scholarly journals Evaluation of the Ecochemical Status of the Danube in Serbia in Terms of Water Quality Parameters

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Ljiljana Takić ◽  
Ivana Mladenović-Ranisavljević ◽  
Milovan Vuković ◽  
Ilija Mladenović

The Danube is an international river passing partly through Serbia. The protection of the environment and sustainable use of water resources is a primary task that implies constant monitoring of the quality status and evaluation of ecochemical status of the water in the Danube basin. The investigation includes calculation of all-inclusive water quality by the Serbian water quality index (SWQI) method and an evaluation of eco-chemical status of the Danube water in terms of water quality parameters from the entry to the exit point along its course through Serbia in the year of 2009. The results show that the overall quality of the Danube water on the territory of Serbia corresponds to the descriptive indicator of “very good” water. According to theCouncil Directive 75/440/EEC, the evaluation of the ecostatus, with slight deviation of individual parameters at Pančevo, corresponds to A1 category of the surface water quality intended for the abstraction of drinking water supplies in member states.

Author(s):  
Romana Rima ◽  
Abdullah Al Ryhan ◽  
Sony Ahmed ◽  
Rafiq Islam ◽  
Sharif Hossain Munshi ◽  
...  

The Meghna River is one of the most important rivers in Bangladesh, one of the three rivers, the Ganges delta, and the largest delta in the world in the Bay of Bengal. The water quality of Meghna has become a matter of concern due to serious levels of pollution. The present study was conducted to assess the surface water quality of upstream of the Meghna River using physic-chemical parameters in summer and winter season at five different points. Water quality was evaluated by laboratory analysis considering a total of six water quality parameters, pH, DO, BOD, COD, salinity and TDS and water samples were collected from five stations. The study indicates that some parameters exceed the permissible limit for drinking purpose, it may cause potential threat to the human, but the water of this river is not immediate threat to human or ecosystem.


Author(s):  
Nguyen Ngan Ha ◽  
Tran Thi Thu Huong ◽  
Pham The Vinh ◽  
Tran Thi Van

This paper presents the study of integrating the remote sensing technology with in-situ ground observation for assessing the status of water quality in Ca Mau city through the Vietnam Water Quality Index (VN-WQI). The Sentinel-2 image and in-situ surface water samples were collected on 20 February 2020 for this study. The sample results were then specified by samples’ coordination. Besides, Sentinel-2 imaging was processed by radiometric and atmospheric correction, geometric registration, and extracted pixel spectral values from the sample locations. The multiple linear regressions of seven water quality parameters including BOD5, COD, NH4, PO4, TSS, pH, Coliform with surface water’s pixel spectral values from the satellite images were calculated and used to simulate water quality parameters on the satellite image. They were integrated into the VN-WQI to estimate, classify, and evaluate the general surface water quality of the Ca Mau city. The results show that there is a regressive correlation between measured data and image spectral values, and the simulation also well fits with the data with an acceptable error. The surface water quality of Ca Mau city is heavily polluted with almost all water quality parameters recognized at B1 to above B2 level according to the QCVN08-MT:2015/BTNMT. In terms of VN-WQI, the results also illustrate the low quality of surface water and heavy pollution only used for water transportation, not for domestic use. This approach can be a powerful method in spatially monitoring water quality and supporting environment management.


Author(s):  
Saroj Nayak

This work evaluates the surface water quality in terms of physico-chemical parameters of the Brahmani River, Odisha using statistical analysis involving the calculation of correlation coefficient and regression equation. Besides this, the work also highlights and draws attention towards the “Water Quality Index” in a simplified format which may be used at large and could represent the reliable picture of water quality. Surface water quality data is taken from OSPCB of various location i.e. Panposh D/S, Rourkela D/S, Rengali, Talcher U/S, Kamalanga D/S, Bhuban, Pattamundai and was assessed for summer, monsoon, winter for the years 2011, 2012, 2013, 2014 and 2015. Average of values, minimum of values and maximum of values of water quality parameters were obtained seasonally over the above mentioned years. Besides this, the standard deviation for the water quality parameters was also obtained for water quality parameters namely pH, Temperature, DO, TDS, Alkalinity, EC, Na+, Ca2+, Mg2+, K+, F-, Cl-, NO3-, SO42- and PO42-. Seasonal changes in various physical and chemical parameters were analysed.The values obtained were compared with the guideline values for drinking water by Bureau of Indian Standard (BIS). A systematic correlation and regression study is carried out for three seasons, showed linear relationship among different water quality parameters. This provides an easy and rapid method of monitoring water quality. Highly significant (0.8< r <1.0), moderately significant (0.6< r <0.8) and significant (0.5< r <0.6) correlations between the parameters have been worked out. High correlation coefficient has been observed between TDS,EC-Na+, Ca2+, Cl-, SO42- ; Na+- Cl-. From the collected quantities, certain parameters were selected to derive WQI for the variations in water quality of each designated sampling site. WQI of Brahmani River ranged from 36.7 to 44.1 which falls in the range of good quality of water.Panposh D/S and Rourkela D/S showed poor water quality in summer and winter season. It is shown that WQI may be a useful tool for assessing water quality and predicting trend of variation in water quality at differentlocations in the Brahmani River.


2018 ◽  
Vol 69 (8) ◽  
pp. 2045-2049
Author(s):  
Catalina Gabriela Gheorghe ◽  
Andreea Bondarev ◽  
Ion Onutu

Monitoring of environmental factors allows the achievement of some important objectives regarding water quality, forecasting, warning and intervention. The aim of this paper is to investigate water quality parameters in some potential pollutant sources from northern, southern and east-southern areas of Romania. Surface water quality data for some selected chemical parameters were collected and analyzed at different points from March to May 2017.


Author(s):  
Hüseyin Güher ◽  
Burak Öterler ◽  
Belgin Elipek ◽  
Okan Yeler ◽  
Gazel Aydin

K?rklareli Reservoir locating in Meri?-Ergene River Basin is an important drinking/using a freshwater resource of K?rklareli Province. In order to ensure the sustainable use of this important reservoir, its current situation should be examined periodically and evaluated by multivariate analyses. For this reason, the water samples were taken between the dates April 2018 and February 2019 at monthly intervals from 3 different stations. The data of environmental and physicochemical variables (water temperature, dissolved oxygen, pH, salinity, conductivity, total dissolved solids, Chlorophyll-a, light permeability, fluoride, chloride, NO2-N, NO3-N, PO4, SO4, and essential/potentially toxic elements) measured and evaluated according to the classes in surface water quality control regulation of Turkey. The parameters exceeding first-class water quality values (chlorophyll-a, pH, NO2-N, chloride, selenium) were mapped in GIS using Spline integration approach. Also, Sodium Absorbtion Ratio, Kelly Index Values, and Magnesium Ratio, were calculated to evaluate the water quality for agricultural irrigation water standards. The water quality of the reservoir was evaluated by using multivariance analyses (Bray-Curtis Similarity Index, Correspondence Analyses, Pearson Correlation Index). As a result, it was emphasized that using GIS approach is a potential useful method of monitoring the sustainable water quality of K?rklareli reservoir which is determined to have an oligomesotrophic character.


2021 ◽  
Author(s):  
Gurusamy Kutralam-Muniasamy ◽  
Fermín Pérez-Guevara ◽  
Ignacio Elizalde Martinez ◽  
Shruti Venkata Chari

Abstract The Santiago River is one of Mexico's most polluted waterways and evaluating its surface water quality during the COVID-19 outbreak is critical to assessing the changes and improvements, if any, from the nationwide lockdown (April-May 2020). Hence, the data for 12 water quality parameters from 13 sampling stations during April-May 2020 (lockdown) were compared with the levels for the same period of 2019 (pre-lockdown) and with the same interval of previous eleven-years (2009-2019). The values of BOD (14%), COD (29%), TSS (7%), f. coli (31%), t. coli (14%) and Pb (20%) declined, while pH, EC, turbidity, total nitrogen and As enhanced by 0.3-21% during the lockdown compared to the pre-lockdown period suggesting decrements of organic load in the river due to the temporary closure of industrial and commercial activities. An eleven-year comparison estimated the reduction of pH, TSS, COD, total nitrogen and Pb by 1-38%. The analysis of water quality index estimates showed short-term improvements of river water quality in the lockdown period, compared to pre-lockdown and eleven-year trend as well as indicated very poor quality of the river. The contamination sources identified by factor analysis were mainly related to untreated domestic sewage, industrial wastewaters and agriculture effluents influencing the river water quality. Overall, our findings demonstrated positive responses of COVID-19 imposed lockdown on water quality of the Santiago River during the study period, providing a foundation for the government policy makers to identify the sources of pollution, to better design environmental policies and plans for water quality improvements.


2019 ◽  
Vol 28 (2) ◽  
pp. 147-158
Author(s):  
Mohammad Saiful Islam ◽  
Romana Afroz ◽  
Md Bodruddoza Mia

This work has been conducted to evaluate the water quality of the Buriganga river. In situ water quality parameters and water samples were collected from 10 locations in January 2016 and analyzed later in laboratory for water quality parameters such as pH, Eh, EC, TDS, cations (Na+, K+, Ca2+, Mg2, As3+), anions (Cl-, HCO3-, NO2-, NO3-, SO42-, F-, Br-, PO43-), heavy metals (Cr2+, Pb2+, Zn2+, Cd+2, Fe2+, Mn2+) to see whether or not the level of these parameters are within the permissible limits. The average values of pH, Eh, EC and temperature were 7.31, –214.9 mV, 928.9 μs/cm and 21.4°C, respectively; the average concentration of Na+, K+, Ca2+, Mg2+, and As3+ were 109.62, 13.38, 46.78, 13.98 and 0.018 mg/l, respectively, while the concentrations of Cl-,HCO3-, PO43-, SO42-, NO3-, NO2-, F and Br -were 79, 331.06, 2.22, 84.32, 0.0254, 0.058, 0.224 and 0.073 mg/l, respectively; and the concentration of heavy metals Pb2+, Zn2+, Fe2+ and Mn2+were 0.28, 0.053, 0.17 and 0.23 mg/l, respectively. The study indicates that most of the parameters are within the permissible limits set by Bangladesh water quality standard. The concentrations of K+, Mn2+, and Pb2+ were beyond the permissible limits meaning that that the water of Buriganga is not safe for drinking. The people living beside Buriganga river should be more cautious about using the polluted/contaminated river water. The concerned authorities should take urgent necessary steps to improve the degraded water quality of the river considering the ecological, environmental and economic implications associated with it. Dhaka Univ. J. Biol. Sci. 28(2): 147-158, 2019 (July)


2020 ◽  
Vol 15 (4) ◽  
pp. 960-972
Author(s):  
M. F. Serder ◽  
M. S. Islam ◽  
M. R. Hasan ◽  
M. S. Yeasmin ◽  
M. G. Mostafa

Abstract The study aimed to assess the coastal surface water quality for irrigation purposes through the analysis of the water samples of some selected estuaries, rivers, and ponds. The analysis results showed that the mean value of typical water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), and chloride (Cl−) ions exceeded the permissible limit of the Department of Environment (DoE), Bangladesh 2010, and FAO, 1985 for the pre- and post-monsoon seasons. The Piper diagram indicated a Na-Cl water type, especially during the pre- and post-monsoon seasons. The water quality parameters in the areas showed a higher amount than the standard permissible limits, indicating that the quality is deteriorating. The water quality index values for domestic uses showed very poorly to unsuitable in most of the surface waters except pond water, especially during the pre- and post-monsoon periods. The surface water quality index for irrigation purpose usages was found to be high and/ or severely restricted (score: 0–55) during the pre- and post-monsoon seasons. The study observed that due to saline water intrusion, the water quality deterioration started from post-monsoon and reached its highest level during the pre-monsoon season, which gradually depreciates the water quality in coastal watersheds of Bangladesh.


2021 ◽  
Vol 6 (4) ◽  
pp. 40-49
Author(s):  
Nur Natasya Mohd Anuar ◽  
Nur Fatihah Fauzi ◽  
Huda Zuhrah Ab Halim ◽  
Nur Izzati Khairudin ◽  
Nurizatul Syarfinas Ahmad Bakhtiar ◽  
...  

Predictions of future events must be factored into decision-making. Predictions of water quality are critical to assist authorities in making operational, management, and strategic decisions to keep the quality of water supply monitored under specific criteria. Taking advantage of the good performance of long short-term memory (LSTM) deep neural networks in time-series prediction, the purpose of this paper is to develop and train a Long-Short Term Memory (LSTM) Neural Network to predict water quality parameters in the Selangor River. The primary goal of this study is to predict five (5) water quality parameters in the Selangor River, namely Biochemical Oxygen Demand (BOD), Ammonia Nitrogen (NH3-N), Chemical Oxygen Demand (COD), pH, and Dissolved Oxygen (DO), using secondary data from different monitoring stations along the river basin. The accuracy of this method was then measured using RMSE as the forecast measure. The results show that by using the Power of Hydrogen (pH), the dataset yielded the lowest RMSE value, with a minimum of 0.2106 at station 004 and a maximum of 1.2587 at station 001. The results of the study indicate that the predicted values of the model and the actual values were in good agreement and revealed the future developing trend of water quality parameters, showing the feasibility and effectiveness of using LSTM deep neural networks to predict the quality of water parameters.


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