• Journal of Environmental Science International
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• v.18 no.9
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• pp.971-981
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• 2009

An objective of this study is as follows: 1) performing sensitivity analysis and parameter estimation of RMA2 and RMA4 models for the West-Nakdong River, 2) drawing up alternatives of gates-operation for water-quality enhancement, and 3) quantitative evaluation of methodology of 'flow-restoration by gates-operation' among 'Comprehensive Plan Improving Water-Quality in the West-Nakdong River(WNR)' with the target water-quality(BOD at Nakbon-N point: below 4.3 mg/L). The parameters for the RMA2 (depth-averaged two-dimensional flow model) and RMA4 (depth-averaged two-dimensional water-quality model) were determined by sensitivity analysis. Result of parameter estimation for RMA2 and RMA4 models is $1,000\;Pa{\cdot}s$ of the eddy viscosity, 20 of the Peclet number, 0.025 of the Manning coefficient, and $1.0\;m^2/s$ of the diffusion coefficient. We have evaluated the effects of water-quality enhancement of the selected alternatives by numerical simulation technique with the models under the steady-state flow condition and the time-variant transport condition. Because of no-resuspension from river bottom and considering BOD as conservative matter, these simulation results slightly differ from real phenomena. In the case of $50\;m^3/s$ of Daejeo-gate inflow, two-dimensional flow pn results result represents that small velocity occurs in the Pyungkang Stream and no flow in the Maekdo River. In the WNR, there occurs the most rapid flow near timhae-bridge. In the WNR, changes of water-quality for the four selected simulation cases(6, 10, 30, $50\;m^3/s$ of the Daejeo-gate inflow) were predicted. Since the Daejeo-Gate and the Noksan-Gate can be opened up to 7 days, it would be found that sustainable inflow of $30\;m^3/s$ at the Daejeo-gate makes BOD in the WNR to be under the target of water-quality.

• Advances in environmental research
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• v.5 no.3
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• pp.153-167
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• 2016

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural network in upstream and downstream water quality stations of the Karaj Reservoir in Iran. For both neural networks, inputs were pH, turbidity, temperature, chlorophyll-a, biochemical oxygen demand (BOD) and nitrate, and the output was dissolved oxygen (DO). We used an MLP neural network with two hidden layers, for upstream station 15 and 33 neurons in the first and second layers respectively, and for the downstream station, 16 and 21 neurons in the first and second hidden layer were used which had minimum amount of errors. For learning process 6-fold cross validation were applied to avoid over fitting. The best results acquired from RBF model, in which the mean bias error (MBE) and root mean squared error (RMSE) were 0.063 and 0.10 for the upstream station. The MBE and RSME were 0.0126 and 0.099 for the downstream station. The coefficient of determination ($R^2$) between the observed data and the predicted data for upstream and downstream stations in the MLP was 0.801 and 0.904, respectively, and in the RBF network were 0.962 and 0.97, respectively. The MLP neural network had acceptable results; however, the results of RBF network were more accurate. A sensitivity analysis for the MLP neural network indicated that temperature was the first parameter, pH the second and nitrate was the last factor affecting the prediction of DO concentrations. The results proved the workability and accuracy of the RBF model in the prediction of the DO.

• Smart Structures and Systems
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• v.26 no.6
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• pp.781-796
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• 2020

Prediction of total sediment load is essential in an extensive range of problems such as the design of the dead volume of dams, design of stable channels, sediment transport in the rivers, calculation of bridge piers degradation, prediction of sand and gravel mining effects on river-bed equilibrium, determination of the environmental impacts and dredging necessities. This paper is aimed to investigate and predict the total sediment load of the Wadi Arbaat in Eastern Sudan. The study was estimated the sediment load by separate total sediment load into bedload and Suspended Load (SL), independently. Although the sediment records are not sufficient to construct the discharge-sediment yield relationship and Sediment Rating Curve (SRC), the total sediment loads were predicted based on the discharge and Suspended Sediment Concentration (SSC). The turbidity data NTU in water quality has been used for prediction of the SSC in the estimation of suspended Sediment Yield (SY) transport of Wadi Arbaat. The sediment curves can be used for the estimation of the suspended SYs from the watershed area. The amount of information available for Khor Arbaat case study on sediment is poor data. However, the total sediment load is essential for the optimal control of the sediment transport on Khor Arbaat sediment and the protection of the dams on the upper gate area. The results show that the proposed model is found to be considered adequate to predict the total sediment load.

• Journal of the Korean association of regional geographers
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• v.19 no.2
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• pp.352-361
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• 2013

This paper aims to analyze the root mean square errors of MODIS LST data and inland water temperature measurement data in order to use MODIS LST data as an input of numerical weather prediction model. MODIS LST data from July 2011 to June 2012 were compared to water temperature measurement data in the automated water quality measurement network. MODIS data have two composites: day-time and night-time. Monthly errors of day-time and night-time LST range $2{\sim}8^{\circ}C$ and $3{\sim}12^{\circ}C$, respectively. Temporally, monthly errors of day-time LST are less in fall and those of night-time LST are less in summer. Spatially, on the four major rivers including the Han, Nakdong, Geum, and Yeongsan rivers, the errors of Yeongsan river were the smallest, which location is the south-most among them. In this study, the errors of MODIS LST as an input of numerical weather prediction model were analyzed and the results can be used as an error level of MODIS LST data for inaccessible areas such as North Korea.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.129-137
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• 2005

In this study, we developed a model to simulate the interaction between sediment and the overlying water. The model deals with water-sediment interaction in terms of the sedimentation of organic detritus from the pelagic zone into the benthic zone and the release of nutrients occurring in the reverse direction. The model was tested and verified by comparing the predicted release rates of phosphorus from the sediment in Osaka Bay with actual observed values. The results accurately reproduced the seasonal change in release rates. The results well represented seasonal change of the release rates. A long-term prediction of water and sediment quality was performed for the period from 1950 to 1999. Nutrient loads from land and the boundary conditions of 3-D baroclinic flows were season-adjusted. The model accurately reproduced the changing trends in phosphorus, nitrogen, and COD concentrations in Osaka Bay over a long period of time.

• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.2
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• pp.3-14
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• 2001

In order to predict nutrient circulation in Hakata bay, we have developed an ecosystem model named the Sediment-Water Ecological Model (SWEM). The model, consisting of two sub-models with hydrodynamic and biological models, simulates the circulation process of nutrient between water column and sediment, such as nutrient regeneration from sediments as well as ecological structures on the growth of phytoplankton and zooplankton. This model was applied to prevent eutrophication in Hakata bay, located in western Japan. The calculated results of the tidal currents by the hydrodynamic model showed good agreement with the observed currents. Moreover, SWEM simulated reasonably well the seasonal variations of water quality, and reproduced spatial heterogeneity of water quality in the bay, observed in the field. According to the simulation of phosphorus circulation at the head of the bay, it was predicted that the regeneration process of phosphorus across the sediment-water interface had a strong influence on the water quality of the bay.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.85-90
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• 2013

Currently, the electric fire prediction system uses PIC(Peripheral Interface Controller) for controller microprocessor. PIC has a slower computing speed than DSP does, so its real-time computing ability is inadequate. So with the basic characteristics waveform during arc generation as the standard reference, the comparison to this reference is used to predict and alarm electric fire from arc. While such alarm can be detected and taken care of from a remote central server, that prediction error rate is high and remote control in mobile environment is not available. In this article, the arc detection of time domain and frequency domain and wavelet-based adaptation algorithm executing the adaptation algorithm in conversion domain were applied to develop an electric fire prediction system loaded with new real-time arc detection algorithm using DSP. Also, remote control was made available through iPhone environment-based app development which enabled remote monitoring for arc's electric signal and power quality, and its utility was verified.

• Journal of Ocean Engineering and Technology
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• v.21 no.2 s.75
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• pp.42-49
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• 2007

It has been known that shallow-water regions, such as tidal flats, sea grass and sea weed beds have water purification capability, and they also serve as nursery grounds for many fishes. On the other hand, tidal flat areas are economically attractive sites for reclamation, to be used for developing industries. When developing shallow-water areas, we have to propose a plan to mitigate the environmental impact associated with such a development plan. However, it is difficult to estimate the affects on the ecosystem and water purification, and the literature related to this matter is insufficient. In order to evaluate the ability of coastal tidal flat and to predict the future changes, it is necessary to develop a reliable prediction technique and construction of data by using a field investigation. In this study, we carried out a numerical model test for the tidal flat ecosystem, using the pelagic system and the benthic system, simultaneously, in order to show a change in the tidal flat ecosystem. The flow of nitrogen, phosphorus and carbon has been identified as a primary consideration of marine ecosystem components, and the capability of water purification and the change of the tidal flat were predicted using this flow. In order to make a more reliable prediction, a field investigation to determine tide, current and creatures of the object coastal area has been done. The purification capability of this shallow-water region is estimated from the model results. According to the results of experiments, the tidal flat has a capability of water purification (Sink) of 11mgN/m2/day, but the other area has a load (Source) of 20mgN/m2/day. As a result, we could confirm that the tidal flat of an object coastal area plays an important role in water purification.

• Journal of the Korean Society of Urban Environment
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• v.18 no.4
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• pp.401-408
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• 2018

EQPS (Effluent Quality Prediction System, Dynamita, France) was applied to analyze the appropriateness of the design of a bioreactor in A sewage treatment plant. A sewage treatment plant was designed by setting the design concentration of the secondary clarifier effluent to total nitrogen and total phosphorus, 10 mg/L and 1.8 mg/L, respectively, in order to comply with the target water quality at the level of the hydrophilic water. The retention time of the 4-stage BNR reactor was 9.6 hours, which was 0.5 for the pre-anoxic tank, 1.0 for the anaerobic tank, 2.9 for the anoxic tank, and 5.2 hours for the aerobic tank. As a result of the modeling of the winter season, the retention time of the anaerobic tank was increased by 0.2 hours in order to satisfy the target water quality of the hydrophilic water level. The default coefficients of the one step nitrification denitrification model proposed by the software manufacturer were used to exclude distortion of the modeling results. Since the process modeling generally presents optimal conditions, the retention time of the 4-stage BNR should be increased to 9.8 hours considering the bioreactor margin. The accurate use of process modeling in the design stage of the sewage treatment plant is a way to ensure the stability of the treatment performance and efficiency after construction of the sewage treatment plant.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.470-478
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• 2017

This study was classified into two groups, normal season group and drought season group, by the cluster analysis using the weather and water quality data from 2012 to 2015, using SPSS 18 version. Also each cluster was classified into three spaces, Gangcheon, Yeoju and Ipoh weir. We performed the multiple regression analysis with each monthly data that concentration of Chl-a was more than algae warming level. 6 groups classified in time and space were analyzed by the correlation analysis between concentration of Chl-a and 3 weather, 11 water quality and discharge factors. We developed Chl-a prediction equations of each group with independent variables of the multiple regression analysis applying to the correlation result. The result of cluster analysis was that the period was divided into two groups, normal group(2012-2013) that total annual precipitation rate was normal and drought group(2014-2015) that total annual precipitation rate was less than 1,000 mm/hr, in time. The months that concentration of Chl-a was more than algae warming level in each group classified by cluster analysis were that the normal group was 3~8 and drought group was 3 and 6~10. The correlation result between Chl-a and weather, water quality and discharge factors for each 6 group was that relationships between Chl-a and water, discharge factors were high in the drought group more than in normal group at all weirs. This was influenced by velocity reduction and increasing HRT according to the intense drought. Weather, water quality and discharge factors that were high correlation with Chl-a were applied to independent variables of Chl-a prediction equations and each equations were developed. Among them, Each adjusted R square of Prediction equations for Chl-a in each group at Ipoh weir where is located in Namhan river downstream and is directly connected to Paldang dam were normal group = 0.920 and drought group = 0.818. It's showed the high linear.