ABSTRACT
The aim of this work is to provide the contribution of water quality indices (WQIs) to environmental management of water resources, during the last three decades in Argentina. As part of the Latin America and the Caribbean region, one of the most water-rich regions in the world, monitoring and management of water stress has not always received enough attention. Particularly, if it is taking into account that due to high temporal and geographic variability in water distribution, it was, it is and it will be the main driver for the development of the activities of the country. A summary of the role of key actors involved in the integral management of water resources is presented, with particular emphasis in those ones responsible of the implementation of water quality monitoring programs and the management of environmental data coming from them. Finally, this work presents different WQIs that have been used in Argentina to assess decision-making. Two case studies (Matanza-Riachuelo River basin and Río de la Plata River) have been selected to show how one of them, the WQI of the Canadian Council of Ministers of Environment, has been implemented.
HIGHLIGHTS
How do WQIs contribute to environmental management in Argentina?
WQIs as communication tools for stakeholders and decision-makers.
WQIs put value on environmental data management and environmental monitoring programs.
Sanitation of the Matanza-Riachuelo basin.
Pollution of the Southern Coastal Strip of the Río de la Plata.
INTRODUCTION
Sources, quality and spatial and temporal distribution of water in Argentina
One of the major challenges of water resources management deals with the availability of water for different stakeholders, which depends on sources, quality, spatial and temporal distribution and sustainability.
Latin America and the Caribbean is one of the most water-rich regions in the world, home to the Amazon and Río de la Plata basins. The region receives 29% of the planet's terrestrial precipitation while accounting for only 10% of the world's population, resulting in an average of 21,300 m3 of water per person per year - four times the global average (Vázquez et al. 2021).
Annual rainfall and direct water balance (precipitation minus evapotranspiration). Source: Vázquez et al. (2021).
Annual rainfall and direct water balance (precipitation minus evapotranspiration). Source: Vázquez et al. (2021).
Monitoring of water stress has not received much attention across the Latin America and the Caribbean region, although many countries have high water stress (Vázquez et al. 2021). Particularly, Argentina ‘faces major challenges in reaching the SDG targets aiming to improve water quality (SDG 6.3) and protect water-related ecosystems (SDG 6.6)’ (Vázquez et al. 2021).
Urban and peri-urban basins (such as Matanza-Riachuelo, Reconquista, Lujan, Salí-Dulce and Mendoza) and the southern coastal strip of the Río de la Plata are polluted by partially treated or untreated domestic and industrial effluents coming from the activities developed in them. Contaminants (bacteria, organic matter, nitrogen, phosphorus and sulfur compounds, heavy metals and persistent organic pollutants) affect the aptitude of use of surface waters and the first aquifer of these basins.
Surface water basins of Argentina and provincial limits. Source: Vázquez et al. (2021).
Surface water basins of Argentina and provincial limits. Source: Vázquez et al. (2021).
In addition, urban development along Argentina's ocean coastline, without adequate sanitation infrastructure, creates punctual pollution sources of solid waste, microplastics (Ronda et al. 2021; Arias et al. 2023), domestic and industrial effluents, hydrocarbon spills from ports and maritime transport. Due to heavy urbanization, industrial settlement and port activities, in the Uruguay and Parana sub-basins, the concentration of nutrients and metals in the Rio de la Plata estuary has increased, changing the eutrophic status of the system (Pizarro & Orlando 1985; Jaime et al. 2001). Waste from highly urbanized areas reaches Río de la Plata through stream, river and storm drain discharge, and travels to distant areas along the Argentine coast (Gonzalez Carman 2015). The ingestion of microplastic threatens marine and freshwater fauna and their biodiversity (Eerkes-Medrano et al. 2015).
Agricultural activities also contribute to the decline in water quality through the use of agrochemicals (pesticides and fertilizers) that spread in the environment through runoff and infiltration, polluting groundwater and surface water; thus, damaging aquatic ecosystems. The most productive areas of Argentina (the so-called Pampa Húmeda) are the ones that receive the major impact of pesticide application (due to soy and corn needs); and the major impact of the use of nitrogen and phosphorous fertilizers (due to wheat and corn needs) (Urseler et al. 2022).
Nutrient enrichment and reservoirs constructions, in the context of climate change, have a direct impact on the composition, structure, and dynamics of marine and freshwater ecosystems. Cyanobacteria blooms that could liberate the toxin microcystin and others are considered an indicator of water stress and are commonly found in Argentina freshwaters in Buenos Aires, Santa Fe, Entre Ríos, La Pampa and Córdoba provinces (Aguilera et al. 2018).
Nitrate constitutes the major contaminant present in groundwater. In the AMBA region, it is associated with overexploitation of the Puelche aquifer (Giannuzzi 2016) and leakages from obsolete sewage systems, and septic tanks in areas without sanitation services (Martínez et al. 2014). The use of nitrogen fertilizers is the main source of nitrate in rural areas; being the irrigation activities, the main mechanism of transport of nitrate to groundwater (Costa et al. 2002; Moschione 2011).
Natural sources provide arsenic, boron and fluoride contaminants to groundwater. Argentina is one of the world's top 12 countries for arsenic concentration in groundwater (Bundschuh et al. 2008). Approximately 10% of people in Argentina are exposed to arsenic, and 2.6% of them suffer from hydroarsenicism. The provinces of Chaco, Córdoba, Tucumán, Santiago del Estero and Buenos Aires are the most affected ones, including most of the highly populated areas of Argentina. Salta, Jujuy, Mendoza, San Juan and San Luis provinces also have areas with the presence of arsenic in groundwater sources (RSA-CONICET 2018). In many of these areas, groundwater is the main source of drinking water throughout the year, mainly exposing rural and dispersed populations without safe surface sources to the contaminants (Grande Cobián 2019). The use of groundwater with arsenic for irrigation purposes in farm fields increases the risk of arsenic contamination (Rosas-Castor et al. 2014).
Conceptual model of sources, contaminants, environmental components and receptors affecting water quality of water resources in Argentina. pT or nT, partially treated and non-treated domestic and industrial effluents; SS, suspended solids; N, nitrogen, S, sulfur; P, phosphorous; As, arsenic; B, boron; F, fluorine. Source: Personal elaboration.
Conceptual model of sources, contaminants, environmental components and receptors affecting water quality of water resources in Argentina. pT or nT, partially treated and non-treated domestic and industrial effluents; SS, suspended solids; N, nitrogen, S, sulfur; P, phosphorous; As, arsenic; B, boron; F, fluorine. Source: Personal elaboration.
Integrated management of water resources in Argentina
Due to its constitution, Argentina has three levels of administration: national, provincial and municipal. The provinces have the original domain of the natural resources existing in their territory (CNA 1994, Art. 124). This multi-level governance system implies a highly decentralized and complex water policy setting, which is primarily driven by the 23 provinces and the city of Buenos Aires, including for shared rivers (OECD 2019). National law N° 25.688 from 2002, about the ‘Regime of Environmental Management of Waters’ encourages the creation of interjurisdictional river basin committees to promote sustainable environmental management of interprovincial river basins. This law was subject to numerous criticisms by most provincial water authorities. Provinces claimed that the law colluded with provincial competences that have not been delegated to the national government, such as river basin institutionalization, management of natural resources, development of local institutions and water planning and management (Pochat 2005). Consequently, this law has not been fully enforced to date.
Argentina has achieved important milestones in the development of its water policy since 1969 (Dardis 2013). The Federal Water Agreement among the provinces in 2003 laid down the foundations of a state water policy with a strong focus on water resources management; with 49 guiding principles acknowledging aspects of the management of water related to its cycle, the environment, the society, management, institutions, the law, the economy, management tools and gender (COHIFE 2023). Principles 6 (water quality), 7 (actions against contamination) and 45 (monitoring) are directly related to the aim of this work. The latter one establishes that ‘Know and evaluate the state and dynamics of water resources with precision in quantity and quality constitutes the basic input of any process planning and management, providing also essential information to control the efficiency and sustainability of water systems and the set of social and economic activities related to water. It is a function of the National State to ensure the collection and dissemination of basic climatic, meteorological and cartographic information’.
Legal frameworks of water resources management widely vary in different provinces. Some of them have well-developed legislation (i.e. Mendoza, Tucuman). Others have not regulated important aspects such as irrigation systems, user's organizations and water rights. Seven provinces still do not have legal provisions for the combined management of surface and groundwater resources (OECD 2019).
Principle 25 of the Federal Water Agreement adopts the basin as the management unit, promoting the formation of basin organizations dedicated to the coordinated and participatory management of water resources within the limits of the basin (COHIFE 2023).
The main challenges of environmental management in Argentina, and particularly basin management, include being proactive, preventive and planned. In order to move in this direction, putting efforts in the provision of enough data and information to improve water management will be a cornerstone (OECD 2019).
Management tools
Environmental monitoring programs and databases
1. The Administrative Commission of the Uruguay River develops and implements the Comprehensive Monitoring Plan of the Uruguay River for the entire shared section. It includes monitoring of water, sediment, phytoplankton and benthos. Biota parameters surveyed were aimed to determine diversity, taxonomic, abundance and biomass of phytoplankton, and the richness, evenness, dominance and diversity of tolerant and sensitive species of benthic macroinvertebrates.
The information of the state of the river is synthesized using a water quality index (WQI) based on a readjustment of the international index ‘water quality index’. It uses 16 parameters representative of different families of contaminants present in the river, which summarizes the quality of water in categories ranging from ‘poor’ to ‘excellent’ (CARU 2019).
2. The Support System for Decision Making of the La Plata basin is an operational platform for managing a large amount of hydrometeorological information produced by Argentina, Bolivia, Brazil, Paraguay and Uruguay, and products related to floods, droughts and water quality, necessary to support timely and informed decision-making related to water management and early warning (SSTD 2024).
3. The Administrative Commission of Río de la Plata in its Environmental Management Plan (CARP 2017) presents the Dredging Material and Water Quality Assessment Program, which aims to:
• provide the basic guidelines for the evaluation of the quality of the water and the materials to be dredged and the dredging, both in the channel and in the emptying areas;
• produce databases and systematize the information generated on water quality and river bottom materials;
• statistically process the quality data generated which is stored and accompanied with the spatial and temporal graphic presentations of results;
• contrast the results obtained with the water and sediment quality criteria taken as reference, and with the baseline of water quality and dredged material, prepared by the CARP.
4. The Argentine-Paraguayan Joint Commission of the Paraná River has a water quality monitoring program upstream and downstream of the Yacyretá dam.
5. The Trinational Commission for the Development of the Pilcomayo River basin has a unique database for water and sediments quality developed from 2006 to the present.
6. The Yacyretá Binational Entity (EBY) developed a water quality monitoring program that is implemented in the section of the Upper Paraná. The work area also includes some of the lateral branches of the main reservoir or larger sub-reservoirs, as well as smaller sub-reservoirs with urban trace, to analyze external contributions to the main course.
Water quality indices
The International Atomic Energy Agency project ARCAL RLA/1/010 (Improvement of management of contamination of surface water bodies contaminated with metals), in accordance with international recommendations (PAHO and WHO), proposed to contribute to the improvement of water quality management of surface water bodies by harmonizing protocols and training the human resources necessary for the evaluation of water quality and the transport of metals in surface water bodies in countries in the Latin American region with problems of metal contamination (natural or anthropogenic); applying nuclear and complementary analytical techniques, including the use of tracers (Cicerone et al. 2011).
One product related to this project is the proposal of a WQI for the Latin American and Caribbean region (Avila Pérez et al. 2011). This document provides a diagnosis regarding the use of WQIs in the region; it reflects the consensus reached during the workshop held in Rio de Janeiro, Brazil, in 2007, where a WQI was suggested for the Latin America and Caribbean region. It highlights the strengths and weaknesses of using this index and demonstrates how it has been applied to various ecosystems in the region (Avila Perez et al. 2011).
Table 1 presents three WQIs used in Argentina across different types of studies to address water quality: research (Vignolo et al. 2006; Nader et al. 2013), development and environmental management. The indexes developed by Martínez de Bascarán (1979) and the Canadian Council of Ministers of Environment (2017) rely on physicochemical and microbiological parameters that describe water quality, most of which are regulated by law regarding water use. In contrast, the Pampean Diatom Index (IDP), developed by Gómez & Licursi (2001), is based on the epipelic diatom community and has been formerly applied at a regional scale for the assessment of water quality in rivers and streams in the Pampean plain.
Water quality indices
Name . | Formula . | Reference . |
---|---|---|
CCME WQI | ![]() | CCME (2017) |
Pampean Diatom Index | ![]() | Gómez & Licursi (2001) |
WQIB | ![]() | Martínez et al. (2014) |
Name . | Formula . | Reference . |
---|---|---|
CCME WQI | ![]() | CCME (2017) |
Pampean Diatom Index | ![]() | Gómez & Licursi (2001) |
WQIB | ![]() | Martínez et al. (2014) |
The IDP is a tool, at the regional scale, developed to assess the water quality of rivers and smaller streams of the Pampean plain in Argentina. The index is based on the sensitivity of the epipelic diatom assemblages integrating the effect of organic enrichment and eutrophication, two phenomena which can hardly be separated (Gómez & Licursi 2001).
For the elaboration of the index, 210 species were identified, quantified and categorized according to their sensitivity to organic enrichment and eutrophication, taking into account the main variables BOD5, and PO4.
The IDP is used by researchers and environmental managers to detect pollution gradients, particularly nutrient enrichment and organic matters; and in the evaluation of the effects of agricultural runoff, urban discharges and industrial pollutants on aquatic ecosystems (Gómez 1999; Licursi & Gómez 2002). It provides a localized assessment, improving its accuracy, supporting management decisions and prioritizing remediation efforts.
The WQI developed by Martínez de Bascarán (1979) simplifies the assessment of water quality by integrating 20 physical, chemical and biological parameters into a single numerical value. It references the operational values of pH, conductivity, dissolved oxygen, permanganate reduction, total coliforms, N-NH4+, chloride, temperature, detergents, aspect, hardness, dissolved solids, fats and oils, sulfate, nitrate, cyanides, sodium, calcium, magnesium, phosphates, nitrites and biological chemical demand, to a situation that is considered admissible or desirable, that is defined by certain standards or criteria. Each parameter is assigned a quality value (Ci) and a weight (Pi) based on its importance to overall water quality. The final WQI is calculated using a weighted average (see Table 1, Equation (3)) providing a clear and comparable metric to assess and communicate water quality conditions effectively across different water bodies.
Limitations
Where it has been applied
This work focuses on the use of the CCME WQI for environmental management in Argentina, particularly in the case studies presented above. Therefore, it is described in detail in the following paragraphs of this section.
The CCME WQI is based on three factors: Scope (F1), which represents the percentage of parameters exceeding the regulated limit during an established time range in relation to the total number of analyzed parameters; Frequency (F2), which represents the percentage of individual results that do not comply with the limits and Amplitude (F3), which represents the amount by which out-of-range values fail to meet the corresponding limits. The calculation methodology of the index is based on the concept that these three factors can be combined to form a resultant vector in a three-dimensional space, producing a single value between 0 and 100 that describes water quality (see Table 2). For more details, see CCME (2017).
WQI categories according to CCME (2017)
WQI (%) . | Category . | Obs . |
---|---|---|
95–100 | Excellent | The water quality is protected, with hardly any deterioration; the resource condition is almost equal to its desired state |
80–94 | Good | The water quality is protected with a lower degree of threat or deterioration; the resource condition rarely deviates from its desired state |
65–79 | Fair | The water quality is usually protected, but occasionally threatened or deteriorated; the resource condition sometimes differs from its desired state |
45–64 | Marginal/poor | The water quality is frequently threatened or deteriorated; the resource condition often differs from its desired state |
0–44 | Very poor | The water quality is almost always threatened or deteriorated; the resource condition usually differs from its desired state |
WQI (%) . | Category . | Obs . |
---|---|---|
95–100 | Excellent | The water quality is protected, with hardly any deterioration; the resource condition is almost equal to its desired state |
80–94 | Good | The water quality is protected with a lower degree of threat or deterioration; the resource condition rarely deviates from its desired state |
65–79 | Fair | The water quality is usually protected, but occasionally threatened or deteriorated; the resource condition sometimes differs from its desired state |
45–64 | Marginal/poor | The water quality is frequently threatened or deteriorated; the resource condition often differs from its desired state |
0–44 | Very poor | The water quality is almost always threatened or deteriorated; the resource condition usually differs from its desired state |
After the evaluation of the index, its value has to be referred to the following categories in order to evaluate water quality.
Case studies
Río de la Plata basin
Introduction
The Río de la Plata sustains multiple uses for a vast population and provides numerous benefits for industries, navigation, recreational activities and water sports. It is also the main source of drinking water and receives the effluents of approximately 35% of the Argentine population. Additionally, it is important for its biodiversity and fishery resources, among other things. However, all this population and the activities generated also produce a negative environmental impact. For this reason, numerous water quality monitoring programs have been carried out for decades, mainly to assess the suitability for recreational use with direct contact.
Monitoring sites of the water quality program of the southern coastal strip of the Río de la Plata.
Monitoring sites of the water quality program of the southern coastal strip of the Río de la Plata.
The current National Environment Authority (Subsecretary of Environment) coordinates the water quality program and 15 other institutions participate in this program:
Ten local coastal governments, which make up the Local Government Information for Information Exchange Network (RIIGLO, by its acronym in Spanish), are responsible for sampling within their respective jurisdictions;
Matanza-Riachuelo Basin Authority (ACUMAR) also samples;
National Water Institute (INA) and Argentine Naval Prefecture (PNA), both for logistics in reaching the sites by boat and transporting the samples to the laboratory;
Water Administration of the Province of Buenos Aires (ADA), the provincial authority on water issues, is one of the laboratories where the samples are analyzed;
Aguas Bonaerenses (ABSA) is the provincial's water and sanitation services company which represents the second laboratory in the program;
AySA (Argentine Water and Sanitation) is the water and sanitation services company in a large number of municipalities and the City of Buenos Aires, which participated as the third laboratory.
The water quality of the study system is evaluated by using a WQI based on the regulated parameters for recreational use with direct contact and the data generated by the monitoring program. The results are published on the Environmental Information Center of Argentina web platform (CIAM 2024).
METHODS
In each of the four annual campaigns, 43 sites are sampled along more than 100 km of coastline, and 23 parameters are surveyed to account for different types of contamination, from sewage, agricultural, and industrial sources, as well as the state of eutrophication. Of the 23 parameters, three are measured in situ with a Hach multiparameter sensor (temperature, dissolved oxygen (DO) and pH), four are organoleptic (smell, color, floating materials and foams), and 16 are analyzed in the laboratory (Table 3).
Reference values according to regulations for the Río de la Plata
. | Parameter . | Value of reference . | Local reference standard of water quality . |
---|---|---|---|
1 | DO | <5 mg/L | MVOTMA Decree N° 253/279 of 1979 (MVOTMA 1979) |
2 | pH | 6.5–8.5 | ADA Resolution N°42/2006 (ADA 2006) |
3 | Temperature | <35 °C | ADA Resolution N°42/2006 (ADA 2006) |
4 | Smell (not natural) | Not noticeable | ADA Resolution N°42/2006 (ADA 2006) |
5 | Color (not natural) | Absent | ADA Resolution N°42/2006 (ADA 2006) |
6 | Floating materials | Absent | ADA Resolution N°42/2006 (ADA 2006) |
7 | Foams | Absent | ADA Resolution N°42/2006 (ADA 2006) |
8 | Faecal coliforms | 150 CFU/100 ml | ADA Resolution N°42/2006 (ADA 2006) |
9 | Escherichia coli | 126 CFU/100ml | ADA Resolution N°42/2006 (ADA 2006) |
10 | Enterococci | 33 CFU/100ml | ADA Resolution N°42/2006 (ADA 2006) |
12 | BOD5 | 10 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
13 | Nitrate | 125 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
14 | Ammonia | 0.5 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
15 | Total phosphorous | 0.025 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
16 | Microcystin | 0.01 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
17 | Chlorophyll ‘a’ | 0.05 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
18 | Total petroleum hydrocarbons | 0.05 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
19 | Chromium | 0.05 mg/L | ACUMAR Resolution N° 283/2019 (ACUMAR 2017) |
20 | Cadmium | 0.005 mg/L | ACUMAR Resolution N° 283/2019 (ACUMAR 2017) |
21 | Turbidity | 100 NTU | ADA Resolution N°42/2006 (ADA 2006) |
22 | DQO | Does not have | – |
23 | Phosphate | Does not have | – |
. | Parameter . | Value of reference . | Local reference standard of water quality . |
---|---|---|---|
1 | DO | <5 mg/L | MVOTMA Decree N° 253/279 of 1979 (MVOTMA 1979) |
2 | pH | 6.5–8.5 | ADA Resolution N°42/2006 (ADA 2006) |
3 | Temperature | <35 °C | ADA Resolution N°42/2006 (ADA 2006) |
4 | Smell (not natural) | Not noticeable | ADA Resolution N°42/2006 (ADA 2006) |
5 | Color (not natural) | Absent | ADA Resolution N°42/2006 (ADA 2006) |
6 | Floating materials | Absent | ADA Resolution N°42/2006 (ADA 2006) |
7 | Foams | Absent | ADA Resolution N°42/2006 (ADA 2006) |
8 | Faecal coliforms | 150 CFU/100 ml | ADA Resolution N°42/2006 (ADA 2006) |
9 | Escherichia coli | 126 CFU/100ml | ADA Resolution N°42/2006 (ADA 2006) |
10 | Enterococci | 33 CFU/100ml | ADA Resolution N°42/2006 (ADA 2006) |
12 | BOD5 | 10 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
13 | Nitrate | 125 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
14 | Ammonia | 0.5 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
15 | Total phosphorous | 0.025 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
16 | Microcystin | 0.01 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
17 | Chlorophyll ‘a’ | 0.05 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
18 | Total petroleum hydrocarbons | 0.05 mg/L | ADA Resolution N°42/2006 (ADA 2006) |
19 | Chromium | 0.05 mg/L | ACUMAR Resolution N° 283/2019 (ACUMAR 2017) |
20 | Cadmium | 0.005 mg/L | ACUMAR Resolution N° 283/2019 (ACUMAR 2017) |
21 | Turbidity | 100 NTU | ADA Resolution N°42/2006 (ADA 2006) |
22 | DQO | Does not have | – |
23 | Phosphate | Does not have | – |
The WQI used is the one created for the Canadian Council of Ministers of the Environment (CCME), which consists of comparing the result of each parameter with the standard of the chosen local regulation. At each site, this comparison is made for the 20 parameters and integrated into a single WQI value.
In this case, we use the ADA Resolution 42/2006 as the standard for most parameters, which is specific for the Río de la Plata and its Maritime Front for recreational use. For two parameters (heavy metals), we use the ACUMAR Resolution 283/2019, which is stricter for these parameters and is for recreational use but for indirect contact (without touching water, just to look at it).
Sampling is carried out at 43 sites along more than 100 km of the river's coastline, from the municipality of Tigre to that of Berisso (10 local governments including CABA) (Table 4).
List of monitoring sites in the coastal zone of the Río de la Plata
. | N° . | Local Government . | Site . | Code . | Latitude . | Longitude . |
---|---|---|---|---|---|---|
North zone | 1 | Tigre | Canal Villa Nueva y Río Luján | TI001 | 34° 21' 30,38'' | 58° 40' 41,59'' |
2 | Río Lujan y Arroyo Caraguatá | TI006 | 34° 23' 03,01'' | 58° 37' 57,04'' | ||
3 | Canal Aliviador y Río Lujan | TI002 | 34° 23' 22,09'' | 58° 37' 19,74'' | ||
4 | Río Carapachay y Arroyo Gallo Fiambre | TI003 | 34° 24' 02,02'' | 58° 35' 41,03'' | ||
5 | Río Reconquista y Río Lujan | TI004 | 34° 24' 29,02'' | 58° 35' 27,02'' | ||
6 | Río Tigre y Río Lujan | TI005 | 34° 24' 55,01'' | 58° 34' 45,01'' | ||
7 | Río Lujan y Canal San Fernando | TI007 | 34° 25' 29,03'' | 58° 33' 29,02'' | ||
8 | Río Capitán y Río San Antonio | TI008 | 34° 22' 32,02'' | 58° 33' 31,03'' | ||
9 | Arroyo Abra Vieja y Santa Rosa | TI009 | 34° 23' 12,01'' | 58° 33' 41,00'' | ||
10 | San Fernando | Del Arca | SF015 | 34° 26' 20,11'' | 58° 32' 11,47'' | |
11 | San Isidro | Espigón La Farola | SI021 | 34° 26' 59,028'' | 58° 30' 16,09'' | |
12 | Reserva Ecológica | SI022 | 34° 27' 55,01'' | 58° 29' 35,02'' | ||
13 | Playa Espigón de Pacheco | SI024 | 34° 28' 10,42'' | 58° 29' 30,12'' | ||
14 | Perú Puente | SI023 | 34° 29' 03,01'' | 58° 28' 46,02'' | ||
15 | Vicente López | Reserva Barrio El Ceibo | VL033 | 34° 29' 42,04'' | 58° 28' 46,02'' | |
16 | Puerto de Olivos Espigón | VL032 | 34° 30' 19,91'' | 58° 28' 25,39'' | ||
17 | Costa y Melo | VL031 | 34° 31' 27,01'' | 58° 27' 59,00'' | ||
Center | 18 | Caba | Parque de los Niños | CA041 | 34° 31' 39,36'' | 58° 27' 19,69'' |
19 | Costanera Norte - Espigón Abanico | CA044 | 34° 32' 49,52'' | 58° 25' 48,83'' | ||
20 | Club de Pescadores | CA046 | 34° 33' 47,63'' | 58° 24' 14,83'' | ||
21 | Reserva Ecológica Costanera Sur - Playita | CA047 | 34° 36' 45,94'' | 58° 20' 26,20'' | ||
22 | Cuatro bocas- desembocadura del Riachuelo | AC001 | 34° 39' 46,04'' | 58° 17' 48,01'' | ||
South zone | 23 | Avellaneda | Escollera de Propaneros | AV054 | 34° 37' 48,00'' | 58° 19' 42,02'' |
24 | Polo Petroquímico Dock Sud | AV051 | 34° 38' 32,03'' | 58° 19' 24,02'' | ||
25 | Arroyo Sarandí | AV052 | 34° 38' 51,00'' | 58° 18' 36,00'' | ||
26 | Costa de Villa Domínico | AV055 | 34° 39' 19,01'' | 58° 18' 15,01'' | ||
27 | Arroyo Santo Domingo | AV053 | 34° 39' 46,04'' | 58° 17' 48,01'' | ||
28 | Quilmes | Espora | QU061 | 34° 41' 31,02'' | 58° 15' 14,00'' | |
29 | Náutico | QU062 | 34° 42' 01,04'' | 58° 13' 44,00'' | ||
30 | Pejerrey Club | QU063 | 34° 42' 24,98'' | 58° 13' 04,01'' | ||
31 | Berazategui | Calle 14 y Costa - Salida cloaca | BZ078 | 34° 44' 39,01'' | 58° 10' 38,03'' | |
32 | Puerto Trinidad calle 47 | BZ077 | 34° 44' 58,52'' | 58° 07' 57,72'' | ||
33 | Costanera Hudson Calle 63 | BZ080 | 34° 45' 10,80'' | 58° 06' 29,81'' | ||
34 | Ensenada | Reserva Punta Lara - Boca Cerrada | EN_adic | 34° 46' 48,5'' | 58° 01' 03,5'' | |
35 | Camping Eva Perón | EN081 | 34° 49' 14,56'' | 57° 57' 55,15'' | ||
36 | Toma de agua Club de Pesca | EN082 | 34° 49' 39,94'' | 57° 56' 38,44'' | ||
37 | Arroyo El Gato | EN083 | 34° 50' 31,09'' | 57° 56' 05,78'' | ||
38 | Ensenada Prefectura Isla Santiago | EN084 | 34° 50' 02,08'' | 57° 52' 48,76'' | ||
39 | BERISSO | Balneario Palo Blanco | BS092 | 34° 51' 20,91'' | 57° 50' 17,32'' | |
40 | Diagonal 66 (descarga cloaca) | BS095 | 34° 52' 01,99'' | 57° 49' 00,01'' | ||
41 | Playa La Bagliardi | BS091 | 34° 52' 23,02'' | 57° 48' 38,02'' | ||
42 | Balneario Municipal | BS094 | 34° 55' 5,98'' | 57° 44' 26,99'' | ||
43 | Playa La Balandra | BS093 | 34° 55' 41,59'' | 57° 43' 02,24'' |
. | N° . | Local Government . | Site . | Code . | Latitude . | Longitude . |
---|---|---|---|---|---|---|
North zone | 1 | Tigre | Canal Villa Nueva y Río Luján | TI001 | 34° 21' 30,38'' | 58° 40' 41,59'' |
2 | Río Lujan y Arroyo Caraguatá | TI006 | 34° 23' 03,01'' | 58° 37' 57,04'' | ||
3 | Canal Aliviador y Río Lujan | TI002 | 34° 23' 22,09'' | 58° 37' 19,74'' | ||
4 | Río Carapachay y Arroyo Gallo Fiambre | TI003 | 34° 24' 02,02'' | 58° 35' 41,03'' | ||
5 | Río Reconquista y Río Lujan | TI004 | 34° 24' 29,02'' | 58° 35' 27,02'' | ||
6 | Río Tigre y Río Lujan | TI005 | 34° 24' 55,01'' | 58° 34' 45,01'' | ||
7 | Río Lujan y Canal San Fernando | TI007 | 34° 25' 29,03'' | 58° 33' 29,02'' | ||
8 | Río Capitán y Río San Antonio | TI008 | 34° 22' 32,02'' | 58° 33' 31,03'' | ||
9 | Arroyo Abra Vieja y Santa Rosa | TI009 | 34° 23' 12,01'' | 58° 33' 41,00'' | ||
10 | San Fernando | Del Arca | SF015 | 34° 26' 20,11'' | 58° 32' 11,47'' | |
11 | San Isidro | Espigón La Farola | SI021 | 34° 26' 59,028'' | 58° 30' 16,09'' | |
12 | Reserva Ecológica | SI022 | 34° 27' 55,01'' | 58° 29' 35,02'' | ||
13 | Playa Espigón de Pacheco | SI024 | 34° 28' 10,42'' | 58° 29' 30,12'' | ||
14 | Perú Puente | SI023 | 34° 29' 03,01'' | 58° 28' 46,02'' | ||
15 | Vicente López | Reserva Barrio El Ceibo | VL033 | 34° 29' 42,04'' | 58° 28' 46,02'' | |
16 | Puerto de Olivos Espigón | VL032 | 34° 30' 19,91'' | 58° 28' 25,39'' | ||
17 | Costa y Melo | VL031 | 34° 31' 27,01'' | 58° 27' 59,00'' | ||
Center | 18 | Caba | Parque de los Niños | CA041 | 34° 31' 39,36'' | 58° 27' 19,69'' |
19 | Costanera Norte - Espigón Abanico | CA044 | 34° 32' 49,52'' | 58° 25' 48,83'' | ||
20 | Club de Pescadores | CA046 | 34° 33' 47,63'' | 58° 24' 14,83'' | ||
21 | Reserva Ecológica Costanera Sur - Playita | CA047 | 34° 36' 45,94'' | 58° 20' 26,20'' | ||
22 | Cuatro bocas- desembocadura del Riachuelo | AC001 | 34° 39' 46,04'' | 58° 17' 48,01'' | ||
South zone | 23 | Avellaneda | Escollera de Propaneros | AV054 | 34° 37' 48,00'' | 58° 19' 42,02'' |
24 | Polo Petroquímico Dock Sud | AV051 | 34° 38' 32,03'' | 58° 19' 24,02'' | ||
25 | Arroyo Sarandí | AV052 | 34° 38' 51,00'' | 58° 18' 36,00'' | ||
26 | Costa de Villa Domínico | AV055 | 34° 39' 19,01'' | 58° 18' 15,01'' | ||
27 | Arroyo Santo Domingo | AV053 | 34° 39' 46,04'' | 58° 17' 48,01'' | ||
28 | Quilmes | Espora | QU061 | 34° 41' 31,02'' | 58° 15' 14,00'' | |
29 | Náutico | QU062 | 34° 42' 01,04'' | 58° 13' 44,00'' | ||
30 | Pejerrey Club | QU063 | 34° 42' 24,98'' | 58° 13' 04,01'' | ||
31 | Berazategui | Calle 14 y Costa - Salida cloaca | BZ078 | 34° 44' 39,01'' | 58° 10' 38,03'' | |
32 | Puerto Trinidad calle 47 | BZ077 | 34° 44' 58,52'' | 58° 07' 57,72'' | ||
33 | Costanera Hudson Calle 63 | BZ080 | 34° 45' 10,80'' | 58° 06' 29,81'' | ||
34 | Ensenada | Reserva Punta Lara - Boca Cerrada | EN_adic | 34° 46' 48,5'' | 58° 01' 03,5'' | |
35 | Camping Eva Perón | EN081 | 34° 49' 14,56'' | 57° 57' 55,15'' | ||
36 | Toma de agua Club de Pesca | EN082 | 34° 49' 39,94'' | 57° 56' 38,44'' | ||
37 | Arroyo El Gato | EN083 | 34° 50' 31,09'' | 57° 56' 05,78'' | ||
38 | Ensenada Prefectura Isla Santiago | EN084 | 34° 50' 02,08'' | 57° 52' 48,76'' | ||
39 | BERISSO | Balneario Palo Blanco | BS092 | 34° 51' 20,91'' | 57° 50' 17,32'' | |
40 | Diagonal 66 (descarga cloaca) | BS095 | 34° 52' 01,99'' | 57° 49' 00,01'' | ||
41 | Playa La Bagliardi | BS091 | 34° 52' 23,02'' | 57° 48' 38,02'' | ||
42 | Balneario Municipal | BS094 | 34° 55' 5,98'' | 57° 44' 26,99'' | ||
43 | Playa La Balandra | BS093 | 34° 55' 41,59'' | 57° 43' 02,24'' |
One sample is taken for each parameter in each of the four annual campaigns. Considering that there are 43 sites per campaign and that each site requires about six containers for all parameters, about 258 samples are transported and processed on each day of the campaign.
The analyses of only 10 parameters were carried out during the first years (2004–2012). Since 2013, additional parameters have been included, and since 2018, a total of 23 parameters have been recorded. The WQI has been calculated from 2013 to the present. All results are published at the CIAM.
RESULTS
Percentage of WQI classes in 2013 and 2023 at the Argentinian coast of the Río de la Plata regarding sites suitable for recreational use with direct contact.
Percentage of WQI classes in 2013 and 2023 at the Argentinian coast of the Río de la Plata regarding sites suitable for recreational use with direct contact.
Percentage of monitoring sites not meeting water quality standards for each parameter regarding suitability for recreational use with direct contact (2023). Source: Subsecretary of Environment (Federal Government).
Percentage of monitoring sites not meeting water quality standards for each parameter regarding suitability for recreational use with direct contact (2023). Source: Subsecretary of Environment (Federal Government).
The most contaminated sites are systematically repeated and they are BS095 in Berisso (due to sewage effluents discharge coming from La Plata, Berisso and Ensenada); SI023 in San Isidro (despite having a very well-known and popular café on the river and a kitesurfing school, and being a central point where many people gather to practice various water sports) and, finally, but not least important, BZ077 and BZ078 in Berazategui (sites close to the discharge of sewage effluents generated by the population of the entire City of Buenos Aires and numerous municipalities of surrounding of the City of Buenos Aires). The parameters furthest from the standard values were the three bacteriological parameters: faecal coliforms, Enterococci and Escherichia coli, followed by total phosphorus and ammonium as the most important (Figure 6).
All these parameters reflect the deficiency of the sewage systems, both the sewer network and the treatment of sewage arriving via the network.
To assess the potential impact of the new sanitary infrastructure currently under construction in the study area, we considered four scenarios of water quality (three of them based on a reduction in sewage effluent discharge):
- Scenario 1: no action (no new sanitary infrastructure developed).
- Scenario 2: The sewage infrastructure is somewhat increased showing an improvement of 25% in bacteriological parameters and a consequent 25% improvement in the parameters ammonium and total phosphorous (TP).
- Scenario 3: The sewage infrastructure increases significantly showing an improvement of 50% in bacteriological parameters, ammonium and TP, and consequently an improvement of 25% in chlorophyll and microcystin parameters.
- Scenario 4: The entire necessary sewage infrastructure is carried out, which reflects a 100% improvement in bacteriological parameters and a 75% decrease of ammonium, TP, chlorophyll and microcystin (the decrease of these last four parameters was not 100% because they have different sources).
Scenario 1: No changes in the WQI, with approximately 50% of sites remaining in the most deteriorated classes of water quality.
Scenario 2: Similar to Scenario 1, but with some records showing slightly improved water quality.
Scenario 3: Similar to Scenario 2, but with more records indicating deteriorated water quality.
Scenario 4: In this scenario, there are no longer any sites with the most deteriorated water quality. Over 80% of sites reflect slightly deteriorated quality, and 5% of sites are deemed suitable for the intended use. This indicates that while sewage pollution remains the primary cause of current water pollution, other sources also impact water quality and must be addressed to achieve further improvements.
Since there is only one sample per site for each parameter, factor 2 (frequency of failed samples) in the WQI calculation formula, is equal to factor 1 (scope) (Table 5).
Percentage of WQI classes for scenarios 1–4 at the Argentinian coast of the Río de la Plata regarding sites suitable for recreational use with direct contact.
Percentage of WQI classes for scenarios 1–4 at the Argentinian coast of the Río de la Plata regarding sites suitable for recreational use with direct contact.
Water quality in relation to compliance with Use IV (see Table 6, Table 3), during the period May 2022–2023, for surface water. The formula used for the calculation of the surface WQI is presented in Table 1 (Equation (1)). Raw data coming from the public database of ACUMAR.
WQI and Factor 1 (scope), Factor 2 (frequency) and Factor 3 (amplitude) for scenarios 1, 2, 3 and 4
. | . | Scenario 1 . | Scenario 2 . | Scenario 3 . | Scenario 4 . | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . |
1 | TI001 | 58 | 26 | 26 | 63 | 62 | 26 | 26 | 54 | 68 | 26 | 26 | 42 | 91 | 11 | 11 | 6 |
2 | TI006 | 46 | 26 | 26 | 86 | 48 | 26 | 26 | 81 | 52 | 26 | 26 | 74 | 91 | 11 | 11 | 2 |
3 | TI002 | 42 | 32 | 32 | 89 | 44 | 32 | 32 | 86 | 47 | 32 | 32 | 80 | 86 | 11 | 11 | 20 |
4 | TI003 | 46 | 32 | 32 | 82 | 49 | 32 | 32 | 77 | 53 | 32 | 32 | 68 | 91 | 11 | 11 | 4 |
5 | TI004 | 37 | 42 | 42 | 91 | 38 | 42 | 42 | 89 | 41 | 42 | 42 | 84 | 80 | 21 | 21 | 16 |
6 | TI005 | 33 | 47 | 47 | 94 | 34 | 47 | 47 | 93 | 36 | 47 | 47 | 89 | 71 | 32 | 32 | 21 |
7 | TI007 | 38 | 42 | 42 | 89 | 40 | 42 | 42 | 86 | 43 | 42 | 42 | 80 | 77 | 26 | 26 | 16 |
8 | TI008 | 58 | 21 | 21 | 67 | 61 | 21 | 21 | 60 | 67 | 21 | 21 | 48 | 95 | 5 | 5 | 3 |
9 | TI009 | 64 | 26 | 26 | 50 | 69 | 26 | 26 | 38 | 77 | 21 | 21 | 26 | 91 | 11 | 11 | 2 |
10 | SF015 | 42 | 28 | 28 | 92 | 43 | 28 | 28 | 90 | 46 | 28 | 28 | 86 | 89 | 11 | 11 | 12 |
11 | SI021 | ||||||||||||||||
12 | SI022 | 53 | 32 | 32 | 69 | 58 | 26 | 32 | 62 | 64 | 26 | 26 | 51 | 90 | 11 | 11 | 7 |
13 | SI024 | 48 | 26 | 26 | 82 | 51 | 26 | 26 | 77 | 55 | 26 | 26 | 68 | 91 | 5 | 5 | 14 |
14 | SI023 | 37 | 33 | 33 | 98 | 37 | 33 | 33 | 98 | 38 | 33 | 33 | 97 | 89 | 11 | 11 | 9 |
15 | VL033 | 44 | 32 | 32 | 87 | 46 | 32 | 32 | 83 | 51 | 26 | 26 | 76 | 88 | 11 | 11 | 14 |
16 | VL032 | 40 | 32 | 32 | 94 | 41 | 32 | 32 | 92 | 43 | 32 | 32 | 88 | 90 | 11 | 11 | 7 |
17 | VL031 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 44 | 32 | 32 | 85 | 89 | 11 | 11 | 11 |
18 | CA041 | 39 | 26 | 26 | 99 | 39 | 26 | 26 | 98 | 40 | 26 | 26 | 97 | 93 | 5 | 5 | 9 |
19 | CA044 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 46 | 26 | 26 | 85 | 95 | 5 | 5 | 3 |
20 | CA046 | 42 | 26 | 26 | 93 | 43 | 26 | 26 | 91 | 47 | 21 | 21 | 87 | 94 | 5 | 5 | 7 |
21 | CA047 | 52 | 26 | 26 | 75 | 55 | 26 | 26 | 69 | 60 | 26 | 26 | 59 | 91 | 11 | 11 | 6 |
22 | AC001 | 29 | 53 | 53 | 97 | 30 | 53 | 53 | 96 | 31 | 53 | 53 | 94 | 67 | 37 | 37 | 25 |
23 | AV054 | 45 | 32 | 32 | 85 | 47 | 32 | 32 | 81 | 51 | 32 | 32 | 73 | 83 | 16 | 16 | 19 |
24 | AV051 | 48 | 32 | 32 | 79 | 50 | 32 | 32 | 73 | 55 | 32 | 32 | 64 | 84 | 11 | 11 | 24 |
25 | AV052 | 49 | 32 | 32 | 76 | 52 | 32 | 32 | 70 | 57 | 32 | 32 | 59 | 86 | 11 | 11 | 19 |
26 | AV055 | 45 | 37 | 37 | 80 | 47 | 37 | 37 | 75 | 54 | 32 | 32 | 65 | 88 | 11 | 11 | 13 |
27 | AV053 | 48 | 32 | 32 | 79 | 48 | 37 | 32 | 73 | 55 | 32 | 32 | 63 | 83 | 16 | 16 | 19 |
28 | QU061 | 51 | 37 | 37 | 67 | 54 | 37 | 37 | 60 | 62 | 32 | 32 | 48 | 88 | 11 | 11 | 14 |
29 | QU062 | 52 | 26 | 26 | 75 | 55 | 26 | 26 | 68 | 63 | 21 | 21 | 57 | 85 | 5 | 5 | 25 |
30 | QU063 | 58 | 26 | 26 | 62 | 62 | 26 | 26 | 55 | 70 | 21 | 21 | 42 | 94 | 5 | 5 | 7 |
31 | BZ078 | 27 | 56 | 56 | 98 | 27 | 56 | 56 | 98 | 28 | 56 | 56 | 97 | 66 | 31 | 31 | 39 |
32 | BZ077 | 32 | 50 | 50 | 93 | 33 | 50 | 50 | 91 | 38 | 44 | 44 | 88 | 78 | 19 | 19 | 28 |
33 | BZ080 | 43 | 38 | 38 | 83 | 45 | 38 | 38 | 79 | 49 | 38 | 38 | 71 | 85 | 13 | 13 | 19 |
34 | EN-adic | 48 | 38 | 38 | 72 | 50 | 38 | 38 | 68 | 59 | 31 | 31 | 57 | 87 | 13 | 13 | 15 |
35 | EN081 | 53 | 37 | 37 | 63 | 55 | 37 | 37 | 57 | 63 | 32 | 32 | 46 | 85 | 16 | 16 | 14 |
36 | EN082 | 57 | 32 | 32 | 59 | 60 | 32 | 32 | 54 | 64 | 32 | 32 | 43 | 85 | 16 | 16 | 14 |
37 | EN083 | 37 | 37 | 37 | 95 | 38 | 37 | 37 | 94 | 40 | 37 | 37 | 91 | 83 | 16 | 16 | 19 |
38 | EN084 | 52 | 32 | 32 | 71 | 55 | 32 | 32 | 63 | 63 | 26 | 26 | 52 | 93 | 5 | 5 | 9 |
39 | BS092 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 44 | 32 | 32 | 86 | 89 | 11 | 11 | 11 |
40 | BS095 | 29 | 53 | 53 | 98 | 29 | 53 | 53 | 97 | 30 | 53 | 53 | 96 | 67 | 32 | 32 | 36 |
41 | BS091 | 42 | 32 | 32 | 89 | 42 | 37 | 32 | 86 | 47 | 32 | 32 | 80 | 86 | 11 | 11 | 20 |
42 | BS094 | 56 | 37 | 37 | 57 | 59 | 37 | 37 | 49 | 64 | 37 | 37 | 35 | 86 | 16 | 16 | 7 |
43 | BS093 | 51 | 26 | 26 | 77 | 54 | 26 | 26 | 71 | 59 | 26 | 26 | 60 | 84 | 5 | 5 | 27 |
. | . | Scenario 1 . | Scenario 2 . | Scenario 3 . | Scenario 4 . | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . | WQI . | F1 . | F2 . | F3 . |
1 | TI001 | 58 | 26 | 26 | 63 | 62 | 26 | 26 | 54 | 68 | 26 | 26 | 42 | 91 | 11 | 11 | 6 |
2 | TI006 | 46 | 26 | 26 | 86 | 48 | 26 | 26 | 81 | 52 | 26 | 26 | 74 | 91 | 11 | 11 | 2 |
3 | TI002 | 42 | 32 | 32 | 89 | 44 | 32 | 32 | 86 | 47 | 32 | 32 | 80 | 86 | 11 | 11 | 20 |
4 | TI003 | 46 | 32 | 32 | 82 | 49 | 32 | 32 | 77 | 53 | 32 | 32 | 68 | 91 | 11 | 11 | 4 |
5 | TI004 | 37 | 42 | 42 | 91 | 38 | 42 | 42 | 89 | 41 | 42 | 42 | 84 | 80 | 21 | 21 | 16 |
6 | TI005 | 33 | 47 | 47 | 94 | 34 | 47 | 47 | 93 | 36 | 47 | 47 | 89 | 71 | 32 | 32 | 21 |
7 | TI007 | 38 | 42 | 42 | 89 | 40 | 42 | 42 | 86 | 43 | 42 | 42 | 80 | 77 | 26 | 26 | 16 |
8 | TI008 | 58 | 21 | 21 | 67 | 61 | 21 | 21 | 60 | 67 | 21 | 21 | 48 | 95 | 5 | 5 | 3 |
9 | TI009 | 64 | 26 | 26 | 50 | 69 | 26 | 26 | 38 | 77 | 21 | 21 | 26 | 91 | 11 | 11 | 2 |
10 | SF015 | 42 | 28 | 28 | 92 | 43 | 28 | 28 | 90 | 46 | 28 | 28 | 86 | 89 | 11 | 11 | 12 |
11 | SI021 | ||||||||||||||||
12 | SI022 | 53 | 32 | 32 | 69 | 58 | 26 | 32 | 62 | 64 | 26 | 26 | 51 | 90 | 11 | 11 | 7 |
13 | SI024 | 48 | 26 | 26 | 82 | 51 | 26 | 26 | 77 | 55 | 26 | 26 | 68 | 91 | 5 | 5 | 14 |
14 | SI023 | 37 | 33 | 33 | 98 | 37 | 33 | 33 | 98 | 38 | 33 | 33 | 97 | 89 | 11 | 11 | 9 |
15 | VL033 | 44 | 32 | 32 | 87 | 46 | 32 | 32 | 83 | 51 | 26 | 26 | 76 | 88 | 11 | 11 | 14 |
16 | VL032 | 40 | 32 | 32 | 94 | 41 | 32 | 32 | 92 | 43 | 32 | 32 | 88 | 90 | 11 | 11 | 7 |
17 | VL031 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 44 | 32 | 32 | 85 | 89 | 11 | 11 | 11 |
18 | CA041 | 39 | 26 | 26 | 99 | 39 | 26 | 26 | 98 | 40 | 26 | 26 | 97 | 93 | 5 | 5 | 9 |
19 | CA044 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 46 | 26 | 26 | 85 | 95 | 5 | 5 | 3 |
20 | CA046 | 42 | 26 | 26 | 93 | 43 | 26 | 26 | 91 | 47 | 21 | 21 | 87 | 94 | 5 | 5 | 7 |
21 | CA047 | 52 | 26 | 26 | 75 | 55 | 26 | 26 | 69 | 60 | 26 | 26 | 59 | 91 | 11 | 11 | 6 |
22 | AC001 | 29 | 53 | 53 | 97 | 30 | 53 | 53 | 96 | 31 | 53 | 53 | 94 | 67 | 37 | 37 | 25 |
23 | AV054 | 45 | 32 | 32 | 85 | 47 | 32 | 32 | 81 | 51 | 32 | 32 | 73 | 83 | 16 | 16 | 19 |
24 | AV051 | 48 | 32 | 32 | 79 | 50 | 32 | 32 | 73 | 55 | 32 | 32 | 64 | 84 | 11 | 11 | 24 |
25 | AV052 | 49 | 32 | 32 | 76 | 52 | 32 | 32 | 70 | 57 | 32 | 32 | 59 | 86 | 11 | 11 | 19 |
26 | AV055 | 45 | 37 | 37 | 80 | 47 | 37 | 37 | 75 | 54 | 32 | 32 | 65 | 88 | 11 | 11 | 13 |
27 | AV053 | 48 | 32 | 32 | 79 | 48 | 37 | 32 | 73 | 55 | 32 | 32 | 63 | 83 | 16 | 16 | 19 |
28 | QU061 | 51 | 37 | 37 | 67 | 54 | 37 | 37 | 60 | 62 | 32 | 32 | 48 | 88 | 11 | 11 | 14 |
29 | QU062 | 52 | 26 | 26 | 75 | 55 | 26 | 26 | 68 | 63 | 21 | 21 | 57 | 85 | 5 | 5 | 25 |
30 | QU063 | 58 | 26 | 26 | 62 | 62 | 26 | 26 | 55 | 70 | 21 | 21 | 42 | 94 | 5 | 5 | 7 |
31 | BZ078 | 27 | 56 | 56 | 98 | 27 | 56 | 56 | 98 | 28 | 56 | 56 | 97 | 66 | 31 | 31 | 39 |
32 | BZ077 | 32 | 50 | 50 | 93 | 33 | 50 | 50 | 91 | 38 | 44 | 44 | 88 | 78 | 19 | 19 | 28 |
33 | BZ080 | 43 | 38 | 38 | 83 | 45 | 38 | 38 | 79 | 49 | 38 | 38 | 71 | 85 | 13 | 13 | 19 |
34 | EN-adic | 48 | 38 | 38 | 72 | 50 | 38 | 38 | 68 | 59 | 31 | 31 | 57 | 87 | 13 | 13 | 15 |
35 | EN081 | 53 | 37 | 37 | 63 | 55 | 37 | 37 | 57 | 63 | 32 | 32 | 46 | 85 | 16 | 16 | 14 |
36 | EN082 | 57 | 32 | 32 | 59 | 60 | 32 | 32 | 54 | 64 | 32 | 32 | 43 | 85 | 16 | 16 | 14 |
37 | EN083 | 37 | 37 | 37 | 95 | 38 | 37 | 37 | 94 | 40 | 37 | 37 | 91 | 83 | 16 | 16 | 19 |
38 | EN084 | 52 | 32 | 32 | 71 | 55 | 32 | 32 | 63 | 63 | 26 | 26 | 52 | 93 | 5 | 5 | 9 |
39 | BS092 | 41 | 32 | 32 | 92 | 42 | 32 | 32 | 90 | 44 | 32 | 32 | 86 | 89 | 11 | 11 | 11 |
40 | BS095 | 29 | 53 | 53 | 98 | 29 | 53 | 53 | 97 | 30 | 53 | 53 | 96 | 67 | 32 | 32 | 36 |
41 | BS091 | 42 | 32 | 32 | 89 | 42 | 37 | 32 | 86 | 47 | 32 | 32 | 80 | 86 | 11 | 11 | 20 |
42 | BS094 | 56 | 37 | 37 | 57 | 59 | 37 | 37 | 49 | 64 | 37 | 37 | 35 | 86 | 16 | 16 | 7 |
43 | BS093 | 51 | 26 | 26 | 77 | 54 | 26 | 26 | 71 | 59 | 26 | 26 | 60 | 84 | 5 | 5 | 27 |
Improving bacteriological quality would require investments in sewage transport and treatment, which would also reduce total phosphorus and nitrate levels, consequently lowering chlorophyll ‘a’ and microcystin concentrations included in the WQI calculation. However, the estimated decreases in these parameters need validation with new data from the water quality program of the southern coastal strip of the Río de la Plata.
The current water quality monitoring program, along with the implementation of a WQI, provides stakeholders with clear and accessible information. The findings highlight a significant deterioration in water quality along the coastal area of the Río de la Plata, prompting a strong recommendation to expand the number and capacity of sewage treatment plants, as the existing infrastructure is inadequate. Additionally, it is crucial to enhance the coverage of the sewage network in urban areas.
In this context, it is noteworthy that during 2024, the government planned to improve the sewage network and effluent treatment systems through the implementation of the ‘Riachuelo System’ in Buenos Aires City and Greater Buenos Aires (extending to Berazategui) (AYSA 2024). If successfully executed, this initiative could lead to scenarios 2 or 3, underscoring the importance of continued monitoring in this region to assess the effectiveness of these structural measures and their impact on water quality.
Conversely, in the southern region (from Berazategui and beyond), no initiatives to improve the sewage network or effluent treatment are currently known. It is therefore strongly recommended that this issue be prioritized on the authorities' agenda and allocated sufficient budgetary resources.
The WQI can be a tool for generating a more horizontal understanding of water quality, for both experts and the general public, but also as a strategic tool for directing necessary works according to the simulation of scenarios where certain parameters are improved and thus how this is reflected in changes in water quality.
Matanza-Riachuelo basin
The Matanza-Riachuelo basin is the emblematic example of an urban contaminated basin. Its main collector, the Matanza-Riachuelo River, receives, along 64 km, daily non-treated or deficiently treated domestic, sewage and industrial effluents. Two-thirds of its mean flow corresponds to them (ACUMAR 2024a).
It is the most challenging system for environmental management in Argentina. Within its 2,047.86 km2, 4,703,058 people reside, representing approximately 10% of the country's population. It is the most industrialized and urbanized area of the country, where three jurisdictions have to articulate: the Federal Government, Buenos Aires province and the City of Buenos Aires. Because of the concerning environmental situation of this basin, the Matanza-Riachuelo Basin Authority (ACUMAR) was established in 2006 through Law No. 26168. This organization is an autonomous, self-sufficient and interjurisdictional entity that coordinates efforts with the three governments that have jurisdiction over the basin's territory.
In 2008, the Supreme Court of Justice of the Nation (SCJN) ordered ACUMAR to implement a cleanup plan in response to the judicial case known as the ‘Mendoza Case’ (CSJN 2008), a claim filed in 2004 by a group of residents. This plan, called the Comprehensive Environmental Cleanup Plan (PISA), is the document that guides the work of ACUMAR, enabling coordinated action among the various stakeholders working to resolve the issues in the basin. It is organized by different lines of action with specific projects, aiming to ensure the improvement of the inhabitants' quality of life, the restoration of the environment in all its components (water, air and soil) and the prevention of damage with a sufficient and reasonable degree of prediction (ACUMAR 2024b).
The implementation of the cleanup plan can be followed by the PISA Monitor, which centralizes information about the advances in each axis of the plan, making available to the public the main works and actions, the results of the Indicator System and the necessary budgetary investment for its fulfillment.
The Indicator System, ruled by ACUMAR Resolution 209/2023, measures the progress in the cleanup of the basin. This regulatory instrument includes a list of indicators and publication schedule and methodological sheets.
The presented information is organized around 10 axes in order to facilitate communication of the progress in its compliance: industrial control, housing solutions, environmental quality, drinking water and sewage treatment, landfill treatment, water management, cleaning of margins and towpaths, environmental health, public information and context indices.
Four indicators have been selected for the environmental quality axes: surface WQI in relation to compliance with Use IV (recreation without direct contact); DO; concentration in surface water; nitrate concentration in groundwater and air quality index. These indicators fulfill the SCJN's ruling (8/7/2008), through Order III – Industrial Pollution, point VIII, that ordered ACUMAR to publicly present information, updated quarterly, on the state of surface and underground water, in addition to the air quality of the basin.
The methodological sheet of Annex III of Resolution 209/2023 (ACUMAR 2023a) presents Indicator N° 12 surface WQI in relation to compliance with Use IV. It contains a short description of the indicator; related mandate; related SDG; relevance for decision-making; category; scope; limitations; formula; units of measurement; description of the variables that make up the indicator; calculation methodology; scale; data source; publication frequency; available series; intra/inter-institutional coordination requirements for data flow; responsible entity; type of results presentation and complementary information.
The indicator shows the status of surface water quality in the Matanza-Riachuelo basin, associated with the compliance of the target values for Use IV derived from ACUMAR Resolution 283/2019. It is based on the application of an internationally recognized index, developed by the CCME. It primarily contributes to the compliance of Mandate III – Industrial Pollution, point VIII (ACUMAR 2023b).
The indicator is relevant for decision-making. It provides a simple measure of surface water quality, easily understandable by the public. Additionally, it allows the evaluation of the degree of compliance with the target values designated by current regulations. Thus, it quickly identifies out-of-range variables and their frequency of occurrence, serving as a tool to analyze trends and highlight specific environmental conditions. It facilitates the assessment of the effectiveness of the application of these regulatory parameters, the execution of programs and/or the implementation of associated public policies. Lastly, it enables the examination of changes over time at each specific point, as well as comparisons between different sites in the same period (ACUMAR 2023a).
The indicator measures the state of water quality for each monitoring station (EM), based on the consideration of 10 parameters regulated for Use IV in Resolution 283/2019, providing a synthetic result that reflects water quality based on compliance with the concentrations for that Use. The measurement period is from June of one year to May of the next, to include all seasonal variability in the calculation.
The methodological sheet also presents the limitations of the indicator: It does not allow direct cause-effect interpretations. These are complex and difficult because water bodies are dynamic and living systems, where different variables fluctuate, not only seasonally, but even daily, due to both natural and anthropogenic causes. Additionally, given the dynamic nature of a lotic system, it is not possible to extrapolate the characteristics of one site to another section or watercourse. Furthermore, the information used to calculate this index is based on manual monitoring that denotes a specific characterization of the moment the sample was taken for that particular site. Finally, the index does not provide compliance or non-compliance rating for Use IV at each EM but integrates the information into a gradual result of surface water quality status by comparing it to the target concentrations established for that Use.
The formula used for the calculation of the surface WQI is presented in Table 1 (Equation (1)) and was described in the WQIs section.
The three factors of the index: Scope (F1), Frequency (F2) and Amplitude (F3) are calculated from the comparison of the measured information with the target concentrations of the 10 parameters regulated for Use IV, as established in Resolution 283/2019 (ACUMAR 2019; see Table 6).
Parameters regulated for Use IV, as established in Resolution 283/2019 (ACUMAR 2019)
pH | 6 < pH < 9 |
Temperature (°C) | <35 °C |
Dissolved oxygen (DO) (mg/L) | >2 mg/L |
Biological oxygen demand (BOD5) (mg/L) | Target value < 15 mg/L |
Total phosphorus (mg/L) | <5 mg/L |
Total sulfides (mg/L) | <1 mg/L |
Detergents (SAAM) (mg/L) | <5 mg/L |
Phenolic substances (mg/L) | <1 mg/L |
Total hydrocarbons (mg/L) | <10 mg/L |
Total cyanides (mg/L) | <0.1 mg/L |
pH | 6 < pH < 9 |
Temperature (°C) | <35 °C |
Dissolved oxygen (DO) (mg/L) | >2 mg/L |
Biological oxygen demand (BOD5) (mg/L) | Target value < 15 mg/L |
Total phosphorus (mg/L) | <5 mg/L |
Total sulfides (mg/L) | <1 mg/L |
Detergents (SAAM) (mg/L) | <5 mg/L |
Phenolic substances (mg/L) | <1 mg/L |
Total hydrocarbons (mg/L) | <10 mg/L |
Total cyanides (mg/L) | <0.1 mg/L |
Results of the evaluation of the surface water quality in relation to compliance with Use IV (May 2022–2023)
Station number . | Location . | Number of samples . | F1 . | F2 . | F3 . | WQI . |
---|---|---|---|---|---|---|
39 | Cebey Creek (Upper basin) | 5 | 22 | 6 | 4 | 87 |
41 | Cebey Creek (Lower basin) | 5 | 56 | 34 | 72 | 44 |
42 | Rodriguez Creek (Upper basin) | 5 | 22 | 24 | 29 | 75 |
68 | Rodriguez Creek (Lower basin) | 5 | 12 | 4 | 0 | 92 |
62 | Cañuelas Creek | 5 | 14 | 12 | 0 | 89 |
33 | Navarrete Creek | 5 | 0 | 0 | 0 | 100 |
1 | Matanza River (Upper basin) | 5 | 29 | 17 | 19 | 78 |
4 | Chacon Creek (Lower basin) | 5 | 29 | 10 | 14 | 81 |
37 | Morales Creek | 5 | 12 | 7 | 2 | 92 |
47 | Cañada Pantanosa Creek | 5 | 12 | 4 | 0 | 92 |
48 | Barreiro Creek | 5 | 11 | 3 | 4 | 93 |
8 | Morales Creek (Lower basin) | 5 | 0 | 0 | 0 | 100 |
6 | Matanza River (Middle basin) | 5 | 33 | 32 | 19 | 71 |
10 | Aguirre Creek | 5 | 14 | 9 | 4 | 90 |
76 | Susana Creek (Upper basin) | 5 | 11 | 3 | 3 | 93 |
77 | Dupuy Creek | 5 | 20 | 11 | 6 | 86 |
11 | Don Mario Creek (Lower basin) | 5 | 20 | 12 | 16 | 84 |
63 | Ortega Creek | 5 | 30 | 20 | 40 | 69 |
72 | Discharge of Rocha lagoon to Matanza River | 5 | 10 | 3 | 1 | 94 |
12 | Matanza River (Richieri Highway) | 5 | 33 | 19 | 25 | 74 |
14 | Santa Catalina Creek | 5 | 20 | 15 | 37 | 74 |
15 | Matanza River (Lower basin) | 5 | 20 | 21 | 16 | 81 |
13 | Old bed of Matanza River | 5 | 20 | 10 | 13 | 85 |
16 | Del Rey Creek | 6 | 20 | 19 | 22 | 80 |
17 | Riachuelo (Pte. La Noria) | 5 | 20 | 17 | 4 | 85 |
19 | Cildañez Creek | 5 | 20 | 23 | 8 | 82 |
21 | Pluvial discharge to Riachuelo | 5 | 20 | 25 | 29 | 75 |
20 | Pluvial discharge to Riachuelo | 5 | 20 | 17 | 25 | 79 |
23 | Erezcano conduct | 5 | 30 | 31 | 22 | 72 |
22 | Pluvial discharge of Millan canal to Riachuelo | 5 | 20 | 18 | 16 | 82 |
24 | Riachuelo (Uriburu bridge) | 6 | 30 | 26 | 19 | 74 |
25 | Teuco Creek | 4 | 33 | 31 | 25 | 70 |
30 | Riachuelo (Old Pueyrredon bridge) | 5 | 30 | 28 | 14 | 75 |
Station number . | Location . | Number of samples . | F1 . | F2 . | F3 . | WQI . |
---|---|---|---|---|---|---|
39 | Cebey Creek (Upper basin) | 5 | 22 | 6 | 4 | 87 |
41 | Cebey Creek (Lower basin) | 5 | 56 | 34 | 72 | 44 |
42 | Rodriguez Creek (Upper basin) | 5 | 22 | 24 | 29 | 75 |
68 | Rodriguez Creek (Lower basin) | 5 | 12 | 4 | 0 | 92 |
62 | Cañuelas Creek | 5 | 14 | 12 | 0 | 89 |
33 | Navarrete Creek | 5 | 0 | 0 | 0 | 100 |
1 | Matanza River (Upper basin) | 5 | 29 | 17 | 19 | 78 |
4 | Chacon Creek (Lower basin) | 5 | 29 | 10 | 14 | 81 |
37 | Morales Creek | 5 | 12 | 7 | 2 | 92 |
47 | Cañada Pantanosa Creek | 5 | 12 | 4 | 0 | 92 |
48 | Barreiro Creek | 5 | 11 | 3 | 4 | 93 |
8 | Morales Creek (Lower basin) | 5 | 0 | 0 | 0 | 100 |
6 | Matanza River (Middle basin) | 5 | 33 | 32 | 19 | 71 |
10 | Aguirre Creek | 5 | 14 | 9 | 4 | 90 |
76 | Susana Creek (Upper basin) | 5 | 11 | 3 | 3 | 93 |
77 | Dupuy Creek | 5 | 20 | 11 | 6 | 86 |
11 | Don Mario Creek (Lower basin) | 5 | 20 | 12 | 16 | 84 |
63 | Ortega Creek | 5 | 30 | 20 | 40 | 69 |
72 | Discharge of Rocha lagoon to Matanza River | 5 | 10 | 3 | 1 | 94 |
12 | Matanza River (Richieri Highway) | 5 | 33 | 19 | 25 | 74 |
14 | Santa Catalina Creek | 5 | 20 | 15 | 37 | 74 |
15 | Matanza River (Lower basin) | 5 | 20 | 21 | 16 | 81 |
13 | Old bed of Matanza River | 5 | 20 | 10 | 13 | 85 |
16 | Del Rey Creek | 6 | 20 | 19 | 22 | 80 |
17 | Riachuelo (Pte. La Noria) | 5 | 20 | 17 | 4 | 85 |
19 | Cildañez Creek | 5 | 20 | 23 | 8 | 82 |
21 | Pluvial discharge to Riachuelo | 5 | 20 | 25 | 29 | 75 |
20 | Pluvial discharge to Riachuelo | 5 | 20 | 17 | 25 | 79 |
23 | Erezcano conduct | 5 | 30 | 31 | 22 | 72 |
22 | Pluvial discharge of Millan canal to Riachuelo | 5 | 20 | 18 | 16 | 82 |
24 | Riachuelo (Uriburu bridge) | 6 | 30 | 26 | 19 | 74 |
25 | Teuco Creek | 4 | 33 | 31 | 25 | 70 |
30 | Riachuelo (Old Pueyrredon bridge) | 5 | 30 | 28 | 14 | 75 |
The spatial unit or scale used by the indicator is the manual point monitoring station (EM) of the ACUMAR Surface Water and Sediment Monitoring Network, distributed in the upper, middle, and lower basins. The Environmental Quality Coordination of ACUMAR provides the data series for the calculation of the indicator, which is published annually since 2010.
In order to do this in a sustainable manner, the following requirements must be fulfilled:
1. The development of systematic sampling campaigns and the determination of the parameters defined for Use IV.
2. The obtained information must be processed and validated beforehand to perform the necessary calculations for the preparation of the WQI based on that presented in Equation (1) of Table 1.
3. At least four campaigns per defined period are required, with information on the 10 parameters related to Use IV in each sampling. However, the WQI can be calculated with a minimum of three campaigns per period and/or seven parameters per sampling, provided that any deviation from the optimal situation is clarified. With values lower than those expressed above, the respective calculation cannot be presented.
The responsible entity of the evaluation of the indicator is the Environmental Quality Coordination of ACUMAR.
Manual monitoring stations (MS) are presented in a map of the Matanza-Riachuelo basin, identifying the sub-basins into which it is divided. Water quality is represented by a chromatic scale corresponding to the five intervals of surface water quality, as indicated previously, for the last sampled period (Figure 8).
Nine percent of the monitored stations during this period had excellent water quality; 51.6% were good; 36.4% were fair and 3% (one station) were very poor. Main excursions from Use IV objectives come from dissolved oxygen, biochemical oxygen demand and sulfur, the latter one most frequently in the lower basin; showing the influence of organic matter coming from anthropogenic sources (insufficiently treated or non-treated sewage and industrial effluents). Occasionally, phenolic substances and TP, as seen in Cebey Creek (station 41), exceeded their target values, significantly decreasing water quality by 43%.
These results show an improvement of water quality for Use IV, regarding the last period evaluated by ACUMAR (2021–2022), giving credit to the impact of the actions implemented under the PISA plan of the Matanza-Riachuelo basin since 2010.
CONCLUSIONS
Over the past 30 years, WQIs have been incorporated as environmental indicators into the decision-making process within the framework of integrated water resources management in Argentina. They are not only used as tools for analyzing water quality, but also as part of a control panel of indicators that facilitate the planning of new infrastructure projects focused on sanitation; institutional control to meet legally mandated remediation objectives and communication with stakeholders.
AUTHOR CONTRIBUTIONS
D.S.C. conceptualized the study, wrote, reviewed, and edited the article. K.Q., P.M. and F.R. present the Río de la Plata case study.
ETHICS STATEMENT
The authors adhere to the highest ethical standards in relation to research that involves human participants.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.