• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.1
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• pp.53-62
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• 2015

To elucidate the microbial consortia responsible for the anaerobic methane oxidation in the methane hydrate bearing sediments, we compared the geochemical constituents of the sediment, the rate of sulfate reduction, and microbial biomass and diversity using an analysis of functional genes associated with the anaerobic methane oxidation and sulfate reduction between chimney site (UBGH2-3) on the continental slope and non-chimney site (UBGH2-10) on the basin of the Ulleung Basin. From the vertical profiles of geochemical constituents, sulfate and methane transition zone (SMTZ) was clearly defined between 0.5 and 1.5 mbsf (meters below seafloor) in the UBGH2-3, and between 6 and 7 mbsf at the UBGH2-10. At the UBGH2-3, the sulfate reduction rate (SRR) in the SMTZ exhibited was appeared to be $1.82nmol\;cm^{-3}d^{-1}$ at the depth of 1.15 mbsf. The SRR in the UBHG2-10 showed a highest value ($4.29nmol\;cm^{-3}d^{-1}$) at the SMTZ. The 16S rRNA gene copy numbers of total Prokaryotes, mcrA, (methyl coenzyme M reductase subunit A), and dsrA (dissimilatory sulfite reductase subunit A) showed the peaks in the SMTZ at both sites, but the maximum mcrA gene copy number of the UBGH2-10 appeared below the SMTZ (9.8 mbsf). ANME-1 was a predominant ANME (Anaerobic MEthanotroph) group in both SMTZs of the UBGH2-3 and -10. However, The sequences of ANME-2 were detected only at 2.2 mbsf of the UBGH2-3 where high methane flux was observed because of massive amount of gas hydrate at shallow depth. And Desulfosarcina-Desulfococcus (DSS) that is associated with ANME-2 was detected in 2.2 mbsf of the UBHG2-3. Overall results demonstrate that ANME-1 and ANME-2 are considered as significant archaeal groups related to methane cycle in the subsurface sediment of the East Sea, and ANME-2/DSS consortia might be more responsible for methane oxidation in the methane seeping region than in non-seeping region.

• Korean Journal of Agricultural Science
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• v.7 no.2
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• pp.131-144
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• 1980

The Linear Regression Model to extend the monthly runoff data in the short-recorded river was proposed by the author in 1979. Here in this study generalization precedure is made to apply that model to any given river basin and to any given station. Lengthier monthly runoff data generated by this generalized model would be useful for water resources assessment and waterworks planning. The results are as follows. 1. This Linear Regression Model which is a transformed water-balance equation attempts to represent the physical properties of the parameters and the time and space varient system in catchment response lumpedly, qualitatively and deductively through the regression coefficients as component grey box, whereas deterministic model deals the foregoings distributedly, quantitatively and inductively through all the integrated processes in the catchment response. This Linear Regression Model would be termed "Statistically deterministic model". 2. Linear regression equations are obtained at four hydrostation in Geum-river basin. Significance test of equations is carried out according to the statistical criterion and shows "Highly" It is recognized th at the regression coefficients of each parameter vary regularly with catchment area increase. Those are: The larger the catchment area, the bigger the loss of precipitation due to interception and detention storage in crease. The larger the catchment area, the bigger the release of baseflow due to catchment slope decrease and storage capacity increase. The larger the catchment area, the bigger the loss of evapotranspiration due to more naked coverage and soil properties. These facts coincide well with hydrological commonsenses. 3. Generalized diagram of regression coefficients is made to follow those commonsenses. By this diagram, Linear Regression Model would be set up for a given river basin and for a given station (Fig.10).

• Journal of Korea Water Resources Association
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• v.44 no.10
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• pp.777-786
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• 2011

In the previous researches for storm sewer design, the flow path, pipe diameter and pipe slope were determined to minimize the construction cost. But in the sewer networks, the flows can be changed according to flow path. The current optimal sewer layout models have been focussed on satisfying the design inflow for sewer designs, whereas the models did not consider the occurrences of urban inundation from excessive rainfall events. However, in this research, the sewer networks are determined considering the superposition effect to reduce the inundation risk by controlling and distributing the inflows in sewer pipes. Then, urban inundation can be reduced for excessive rainfall events. An Optimal Sewer Layout Model (OSLM) was developed to control and distribute the inflows in sewer networks and reduce urban inundation. The OSLM uses GA (Genetic Algorithm) to solve the optimal problem for sewer network design and SWMM (Storm Water Management Model) to hydraulic analysis. This model was applied to Hagye basin with 44 ha. As the applied results, in the optimal sewer network, the peak outflow at outlet was reduced to 7.1% for the design rainfall event with 30 minutes rainfall duration versus that of current sewer network, and the inundation occurrence was reduced to 24.2% for the rainfall event with 20 years frequency and 1 hour duration.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1083-1095
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• 2003

The analysis of drying stream characteristics for about 500 streams from field survey data with 19 items has been fulfilled. Also, a study area has been determined, and criteria of estimation has been established : criteria such as, available hydrological data, the size of stream lengths and basin areas and regional characteristics. Then they are applied to designated study areas. The final selected study areas are 8 basins. The analysis of drying stream characteristics using a GIS has been applied to 5 basins in which spacial data is comparatively implemented among the final 8 target catchments. The spacial analysis using a GIS is applied to stream slopes for upstream and downstram at weirs, overlaying the map of buffering stream networks and ground water pump stations map, sinuosity of drying stream. As a result of drying streams survey analysis, drying stream characteristics are followed; levee types are earth and natural, cross sectional shapes are trapezoid, stream bed materials are gravels and sands, facilities in streams are weirs. As a result of GIS analysis, stream slopes are comparatively larger downstream than upstream close to weirs. There are arranged ground water pump stations less than 500m from stream networks. Also the average of sinuosity for each drying stream is in the range of 1.229∼1.475, comparatively a serious.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.43-49
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• 2011

In the face of growing concern about global warming, increasing attention has been focused on the reduction of carbon dioxide emissions. One method to mitigating the release of carbon dioxide is Carbon Capture and Storage (CCS). CCS includes separation of carbon dioxide from industrial emission in plants, transport to a storage site, and long-term isolation in underground. It is necessary to conduct analyses on optimal site selection, surface monitoring, and additional effects by the construction of CCS facility in Gyeongsang basin, Korea. For the optimal site selection, necessary data; geological map, landcover map, digital elevation model, and slope map, were prepared, and a weighted overlay analysis was performed. Then, surface monitoring was performed using high resolution satellite image. As a result, the candidate region was selected inside Gyeongnam for carbon storage. Finally, the related regulations about CCS facility were collected and analyzed for legal question of selected site.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.298-304
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• 2011

We conducted magnetic survey using IBRV (Ice Breaker Research Vessel) ARAON of KORDI (Korea Ocean Research and Development Institute), ROV (Remotely Operated Vehicle) of Oceaneering Co. and three components vector magnetometer, at Apr., 2011 in the western slope of the caldera of TA25 seamount, the Lau Basin, the southwestern Pacific. The depth ranges of the survey area are from about 900 m to 1200 m, below sea level. For the deep sea magnetic survey, we made the nation's first small deep sea three components magnetometer of Korea. The magnetometer sensor and the data logger was attached with the upper part and lower part of ROV, respectively. ROV followed the planning tracks at 25 ~ 30 m above seafloor using the altimeter and USBL (Ultra Short Base Line) of ROV. The three components magnetometer measured the X (North), Y (East) and Z (Vertical) vector components of the magnetic field of the survey area. A motion sensor provided us the data of pitch, roll, yaw of ROV for the motion correction of the magnetic data. The data of the magnetometer sensor and the motion sensor were recorded on a notebook through the optical cable of ROV and the network of ARON. The precision positions of magnetic data were merged by the post-processing of USBL data of ROV. The obtained three components magnetic data are entirely utilized by finding possible hydrothermal vents of the survey area.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.119-132
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• 2012

Recently, forest soil sediment disasters resulting from locally concentrated heavy rainfall have been occurring frequently in steep slope areas. The importance of landslide hazard map is emerging to analyze landslide vulnerable areas. This study was carried out to develop HyGIS-Landslide based on Hydro Geographic Information System in order to analyze forest soil sediment disaster in the mountainous river basin. HyGIS-Landslide is one of HyGIS components designed by considering the landslide hazard criteria of Korea Forest Service. It could show the distribution of landslide hazard areas after calculating the spatial data. In this system, the user could reset the weight of hazard criteria to reflect the regional characteristics of the landslide area. This component provided user interface that could make the latest spatial data available in the area of interest. HyGIS-Landslide could be applied to the surveyor's compensation score and it was possible to reflect the landslide risk exactly through it. Also, it could be used in topographic analysis techniques providing spatial analysis and making topographical parameters in HyGIS. Finally the accuracy could be acquired by calculating the landslide hazard grade map and landslide mapping data. This study applied HyGIS-Landslide at the Gangwon-do province sample site. As a result, HyGIS-Landslide could be applied to a decision support system searching for mountainous disaster risk region; it could be classified more effectively by re-weighting the landslide hazard criteria.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.119-136
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• 2012

The goal of this study is to apply the IPCC(Intergovernmental Panel on Climate Change) concept of vulnerability to climate change and verify the use of a combination of vulnerability index and fuzzy logic to flood vulnerability analysis and mapping in Seoul using GIS. In order to achieve this goal, this study identified indicators influencing floods based on literature review. We include indicators of exposure to climate(daily max rainfall, days of 80mm over), sensitivity(slope, geological, average DEM, impermeability layer, topography and drainage), and adaptive capacity(retarding basin and green-infra). Also, this research used fuzzy model for aggregating indicators, and utilized frequency ratio to decide fuzzy membership values. Results show that the number of days of precipitation above 80mm, the distance from river and impervious surface have comparatively strong influence on flood damage. Furthermore, when precipitation is over 269mm, areas with scare flood mitigation capacities, industrial land use, elevation of 16~20m, within 50m distance from rivers are quite vulnerable to floods. Yeongdeungpo-gu, Yongsan-gu, Mapo-gu include comparatively large vulnerable areas. This study improved previous flood vulnerability assessment methodology by adopting fuzzy model. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing flood mitigation policies.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1321-1330
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• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.