• Journal of the Korean earth science society
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• v.42 no.5
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• pp.496-503
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• 2021

By analyzing the characteristics of atmospheric stability in the southern coastal region of the Korean Peninsula in the summer of 2019, a quantitative threshold of atmospheric instability indices was derived for predicting rainfall events in the Korean Peninsula. For this analysis, we used data from all of the 243 radiosonde intensive observations recorded at the Boseong Standard Weather Observatory (BSWO) in the summer of 2019. To analyze the atmospheric stability of rain events and mesoscale atmospheric phenomena, convective available potential energy (CAPE) and storm relative helicity (SRH) were calculated and compared. In particular, SRH analysis was divided into four levels based on the depth of the atmosphere (0-1, 0-3, 0-6, and 0-10 km). The rain events were categorized into three cases: that of no rain, that of 12 h before the rain, and that of rain. The results showed that SRH was more suitable than CAPE for the prediction of the rainfall events in Boseong during the summer of 2019, and that the rainfall events occurred when the 0-6 km SRH was 150 m² s^-2 or more, which is the same standard as that for a possible weak tornado. In addition, the results of the atmospheric stability analysis during the Changma, which is the rainy period in the Korean Peninsula during the summer and typhoon seasons, showed that the 0-6 km SRH was larger than the mean value of the 0-10 km SRH, whereas SRH generally increased as the depth of the atmosphere increased. Therefore, it can be said that the 0-6 km SRH was more effective in determining the rainfall events caused by typhoons in Boseong in the summer of 2019.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.480-489
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• 2021

Climate change poses great threats to wildlife populations by decreasing their number and destroying their habitats, jeopardizing biodiversity conservation. Asiatic salamander (Hynobiidae) species are particularly vulnerable to climate change due to their small home range and limited dispersal ability. Thus, this study used one salamander species, the Korean clawed salamander (Onychodactylus koreanus), as a model species and examined their habitat characteristics and current distribution in South Korea to predict its spatial distribution under climate change. As a result, we found that altitude was the most important environmental factor for their spatial distribution and that they showed a dense distribution in high-altitude forest regions such as Gangwon and Gyeongsanbuk provinces. The spatial distribution range and habitat characteristics predicted in the species distribution models were sufficiently in accordance with previous studies on the species. By modeling their distribution changes under two different climate change scenarios, we predicted that the distribution range of the Korean clawed salamander population would decrease by 62.96% under the RCP4.5 scenario and by 98.52% under the RCP8.5 scenario, indicating a sharp reduction due to climate change. The model's AUC value was the highest in the present (0.837), followed by RCP4.5 (0.832) and RCP8.5 (0.807). Our study provides a basic reference for implementing conservation plans for amphibians under climate change. Additional research using various analysis techniques reflecting habitat characteristics and minute habitat factors for the whole life cycle of Korean-tailed salamanders help identify major environmental factors that affect species reduction.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.504-515
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• 2021

To examine the relationship between environmental factors influencing the habitat of Aconitum austrokoreense Koidz., this study employed the MexEnt model to evaluate 21 environmental factors. Fourteen environmental factors having an AUC of at least 0.6 were found to be the age of stand, growing stock, altitude, topography, topographic wetness index, solar radiation, soil texture, mean temperature in January, mean temperature in April, mean annual temperature, mean rainfall in January, mean rainfall in August, and mean annual rainfall. Based on the response curves of the 14 descriptive factors, Aconitum austrokoreense Koidz. on the Baekun Mountain were deemed more suitable for sites at an altitude of 600 m or lower, and habitats were not significantly affected by the inclination angle. The preferred conditions were high stand density, sites close to valleys, and distribution in the northwestern direction. Under the five-age class system, the species were more likely to be observed for lower classes. The preferred solar radiation in this study was 1.2 MJ/m². The species were less likely to be observed when the topographic wetness index fell below the reference value of 4.5, and were more likely observed above 7.5 (reference of threshold). Soil analysis showed that Aconitum austrokoreense Koidz. was more likely to thrive in sandy loam than clay. Suitable conditions were a mean January temperature of - 4.4℃ to -2.5℃, mean April temperature of 8.8℃-10.0℃, and mean annual temperature of 9.6℃-11.0℃. Aconitum austrokoreense Koidz. was first observed in sites with a mean annual rainfall of 1,670- 1,720 mm, and a mean August rainfall of at least 350 mm. Therefore, sites with increasing rainfall of up to 390 mm were preferred. The area of potential habitats having distributive significance of 75% or higher was 202 ha, or 1.8% of the area covered in this study.

• Clean Technology
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• v.25 no.2
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• pp.107-113
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• 2019

Numerical model that considered the shrinking core model and elutriation and degradation of particles was developed to predict selective chlorination of ilmenite and carbo-chlorination of $TiO_2$ in a two stage fluidized bed chlorination furnace. It is possible to analyze the fluidized bed chlorination reaction to be able to reflect particle distribution for mass balances and the chlorination reaction. The numerical model showed an accuracy with error less than 6% compared with fluidized bed experiments. The chlorination degree with particle size change was greater with a smaller particle size, and there was a 100 min difference to obtain a chlorination degree of 1 between $75{\mu}m$ and $275{\mu}m$. This was not shown to such a great extent with variation of temperature ($800{\sim}1000^{\circ}C$), and there was only a 10 min difference to obtain a chlorination degree of 0.9. In the first selective chlorination process, the mass reduction rate approached to the theoretical value of 0.4735 after 180 min, and chlorination changed the Fe component into $FeCl_2$ or $FeCl_3$ and showed nearly 1. In the second carbo-chlorination process, the chlorination degree of $TiO_2$ approached 0.98 and the mass fraction reached 0.02 with conversion into $TiCl_4$. In the first selective chlorination process, 98% of $TiO_2$ was produced at 180 min, and this was changed into 99% of $TiCl_4$ after an additional 90 min. Also the mass reduction rate of $TiO_2$ was reduced to 99% in the second continuous carbo-chlorination process.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.562-581
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• 2018

This study was designed to predict the changes in species richness of plants under the climate change in South Korea. The target species were selected based on the Plants Adaptable to Climate Change in the Korean Peninsula. Altogether, 89 species including 23 native plants, 30 northern plants, and 36 southern plants. We used the Species Distribution Model to predict the potential habitat of individual species under the climate change. We applied ten single-model algorithms and the pre-evaluation weighted ensemble method. And then, species richness was derived from the results of individual species. Two representative concentration pathways (RCP 4.5 and RCP 8.5) were used to simulate the species richness of plants in 2050 and 2070. The current species richness was predicted to be high in the national parks located in the Baekdudaegan mountain range in Gangwon Province and islands of the South Sea. The future species richness was predicted to be lower in the national park and the Baekdudaegan mountain range in Gangwon Province and to be higher for southern coastal regions. The average value of the current species richness showed that the national park area was higher than the whole area of South Korea. However, predicted species richness were not the difference between the national park area and the whole area of South Korea. The difference between current and future species richness of plants could be the disappearance of a large number of native and northern plants from South Korea. The additional reason could be the expansion of potential habitat of southern plants under climate change. However, if species dispersal to a suitable habitat was not achieved, the species richness will be reduced drastically. The results were different depending on whether species were dispersed or not. This study will be useful for the conservation planning, establishment of the protected area, restoration of biological species and strategies for adaptation of climate change.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.41-54
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• 2021

It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.451-468
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• 2021

Predicting hazardous ground conditions ahead of a TBM (Tunnel Boring Machine) tunnel face is essential for efficient and stable TBM advance. Although there have been several studies on the electrical resistivity survey method for TBM tunnelling, sufficient experimental data considering TBM advance were not established yet. Therefore, in this study, the laboratory-scale model experiments for simulating TBM excavation were carried out to analyze the applicability of an electrical resistivity survey for predicting hazardous ground conditions ahead of a TBM tunnel face. The trend of electrical resistivity during TBM advance was experimentally evaluated under various hazardous ground conditions (fault zone, seawater intruded zone, soil to rock transition zone, and rock to soil transition zone) ahead of a tunnel face. In the course of the experiments, a scale-down rock ground was provided using granite blocks to simulate the rock TBM tunnelling. Based on the experimental data, the electrical resistivity tends to decrease as the tunnel approaches the fault zone. While the seawater intruded zone follows a similar trend with the fault zone, the resistivity value of the seawater intrude zone decreased significantly compared to that of the fault zone. In case of the soil-to-rock transition zone, the electrical resistivity increases as the TBM approaches the rock with relatively high electrical resistivity. Conversely, in case of the rock-to-soil transition zone, the opposite trend was observed. That is, electrical resistivity decreases as the tunnel face approaches the rock with relatively low electrical resistivity. The experiment results represent that hazardous ground conditions (fault zone, seawater intruded zone, soil-to-rock transition zone, rock-to-soil transition zone) can be efficiently predicted by utilizing an electrical resistivity survey during TBM tunnelling.