• Korean Journal of Fisheries and Aquatic Sciences
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• v.29 no.3
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• pp.386-392
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• 1996

A numerical method based on genetic algorithms was introduced to characterize the grain-size distribution more effectively. This technique was proved significant particularly for multimodal size distributions, as was verified for samples from Korea Strait continental shelf. Sediment samples collected from the Korea Strait continental shelf revealed that $96\%$ of the grain-size distributions were multimodal. Therefore, the use of grain-size parameters was not the ideal method. As an alternative method, the decomposition of sue curves into elementary normal component curves was used. Means and standard deviations of 593 decomposed normal components were calculated by a numerical method from 268 size curves of Korea Strait sediments. The mean values of decomposed normal components showed peaks at $1\~3\phi\;and\;7\~9\phi$ size classes. The plot of mean and standard deviation values of the coarse fraction normal components on the map showed a characteristic areal distribution. The characteristic distribution was found to derive from underlying Pleistocene sediment on the basis of sea bottom geologic distribution of the area. The method of decomposition into normal components was found to be more effective than the analysis using traditional grain-size parameters in investigation of multimodal size distribution of Korea Strait shelf sediment.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.739-744
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• 2002

Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

• Journal of Korean Society of Rural Planning
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• v.7 no.1 s.13
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• pp.77-88
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• 2001

In order to evaluate the applicability of GWLF model which can efficiently estimate non-point and point source pollutant loadings in rural watershed including urban district, the model was applied to an experimental watershed. The model was calibrated using observed data such as daily runoffs, sediment yields, T-N, and T-P. Simulated daily runoffs and sediment yields by the model using calibrated parameters were in food agreement with the observed data. There were difference between the simulated and observed nutrient loading which was considered resonable. The simulated results by the model showed that T-N, T-P and sediment yields were dependent on the amount of stream runoff discharge and land use. GWLF model is believed to applicable to estimate amount of pollutant loading of non-point source pollution for the water qualify control of agricultural watersheds.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.3
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• pp.321-327
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• 2018

To classify seafloor sediments using a probabilistic neural network (PNN), the frequency-dependent characteristics of broadband acoustic scattering, which make it possible to qualitatively categorize seabed type, were collected from three different geographical areas in Korea. The echo data samples from three types of seafloor sediment were measured using a chirp sonar system operating over a frequency range of 20-220 kHz. The spectrum amplitudes for frequency responses of 35-75 kHz were fed into the PNN as input feature parameters. The PNN algorithm could successfully identify three seabed types: mud, mud/shell and concrete sediments. The percentage probabilities of the three seabed types being correctly classified were 86% for mud, 66% for mud/shell and 72% for concrete sediment.

• Journal of the Korean earth science society
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• v.34 no.2
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• pp.120-135
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• 2013

To investigate the changes in depositional environment around Gangneung Harbor, we analyzed the surface sediment textural parameters and topography data collected five times from February 2007 to February 2009. In the study area, sediments were mainly composed of sand and its sediment size became finer at offshore sites. During summer time, however, the sand grains became coarser than winter season near Namhangjin Beach, inside the harbor, and offshore areas. On the other hand, the grain size of Anmok Beach showed a gradual finer trend with time. Compared with the previous studies conducted before the completion of Gangneung Harbor construction, the mean grain size became finer on Anmok Beach, while it was coarser on Namhangjin Beach. The bathymetric changes observed over a 2-year period showed predominant erosion in the area of 5 to 10 m water depths and deposition in 2 to 5 m water depths. The shallower area less than 2 m water depths showed an alternating trend and yet slightly more dominant erosion process. The sediment textural parameters and the distribution of erosion and deposition have changed continuously. Results imply that such changes show long-term trends as well as seasonal variations in which the trend may have been formed after the completion of Gangneung Harbor construction.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.5
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• pp.601-607
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• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.

• Journal of Environmental Science International
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• v.20 no.9
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• pp.1151-1163
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• 2011

The bed change analysis near the opening gate of a dam or weir to release deposited sediments have been conducted mostly using the numerical models. However, the use of unverified input parameters in the numerical model is able to produce the different results with natural and real conditions. Also, the bed changes near the opening gate of a dam or weir calculated with a numerical model could be varied depending on the geometry extent included the downstream area with supercritical flow in the model. In addition, the different time steps could provide different results in the bed change calculation, even though other conditions such as input parameters, geometries, and total simulation time were same. Therefore, in this study, hydraulic experiments were performed to validate the eddy viscosity coefficient which is the one of important input parameters in the RMA2 model and relevant to variation of simulation results. The bed changes were calculated using the SED2D model based on flow results calculated in the RMA2 model with the verified and selected eddy viscosity coefficient and also compared with experimental results. The bed changes near the opening gate were underestimated in the numerical model comparing with experimental results except only the numerical case without the modeling section of sediment release pipe and downstream area where the supercritical flow was produced. For the simulation of minimum time steps, different shapes of scour hole were produced in numerical and physical modeling.

• Ocean Systems Engineering
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• v.6 no.1
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• pp.61-97
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• 2016

This is the second of two papers on the 3D numerical modeling of nearshore hydro- and morphodynamics. In Part I, the focus was on surf and swash zone hydrodynamics in the cross-shore and longshore directions. Here, we consider nearshore processes with an emphasis on the effects of oceanic forcing and beach characteristics on sediment transport in the cross- and longshore directions, as well as on foreshore bathymetry changes. The Delft3D and XBeach models were used with four turbulence closures (viz., ${\kappa}-{\varepsilon}$, ${\kappa}-L$, ATM and H-LES) to solve the 3D Navier-Stokes equations for incompressible flow as well as the beach morphology. The sediment transport module simulates both bed load and suspended load transport of non-cohesive sediments. Twenty sets of numerical experiments combining nine control parameters under a range of bed characteristics and incident wave and tidal conditions were simulated. For each case, the general morphological response in shore-normal and shore-parallel directions was presented. Numerical results showed that the ${\kappa}-{\varepsilon}$ and H-LES closure models yield similar results that are in better agreement with existing morphodynamic observations than the results of the other turbulence models. The simulations showed that wave forcing drives a sediment circulation pattern that results in bar and berm formation. However, together with wave forcing, tides modulate the predicted nearshore sediment dynamics. The combination of tides and wave action has a notable effect on longshore suspended sediment transport fluxes, relative to wave action alone. The model's ability to predict sediment transport under propagation of obliquely incident wave conditions underscores its potential for understanding the evolution of beach morphology at field scale. For example, the results of the model confirmed that the wave characteristics have a considerable effect on the cumulative erosion/deposition, cross-shore distribution of longshore sediment transport and transport rate across and along the beach face. In addition, for the same type of oceanic forcing, the beach morphology exhibits different erosive characteristics depending on grain size (e.g., foreshore profile evolution is erosive or accretive on fine or coarse sand beaches, respectively). Decreasing wave height increases the proportion of onshore to offshore fluxes, almost reaching a neutral net balance. The sediment movement increases with wave height, which is the dominant factor controlling the beach face shape.

• Journal of Environmental Science International
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• v.25 no.1
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• pp.1-10
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• 2016

Bottom sediment pollution with heavy metals of the Sventoji River in Ukmerge, Lithuania using X-ray fluorescence spectrometry is analyzed in this article. During the research, qualitative and quantitative parameters of heavy metal concentrations and their distribution were investigated. This article presents obtained results of study, where bottom sediment samples were examined from both shores of the river of Sventoji. During this research, received data was treated using GIS software, which helped to interpolate the data of concentrations into the research polygon of the river. GIS software also helped to evaluate the urban runoff influence to the bottom sediment quality and exclude sources of pollution. The runoff dischargers which transport surface wastewater to the river were registered before sampling. At the mouth of streams, flowing into the river of Sventoji, additional samples were taken. After comprehensive river bottom sediment research there is a possibility to assess the extent of anthropogenic activity and its impact on the river ecosystem and human health.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.399-403
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• 1998

Absorption coefficient per mass unit of particles, specific absorption coefficient, is one of main parameters in developing algorithms for ocean color remote sensing. Specific absorption coefficient of chlorophyll (a$^*_{ph}$) and suspended sediment (SS) were analyzed by "wet filter technique" and "Kishino method" for data sets observed in the Yellow and Mediterranean Seas. A new data-recovering method for the filter technique was also developed using spectrum slopes. This method recovered the baseline of spectrum that was often missed in the Kishino method. High a$^*_{ph}$($\lambda$) values in the oligotrophic Mediterranean Sea and low values in the Yellow Sea were observed, spanning over the range of 0.02 to 0.12 $m^2$/mg, at the chlorophyll maximum absorption wavelength 440nm. The empirical relationship between a$^*_{ph}$ and chlorophyll concentration was found to fit a power function, which was slightly different from that proposed by Bricaud et ai. (1995). Absorption specific coefficients for suspended sediment (a$^*_{SS}$) didn't show any relationship with concentrations of suspended sediment. However, the average value of a$^*_{SS}$ at 440nm was close to the specific absorption coefficient of soil (loess) measured by Ahn (1990). The more-pronounced variability of a$^*_{SS}$ than a$^*_{ph}$ perhaps can explain more wide range of size-distribution for SS, which were determined by their specific gravity and agitation of water mass in the sea surface.