Analysis of the Influences of Seawater Freezing and Melting on the Water Quality of Sea Surface Based on Monitoring Data

2021 ◽  
Vol 31 (4) ◽  
pp. 429-434
Author(s):  
Shuai Yuan ◽  
Ning Xu ◽  
Yuan Chen ◽  
Wenqi Shi ◽  
Lina Song
Keyword(s):  
Water Quality ◽  
Sea Surface ◽  
Monitoring Data

scholarly journals The Evolutions for Water Quality of Son La Hydropower Reservoir from Environmental Monitoring Data (2010 - 2018)

2019 ◽  
Vol 35 (3) ◽  
Author(s):  
Do Xuan Duc ◽  
Luu Duc Hai ◽  
Do Huu Tuan
Keyword(s):  
Water Quality ◽  
Phase 1 ◽  
Water Environment ◽  
Monitoring Data ◽  
Hydropower Plant ◽  
Monitoring Site ◽  
Data Collection And Analysis ◽  
Before And After ◽  
Hydropower Reservoir

In 2010, the time of blocking dams for electricity generation activities of the Son La hydropower plant on Da river, up to now, after nearly 08 years of water storage, the Son La reservoir environment has stabilized and formed the soil ecosystem. flood - typical reservoir ecosystem in the highlands of the Northwest, Vietnam. Basing on the monitoring data of the Da River at the beginning of 2010, monitoring data for Son La hydropower reservoir (2010 - 2017), monitoring data for Lai Chau hydropower reservoir (phase 1/2018). This paper uses data collection and analysis method to compare the quality of Da river water before and after the dam to the Son La reservoir at 03 observation sites: Hang Tom bridge Muong Lay, Dien Bien), Pa Uon Bridge (Quynh Nhai, Son La), Upper Muong La (Son La). Analyze the quality of Son La hydropower reservoir through input data (Lai Chau hydropower reservoir) and output at monitoring site (downstream of the dam) in Son La province during 2015-2017. The analytical results confirmed the process of changes in the groups of physical, chemical, microbiological, pesticide residues in the lake water environment and proved to change the quality of hydropower reservoirs. Son La seasonal. At the same time, discuss and evaluate some natural, social and human factors that affect the water quality of Son La hydropower reservoir.    

scholarly journals Long-Term Statistical Assessment of the Water Quality of Tundja River

2012 ◽  
Vol 19 (2) ◽  
pp. 213-226 ◽  
Author(s):  
Petia Papazova ◽  
Pavlina Simeonova
Keyword(s):  
Water Quality ◽  
Industrial Wastes ◽  
Monitoring Data ◽  
Anthropogenic Sources ◽  
Physical Parameters ◽  
Statistical Assessment ◽  
Seasonal Behavior ◽  
The Impact

Long-Term Statistical Assessment of the Water Quality of Tundja RiverTwo major environmetric methods (Cluster analysis(CA) andPrincipal components analysis(PCA)) were applied for statistical assessment of the water quality of trans-border river Tundja. The study used long-term monitoring data from 26 sampling sites characterized by 12 physicochemical parameters. Clustering of chemical indicators results in 3 major clusters: the first one shows the impact of anthropogenic sources, the second - the impact of agriculture and farming activities and the last one describes the role of the physical parameters on the water quality and also the impact of urban wastes. For better assessment of the monitoring data, PCA was implemented, which identified four latent factors. Two of them - "urban wastes" factor and "agriculture" factor correspond almost entirely to clusters 3 and 2 from the previous statistical analysis. The third one, named "industrial wastes" factor, reveals a specific seasonal behavior of the river system. The last latent factor describes the active reaction of the water body and is determined as "acidity" factor. The linkage of the sampling sites along the river flow by CA formed two clusters with the spatial "upstream-downstream" separation. The apportionment model of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters.

scholarly journals Basin of small rivers as an indicator of the environment state

2018 ◽  
Author(s):  
Olena Mitryasova ◽  
Volodymyr Pohrebennyk
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Trend Analysis ◽  
Natural Waters ◽  
Water Environment ◽  
Sharp Decrease ◽  
Monitoring Data ◽  
Small Rivers ◽  
Time Periods

Background. Small rivers are an important component of the natural environment. Water resources of small rivers are part of the shared water resources and are often the main and sometimes the only one source of local water. Small rivers are the regulators of the water regime of the landscapes, the factors for maintaining balance and redistribution of moisture. The aim is analysis of interaction between parameters of the quality of the water environment like conductivity and nitrates on the example of natural waters of small rivers. Objects are small rivers Bìst and Rosselle (Saardand lands, Germany) and Mertvovod (Mykolaiv region, Ukraine). Methods. We used the method of correlative analysis which is effective and efficient for the determination of connections between the parameters of water quality that helps to identify sources of pollution, as well as interpret phenomena, forecast the situation related to the change in the quality of natural waters. The hydrochemical monitoring data were obtained from autonomous automated stations that are located on the rivers Bist, Rossel and Mertvovod. We investigated the following correlation dependencies between such combinations of natural waters quality parameters: nitrates and conductivity. Monitoring data are processed using software MS Excel; correlation dependence was defined using the CORREL. Results. Correlation value is changed in the range from −1 to + 1 that demonstrates the indirect and direct dependence between the selected parameters. If the value is closer to +1, this means the presence of a strong connection, if closer to 0 – weak. The time periods for the calculation of the correlation between the parameters of natural waters quality is selected: 4, 8, 16 and 24 hours respectively. The following time periods allow the best to trace and predict changes in the natural aquatic environment. Correlation analysis of the concentration of nitrates and conductivity showed that for r. Bìst and r. Rosselle dominates is the positive value of the correlation between the study parameters, which proves their strong interaction. However, at certain concentrations of nitrate-ions observed custom phenomenon of sharp decrease in correlation to the «-1», which is explained by the Onsager equation, namely an excess concentration of nitrates is associated with erosion of different types of fertilizers from the fields as a result of rainfall. Discussion. Trend analysis of the studied indicators of Mertvovod water quality was conducted on an average value of each indicator (pH, phosphates, nitrates, BOD, soluble oxygen). We used trend analysis for Mertvovod because we did not have enough data in time. Found a significant increase in phosphates with time. This can be explained by the arrival of various surface active substances and, to a lesser extent, the lack of quality sewage treatment facilities. Positive changes are founded in water object that is related to a decrease in the value of BOD.

scholarly journals Basin of small rivers as an indicator of the environment state

2018 ◽  
Author(s):  
Olena Mitryasova ◽  
Volodymyr Pohrebennyk
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Trend Analysis ◽  
Natural Waters ◽  
Water Environment ◽  
Sharp Decrease ◽  
Monitoring Data ◽  
Small Rivers ◽  
Time Periods

Background. Small rivers are an important component of the natural environment. Water resources of small rivers are part of the shared water resources and are often the main and sometimes the only one source of local water. Small rivers are the regulators of the water regime of the landscapes, the factors for maintaining balance and redistribution of moisture. The aim is analysis of interaction between parameters of the quality of the water environment like conductivity and nitrates on the example of natural waters of small rivers. Objects are small rivers Bìst and Rosselle (Saardand lands, Germany) and Mertvovod (Mykolaiv region, Ukraine). Methods. We used the method of correlative analysis which is effective and efficient for the determination of connections between the parameters of water quality that helps to identify sources of pollution, as well as interpret phenomena, forecast the situation related to the change in the quality of natural waters. The hydrochemical monitoring data were obtained from autonomous automated stations that are located on the rivers Bist, Rossel and Mertvovod. We investigated the following correlation dependencies between such combinations of natural waters quality parameters: nitrates and conductivity. Monitoring data are processed using software MS Excel; correlation dependence was defined using the CORREL. Results. Correlation value is changed in the range from −1 to + 1 that demonstrates the indirect and direct dependence between the selected parameters. If the value is closer to +1, this means the presence of a strong connection, if closer to 0 – weak. The time periods for the calculation of the correlation between the parameters of natural waters quality is selected: 4, 8, 16 and 24 hours respectively. The following time periods allow the best to trace and predict changes in the natural aquatic environment. Correlation analysis of the concentration of nitrates and conductivity showed that for r. Bìst and r. Rosselle dominates is the positive value of the correlation between the study parameters, which proves their strong interaction. However, at certain concentrations of nitrate-ions observed custom phenomenon of sharp decrease in correlation to the «-1», which is explained by the Onsager equation, namely an excess concentration of nitrates is associated with erosion of different types of fertilizers from the fields as a result of rainfall. Discussion. Trend analysis of the studied indicators of Mertvovod water quality was conducted on an average value of each indicator (pH, phosphates, nitrates, BOD, soluble oxygen). We used trend analysis for Mertvovod because we did not have enough data in time. Found a significant increase in phosphates with time. This can be explained by the arrival of various surface active substances and, to a lesser extent, the lack of quality sewage treatment facilities. Positive changes are founded in water object that is related to a decrease in the value of BOD.

Spatial and Temporal variation analysis of water quality of Hemavathi River, Karnataka, India

2018 ◽  
Vol 6 (9) ◽  
pp. 196
Author(s):  
Santhosh K. M ◽  
S. Prashanth
Keyword(s):  
Water Quality ◽  
Agricultural Runoff ◽  
Spatial And Temporal Variation ◽  
Final Conclusion ◽  
Variation Analysis ◽  
Pollution Load ◽  
Quality Of Water ◽  
Pollution Loading ◽  
Origin Point

Urban development, agricultural runoff and industrialization have contributed pollution loading on the environment.  In this study Hemavathi river water from a stretch from its origin point to its sangama was studied for pollution load by determining parameters of water quality like pH, Alkalinity,  Ca, Mg, Nitrate, TDS, BOD, COD , and the results were compared with WHO and BIS standards to draw final conclusion on the quality of water.

Changes of microbial indices of water quality in the Vistula and Brda rivers as a result of sewage treatment plant operation

2008 ◽  
Vol 37 (2) ◽  
Author(s):  
Maciej Walczak
Keyword(s):  
Water Quality ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Sewage Treatment Plants ◽  
Plant Operation ◽  
Treated Sewage ◽  
Microbiological Parameters ◽  
Microbial Indices

Changes of microbial indices of water quality in the Vistula and Brda rivers as a result of sewage treatment plant operationThis paper reports the results of studies of microbiological changes in the water quality of the Vistula and Brda rivers after the opening of sewage treatment plants in Bydgoszcz. The study involved determining the microbiological parameters of water quality. Based on the results obtained, it was found that the quality of the water in both rivers had improved decidedly after the opening of the plants, although an increased number of individual groups of microorganisms was found at the treated sewage outlet from one of the plants.

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