• Journal of Wetlands Research
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• v.23 no.4
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• pp.277-286
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• 2021

This study compares the long-term hydrological cycles of the Seolmacheon and Cheongmicheon basin by applying the structural equation model (SEM). These two basins are found different especially in their land-use pattern. Both basins have the actual evapotranspiration data measured by the eddy-covariance method as well as the rainfall and runoff data. The length of the data considered in this study is nine years from 2010 to 2018. The structure of the SEM is determined by considering the correlations among the data as well as the general knowledge on the hydrological cycle. As a result, a total of three SEMs are applied sequentially to analyze their fittings. As irony would have it, two basins are found to be similar in the application of one SEM, but different in the application of another. Especially, when considering the feedback process between precipitation and evapotranspiration, two basins are found to be very different. That is, the feedback process between precipitation and evapotranspiration is found to be significant in the Cheongmicheon basin where the portion of agricultural area (i.e., paddy) is more than 40%.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• Korean Journal of Breeding Science
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• v.49 no.3
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• pp.180-189
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• 2017

Genetically modified (GM) crops have been developed worldwide through the recombinant DNA technology and commercialized by global agricultural companies. Until now, GM crops have not been cultivated commercially in Korea. Commercialization of GM crops requires a compulsory assessment of environmental risk associated with the release of GM crops. This study was conducted to evaluate the frequency of pollen mediated gene flow from Bt transgenic rice (Agb0101) to japonica non-GM rice (Nakdongbyeo), indica non-GM rice (IR36), and weedy rice (R55). A total of 729,917, 596,318 and 230,635 seeds were collected from Nakdongbyeo, IR36, and R55, respectively, which were planted around Agb0101. Selection of the hybrids was determined by repeated spraying of herbicide and Cry1Ac1 immunostrip assay. Finally, the hybrids were confirmed by PCR analysis using specific primer. The hybrids were found in all non-GM rice and out-crossing ranged from 0.0005% at IR36 to 0.0027% at Nakdongbyeo. All of hybrids were located within 1.2 m distance from the Agb0101 rice plot. The meteorological elements including rainfall and temperature during rice flowering time were found to be important factors to determine rice out-crossing rate. Consideration should be taken for many factors like the meteorological elements of field and physiological condition of crop to set up the safety management guideline to prevention of GM crops gene flow.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1247-1260
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• 2018

This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affecting South Korea, total rainfall amount and number of rainy days during the monsoon season in South Korea. For this analysis, the monthly AOI data were transformed into the average data about January and seasonal AOI data representing winter, spring, fall and winter. The typhoon data and monsoon data were all those collected annually. The data period for this analysis was determined to be from 1961 to 2016 by considering the data available. Based on this analysis, it was found that the arctic oscillation has a weak but statistically significant effect on the monsoon characteristics of South Korea. However, the level of effect was not consistent over the data period but varied significantly periodically. For example, the cross-correlation coefficient derived for the recent 10 years was estimated to be higher than 0.8, but was simply insignificant during the 30 years before the last decade. The overall effect of arctic oscillation on the occurrence of typhoon was found to be statistically insignificant, but was also fluctuating periodically to show somewhat significant effect. Finally, it should be mentioned that the effect of arctic oscillation on the typhoon and monsoon had been changing by turns from 1960s to 2000s. However, in the 2010s, it happened that the effect of arctic oscillation has become significant on both typhoon and monsoon in South Korea.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.39-50
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• 2012

KMA(Korea Meteorological Administration) projected that annual mean temperatures of South Korea will rise $3.8^{\circ}C$ and the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea. Thus the risk of landslide by heavy rain is expected to increase. After the landslide of Mt. Umyeon occurred in July 2011, disaster of forest sector is highlighted. Therefore vulnerability assessment of landslide is urgent. However, vulnerability assessment based on local governments was not done yet. In this study, we assess vulnerability of landslide by heavy rain for local governments. We used several scenarios to consider uncertainty of climate change. Through this study, local governments can use the results to establish adaptation plans. Also, the results could be used to decrease vulnerability of landslide.

• Journal of the Geological Society of Korea
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• v.54 no.5
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• pp.545-556
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• 2018

This study was conducted to estimate the deep percolation using numerical modeling and field observation data based on rainfall in Haean basin. Soil moisture sensors were installed to monitoring at 30, 60 and 90 cm depths in four sites (YHS1-4) and automatic weather station was installed to around YHS3. Soil moisture and meteorological data was observed from March 25, 2017 to March 25, 2018 and May 06, 2016 to May 06, 2018, respectively. Numerical analysis was performed from June to August, 2017 using the HYDRUS-1D. Average soil moisture contents were high to generally in YHS3 for 0.300 to $0.334m^3/m^3$ and lowest in YHS1 for 0.129 to $0.265m^3/m^3$ during the soil moisture monitoring period. The results of soil moisture flow modeling showed that field observations and modeling values were similar but the peak values were larger in the modeling result. Correlation analysis between observation and modeling data showed that r, $r^2$ and RMSE were 0.88, 0.77, and 0.0096, respectively. This show high correlation and low error rate. The total deep percolation was 744.2 mm during the period of modelling at 500 cm depth. This showed that 61.3% of the precipitation amount (1,214 mm) was recharged in 2017. Deep percolation amount was high in the study area. This study is expected to provide basic data for the estimation of groundwater recharge through unsaturated zone.

• The Journal of Engineering Geology
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• v.29 no.1
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• pp.23-35
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• 2019

Landslides occur due to heavy rainfall in the summer season. Some of water may infiltrate into the ground; it causes a high saturation condition capable of causing a landslide. Soil properties are crucial in estimating slope stability and debris flow occurrence. The main study areas are Gwanaksan, Suraksan and Bukhansan (Mountain) in Seoul. A total of 44 soil samples were taken from the study area; and a series of geotechnical tests were performed. Physical and mechanical properties were obtained and compared based on region. As a result, among well-graded soils, they are classified as a clayey sand. Coarse-grained and fine-grained contents are approximately 95% and 5%, respectively, with very low amount of clay content. Density, liquid limit and dry unit weight are ranged in $2.62{\sim}2.67g/cm^3$, 27.93~38.15% and $1.092{\sim}1.814g/cm^3$. Cohesion and internal friction angle are 4 kPa and $35^{\circ}$ regardless of mountain area. Coefficient of permeability is varied between $3.07{\times}10^{-3}{\sim}4.61{\times}10^{-2}cm/sec$; it means that it results in great seepage. Permeability is inversely proportional to the uniformity coefficient and is proportional to the effective particle size. In the formal case, there was a difference by mountain area, while in the latter, the tendency was almost similar.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.289-299
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• 2021

This study analyzes bifurcation characteristics of the Seolmacheon experimental catchment by extracting the shape variation of channel network due to variable scale of source basin or threshold area. As the area of source basin decreases, a bifurcation process of channel network occurs within the basin of interest, resulting in the elongation of channel network (increase of total channel length) as well as the expansion of channel network (increase of the source number). In the former case, the elongation of channel reaches overwhelms the generation of sources, whereas, in the latter case, the drainage path network tends to fulfill the inner space of the basin of interest reflecting the opposite trend. Therefore, scale invariance of natural channel network could be expressed to be a balanced geomorphologic feature between the elongation of channel network and the expansion of channel network due to decrease of source basin scale. The bifurcation structure of the Seolmacheon experimental catchment can be characterized by the coexistence of the elongation and scale invariance of channel network, and thus a further study is required to find out which factor is more crucial to rainfall transformation into runoff.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.60-66
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• 2020

Torrential rain causes landslide damage every year. In particular, the 2011 downpour caused landslides at numerous points throughout Mt. Woomyeon, which resulted in considerable damage to people and property. Because it occurred in an urban area, this case became a major social issue and received public attention. Measures were quickly implemented for multilateral investigations and recovery. Landslides caused by heavy rain are greatly affected by rainfall at the time. Landslides from the upper part erode the flow path, increasing the size, causing much damage to the lower part. This study selected a rural village area among the damaged areas of Mt. Woomyeon, and analyzed the change in terrain profile before and after a landslide using the DSM data obtained from airborne LiDAR. This area can be divided into three hydrological basins. For each basin, the analysis was performed on the average slope of each part of the flow path, as well as the erosion and deposition due to soil flow. As a result of the analysis, it was estimated that the total amount of soil from the Jeonwon village was 15,300㎥. These field data based on GIS can be used as basic information to predict damage in the case of a similar disaster, and it can be helpful in analyzing the results of various debris flow simulations.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.