• Korean Journal of Environmental Agriculture
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• v.26 no.4
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• pp.343-350
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• 2007

Three different experiments were carried out to investigate the runoff and erosion losses of endosulfan from sloped-field by rainfall. The mobility of endosulfan and which phase it was transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide loss were evaluated in simulated rainfall study, and the pesticide losses from soybean-grown field comparing with bare soil were measured in field lysimeter study. Adsorption parameter (K) of endosulfan ranged from 77 to 131 by adsorption method and K values by the desorption method were higher than those by the adsorption method. By the SSLRC's classification for pesticide mobility endosulfan was classified as non-mobile class ($K_{oc}>4,000$). Runoff and erosion loss of endosulfan by three rainfall scenarios ranged from 3.4 to 5.6%and from 4.4 to 15.6%of the amount treated. Endosulfan residues were mainly remained at the top 5 cm of soil depth after the simulated rainfall study. Pesticide loss in case of 30%-slope degree ranged from 0.6 to 0.9 times higher than those in case of 10%-slope degree. The difference of pesticide runoff loss was related with its concentration in runoff water and the difference of pesticide erosion loss would related closely with the quantity of soil eroded. Endosulfan losses from a series of lysimeter plots in sloped land by rainfall ranged from 5 to 35% of the amount treated. The erosion rate of endosulfan from soybean-plots was 66% of that from bare soil plots. The effect of slope conditions was not great for runoff loss, but was great for erosion loss as increasing to maximum $4{\sim}12$ times with slope degree and slope length. The peak runoff concentration of endosulfan in soybean-plots and bare soil plots ranged from 8 to 10 and from 7 to $9{\mu}gL^{-1}$ on nine plots with different slope degree and slope length. Therefore the difference of the peak runoff concentrations between bare soil plots and soybean-plots were not great.

• Journal of Environmental Impact Assessment
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• v.23 no.5
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• pp.379-392
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• 2014

This study was performed to predict the future climate envelope of Pinus pumila, a subalpine plant and a Climate-sensitive Biological Indicator Species (CBIS) of Korea. P. pumila is distributed at Mt. seorak in South Korea. Suitable habitat were predicted under two alternative RCPscenarios (IPCC AR5). The SDM used for future prediction was a Maxent model, and the total number of environmental variables for Maxent was 8. It was found that the distribution range of P. pumila in the South Korean was $38^{\circ}7^{\prime}8^{{\prime}{\prime}}N{\sim}38^{\circ}7^{\prime}14^{{\prime}{\prime}}N$ and $128^{\circ}28^{\prime}2^{{\prime}{\prime}}E{\sim}128^{\circ}27^{\prime}38^{{\prime}{\prime}}E$ and 1,586m~1,688m in altitude. The variables that contribute the most to define the climate envelope are altitude. Climate envelope simulation accuracy was evaluated using the ROC's AUC. The P. pumila model's 5-cv AUC was found to be 0.99966. which showed that model accuracy was very high. Under both the RCP4.5 and RCP8.5 scenarios, the climate envelope for P. pumila is predicted to decrease in South Korea. According to the results of the maxent model has been applied in the current climate, suitable habitat is $790.78km^2$. The suitable habitats, are distributed in the region of over 1,400m. Further, in comparison with the suitable habitat of applying RCP4.5 and RCP8.5 suitable habitat current, reduction of area RCP8.5 was greater than RCP4.5. Thus, climate change will affect the distribution of P. pumila. Therefore, governmental measures to conserve this species will be necessary. Additionally, for CBIS vulnerability analysis and studies using sampling techniques to monitor areas based on the outcomes of this study, future study designs should incorporate the use of climatic predictions derived from multiple GCMs, especially GCMs that were not the one used in this study. Furthermore, if environmental variables directly relevant to CBIS distribution other than climate variables, such as the Bioclim parameters, are ever identified, more accurate prediction than in this study will be possible.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.579-596
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• 1997

A simulation study was carried out to delineate potential effects of the lake-induced climate change on crop productivity around Lake Imha which was formed after a multi-purpose dam construction in Andong, Korea. Twenty seven cropping zones were identified within the 30 km by 25 km study area. Five automated weather stations were installed within the study area and operated for five years after the lake formation. A geostatistical method was used to calculate the monthly climatological normals of daily maximum and minimum temperature, solar radiation and precipitation for each cropping zone before and after the dam construction. Daily weather data sets for 30 years were generated for each cropping zone from the monthly normals data representing "No lake" and "After lake" climatic scenarios, respectively. They were fed into crop models (ORYZA1 for rice, SOYGRO for soybean, CERES-maize for corn) to simulate the yield potential of each cropping zone. Calculated daily maximum temperature was higher after the dam construction for the period of October through March and lower for the remaining months except June and July. Decrease in daily minimum temperature was predicted for the period of April through August. Monthly total radiation was predicted to decrease after the lake formation in all the months except February, June, and September and the largest drop was found in winter. But there was no consistent pattern in precipitation change. According to the model calculation, the number of cropping zones which showed a decreased yield potential was 2 for soybean and 6 for corn out of 27 zones with a 10 to 17% yield drop. Little change in yield potential was found at most cropping zones in the case of paddy rice, but interannual variation was predicted to increase after the lake formation. the lake formation.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.59-75
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• 2020

This study is a case study that applied 'UNDRR's Urban Disaster Resilience Scorecard', an evaluation tool necessary for Incheon Metropolitan City to be certified as an international safe city. I would like to present an example that the results derived from this scorecard contributed to the Incheon Metropolitan City Disaster Reduction Plan. Of course, the Disaster Resilience Scorecard can't provide a way to improve the resilience of every disaster facing the city. However, it is to find the weakness of the resilience that the city faces, and to propose a solution to reduce the city's disaster risk. This is to help practitioners to recognize the disaster risks that Incheon Metropolitan City faces. In addition, the solution recommended by UNDRR was suggested to provide resilience in areas vulnerable to disasters. It was confirmed that this process can contribute to improving the disaster resilience of Incheon Metropolitan City. UNDRR has been spreading 'Climate Change, Disaster-resistant City Creation Campaign', aka MCR (Making Cities Resilient) Campaign, to cities all over the world since 2010 to reduce global cities' disasters. By applying the disaster relief guidelines adopted by UNDRR, governments, local governments, and neighboring cities are encouraged to collaborate. As a result of this study, Incheon Metropolitan city's UN Urban Resilience Scorecard was evaluated as a strong resilience field by obtaining scores of 4 or more (4.3~5.0) in 5 of 10 essentials; 1. Prepare organization for disaster resilience and prepare for implementation, 4. Strong resilience Urban development and design pursuit, 5. Preservation of natural cushions to enhance the protection provided by natural ecosystems, 9. Ensure effective disaster preparedness and response, 10. Rapid restoration and better reconstruction. On the other hand, in the other five fields, scores of less than 4 (3.20~3.85) were obtained and evaluated as weak resilience field; 2. Analyze, understand and utilize current and future risk scenarios, 3. Strengthen financial capacity for resilience, 6. Strengthen institutional capacity for resilience, 7. Understanding and strengthening social competence for resilience, 8. Strengthen resilience of infrastructure. In addition, through this study, the risk factors faced by Incheon Metropolitan City could be identified by priority, resilience improvement measures to minimize disaster risks, urban safety-based urban development plans, available disaster reduction resources, and integrated disasters. Measures were prepared.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.134-153
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• 2015

When making urban planning, it is important to understand climate effect caused by urban structural changes. Seoul city applies UPIS(Urban Plan Information System) which provides information on urban planning scenario. Technology for analyzing climate effect resulted from urban planning needs to developed by linking urban planning scenario provided by UPIS and climate analysis model, CAS(Climate Analysis Seoul). CAS develops for analyzing urban climate conditions to provide realistic information considering local air temperature and wind flows. Quantitative analyses conducted by CAS for the production, transportation, and stagnation of cold air, wind flow and thermal conditions by incorporating GIS analysis on land cover and elevation and meteorological analysis from MetPhoMod(Meteorology and atmospheric Photochemistry Meso-scale model). In order to reflect land cover and elevation of the latest information, CAS used to highly accurate raster data (1m) sourced from LiDAR survey and KOMPSAT-2(KOrea Multi-Purpose SATellite) satellite image(4m). For more realistic representation of land surface characteristic, DSM(Digital Surface Model) and DTM(Digital Terrain Model) data used as an input data for CFD(Computational Fluid Dynamics) model. Eight inflow directions considered to investigate the change of flow pattern, wind speed according to reconstruction and change of thermal environment by connecting green area formation. Also, MetPhoMod in CAS data used to consider realistic weather condition. The result show that wind corridors change due to reconstruction. As a whole surface temperature around target area decreases due to connecting green area formation. CFD model coupled with CAS is possible to evaluate the wind corridor and heat environment before/after reconstruction and connecting green area formation. In This study, analysis of climate impact before and after created the green area, which is part of 'Connecting green network across the north and south in Seoul' plan, one of the '2020 Seoul master plan'.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Journal of the Korean Geographical Society
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• v.42 no.1 s.118
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• pp.133-155
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• 2007

The sustainable urban development has emerged as a new paradigm of urban studies in recent years. A review of the literature of land use and transport policies in relation to sustainable development reveals a consensus that the main objectives of sustainable strategy should decrease the numbers and length of journeys, and change the land use pattern towards mixed use and high density. However, there is a lack of empirical research as to what types of policies might influence effectively the reduction in the energy consumption and emission of $CO_2$. in order to sustain urban development. This paper tries to construct the conceptual structure of the PSS(planning support system), which is designed to the simulation of the probable effects of policies and planning of different kinds in cities, and evaluate the sustainablilty level according to construct the structure of the PSS(planning support system), which is designed to the simulation of the probable effects of policies and planning of different kinds in cities, and evaluate the sustainablilty level according to the alternative scenarios. The PSS is composed of three components (input-modeling-output). The core of PSS is integrating land use-transport-environment modeling. The advantages of integrating land use-transport-environment modeling are well known, but there are very few such integrated modeling packages in practice. So this paper tries to apply TRANUS software, which is an integrated land use and transport model. The TRANUS system was calibrated to city of Yongin for the base year. The purpose of the application of TRANUS to Yongin is to examine the operability of TRANUS system in Korea. From the outputs and results of operating the system, TRANUS may be effectively used to evaluate the effects of alternative sustainable urban development policies, since sustainablilty indicators can be extracted from several aspects such as land use consumption, total trips, distance and cost, energy consumption, ratio of transport split.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.779-797
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• 2016

A calibrated hydrological model is a useful tool for quantifying the impacts of the climate variations and land use/land cover changes on sediment load, water quality and runoff. In the rainy season each year, the Xe Bang Fai river basin is provisionally flooded because of typhoons, the frequency and intensity of which are sensitive to ongoing climate change. Severe heavy rainfall has continuously occurred in this basin area, often causing severe floods at downstream of the Xe Bang Fai river basin. The main purpose of this study is to investigate the climate change impact on river discharge using a Soil and Water Assessment Tool (SWAT) model based on future climate change scenarios. In this study, the simulation of hydrological river discharge is used by SWAT model, covering a total area of $10,064km^2$ in the central part of country. The hydrological model (baseline) is calibrated and validated for two periods: 2001-2005 and 2006-2010, respectively. The monthly simulation outcomes during the calibration and validation model are good results with $R^2$ > 0.9 and ENS > 0.9. Because of ongoing climate change, three climate models (IPSL CM5A-MR 2030, GISS E2-R-CC 2030 and GFDL CM3 2030) indicate that the rainfall in this area is likely to increase up to 10% during the summer monsoon season in the near future, year 2030. As a result of these precipitation increases, the SWAT model predicts rainy season (Jul-Aug-Sep) river discharge at the Xebangfai@bridge station will be about $800m^3/s$ larger than the present. This calibrated model is expected to contribute for preventing flood disaster risk and sustainable development of Laos

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.