surface water quality
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2022 ◽  
Vol 14 (2) ◽  
pp. 667
Author(s):  
Andrés Estrada-Rivera ◽  
Alfonso Díaz Fonseca ◽  
Samuel Treviño Mora ◽  
Wendy Argelia García Suastegui ◽  
Edith Chávez Bravo ◽  
...  

Population growth, poorly planned industrial development and uncontrolled production processes have left a significant footprint of environmental deterioration in the Alto Atoyac watershed. In this study, we propose using the integrated pollution index (PI) to characterize the temporary variations in surface water quality during the rapid urbanization process in the municipalities of San Martín Texmelucán (SMT) and Tepetitla de Lardizabal (TL), in the states of Puebla and Tlaxcala, between 1985 and 2020. We assessed the correlation between the population growth rate and the water quality parameters according to the Water Quality Index (ICA). The contribution of each polluting substance to the PI was determined. The industry database was created and the increase in population and industry, and their densities, were estimated. The results indicated that the temporal pattern of surface water quality is determined by the level of urbanization. The water integrated pollution index (WPI) increased with the passage of time in all the localities: SLG 0.0 to 25.0; SMTL 25.0 to 29.0; SRT 4.0 to 29.0; VA 6.0 to 30.0; T 3.5 to 24.0 and SMA 4.0 to 27.0 from 2010 to 2020, respectively. The correlation coefficients between the five parameters (BOD5, COD, CF, TU and TSS) in the six localities were positive with the population. The values that showed a higher correlation with the population were: SLG (FC 0.86), SMTL (BOD5 0.61, COD 0.89, TSS 0.64) and SRT (TU 0.83), corresponding to highly polluted localities, which generates complex and severe environmental implications due to the unsustainable management of water resources. Achieving the sustainability of water in the watershed is a challenge that should be shared between society and state. This type of research can be a useful tool in making environmental management decisions.


2022 ◽  
Author(s):  
Pramod Jena ◽  
*Sayed Modinur Rahaman ◽  
Pradeep Kumar DasMohapatra ◽  
Durga Prasad Barik ◽  
Dikshya Surabhi Patra

Abstract A decision tree -based approach is projected to predict surface water quality and is a good tool to assess quality and guarantee property safe use of water for drinking. The most objective of this study is to assess the surface water quality of the Daya watercourse to work out the quality of drinking functions. Samples were collected from designated locations throughout totally different seasons (winter, summer, rainy) over a amount of five years (2016, 2017, 2018, 2019, and 2020). Total dissolved solids, pH, alkalinity, chloride, nitrate, total hardness, calcium, magnesium, iron, fluoride, were all tested as well as total coliform, fecal coliform, and E. coli. The main goal is to use decision tree regression to construct a model to assess and predict water quality changes in the Daya geographic region of Odisha, India, and compare it to statistical methods.


Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 129
Author(s):  
Roxana Zait ◽  
Brindusa Sluser ◽  
Daniela Fighir ◽  
Oana Plavan ◽  
Carmen Teodosiu

The Integrated Water Resources Management regulations aim to ensure a good status of surface water quality and its sustainable use. Water quality monitoring of various water users supports the identification of pollution sources and their environmental impacts. The priority pollutants generated by wastewater discharges from municipal, industrial wastewater treatment plants or agricultural areas are of great interest due to their eco-toxicological effects and bio-accumulative properties. The aim of this study was to monitor the priority organic and inorganic pollutants from the Siret River basin, in Romania, with the purpose of assessing the surface water quality status and evaluating it by the Water Quality Index (WAWQI) method. The monitoring of inorganic priority pollutants (e.g., As, Cd, Hg, Ni, Pb) and organic priority pollutants (e.g., Naphthalene, Anthracene, Phenanthrene, Fluoranthene, Benzo(a)anthracene, Benzo(b)fluoranthene, Benzo(k)fluoranthene, Benzo(a)pyrene, Benzo(ghi)perylene, Indeno(1,2,3-cd)pyrene, α, β, and γ-Hexachlorocyclohexane, and Di-2-ethyl-hexyl-phthalate) was conducted within the Siret River basin, during the period 2015–2020. With this purpose, 21 sampling points (18 river sections and 3 lakes) were considered to assess the water quality. The results of this study proved that the water quality within the Siret River basin is generally classified in the 2nd or 3rd class. The spatial distribution of the water quality index values, using ARCGIS, also highlighted the fact that the water quality is mostly unsuitable for drinking water supplies, being influenced by the quality of its main tributaries, as well as by the effluent of wastewater treatment plants.


2022 ◽  
Vol 23 (1) ◽  
pp. 73-82
Author(s):  
Rosye Tanjung ◽  
Marcelino Yonas ◽  
Suwito Suwito ◽  
Hendra Maury ◽  
Yulius Sarungu ◽  
...  

2022 ◽  
Vol 301 ◽  
pp. 113818
Author(s):  
R. Elliott Carver ◽  
Nathan O. Nelson ◽  
Kraig L. Roozeboom ◽  
Gerard J. Kluitenberg ◽  
Peter J. Tomlinson ◽  
...  

Author(s):  
K. Utkina ◽  
A. Garbuz ◽  
M. Kulyk

The aim of the paper is to assess dynamics of water quality in four main recreational areas in Kharkiv and to develop recommendations for water quality improvement. Methods. Field and laboratory methods and analytical data processing. Results. The paper presents analysis of dynamics in water quality for four main recreational areas located in Kharkiv: Zhuravlevskiy Hydropark, Oleksiivskiy Lugopark, Udyanskiy Hydropark and Osnovyanske Lake. Period of study: 2006-2020, time: May-June and August-September. Average data are presented. Samples were analysed at certified Laboratory of Analytical Chemical Research of the Karazin Institute of Environmental Sciences. Laboratory data were compared with national UA standards and European ones. Conclusions were made for the following key parameters: dissolved oxygen and BOD5, total mineralization, biogenic substances content, oil products and surfactants, toxic heavy metals content. There is no specific dynamics on the pollution level. Conclusions. The following recommendations for improvement of water quality were developed: (i) to preform regular monitoring of water quality; (ii) to introduce regular and systematic control by one local authority; (iii) to improve infrastructure of recreational areas; (iv) to introduce regular cleaning of the recreational areas; (v) to install bio-WC; (vi) to install additional waste containers (preferably with separate waste collection); (vii) plant trees for better isolation from highways; (viii) to improve level of water treatment on WWTP; (ix) to create nature protected areas along rivers


2021 ◽  
Vol 25 (9) ◽  
pp. 1671-1675
Author(s):  
B.O. Ekute ◽  
E.U. Etim

The effect of industrial effluents on surface water quality of Oruku River was investigated in this study by analyzing selected water quality indicators such as pH, dissolved oxygen (DO) and total dissolved solids (TDS) were examined amongst other physicochemical parameters using standard methods. Results show that, average pH of the surface waters ranged from 5.53±0.31 to 6.23±0.45 with SR3 having the highest value. This indicates that all the water sources were alkaline. The effluents had an average pH range of 5.95 ± 1.12 to 6.40 ± 0.48. A comparison of these average pH values with effluent quality standards indicated that the effluents pH were below limit (6.5-9.5). The average BOD levels in surface water ranged from 1.94 ± 0.95 for SR-4 to 3.78 ± 1.61 for SR-1. DO average values in surface water was found to be higher at SR-1 with a mean value of 5.36 ± 1.55 and lower at SR-2 with a mean value of 3.05 ± 0.68. The mean COD value for surface water ranged from 108.66 ± 73.03mg/L to 232.81 ± 155.46mg/L. SR-3 had the highest COD average value of 232.81 ± 155.46mg/L while there was a reduction at SR-5 to an average value of 108.66 ± 73.03mg/L. The high COD value in the surface water indicates that gross-organic pollution of the water source may be from other sources such as agricultural and urban run-offs.


Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 164
Author(s):  
Monika Puchlik ◽  
Janina Piekutin ◽  
Katarzyna Dyczewska

This article presents the influence of climatic conditions on surface water quality. The research methodology, including physicochemical analysis from the Gołdapa and Bludzia rivers, is presented. The research lasted for two years. The results of the physicochemical studies of the Gołdapa and Bludzia rivers in early spring, spring, and autumn show that each of these seasons impacts the quality of surface waters. Moreover, it was proven that all the parameters are strongly correlated with the air temperature, the sum of daily precipitation, and water levels. For detailed analysis, the obtained results of own research were compared with meteorological and hydrological data from the last 15 years (2005–2021) for the region of north-eastern Poland. It was proven that temperature changes contribute to increased surface water pollution in the north-eastern part of Poland. Waters from areas that humans have not developed are of better quality than those that drain the urban area, which is reflected in the case of the superior quality of the Bludzia river compared to the Gołdapa river. The upward trend in temperature in the Gołdap region indicates that global warming will continue.


2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Shilpa Yakkerimath ◽  
Sanjaykumar Divekar ◽  
Chidanand Patil ◽  
Amruth A ◽  
Purandara Bekal

Surface water samples were collected from selected locations along river Panchaganga, from Kolhapur to Narsobawadi during April 2019. Physicochemical parameters were determined in the laboratory and chemical mass balance approach was adopted to estimate the individual ionic loads in the river water. Streeter-Phelps equation was applied to derive a relationship between DO and BOD5. Model parameters such as De-oxygenation Rate (Kd) and Re-aeration Rates (Kr ) were optimized using different empirical methods. The result of chemical mass balance showed an increase in the loading of various ions from upstream to downstream which could be attributed to agricultural and industrial wastes that enter the main stream. De-oxygenation rate and re-aeration constants were calculated using various empirical methods. DO sag curve was developed using Streeter Phelp’s model and compared with the observed parameters which showed a significant correlation. DO-BOD concentration observed along the course of the river indicated that the self-purification capacity of the river is high due to which the river regains the lost DO level at a distance less than 50 meters. 


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