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The Chillán River in Central Chile plays a fundamental role in local society, as a source of irrigation and drinking water, and as a sink for urban wastewater. In order to characterize the spatial and temporal variability of surface water quality in the watershed, a Water Quality Index (WQI) was calculated from nine physicochemical parameters, peri...
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Context 1
... Chillán River Watershed ( Figure 1) is located in the Biobıo Region, Central Chile (71 ◦ 00–72 ◦ 30 W, 36 ◦ 30–37 ◦ 00 S). It occupies a total surface area of 757 km 2 . Elevation ranges from 3200 m.a.s.l. in the Andes to 75 m.a.s.l. in the Central Valley. The total length of the Chillán River is 105 km. The climate in the area is Mediterranean with a dry and warm summer period and a cold and humid winter period, both of approximately equal length. In the lower part of the watershed, the mean maximum temperature during January, the hottest month, is 28.8 ◦ C. The mean minimum temperature for July, the coldest month, is 3.5 ◦ C. Average annual precipitation is 1624 mm. Most rainfall occurs between May and September. Mean annual river flow for the Chillán River is 22.9 m 3 s − 1 . Winter discharge can rise well above 100.0 m 3 s − 1 , while summer discharges as low as 1.0 m 3 s − 1 have been recorded. The Andean part of the watershed is mainly covered by native forests, while the land use in the Central Valley is dominated by agriculture (sugar beet and cereals). The City of Chillán (162.000 inhabitants) functions as a service and distribution center for the agro-business. No important industrial activity takes place within the watershed. To characterize water quality and its’ spatial variability along the river network, locations for 18 sampling stations were carefully selected. From these, eight sites were defined on the main course, while the remaining 10 sites were located on tributaries (Figure 1). The first sampling station for the Chillán River (E1) was located at the point where the river leaves the Andes Mountain Range and enters the Central Valley (76.6 km – measured along the river starting from the outlet). The river is expected to have good water quality conditions here, as human activities upstream of this point are limited. Station E2 (57.1 km) is located directly downstream of the small urban center of Pinto, while station E3 (48.0 km) reflects the water quality near the intake of the drinking water supply for the City of Chillán. Station E4 (34.7 km) and E5 (31.8 km) are upstream and south of the city centre, respectively. Station E6 (26.6 km) is 3.6 km upstream of the Las Toscas Tributary, which receives the city’s urban wastewater only a short distance ( ca . 500 m) before it enters the Chillán River. Station E7 (16.8 km) is 6.2 km downstream of the confluence of the Las Toscas Tributary with the Chillán River, and 1.1 km downstream of the Quilmo River, the most important tributary. Station E8 (3.2 km) indicates conditions in the Chillán River near the outlet of the watershed. For the tributaries in the Central Valley, sampling stations were assigned to their middle reaches (T1-T2-T3-T4-T5-T8) and to a point near their confluence with the Chillán River (T6-T7-T9-T10). The station on the Las Toscas River (T10) is located just below the waste water discharge. The tributaries in the Andean part were not considered in this study, as their water quality conditions were supposed to be reflected by the water quality in the main river at station E1. Temporal variability of water quality was evaluated by realizing sampling campaigns at a two-months interval, starting in January 2000 and ending in November 2000. March, at the end of the Austral summer, typically represents the lowest discharge rates, while frequent rainfall (autumn and winter) and snow-melt (spring) lead to much higher discharges between April–May and ...
Context 2
... Chillán River Watershed ( Figure 1) is located in the Biobıo Region, Central Chile (71 ◦ 00–72 ◦ 30 W, 36 ◦ 30–37 ◦ 00 S). It occupies a total surface area of 757 km 2 . Elevation ranges from 3200 m.a.s.l. in the Andes to 75 m.a.s.l. in the Central Valley. The total length of the Chillán River is 105 km. The climate in the area is Mediterranean with a dry and warm summer period and a cold and humid winter period, both of approximately equal length. In the lower part of the watershed, the mean maximum temperature during January, the hottest month, is 28.8 ◦ C. The mean minimum temperature for July, the coldest month, is 3.5 ◦ C. Average annual precipitation is 1624 mm. Most rainfall occurs between May and September. Mean annual river flow for the Chillán River is 22.9 m 3 s − 1 . Winter discharge can rise well above 100.0 m 3 s − 1 , while summer discharges as low as 1.0 m 3 s − 1 have been recorded. The Andean part of the watershed is mainly covered by native forests, while the land use in the Central Valley is dominated by agriculture (sugar beet and cereals). The City of Chillán (162.000 inhabitants) functions as a service and distribution center for the agro-business. No important industrial activity takes place within the watershed. To characterize water quality and its’ spatial variability along the river network, locations for 18 sampling stations were carefully selected. From these, eight sites were defined on the main course, while the remaining 10 sites were located on tributaries (Figure 1). The first sampling station for the Chillán River (E1) was located at the point where the river leaves the Andes Mountain Range and enters the Central Valley (76.6 km – measured along the river starting from the outlet). The river is expected to have good water quality conditions here, as human activities upstream of this point are limited. Station E2 (57.1 km) is located directly downstream of the small urban center of Pinto, while station E3 (48.0 km) reflects the water quality near the intake of the drinking water supply for the City of Chillán. Station E4 (34.7 km) and E5 (31.8 km) are upstream and south of the city centre, respectively. Station E6 (26.6 km) is 3.6 km upstream of the Las Toscas Tributary, which receives the city’s urban wastewater only a short distance ( ca . 500 m) before it enters the Chillán River. Station E7 (16.8 km) is 6.2 km downstream of the confluence of the Las Toscas Tributary with the Chillán River, and 1.1 km downstream of the Quilmo River, the most important tributary. Station E8 (3.2 km) indicates conditions in the Chillán River near the outlet of the watershed. For the tributaries in the Central Valley, sampling stations were assigned to their middle reaches (T1-T2-T3-T4-T5-T8) and to a point near their confluence with the Chillán River (T6-T7-T9-T10). The station on the Las Toscas River (T10) is located just below the waste water discharge. The tributaries in the Andean part were not considered in this study, as their water quality conditions were supposed to be reflected by the water quality in the main river at station E1. Temporal variability of water quality was evaluated by realizing sampling campaigns at a two-months interval, starting in January 2000 and ending in November 2000. March, at the end of the Austral summer, typically represents the lowest discharge rates, while frequent rainfall (autumn and winter) and snow-melt (spring) lead to much higher discharges between April–May and ...
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Citations
... The WQI was firstly proposed by Horton in 1965(Horton, 1965 and then modified by Brown and co-workers in 1970 (Brown et al., 1970). Since then, various approaches to assess the surface water quality are being proposed by several authors and widely used in the water quality assessment studies (Debels et al., 2005;Lumb et al., 2011;Sutadian et al., 2016;Ibrahim, 2019). Most of the WQI model components have been developed based on expert views and this approach overcomes the traditional method, which compares the individual parameter with guideline permissible limit values (Bora;Goswami, 2017). ...
Wastewater reuse is a useful tool for minimizing the amount of wastewater discharged into the environment. However, it is associated with threats to the environment and public health; consequently, effluent quality assessment is essential prior to reuse. The aim of this study is to assess the physicochemical and microbiological quality of treated wastewater from Cap Falcon wastewater treatment plant for reuse in irrigation. The suitability of treated wastewater from Cap Falcon plant for irrigation was assessed based on its composition and Algerian irrigation water quality standards. The average biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) values decrease from 316 mg/L to 21 mg/L with a mean removal efficiency of 93.0% and from 659 to 40 mg/L with removal efficiency of 93.7% respectively. For total suspended solids (TSS), the concentration at the inlet of the treatment plant is very high but reduces greatly after biological treatment with a removal efficiency over 94.5%. The physico-chemical analyses of treated wastewater samples from the storage reservoir indicated that pH varied from 6.81 to 8.20 with an average value of 7.43, which is slightly alkaline in nature. Electrical conductivity is one of the criteria used to evaluate the suitability of water for agricultural use; the average value was found less than 1500 μS/cm, indicating that the treated wastewater is considered as suitable for irrigation use. On the other hand, microbiological analyses indicate that faecal coliforms are high compared with Algerian water quality reuse standards. Furthermore, the overall quality of tertiary treated wastewater was analyzed by calculating the water quality index. The calculated index for the physicochemical and microbiological parameters was 96, which corresponds to a water quality type “very poor” signifying that this effluent can only be used for restricted irrigation practices.
... This study has employed the WQI approach considering several reasons that make the technique the best (Chandra et al. 2015;Zakir et al. 2020). It can give an overall high quality of water assessment as it takes into consideration the various parameters like pH, biological oxygen demand, chemical oxygen demand, total dissolved solids, total suspended solids, sulfate, nitrate, dissolved oxygen, calcium, magnesium, and alkalinity (Debels et al. 2005) that are within single measurements rather than looking at them on an individual basis. Secondly, it enables water classi cation into various categories. ...
... The selection of WQI model's parameters was generally chosen based on the data's availability, expert knowledge, and the environmental importance of a particular water quality indicator. According to (Debels et al. 2005), numerous WQI models often used essential water quality parameters only because there was not enough measured data for other parameters. Several researchers adjusted the parameter list for the model based on the data availability and accessibility factor. ...
The objective of the research was to assess the state of the Sharda Canal, a critical irrigation and household water source in Uttar Pradesh, India. More specifically, the analysis applied the Water Quality Index methodology. A total of five survey sites were selected along the 258.80 km of the Sharda Kheri Branch, chosen based on the land use type and potential source of pollution. The analysis examined chemical concentration and dissolved solids in terms of pH, DO, COD, BOD, Nitrates, Sulphates, TDS, TSS, hardness, alkalinity, calcium, and magnesium as the most relevant parameters. WQI was calculated using the weighted arithmetic index method. The results show a significant difference in the pollutant load between the locations. The water quality index at the Sharda Barrage in Lakhimpur Kheri was 110.60, and at the Bakshi ka talab distributary in Lucknow, the water quality index was 124.92. The obtained high values of TDS, COD, sulfates, and nitrates reflect the probable existence of contaminants that could cause catastrophic impacts on the regional water quality and aquatic ecology. In conclusion, the results of this evaluation draw clear lines and demonstrate a genuine integrated action is warranted to curb the quick decay of water quality in the Sharda Canal. As a result, the WQI, an integrated physicochemical appraisal tool, has been used to achieve a concise understanding of the water quality variables at work in the Sharda Canal. Possible measures to improve the situation may involve expanding industrial and agricultural regulations and practices, enhancing treatment plants’ efficiency, raising public awareness, and decreasing pollution sources.
... WQI is considered the most efficient way to approach the water quality status. It is one of the most widely used tools for assessing surface as well as groundwater and plays a crucial part in managing water resources (Debels et al., 2005;Lumb et al., 2011;Mohebbi et al., 2013;Sutadian et al., 2016). ...
... The idea of using indices for the representation of water quality standards was initially introduced by Horton using 10 variables in 1965 and later advanced by Brown et al., (1970).Many authors have formulated various techniques for calculating WQI (Debels et al., 2005, Tsegaye et al., 2006. Several methods formulated worldwide are the US National Sanitation Foundation Water Quality Index (NSFWQI) (Brown et al., 1970), Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI), British Columbia Water Quality Index (BCWQI), Oregon Water Quality Index (OWQI) (Debels et al., 2005), etc. ...
... The idea of using indices for the representation of water quality standards was initially introduced by Horton using 10 variables in 1965 and later advanced by Brown et al., (1970).Many authors have formulated various techniques for calculating WQI (Debels et al., 2005, Tsegaye et al., 2006. Several methods formulated worldwide are the US National Sanitation Foundation Water Quality Index (NSFWQI) (Brown et al., 1970), Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI), British Columbia Water Quality Index (BCWQI), Oregon Water Quality Index (OWQI) (Debels et al., 2005), etc. Workers like Debels et al., (2005), Wu et al., (2018), Sener et al., (2017), and Ewaid (2020), etc have evaluated and developed WQI for different rivers worldwide. ...
... By effectively assessing, predicting, and controlling water pollution, we can safeguard water resources and also lay the foundations for their sustainable use [29]. In developed countries, nutrient enrichment and eutrophication of water resources are issues that have to face as a challenge [30,31]. Meanwhile, developing countries contend with a set of problems, where they seek to balance the preservation of water quality with the current efforts to enhance water supply and santitation insfraestructure [29,31,32]. ...
... In developed countries, nutrient enrichment and eutrophication of water resources are issues that have to face as a challenge [30,31]. Meanwhile, developing countries contend with a set of problems, where they seek to balance the preservation of water quality with the current efforts to enhance water supply and santitation insfraestructure [29,31,32]. ...
... To the date, more than 35 WQI models were introduced, each one of them have been developed with variations in model structure, the parameters used and their weight, the methods used for sub-indexing and aggregations [31,[38][39][40]. Though, WQI have been applied to all major types of waterbodies, where 82 % of applications have been to assess river water quality. ...
Water is a resource that influences sustainable development in different ways in social, economic, and environmental aspects, being the Andes the major provider of this resource. However, they have been affected mainly by anthropogenic activities due to the proximity of settlements in the watersheds, so they tend to have more significant contamination, and their evaluation is essential to mitigate problems for those who consume them. However, despite being a fundamental resource and one of the main contributors of water, it is not so studied, so the present study aims to determine the studies based on the water quality of the high mountain rivers of the Andes by using a PRISMA methodology with the scoping review extension, based on search techniques, inclusion and exclusion criteria, and monitoring tables, in order to maintain a line of research attached to the objective of the study. After using the methodology, ten articles were obtained, which were analyzed after a bibliometric analysis to determine features of interest, such as countries in which the studies were carried out, years of publication, methodologies used, and authors' consensus. High Andean rivers' importance, the need for more studies within these areas, and the lack of suitable indexes for these unique ecosystems are highlighted.
... The water quality index (WQI) is an important and valuable criterion for determining the quality of drinking water, which, taking into account various parameters, determines whether the quality of this water sample is suitable for drinking or not. Patrick Debels and his research team undertook a comprehensive analysis of water quality in a basin, utilizing the Water Quality Index (WQI) and examining nine hydrochemical parameters (Debels et al. 2005). Expanding upon this foundational work, CR Ramakrishnaiah et al. conducted a further investigation (2009), employing a more extensive set of 12 physicochemical parameters to determine the WQI. ...
Population growth and escalating water demands in arid regions have led to a surge in deep well water extraction, adversely affecting water quality. The Water Quality Index (WQI) emerges as a crucial tool for systematically assessing and monitoring the impact of these trends. By integrating various physicochemical parameters, the WQI provides a concise and comprehensive measure to evaluate the overall health and sustainability of water resources in the region. This study employed the Water Quality Index (WQI) to assess the water quality status of 37 wells in the Abarkuh Plain in Yazd province, Iran. Spatial distribution maps for 10 key water quality parameters were generated using the Inverse Distance Weighted interpolation method (IDW) in the ArcGIS tool. A Pearson’s test was conducted to examine the correlations among the different variables. The major findings of this study indicated that, among anions and cations, chloride ion (Cl⁻) and sodium ion (Na⁺) were the most prevalent. Water Quality Index (WQI) classified 70% of samples as good, 11% as poor, 14% as very poor, and 5% as unsafe. In this research, a new index named IWQI is introduced which is enhanced through the application of the entropy method. The entropy method utilizes data dispersion for parameter weighting, assigning a singular rank to each parameter.. After applying this method, the revised classification showed 68% as good, 5% as poor, 8% as very poor, and 19% as unsafe. Aligned with the Piper diagram, the facies of the water in terms of the dominant anions are sulfate and chloride, and also the facies of the water in terms of the dominant cations are calcium, and magnesium. Therefore, this diagram showed that the composition of groundwater in the Abarkuh plain was affected by the interaction of water and rock. This research underscores the value of spatial distribution maps of hydrochemical parameters and IWQI for effective decision-making in water resources management by local and international authorities.
... Indicators of water pollution, such as water quality index (WQI), organic pollution index (OPI) and Carlson trophic state index (CTSI) were estimated in accordance with Debels et al. (2005), Kannel et al. (2007), and Sánchez et al. (2007) methods. Two steps were followed for its calculation. ...
... With the help of appropriate weighting factors that consider how important each variable is as a gauge of water quality for aquatic life, sub-indices were averaged to get a WQI value (Sarkar and Abbasi, 2006). In the case of our study and in keeping with the literature, our study closely utilized relative weights and normalization factors to calculate this index using the following parameters: temperature, pH, electrical conductivity (EC), dissolved oxygen (DO), turbidity (Tur), SRSi, SRP, ammonium, and nitrite values (Pesce and Wunderlin, 2000;Cude, 2001;Jonnalagadda and Mhere, 2001;Debels et al., 2005;Kannel et al., 2007;Sánchez et al., 2007). The equation for subjective WQI Rodriguez de Bassoon Equations 2 and 3 (Pesce and Wunderlin, 2000) is: ...
In Africa, cage aquaculture has been growing due to its potential to address
food insecurity concerns, provide livelihoods, and contribute to local economies.
However, there is a need for continued research on the sustainability and
potential ecological eects of cage aquaculture in African lakes and reservoirs.
Even with an adequate amount of water, lakes and reservoirs cannot provide
ecosystem services if their water quality is not properly managed. The current
study on Lake Kivu, DRC focuses on understanding the eects of tilapia
cage aquaculture on selected water quality physico-chemical parameters in
the Bukavu sub-basin, DRC. The research was conducted in both caged
and uncaged sampling stations, on the spatial and temporal scale from April
to September 2023 at three bays serving as sampling stations: two caged
(Ndendere, Honga) and one non-caged (Nyofu). Some physico-chemical
parameters were measured in situ, whereas chlorophyll a and nutrients analysis
were performed at the Institut Supérieur Pédagogique (I.S.P) laboratory in
Bukavu. The parameters were used to calculate three indices water quality
indices: the water quality index (WQI) to classify the water quality at the
stations, the organic pollution index (OPI) to determine the level of organic
pollution, the Carlson’s Trophic Status Index (CTSI) to classify the trophic state
of the stations. Chlorophyll a concentration was a measure of algal biomass.
All physico-chemical parameters, apart from DO, ammonium and temperature
showed no significant dierences among stations and depths. Interaction
between stations and between seasons was only observed on turbidity. The WQI
for all the sampling stations ranged from medium to good quality (51–90). The
OPI for all stations showed minimal level of pollution (4.6–5.0) hence lake’s water
still organically unpolluted. CTSI results indicated the sampling stations are in
a eutrophic state (50 to 70). Fish cage aquaculture does not yet pose harm the water quality of the two Lake Kivu stations under consideration, according
to the study’s findings. However with the anticipated growth of cage fish
farming activities to meet the rising fish demand, continuous monitoring of water
quality in the Lake should be done to inform management decisions and for
sustainable aquaculture.
... Water quality evaluation is usually based on the comparison of physical, chemical, and biological parameters with established water quality criteria (Simeonov et al. 2003). There are many methods for evaluating water quality status, including (1) using the most sensitive water quality parameters to evaluate the water quality status (Debels et al. 2005), (2) evaluating the water quality status based on the nutrient status calculated by the nitrogen and phosphorus concentrations (Wu et al. 2018), and (3) considering all water quality parameters for the comprehensive evaluation of the water quality status, namely, the water quality index (WQI) method (Bordalo et al. 2006). The first two methods often fail to fully consider all water quality parameters, which is slightly one-sided. ...
The water quality index (WQI) is an important tool for evaluating the water quality status of lakes. In this study, we used the WQI to evaluate the spatial water quality characteristics of Dianchi Lake. However, the WQI calculation is time-consuming, and machine learning models exhibit significant advantages in terms of timeliness and nonlinear data fitting. We used a machine learning model with optimized parameters to predict the WQI, and the light gradient boosting machine achieved good predictive performance. The machine learning model trained based on the entire Dianchi Lake water quality data achieved coefficient of determination (R2), mean square error, and mean absolute error values of 0.989, 0.228, and 0.298, respectively. In addition, we used the Shapley additive explanations (SHAP) method to interpret and analyse the machine learning model and identified the main water quality parameter that affects the WQI of Dianchi Lake as NH4+-N. Within the entire range of Dianchi Lake, the SHAP values of NH4+-N varied from −9 to 3. Thus, in future water environmental governance, it is necessary to focus on NH4+-N changes. These results can provide a reference for the treatment of lake water environments.
... Indicators of water pollution, such as water quality index (WQI), organic pollution index (OPI) and Carlson trophic state index (CTSI) were estimated in accordance with Debels et al. (2005), Kannel et al. (2007), and Sánchez et al. (2007) methods. Two steps were followed for its calculation. ...
... With the help of appropriate weighting factors that consider how important each variable is as a gauge of water quality for aquatic life, sub-indices were averaged to get a WQI value (Sarkar and Abbasi, 2006). In the case of our study and in keeping with the literature, our study closely utilized relative weights and normalization factors to calculate this index using the following parameters: temperature, pH, electrical conductivity (EC), dissolved oxygen (DO), turbidity (Tur), SRSi, SRP, ammonium, and nitrite values (Pesce and Wunderlin, 2000;Cude, 2001;Jonnalagadda and Mhere, 2001;Debels et al., 2005;Kannel et al., 2007;Sánchez et al., 2007). The equation for subjective WQI Rodriguez de Bassoon Equations 2 and 3 (Pesce and Wunderlin, 2000) is: ...
Environmental impacts of tilapia fish cage aquaculture on water physico-chemical parameters of Lake Kivu, Democratic Republic of the Congo
... According to UN-Water (2009), the most important sources of diffuse pollution are non-recycled domestic wastewater from agglomerations, mining and agricultural activities, while urbanization, urban runoff and land use in the catchment area are the point sources of pollution in the aquatic environment. Additionally, more than 80% of wastewater is likely to directly enter the environment without adequate treatments (Debels et al., 2005;UNESCO, 2017). In several developing countries, only a very small fraction (in some cases less than 5%) of domestic and urban wastewaters is treated before discharge into the environment (UN-Water, 2009). ...
... Several approaches have been introduced to assess water quality on the basis of physico-chemical parameters in lakes and rivers (Cude, 2001;Kannel et al., 2007;Pesce & Wunderlin, 2000). One of these is the calculation of the water quality index (WQI), which enables water quality to be expressed in a practical, comprehensible and comparative way (Debels et al., 2005;Jonnalagadda & Mhere, 2001;Sanchez et al., 2007). ...
... The WQI has been calculated as an indicator of the water pollution according to Debels et al. (2005), S anchez et al. (2007), and Kannel et al. (2007). It was calculated in two stages. ...
... The water quality index calculation strategy created in 1965 by Horton is used (Kachroud et al., 2019;Kadam et al., 2019). Researchers nowadays are still using the method with some modifications, which are also accounted for in this work (Debels et al., 2005;Jha et al., 2015;Panneerselvam et al., 2022). The present study is being conducted on Sagar Island. ...
In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium , cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.
