), 70.5% of rivers and streams presented values below unity (WSI <1), meaning that the physical, chemical, and biological conditions of most water bodies were still maintained. The same behavior was observed for the current scenario (2025); however, in this case, 55% of rivers and streams presented WSI values below unity.

Regarding the change in the original efficiencies of the existing Wastewater Treatment Plants (WWTPs) in the system and the WWTPs created to treat all raw sewage, after implementing these changes for the current scenario, only one watercourse (approximately 1%) fails to meet the dilution flow rate requirement below the reference flow rate. In the future scenario, however, 100% of rivers and streams meet these requirements.

For the class change, following the proposed improvement in the scenario, 82.5% of rivers and streams now meet the requirement that all discharged effluent loads be diluted, and in the future scenario, 78% will have their loads diluted.

Therefore, the model in question can be applied to any watershed where the physical, chemical, and biological conditions are desired, as well as the dilution capacity of effluent concentrations discharged into the waterways. Thus, the gray water footprint can be considered a water resource management tool, used to assess impacts and degradability of the aquatic environment, making it important in decision-making to prevent or remediate environmental impacts.

DATA AVAILABILITY STATEMENT

Research data is available upon request.

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Edited by

• Editor in-Chief:
  Adilson Pinheiro

• Associated Editor:
  Rosa Maria Formiga-Johnsson

Publication Dates

• Publication in this collection
  27 Mar 2026
• Date of issue
  2026

History

• Received
  30 Aug 2025
• Reviewed
  05 Nov 2025
• Accepted
  13 Nov 2025