• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.51-64
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• 2022

Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.613-621
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• 2022

Due to the global climate change, the rainfall volume and frequency on the Korean Peninsula are predicted to increase at the end of the 21st century. In addition, impervious surface areas have increased due to rapid urbanization which has caused the urban water cycle to deteriorate. Green Infrastructure (GI) researches have been conducted to improve the water cycle soundness; the efficiency of this technique has been verified through various studies. However, there are still no suitable GI design guidelines for this aspect. Therefore, the rainfall scenarios are set up for each percentile (60, 70, 80, 90) based on the volume and frequency analysis using 10-year rainfall data (Busan Meteorological Station). After determining the GI areas for each scenario, the runoff reduction characteristics are analyzed based on Storm Water Management Model (SWMM) 10-year rainfall-runoff-simulations. The total runoff reduction efficiency for each GI areas are computed to have a range of 13.1~52.1%. As a results of the quantitative analysis, the design rainfall for GI is classified into the 80~85 percentile in the study site.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.70-77
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• 2023

In response to climate change, each country is proposing a goal to reduce greenhouse gases in its energy supply and demand plan, and the use of hydrogen gas is a topic that is always prioritized as an energy resource for implementation. A popular way to use this hydrogen gas is the use of hydrogen fuel cell vehicles, and expansion of hydrogen charging stations is essential for using these hydrogen fuel cell vehicles. However, there are several limitations to the expansion of hydrogen refueling stations, the most representative of which is resident acceptance. Most of the hydrogen charging stations currently built in Korea are located in the outskirts with low population density, so the inconvenience to hydrogen fuel cell vehicle users has not been resolved, and as a result, there has been no progress in the spread of hydrogen fuel cell vehicles. In this paper, we analyzed the consequences of accident damage to determine the risks of constructing a hydrogen charging station on a railroad site frequently used by citizens. The target hydrogen charging station site was a railroad depot in Busan, and there are trains, national highways, and commercial facilities around this site. Assuming the worst-case scenario, we would like to consider the safety of the hydrogen refueling station site by analyzing the area affected by the accident and its consequence.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.215-222
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• 2017

The potential change of the cultivation area of main citrus cultivars, satsuma mandarin (Citrus unshiu Marc.) and 'Shiranuhi' mandarin hybrid [(Citrus unshiu ${\times}$ C. sinensis) ${\times}$ C. reticulata] were determined with base year (1981 to 2010) to 2090. The meteorological data provided by the Korea Meteorological Administration (KMA), and the digital agricultural climate map of 30m-solution based on the Representative Concentration Pathways (RCP) 8.5 was used for projection of potential cultivation area. As a result, the potential suitable region of satsuma mandarin included almost Jeju region during base year. At the 2030s, the potential suitable region of satsuma mandarin increased and the cultivable region also increased focused on the coast region of Jeonnam province. From the 2060s, the suitable area spread out to mountain area of Jeju, Jeonnam, Gyeongnam, and the coast region of Kangwon, and the cultivable region expanded to the area of Gyeongbuk, Chungnam, and Jeonbuk. In the case of 'Shiranuhi' mandarin hybrid, the suitable region included only the partial coast area of Jeju, and cultivable area covered Jeju region and the partial southern coast of Jeonnam during the standard period. At the 2030s, the suitable region of 'Shiranuhi' included the current cultivation area of satsuma mandarin, and the cultivable region moved to northward by the partial southern coast region. At the 2090s, the slightly increased suitable region covered all Jeju regions, Jeonnam, Gyeongnam, and the coast area of Kangwon, and the cultivable region proceeded northward focusing on the coastline. In conclusion, the prediction of the potential land for citrus cultivation based on the RCP 8.5 showed that the suitable region of satsuma mandarin decreased, whereas that of cultivation of 'Shiranuhi' increased. Moreover, it was forecasted that citrus cultivation area would extend to Kangwon region at the end of the $21^{st}$ century.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.353-362
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• 2018

The purpose of this study is to suggest a structure plan for improving the utilization of inactive storage in the dam for overcoming the drought. Inactive storage in the dam is composed of the emergency storage and dead storage. The emergency storage can be used for the case of emergency such as drought. But, in general, the dead storage for sedimentation is not used even for the emergency. Therefore, this study considers the part of dead storage that the sedimentation is not progressed yet can be used during the severe drought period and is called "drought storage in a dam". The accurate Sediment Level(SL) analysis for the computation of the drought storage should be performed and so the present and future SL in the dam reservoir is estimated using SED-2D linked with RMA-2 model of SMS. After the consideration of additionally available storage capacity based on the estimated SL, the drought storage is finally determined. Present data based on historical data, future predicted future climate factors by Representative Concentrarion Pathways(RCP) 8.5 scenario. Then, using the TANK model, dam inflows were determined, and future period such as SL and drought storage were suggested. As the results, we have found that the available drought storage will be reduced in the future when we compare the present drought storage with the future one. This is due to a increase variability of climate change. Therefore, we should take the necessary study for the increase of available drought storage in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.630-638
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• 2011

This study aims to verify the economic validity of the REDD project in North Korea by estimating the potential carbon credits and the cost of REDD project. The REDD potential credits of North Korea are estimated based on the international statistics of forest area and population from 1990 to 2010, and the cost of REDD project is estimated indirectly by annual land opportunity cost of agriculture assuming that South Korea will aid the food production per area in North Korea. When the 25% reduction scenario was applied to the annual deforestation rate in North Korea, the potential REDD credits were estimated to be $4,232million{\sim}5,290milliontCO_2eq.$ for 20 years. It would account for 28~35% of South Korea's national medium-term greenhouse gas reduction target. On the other hand, the break-even price of REDD project was calculated as the profit of agriculture in the land available by forest conversion in North Korea. It was estimated to be 19.19$/$tCO_2eq.$ when the non-permanence risk of forest conserved through a REDD contract is assumed to be 20%. This price is higher than the price of REDD carbon credit 5$/$tCO_2eq.$ dealt in the 2010 voluntary carbon market, leading to no economic feasibility. However, REDD project provides co-benefits besides climate mitigation. As previous studies indicate, the break-even price is lower than 20$/$tCO_2eq.$, which is the social marginal cost of greenhouse gas emissions by loss of forest. Therefore REDD in North Korea can be justified against the social benefits. The economic feasibility of REDD project in North Korea can be largely influenced by the risk percentage. Thus, North Korean REDD project needs a strong guarantee and involvement by the government and people of North Korea to assure the project's economic feasibility.