scholarly journals FIELD OBSERVATION ABOUT HYDRAULIC FACTORS INFLUENCING WATER QUALITY IN A TIDAL AREA OF THE ARA RIVER

2002 ◽  
Vol 46 ◽  
pp. 929-934 ◽  
Author(s):  
Yoshiki MOTONAGA ◽  
Yoshinori TAKEUTI ◽  
Manabu DOHI ◽  
Tadashi YAMADA
Keyword(s):  
Water Quality ◽  
Field Observation ◽  
Factors Influencing ◽  
Tidal Area

scholarly journals Artificial floating islands for water quality improvement

2017 ◽  
Vol 25 (3) ◽  
pp. 350-357 ◽  
Author(s):  
Yueya Chang ◽  
He Cui ◽  
Minsheng Huang ◽  
Yan He
Keyword(s):  
Water Quality ◽  
Quality Improvement ◽  
Constructed Wetlands ◽  
Oxygen Demand ◽  
Key Factors ◽  
Water Quality Improvement ◽  
Factors Influencing ◽  
Wetland Treatment ◽  
Improve Water Quality

Artificial floating islands (AFIs) are a variation of wetland treatment systems for water quality improvement. This paper provides a review concerning AFIs in terms of their development, classification, and applications in the removal of nutrients, heavy metals, and chemical oxygen demand on waterways. The role of microorganisms, aquatic plants, and aquatic animals in AFIs for water decontamination and purification was also discussed. Additionally, some key factors influencing the AFIs’ performances were discussed and comparisons between AFIs and constructed wetlands were reviewed. Finally, further perspectives of artificial floating islands were identified to possibly improve their performances. The understanding of the mechanisms in AFIs that drive removal of various contaminants to improve water quality is crucial, and is also highlighted in this paper.

Factors Influencing the Bacteriological Quality of Spa-Pool Waters in New South Wales (Australia)

1989 ◽  
Vol 21 (2) ◽  
pp. 141-145
Author(s):  
A. G. Bernard
Keyword(s):  
Water Quality ◽  
New South ◽  
New South Wales ◽  
Chlorine Disinfection ◽  
Bacteriological Quality ◽  
Department Of Health ◽  
Factors Influencing ◽  
South Wales ◽  
Principal Factors

The increasing popularity in the use of spa pools during the 1970's and 1980's and the accompanying incidents of folliculitis and ear infections caused by Pseudomonas aeruginosa associated with spa-pool use has necessitated the development of bacteriological and chemical guidelines for spa-pool water quality. The New South Wales (N.S.W.) Department of Health introduced a bacteriological standard for swimming pools and spa-pools in 1981 based on the findings of a series of surveys aimed at identifying the principal factors influencing the bacteriological quality of spa waters. Four surveys are summarised in this paper. The major findings described are the tenfold higher recovery of P. aeruginosa from spa-pools than from outdoor pools; the need for at least 2.0 milligrams per litre (mg/L) free chlorine residual in order to achieve reliable satisfactory water quality in spas compared with a requirement of 1.0mg/L to achieve the same quality in outdoor pools; the need to maintain pH below 8.0 in order to ensure efficient chlorine disinfection; the apparent inability of bromochlorodimethylhydantoin to adequately disinfect spas during heavy bather load periods; and the success of the Health Department's spa-pool operator education program which resulted in a 30% reduction in the incidence of bacteriologically unsatisfactory spa-pool waters in N.S.W. between 1980 and 1986.

Application of Data Fusion for Uncertainty and Sensitivity Analysis of Water Quality in the Shenandoah River

2019 ◽  
pp. 1383-1410
Author(s):  
Mbongowo Joseph Mbuh
Keyword(s):  
Water Quality ◽  
Data Fusion ◽  
Field Observation ◽  
Water Quality Modeling ◽  
Coefficient Of Determination ◽  
Water Quality Simulation ◽  
Quality Modeling ◽  
Invaluable Tool ◽  
Using Data ◽  
Very High

This article is aimed at demonstrating the feasibility of combining water quality observations with modeling using data fusion techniques for efficient nutrients monitoring in the Shenandoah River (SR). It explores the hypothesis; “Sensitivity and uncertainty from water quality modeling and field observation can be improved through data fusion for a better prediction of water quality.” It models water quality using water quality simulation programs and combines the results with field observation, using a Kalman filter (KF). The results show that the analysis can be improved by using more observations in watersheds where minor variations to the analysis result in large differences in the subsequent forecast. Analyses also show that while data fusion was an invaluable tool to reduce uncertainty, an improvement in the temporal scales would also enhance results and reduce uncertainty. To examine how changes in the field observation affects the final KF analysis, the fusion and lab analysis cross-validation showed some improvement in the results with a very high coefficient of determination.

Assessment of the water quality factors influencing the primary production in Lake Kasumigaura

2020 ◽  
Vol 76 (7) ◽  
pp. III_11-III_17
Author(s):  
Kazuhiro KOMATSU ◽  
Megumi NAKAGAWA ◽  
Kenji TSUCHIYA ◽  
Ayato KOHZU ◽  
Ryuichiro SHINOHARA ◽  
...  
Keyword(s):  
Water Quality ◽  
Primary Production ◽  
Lake Kasumigaura ◽  
Quality Factors ◽  
Factors Influencing
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