• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1119-1130
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• 2020

Flood disasters have been recently increasing worldwide due to climate change and extreme weather events. Since flood damage recovery has been conducted as a common coping strategy to flood disasters in the Republic of Korea, it is necessary to predict the regional flood damage costs by rainfall characteristics for a preventative measure to flood damage. Therefore, the purpose of this study is to present the regression functions for human and economic flood damage assessments for the 7 metropolises in the Republic of Korea. A comprehensive regression analysis was performed through the total 48 simple regression models on the two types of flood damage records for human and economic costs over the past two decades from 1998 to 2017 using the four kinds of nonlinear equations with each of the six rainfall variables. The damage assessment functions for each metropolis were finally selected by the evaluation of the regression results with the coefficient of determination and the statistical significance test, and then used for the human and economic flood damage assessments for 100-year rainfall in the 7 metropolises. The results of this study are expected to provide the basic information on flood damage cost assessments for flood damage mitigation measures.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.999-1009
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• 2021

As the frequency and intensity of extreme weather events due to climate change are increasing in recent years, it is very important to evaluate and analyze climate conditions to manage and respond to the negative effects of climate change in advance. In this study, the trends and characteristics of regional climate change were analyzed by calculating the climate indices for the Chungcheong Province. Annual and monthly UNEP-MP, UNEP-PM and MDM indices were calculated using daily data from 1973-2020 collected from 10 synoptic meteorological stations operated by the Korea Meteorological Administration. The normality of climate data was analyzed through the KS test, and the climate change trend was analyzed by applying the Spearman and Pearson methods. The Chungcheongnam-do region had a relatively humid climate than the Chungcheongbuk-do region, and the annual climate indices showed a dry climate trend in Cheongju and Chungju, while the climate of Seosan and Buyeo was becoming humid. Based on the monthly trend change analysis, a humid climate trend was observed in summer and autumn, while a dry climate trend was observed in spring and winter. Comparison of climate indices during the past (2001-2010) and the recent (2011-2020) years showed a higher decrease in the average climate indices during the last 10 years and a gradually drying climate change trend was recorded.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1505-1515
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• 2023

As extreme weather events caused by climate change are occurring around the world, blue carbon has recently been gaining attention as a carbon sink. Blue carbon has been officially recognized by the Intergovernmental Panel on Climate Change (IPCC) as a means of reducing greenhouse gases, and various studies are underway to discover new blue carbon sources both domestically and internationally. Domestic blue carbon research is centered on carbon absorption and storage in tidal flats, which account for most of the coastal wetlands, but there is a lack of research on spatial information. This study utilized the carbon storage of tidal flats from previous studies and converted it into location and spatial information for each basin of the Geumgang and Nakdong rivers. In addition, a proxy value of carbon storage per area by basin was calculated to compare and analyze the total carbon storage of various tidal flats in Korea and abroad. As a result of the analysis, both the Geumgang and Nakdong River basins showed different amounts of carbon storage depending on the tidal flats data, with the highest amount in the Geumgang basin coming from the National Ocean Survey (469,810.1 Mg C) and the highest amount in the Nakdong River basin coming from the Ministry of Environment (217,145.01 Mg C). The results of this study can be used as a basis for future research on the establishment of domestic blue carbon spatial information.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.117-128
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• 2023

Tree dieback in Geumgang pine forest has occurred in Uljin and Bonghwa since the 2010s. In order to identify status of tree dieback and prevent further damages, a monitoring project for tree dieback in Geumgang pine forest had been launched by Southern regional office of forest service in 2020. This study was conducted to understand the characteristics of tree dieback occurrence and assess the high risk areas using the occurrence data in the project. Pine tree dieback occurred frequently in areas with mountain ridges in high elevation, dry south-facing slopes, mature stands, and high temperature rise in winter. Furthermore, the result of risk assessment showed that 6.2 percent(5,294ha) of Geumgang pine forest(85,000 ha) in total study area are at high risk of tree dieback. As the pine trees in the high risk area are prone to experience the dieback due to temperature and drought-related extreme weather events, regular forest management activities are needed to reduce the drought stress of pine trees. Forest health management for the pine forest with high protection priority can be also useful strategy to counter the risk of decline. This results can be used as the basic information for the adaptive forest management to climate change.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.259-270
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• 2020

Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.103-110
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• 2019

Recently, Korea has been affected by extreme weather events including extended summers and increased temperatures caused by global warming and climate change. Environmental temperature is especially important to the livestock industry because it is closely related to livestock productivity. This study was conducted to investigate the influence of different environmental temperatures on respiration rate, rectal temperature and body-surface temperature in finishing pigs. Pigs ($98.3{\pm}6.6kg$) were housed in individual cages inside an experimental chamber and exposed continuously to one of five environmental treatments ($22^{\circ}C$, $24^{\circ}C$, $26^{\circ}C$, $28^{\circ}C$, $30^{\circ}C$) for 10 days without providing additional rest time. Feed and water intake, respiration rate, rectal temperature and body-surface (head, ear, neck, back, side) temperature were measured two times daily during the experimental period. A significant increase in respiration rate from $26^{\circ}C$ and in body-surface temperature from $24^{\circ}C$ (p<0.05) was observed. At $30^{\circ}C$, the respiration rate had almost doubled and the body-surface temperature increased by about $5^{\circ}C-7^{\circ}C$. Moreover, ear skin temperature was very sensitive to environmental temperature. However, feed intake, water intake and rectal temperature did not change significantly during the experiment.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.