• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.596-604
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• 2019

This study conducted a sediment culture experiment to investigate the effects of sediment oxygen demand (SOD) and environmental factors on sediment and water quality. We installed a leaching tank in the laboratory, cultured it for 20 days, and analyzed the relationship between P and Fe in the sediment. As a result, the dissolved oxygen of the water layer decreased with time, while the oxidation-reduction potential of the sediment progressed in the negative direction to form an anaerobic reducing environment. The SOD was measured to be 0.05 mg/g at the initial stage of cultivation and increased to 0.09 mg/g on the 20th day, indicating the tendency of increasing consumption of oxygen by the sediment. The change is likely to have caused by oxygen consumption from biological-SOD, which is the decomposition of organic matter accumulated on the sediment surface due to the increase of chl-a, and chemical-SOD consumed when the metal-reducing product produced by the reduction reaction is reoxidized. The correlation between SOD and causality for sediment-extracted sediments was positive for Ex-P and Org-P and negative for Fe-P. The analysis of the microbial community in the sediment on the 20th day showed that anaerobic iron-reducing bacteria (FeRB) were the dominant species. Therefore, when the phosphate bonded to the iron oxide is separated by the reduction reaction, the phosphate is eluted into the water to increase the primary productivity. The reduced substance is reoxidized and contributes to the oxygen consumption of the sediment. The results of this study would be useful as the reference information to improve oxygen resin.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1059-1068
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• 2003

Geographic Information System (GIS) combined with Universal Soil Loss Equation (USLE) was used to estimate the soil erosion of Asan Bay experiment watershed in Korea. Spatial data for each USLE factors were obtained from the Landsat-5 TM remote sensing images and 1/25,000 scale digital contour maps. Sediment yield to Asan Bay was estimated by the sediment delivery ratio and trap efficiency. The estimated sediment yield was compared with observed on the Asan and Sapgyo estuary sub-watershed within Asan Bay experimental watershed for the period from 1981 to 2000. The calculated total annual sediment yields from Asan and Sapgyo estuary sub-watershed to Asan Bay were 5,665tonnes/yr and 6,766tonnes/yr, respectively. The measured sediment yields were 12,937tonnes/yr and 12,395tonnes/yr, respectively on an average.

• 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 for Geospatial Information Science
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• v.22 no.3
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• pp.11-19
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• 2014

This study is analyze future climate and land cover change affects behaviors for amount of streamflow and sediment discharge within basin. We used the climate forecast data in RCP 4.5 and 8.5 (2011-2100) which is opposite view for each other among RCP scenarios that are discussed for 5th report for IPCC. Land cover map built based on a social economic storyline in RCP 4.5/8.5 using Logistic Regression model. In this study we set three scenarios: one scenario for climate change only, one for land cover change only, one for Last both climate change and land cover change. It simulated amount of streamflow and sediment discharge and the result showed a very definite change in the seasonal variation both of them. For climate change, spring and winter increased the amount of streamflow while summer and fall decreased them. Sediment showed the same pattern of change steamflow. Land cover change increases the amount of streamflow while it decreases the amount of sediment discharge, which is believed to be caused by increase of impervious Surface due to urbanization. Although land cover change less affects the amount of streamflow than climate change, it may maximize problems related to the amount of streamflow caused by climate change. Therefore, it's required to address potential influence from climate change for effective water resource management and prepare suitable measurement for water resource.

• Spatial Information Research
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• v.10 no.2
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• pp.301-316
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• 2002

Soil Loss by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. Also, validity pondage of reservoir or dam is decreased by rivers inflow of eroded soil. Revised Universal Soil Loss Equation(RUSLE) is mainly used to presume soil loss amount of basin using GIS. But, because comparison with survey data is difficult, it is no large meaning that estimate calculated soil loss amount as quantitative. This research used unit sediment deposit survey data of Bo-seong basin for quantitative conclusion of soil loss amount that calculate on RUSLE. Through comparison examination with unit sediment yield that calculate on RUSLE and unit sediment deposit survey data, we can estimate resolution far RUSLE Model. As a result, cell size of 150m was estimated by thing which is most suitable.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.4
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• pp.366-373
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• 2017

Urinalysis is considered to be easier and simpler than other tests. It has been known to cause no burden to patients, while offering important information on diagnosing, treating, and determining the prognoses of kidney and urinary tract diseases. Urinary sediments are usually performed by microscopic examination of centrifuged urine by technologist. The guidelines proposed by the Korean Association of External Quality Assessment Service are actually different from those actually practiced by medical institutions and taught to biomedical students in textbooks. Therefore, we verified whether different sediment preparation methods lead different test results. Specimens that tested positive from the occult blood and leukocyte esterase in the urine dipstick test were randomly selected for a microscopic examination. The differences in the urine sediment preparation affected the sediment concentrations, which influenced the cell grade and cell number per HPF. The first factor in determining the sediment concentration is the centrifugal force. Many medical institutions use 1,500 rpm as the centrifugal speed without considering the radius of the centrifuge; such a value may not be accurate for 400 G. Consequently, there were differences in urine concentrations, which influenced the results. The second factor is the amount of sediment in urine. Different amounts of the remaining supernatant led to different sediment concentration factors, again, causing different results. Furthermore, not only by using a pipette to obtain an accurate amount as stipulated, but also by roughly obtaining a drop, the microscopic examination using such a volume of sediment examined affected the results. Therefore, this study highlights the importance of standardization of urine sediment preparation procedures to promote consistency and accuracy across institutions.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.111-120
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• 2017

In this paper, we propose novel feature extraction algorithm for classification of seabed sediment. In previous researches, acoustic reflection coefficient has been used to classify seabed sediments, which is constant in terms of frequency. However, attenuation of seabed sediment is a function of frequency and is highly influenced by sediment types in general. Hence, we developed a feature vector by using attenuation variation with respect to frequency. The attenuation variation is obtained by using reflected signal from the second sediment layer, which is generated by broadband chirp. The proposed feature vector has advantage in number of dimensions to classify the seabed sediment over the classical scalar feature (reflection coefficient). To compare the proposed feature with the classical scalar feature, dimension of proposed feature vector is reduced by using linear discriminant analysis (LDA). Synthesised acoustic amplitudes reflected by seabed sediments are generated by using Biot model and the performance of proposed feature is evaluated by using Fisher scoring and classification accuracy computed by maximum likelihood decision (MLD). As a result, the proposed feature shows higher discrimination performance and more robustness against measurement errors than that of classical feature.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.586-593
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• 2020

Purpose: This study aims to develop an algorithm for predicting sediment discharge by debris flow, and develop GIS-based decision support system for optimal arrangement of check dam. Method: The average stream width and flow length were used to predict the cumulative sediment discharge by debris flow. At this time, the amount of slope failure on source area and average flow length were utilized as input factors. Result: The predicted sediment discharge calculated through the algorithm was 1.1 times different on average compared to the actual sediment discharge by debris flow. In addition, the program is an objective indicator that selects the location and size of the check dam, and it can help practitioners make rational decisions. Conclusion: The soil erosion control works are being implemented every year. Therefore, it is expected that the GIS-based decision support system for location and size of the check dam will contribute to the prevention of sediment-related disasters.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.5
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• pp.236-241
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• 2016

This study conducted a screening-level ecological risk assessment for heavy metals in dredged sediment for recycling in terrestrial environment. Toxicological information of six heavy metals (i.e., Cu, Zn, Cd, Pb, Cr, and Ni) was collected from ECOTOX of US Environmental Protection Agency, and screened and qualified for the use in the screening-level ecological risk assessment. According to the number of terrestrial ecological receptors for which toxicological information is available, PNEC (Predicted No Effect Concentration) of each heavy metal was derived using either stochastic approach (for Cu, Zn, and Cd), or deterministic approach (for Pb, Cr, and Ni). Hazard quotients of the six heavy metals were derived for a field-collected dredged sediment using the PNEC derived and the PEC (Predicted Environmental Concentration) determined for the dredged sediment. The HQs of Cu, Zn, Cr, Pb and Ni were higher than unity indicating a possibility of ecological risk of the five heavy metals when the dredged sediment is applied in terrestrial environment. Accordingly, remediation processes or a higher-level ecological risk assessment would be needed for the recycling of the material.