• Environmental Engineering Research
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• v.15 no.2
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• pp.123-126
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• 2010

Modeling non-point pollution across multiple scales has become an important environmental issue. As a more representative and practical approach in quantifying and qualifying surface water, a modular neural network (MNN) was implemented in this study. Two different site-scales ($1.5\;{\times}\;10^5$ and $1.62\;{\times}\;10^6\;m^2$) with the same plants, soils, and paddy field management practices, were selected. Hydrologic data (rainfall, irrigation and surface discharge) and water quality data (time-series nutrient loadings) were continuously monitored and then used for the verification of MNN performance. Correlation coefficients (R) for the results predicted from the networks versus measured values were within the range of 0.41 to 0.95. The small block could be extrapolated to the large field for the rainfall-surface drainage process. Nutrient prediction produced less favorable results due to the complex phenomena of nutrients in the drainage water. However, the feasibility of using MNN to generate improved prediction accuracy was demonstrated if more hydrologic and environmental data are provided. The study findings confirmed the estimation accuracy of the upscaling from a small-segment block to large-scale paddy field, thereby contributing to the establishment of water quality management for sustainable agriculture.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.53-59
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• 2001

The Primary Production of phytoplanktons produces organic matter in high concentration in eutrophicated Hakata Bay, Japan, even during the winter season in spite of low water temperature. Phytoplanktons are considered to have any biological capabilities to keep activities of photosynthesis under the unfavorable conditions, and this affects water quality of the bay. In this study, seasonal variations in primary production efficiency were predicted by using a simple box-type ecosystem model, which introduced the concept of efficiency for absorption of solar radiation energy in relation to growth of phytoplanktons under the low solar radiation intensity. According to the simulation result of primary production, it was organic pollution comes from dissolved organic carbon (DOC) throughout the year, DOC of which is originated from the primary production of phytoplanktons on biological response of the seasonal variation of ambient conditions.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.525-530
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• 2000

The loss of soil and nutrients from land surfaces to surface water supplies continues to be an important source of nonpoint source pollution. This study was initiate to develop an empirical relationship among the contaminants. SS, COD, T-N, and T-P were collected from agricultural surface water quality studies carried out in Hwasung-Gun, Kyonggi-Do. Correlation analysis, regression analysis, and reliability analysis were conducted. The regression equations were developed between SS and COD, SS and T-P, COD and T-P, and the resulting r$\^$2/ value was over 0.78. The regression equation enables a reasonable prediction of phosphorus concentration and COD concentration for known suspended solid concentration.

• Journal of the Korean Society of Safety
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• v.10 no.2
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• pp.56-63
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• 1995

A simulation of contaminant dispersion in a water reservoir has been done using 2-D finite difference method(FDM). The steady state velocity field of the reservoir was computed using stream function-vorticity formulation of Wavier-Stokes equation and continuity equation. Based on the computed steady state velocity field, the transient convective diffusion equation of the contaminant dispersion was computed. For the 1m$\times$1m reservoir model with inlet and outlet attached, it was shown that the center of circulation located toward right. For the numerical values of v =0.01($\textrm{cm}^2$/s) and D=0.6($\textrm{cm}^2$/s) and the flow of 50($\textrm{cm}^3$/s ), it was determined that the outflow had to be shut down in 18 seconds to prevent from severe pollution. Also the required time was computed to be 6 seconds for the inflow of 100 ($\textrm{cm}^3$/s). The result of this study is considered, hopefully, to be useful for the design of the water reservoir systems that are the subjects to various contamination.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3726-3734
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• 2012

This study evaluated the behavior of pollutants based on the seasonal change by selecting the branch river's factors that influence the outflow of pollutants in Soyang lake basin. The analysis method was the factor analysis that classified the factors of the drainage area influencing the outflow of pollutants, and evaluated selected representative factors. As a result of the study, SS and T-P factors should be classified as similar factors to the storm water runoff, and the improvement of water must be strived through managing source of pollution at the time of no rain. Second, as the result of the influence from the factors, spring and winter seasons usually exert 36% influence and summer and fall exert over 90% significant influence that the improvement of water through managing source of water seems possible. At last, the prediction about delivery pollution load considering the outflow characteristic of pollutants at the drainage area based on seasonal change by regarding selected factors as independent variables is possible.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.383-400
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• 2023

Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.470-480
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• 2019

The Doam lake watershed was designated as a non-point pollution management area in 2007 to improve water quality based on watershed management implementation. There have been studies of non-point source reduction with respect to the watershed management impacting the pollutant transport of the reservoir. However, a little attention has been focused on the impact of water quality improvement by the management of the dam operation or the guidelines on the dam operation. In this study, the impact of in-lake management practices combined with watershed management is analyzed, and the appropriate guidelines on the operation of the dam are suggested. The integrated modeling system by coupling with the watershed model (HSPF) and reservoir water quality model (CE-QUAL-W2) was applied for analyzing the impact of water quality management practices. A scenario implemented with sedimentation basin and suspended matter barrier showed decrease in SS concentration up to 4.6%. The SS concentration increased in the scenarios adjusting withdrawal location from EL.673 m to the upper direction(EL.683 m and EL.688 m). The water quality was comparably high when the scenario implemented all in-lake practices with water intake at EL.673 m. However, there was improvement in water quality when the height of the water intake was moved to EL.688 m during the summer by preventing sediments inflow after the rainfall. Therefore, to manage water quality of the Doam lake, it is essential to control the water quality by modulating the height of water intake through consistent turbidity monitoring during rainfall.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.832-840
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• 2019

Recently, pollution from gunpowder due to shell shootings at military drilling sites has raised various environmental concerns. The purpose of this study is to predict the contamination level of RDX in the soil area of the firing range zone near Anwol river watershed, the study site, and the intake area, Anwol river and Imjin river, as a function of time and space. In this study, a multimedia model was developed to predict the variation of RDX contamination by rainfall. The range of the medium was limited to soil, water, and sediment, and excluded the atmosphere, taking into account the physical and chemical properties of RDX with low vapor pressure and low Henry's constant. The pollutant levels of the waters of compartments, including the last section of the Imjin River affecting the water intake, was compared with the environmental standard for RDX.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.189-204
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• 2021

In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.221-230
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• 2009

In Korea, many water intake plants are easily affected by effluents of sewage treatment plants because sewage treatment plants are usually located upstream or nearby the plants of the same riverine area. Furthermore, the inflow of harmful contaminants owing to pollutant spills or transportation accidents of vehicles using the roads and bridges intersecting the river causes significant impact on the management of water intake plants. Paldang lake, the main water intake plants in Korea, is especially exposed to various water pollution accidents, because the drainage basin area is significantly large compared to the water surface area of the lake. Therefore it is necessary to predict the possible pollutant spill in advance and consider measurements in case of water pollution. In this study, water quality prediction was performed in Paldang Lake in Korea durig the dry season using two-dimensional numerical models. In order to represent the cases of pollutant accidents, the difference of pollutant transport patterns with varying injection points was analyzed. Numerical simulations for hydrodynamics of water flow and water quality predictions were performed using RMA-2 and RAM4 respectively. As a result of simulation, the difference of pollutant transport with the injection points was analyzed. As a countermeasure against the pollutant accident, the augmentation of the flow rate is proposed. In comparison with the present state, the rapid dilution and flushing effects on the pollutant cloud could be expected with increase of flow rate. Thus, increase of flow rate can be used for operation of water intake plants in case of pollutant spill accidents.