• Journal of Soil and Groundwater Environment
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• v.14 no.6
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• pp.65-70
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• 2009

Reduction of groundwater surface tension prior to air sparging (SEAS, surfactant-enhanced air sparging) was known to increase air saturation in the aquifer under influence, possibly enhancing the removal rates of volatile contaminants. Although SEAS was known to be efficient for increasing air saturation, little information is available for different hydrogeological settings including soil particle sizes and the depth of aquifer. We investigated water saturations in the sparging influence zone during SEAS using one-dimensional column packed with sands of different particle sizes and different aquifer depths. An anionic surfactant was used to suppress the surface tension of water. Two different sands were used; the air entry pressures of the sands were measured to be $15.0\;cmH_2O$, and $36.3\;cmH_2O$, respectively. No significant difference was observed in the water saturation-surface tension relationship for sands with different particle sizes. As the surface tension decreased, the water saturation decreased to a lowest point and then it increased with further decrease in the surface tension. Both sands reached their lowest water saturations when the surface tension was set approximately at 42 dyne/cm. SEAS was conducted at three different aquifer depths; 41 cm, 81 cm, and 160 cm. Water saturation-surface tension relationship was consistent regardless of the aquifer depth. The size of sparging influence zone during SEAS, measured using two-dimensional model, was found to be similar to the changes in air saturation, measured using one-dimensional model. Considering diverse hydrogeological settings where SEAS to be applied, the results here may provide useful information for designing SEAS process.

• Journal of the Korean association of regional geographers
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• v.14 no.1
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• pp.19-26
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• 2008

A validation study has been performed using the Soil and Water Assessment Tool(SWAT) model with data collected for the Neponset River watershed, which includes roughly 130 square miles of land located southwest of Boston. All of this land drains into the Neponset River, and ultimately into Boston Harbor. This paper presents the methodology of a SWAT model. The calculated contribution of the baseflow to the streamflow is far too high whereas the interflow is strongly underestimated. Alternatively, the modified and calibrated model yields far better results for the catchment. The modification allows hydrological processes to be modeled while not restraining the applicability of the model to catchments with other characteristics. For this study, the SWAT 2005 model is used with ArcGIS 9.1 as an interlace, and sensitivity analysis is performed to provide rough estimated values before adjusting sensitive input parameters during calibration period.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.116-127
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• 2011

This study conducted landslide susceptibility analysis using logistic regression. The performance of prediction model needs to be evaluated considering two aspects such as a goodness of fit and a prediction accuracy. Thus to gain more objective prediction results in this study, the prediction performance of the applied model was evaluated considering two such evaluation aspects. The selected study area is located between Inje-eup and Buk-myeon in the middle of Kwangwon. Landslides in the study area were caused by heavy rain in 2006. Landslide causal factors were extracted from topographic map, forest map and soil map. The evaluation of prediction model was assessed based on the area under the curve of the cumulative gain chart. From the results of experiments, 87.9% in the goodness of fit and 84.8% in the cross validation were evaluated, showing good prediction accuracies and not big difference between the results of the two evaluation methods. The results can be interpreted in terms of the use of environmental factors which are highly related to landslide occurrences and the accuracy of the prediction model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.177-185
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• 2015

City-based Lifeline is expected to cause significant social and economic loss accompanied the secondary damage such as paralysis of urban functions and a large fire as well as the collapse caused by earthquake. Earthquake Disaster Response System of Korea is being operated with preparation, calculates the probability of failure of the facility through Seismic Fragility Model and evaluates the degree of earthquake disaster. In this paper, the time history analysis of buried gas pipeline in city-based lifeline was performed with consideration for ground characteristics and also seismic fragility model was developed by maximum likelihood estimation method. Analysis model was selected as the high-pressure pipe and the normal-pressure pipe buried in the city of Seoul, Korea's representative, modeling of soil was used for Winkler foundation model. Also, method to apply developed fragility model at GIS is presented.

• Journal of the Korean Geosynthetics Society
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• v.14 no.4
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• pp.117-127
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• 2015

Recently, there has been a string of negligent accidents for the retaining wall and slope. In order to measure the ground deformation for the MSE wall, the authors carried out the model test to assess behavioral characteristics of geogrid MSE walls in active failure state with different conditions of geogrid reinforcement. The models are built in the soil container box having dimension, 100 cm long, 90 cm height, and 10 cm wide. The reinforcement used in the model test is geogrid (polyvinyl chloride, PVC). Three geogrids are sized by $30cm{\times}60cm$, $30cm{\times}70cm$, $30cm{\times}80cm$ (width ${\times}$ length) respectively. In this study, the laboratory model tests represented for several conditions of the MSE wall, and then its results were compared to 2D FE analysis.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.246-251
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• 2007

The purpose of this study is to develop a grid based model for calculating the critical nonpoint source (NPS) pollution load (BOD, TN, TP) in Nak-dong area in South Korea. In the last two decades, NPS pollution has become a topic for research that resulted in the development of numerous modeling techniques. Watershed researchers need to be able to emphasis on the characterization of water quality, including NPS pollution loads estimates. Geographic Information System (GIS) has been designed for the assessment of NPS pollution in a watershed. It uses different data such as DEM, precipitation, stream network, discharge, and land use data sets and utilizes a grid representation of a watershed for the approximation of average annual pollution loads and concentrations. The difficulty in traditional NPS modeling is the problem of identifying sources and quantifying the loads. This research is intended to investigate the correlation of NPS pollution concentrations with land uses in a watershed by calculating Expected Mean Concentrations (EMC). This work was accomplished using a grid based modelling technique that encompasses three stages. The first step includes estimating runoff grid by means of the precipitation grid and runoff coefficient. The second step is deriving the gird based model for calculating NPS pollution loads. The last step is validating the gird based model with traditional pollution loads calculation by applying statistical t-test method. The results on real data, illustrate the merits of the grid based modelling approach. Therefore, this model investigates a method of estimating and simulating point loads along with the spatially distributed NPS pollution loads. The pollutant concentration from local runoff is supposed to be directly related to land use in the region and is not considered to vary from event to event or within areas of similar land uses. By consideration of this point, it is anticipated that a single mean estimated pollutant concentration is assigned to all land uses rather than taking into account unique concentrations for different soil types, crops, and so on.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.802-809
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• 2010

An automatic calibration tool of Hydrological Simulation Program-Fortran (HSPF), Parameter Estimation (PEST) program, was applied at the Imha lake watershed to get optimal hydrological parameters of HSPF. Calibration of HSPF parameters was performed during 2004 ~ 2008 by PEST and validation was carried out to examine the model's ability by using another data set of 1999 ~ 2003. The calibrated HSPF parameters had tendencies to minimize water loss to soil layer by infiltration and deep percolation and to atmosphere by evapotranspiration and maximize runoff rate. The results of calibration indicated that the PEST program could calibrate the hydrological parameters of HSPF with showing 0.83 and 0.97 Nash-Sutcliffe coefficient (NS) for daily and monthly stream flow and -3% of relative error for yearly stream flow. The validation results also represented high model efficiency with showing 0.88 and 0.95, -10% relative error for daily, monthly, and yearly stream flow. These statistical values of daily, monthly, and yearly stream flow for calibration and validation show a 'very good' agreement between observed and simulated values. Overall, the PEST program was useful for automatic calibration of HSPF, and reduced numerous time and effort for model calibration, and improved model setup.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.6
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• pp.701-717
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• 2003

The objective of this study was to extensively estimate the air quality trends of the study area by surveying con-centration trends in months or seasons, after analyzing the mass concentration of PM-10 samples and the inorganic lements, ion, and total carbon in PM-10. Also, the study introduced to apply the PMF (Positive Matrix Factoriza-tion) model that is useful when absence of the source profile. Thus the model was thought to be suitable in Korea that often has few information about pollution sources. After obtaining results from the PMF modeling, the existing sources at the study area were qualitatively identified The PM-10 particles collected on quartz fiber filters by a PM-10 high-vol air sampler for 3 years (Mar. 1999∼Dec.2001) in Kyung Hee University. The 25 chemical species (Al, Mn, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, Pb, Si, N $a^{#}$, N $H_4$$^{+}$, $K^{+}$, $Mg^{2+}$, $Ca^{2+}$, C $l^{[-10]}$ , N $O_3$$^{[-10]}$ , S $O_4$$^{2-}$, TC) were analyzed by ICP-AES, IC, and EA after executing proper pre - treatments of each sample filter. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols. the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided source profiles (scaled F matrix). So, 11 sources were qualitatively identified, such as secondary aerosol related source, soil related source, waste incineration source, field burning source, fossil fuel combustion source, industry related source, motor vehicle source, oil/coal combustion source, non-ferrous metal source, and aged sea- salt source, respectively.ively.y.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.53-63
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• 2012

The objectives of this study were to develop a linked watershed-waterbody modeling system and to assess the impacts of indirect wastewater reuse on irrigation water quality. The Osan stream watershed within Gyeonggi-do of South Korea was selected for this study. The linked modeling system was composed of the SWAT (Soil and water assessment tool) and QUALKO2 models. The SWAT model was calibrated and validated using the stream discharge and water quality data from 2010 to 2011. Runoff and non-point source pollutants from each subbasin and stream discharge from 1980 to 2009 were simulated by the SWAT model and applied to the QUALKO2 model. The QUALKO2 model was calibrated and validated under the conditions of low water and normal discharges, respectively. Finally, The 10-day irrigation water quality from April to September was simulated. The statistical measures of coefficient of determination ($R^2$), reliability index (RI), and efficiency index (EI) were used to evaluate the system performance. The $R^2$, RI and EI values ranged from 0.5 to 1.0, 1.03 to 1.92, and -35.03 to 0.95, respectively. The 10-day irrigation water quality showed the concentrations of BOD and coliform exceeded the water quality guidelines for wastewater reuse. The linked modeling system can be a useful tool to estimate non-point source pollutant loads in watershed and to control the water quality of effluent from a wastewater treatment plant and irrigation water in the downstream waterbody.