• Journal of Environmental Impact Assessment
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• v.26 no.5
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• pp.291-302
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• 2017

The research was carried out in order to find climate factors which determine the distribution of Eurya japonica, and the potential habitats (PHs) under the current climate and climate change scenario by using species distribution models (SDMs). Four climate factors; the warmth index (WI), the minimum temperature of the coldest month (TMC), summer precipitation (PRS), and winter precipitaion (PRW) : were used as independent variables for the model. Seventeen general circulation models under RCP (Representative concentration pathway) 8.5 scenarios were used as future climate scenarios for the 2050s (2040~2069) and 2080s (2070~2099). Highly accurate SDMs were obtained for E. japonica. The model of distribution for E. japonica constructed by SDMs showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of E. japonica. The area above the $-5.7^{\circ}C$ of TMC revealed high occurrence probability of the E. japonica. Future PHs for E. japonica were projected to increase respectively by 2.5 times, 3.4 times of current PHs under 2050s and 2080s. It is expected that the potential of E. japonica habitats is expanded gradually. E. japonica is applicable as indicator species for monitoring in the Korean Peninsula. E. japonica is necessary to be monitored of potential habitats.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

• Journal of Life Science
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• v.18 no.1
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• pp.103-108
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• 2008

An agar-degrading marine bacterium, strain AS-1 was isolated from the seawater. The strain AS-1 was identified as Sphingomonas paucimobilis (90% probability) by VITEK. The optimum medium for agarase activity of the isolated strain was determined to be marine medium, marine broth 2216 containing 0.1% agar as carbon source. An extracellular agarase was purified 104-fold from the culture supernatant by ammonium sulfate precipitation, ion exchange chromatography and gel filtration methods. The molecular weight of the purified enzyme was estimated to be 80 kDa by SDS-PAGE. The optimum pH and temperature for activity were 7.0 and $40^{\circ}C$, respectively. Antioxidative activity of the strain AS- was 72% in the supernatant cultured for 12 h. The culture supernatant of the strain AS-1 showed antibacterial activity against bacteria causing putrefaction and food poisoning such as Escherichia coli, Staphylococcus aureus and Proteus vulgaris. However, the cell growth of the lactic aicd forming strain, Lactobacillus plantarium was promoted by the treatment of 10% culture supernatant of an agar-degrading strain.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.189-189
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• 2016

To generate information that contributes to climate change risk management, it is important to perform a precise assessment on the impact in diverse aspects. Considering this academic necessity, Japanese government launched continuous research project for the climate change impact assessment, and one of the representative project is Program for Risk Information on Climate Change (Sousei Program), Theme D; Precise Impact Assessment on Climate Change (FY2012 ~ FY2016). In this research program, quantitative impact assessments have been doing from a variety of perspectives including natural hazards, water resources, and ecosystems and biodiversity. Especially for the natural hazards aspect, a comprehensive impact assessment has been carried out with the worst-case scenario of typhoons, which cause the most serious weather-related damage in Japan, concerning the frequency and scale of the typhoons as well as accompanying disasters by heavy rainfall, strong winds, high tides, high waves, and landslides. In this presentation, a framework of comprehensive impact assessment with the worst-case scenario under the climate change condition is introduced based on a case study of Theme D in Sousei program There are approx. 25 typhoons annually and around 10 of those approach or make landfall in Japan. The number of typhoons may not change increase in the future, but it is known that a small alteration in the path of a typhoon can have an extremely large impact on the amount of rain and wind Japan receives, and as a result, cause immense damage. Specifically, it is important to assess the impact of a complex disaster including precipitation, strong winds, river overflows, and high tide inundation, simulating how different the damage of Isewan Typhoon (T5915) in 1959 would have been if the typhoon had taken a different path, or how powerful or how much damage it would cause if Isewan Typhoon occurs again in the future when the sea surface water temperature has risen due to climate changes (Pseudo global warming experiment). The research group also predict and assess how the frequency of "100-years return period" disasters and worst-case damage will change in the coming century. As a final goal in this research activity, the natural disaster impact assessment will extend not only Japan but also major rivers in Southeast Asia, with a special focus on floods and inundations.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.545-556
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• 2022

It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.1
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• pp.57-74
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• 2022

Seed zones were constructed using temperature and precipitation data for the Korean Peninsula and were described as 65 zones. Seed zones for South Korea were reclassified, and they were classified into 34 districts. This study was conducted to define the spread of 5 native seed species (Pinus densiflora, Quercus acutissima, Quercus variabilis, Acer pictum, Carpinus tschonoskii) by linking the seed zones with MaxEnt. The emergence point of native seeds was acquired through the 1:5,000 Forest Type Map and the 4th national natural environment survey data. Based on the MaxEnt result, regions with a habitat probability of 0.5 or more were extracted and overlapped with seed zones to identify the native seed habitat. After analyzing the climate regions with high habitat density, regions with high habitat density of native seeds for each administrative district were identified. In the case of Pinus densiflora, Quercus acutissima, and Quercus variabilis, the Winter minimum temperature(WMT) -9.4~-6.6℃, Annual Heat:Moisture(AH:M) 19~24℃/m was 37%, 43%, and 34%, respectively. occupied the largest area. In Acer pictum, WMT -6.6~-3.8℃ and AH:M 16~19℃/m accounted for 42% of the area, and Carpinus tschonoskii had WMT -3.8~-1.1℃, AH:M <16℃/m Districts accounted for the largest area at 33%. The regions with high density of Pinus densiflora, Quercus acutissima, and Quercus variabilis by administrative district were distributed in high density in Seoul, Southern Gyeonggi-do, Chungcheong-do, and Gyeongsangbuk-do. Acer pictum was distributed in high density in Jeolla-do and Gyeongsang-do, and Carpinus tschonoskii in Jeju, Jeollanam-do and Gyeongsangnam-do. Through this study, seed zones for each of the 5 native seeds were established, and it is expected to provide basic data for the management of native seeds.

• Journal of the Korean Geosynthetics Society
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• v.21 no.2
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• pp.31-38
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• 2022

Recently, irregular torrential rainfall have frequently occurred due to abnormal climate, and landslide damage is increasing. In Korea, more than 70% of the total land is mountainous areas, appropriate measures are needed to prevent landslides by heavy rainfall. When improved soil is applied to the surface of the slope, it is possible to suppress an increase in groundwater level due to rainfall penetration and secure stability of the slope. In this study, the appropriate depth of improved soil that can confirm the increase in groundwater level and secure stability by applying improved soil to the weathered soil slope was studied. A total of three cases were analyzed for the slope of the cross-section: standard slope for weathered soil (1:1.5, 1:1.8, and 1:2.0). For rainfall conditions, referring to the regional frequency probability rainfall provided by the Water resource Management Information System, the increase in groundwater level by stage was confirmed by assuming a 500-year frequency precipitation maximum duration of 48 hours. As a result of the study, in the case of natural slopes, the slope was completely saturated before 48 hours the rainfall duration, and there was a possibility of collapse. the improvement depth in the slope of 1:1.5 was appropriate for more than 1m from the surface regardless of the rainfall duration, and in the the slope of 1:1.8 was appropriate of 1m for more than 36 hours. in the slope of 1:2.0, it was appropriate for that safety when improved soil of 0.5m for rainfall duration 48 hours or more.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.599-606
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• 2010

Due to the short period of precipitation data in Korea, the uncertainty of drought analysis is inevitable from a point frequency analysis. So it is desired to introduce a regional drought frequency analysis. This study first extracted drought characteristics from 3-month and 12-month moving average rainfalls which represent short and long-term droughts, respectively. Then, the homogeneous regions were distinguished by performing a principal component analysis and cluster analysis. The Korean peninsula was classified into five regions based on drought characteristics. Finally, this study applied the bivariate frequency analysis using a kernel density function to quantify the regionalized drought characteristics. Based on the bivariate drought frequency curves, the drought severities of five regions were evaluated for durations of 2, 5, 10, and 20 months, and return periods of 5, 10, 20, 50, and 100 years. As a result, the largest severity of drought was occurred in the Lower Geum River basin, in the Youngsan River basin, and over in the southern coast of Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.257-264
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• 1991

Korea has accomplished the afforestation of its forest land in the early 1980's. To meet the increasing demand for forest products and forest recreation, a development of scientific forest management system is needed as a whole. For this purpose the development of efficient forestfire management system is essential. In this context, the purpose of this study is to develop a theoretical foundation of forestfire danger rating system. In this study, it is hypothesized that the degree of forestfire risk is affected by Weather Factor and Man-Caused Risk Factor. (1) To accommodate the Weather Factor, a statistical model was estimated in which weather variables such as humidity, temperature, precipitation, wind velocity, duration of sunshine were included as independent variables and the probability of forestfire occurrence as dependent variable. (2) To account man-caused risk, historical data of forestfire occurrence was investigated. The contribution of man's activities make to risk was evaluated from three inputs. The first, potential risk class is a semipermanent number which ranks the man-caused fire potential of the individual protection unit relative to that of the other protection units. The second, the risk sources ratio, is that portion of the potential man-caused fire problem which can be charged to a specific cause. The third, daily activity level is that the fire control officer's estimate of how active each of these sources is, For each risk sources, evaluate its daily activity level ; the resulting number is the partial risk factor. Sum up the partial risk factors, one for each source, to get the unnormalized Man-Caused Risk. To make up the Man-Caused Risk, the partial risk factor and the unit's potential risk class were considered together. (3) At last, Fire occurrence index was formed fire danger rating estimation by the Weather Factors and the Man-Caused Risk Index were integrated to form the final Fire Occurrence Index.