The Role of Modelling in the Control of Seawater Pollution

1988 ◽  
Vol 20 (6-7) ◽  
pp. 277-286 ◽  
Author(s):  
Takeshi Horie
Keyword(s):  
Water Quality ◽  
Quality Improvement ◽  
Quality Prediction ◽  
Sediment Characteristics ◽  
Benthic Species ◽  
Field Surveys ◽  
Water Quality Prediction ◽  
Organism Growth ◽  
Seawater Quality

A feasibility study of seawater improvement projects in selected bays where seawater is highly polluted by organic substances is being conducted. The study includes field surveys in these bays of, for example, seawater quality, sediment characteristics, sediment release rate, sediment settling rate, organism growth rates, and biological activity. Numerical analysis of the situation is also being conducted, using a set of mathematical models. A water quality prediction model was formulated on the basis of phosphorus cycling between seawater, phytoplankton, and sediment. The results of the simulation predicted that the effect of seawater quality improvement would be unexpectedly small, because of dilution due to advection and dispersion by seawater circulation. However, in the field, ecological conditions seem to be significantly improved, given that the number of benthic species and the populations of these species increase on treated sediment, even though the improvement of water quality is less than expected. Based on these results, the author discusses the role of the numerical model and gives examples of its application in predicting the environmental improvement due to seawater quality improvement.

Integrated modelling under uncertainty in watershed-level assessment and management

2007 ◽  
Vol 56 (8) ◽  
pp. 31-39 ◽  
Author(s):  
J.H. Ham ◽  
C.G. Yoon ◽  
K.W. Jung ◽  
J.H. Jang
Keyword(s):  
Water Quality ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Watershed Management ◽  
Management Practices ◽  
Control Measures ◽  
Integrated Modelling ◽  
Quality Prediction ◽  
Water Quality Prediction ◽  
Modelling System

Uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modelling system (modified-BASINS) under uncertainty is described and demonstrated for use in receiving-water quality prediction and watershed management. A Monte Carlo simulation was used to investigate the effect of various uncertainty types on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorus (T-P) in the Hwaong Reservoir, considering three uncertainty types, would be less than about 4.4 and 0.23 mg L−1, respectively, in 2012, with 90% confidence. The effects of two watershed management practices, wastewater treatment plants (WWTP) and constructed wetlands (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaong Reservoir to less than 3.4 and 0.14 mg L−1, 24 and 41% improvements, respectively, with 90% confidence. Overall, the Monte Carlo simulation in the integrated modelling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on the probability and level of risk, and its application is recommended.

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.

Water quality prediction model in open limestone systems

2020 ◽  
pp. 279-282
Author(s):  
Louis McDonald ◽  
Qingyun Sun ◽  
Jeffrey Skousen ◽  
Paul Ziemkiewicz
Keyword(s):  
Water Quality ◽  
Prediction Model ◽  
Quality Prediction ◽  
Water Quality Prediction
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