KSCE Journal of Civil and Environmental Engineering Research
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v.40
no.3
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pp.273-283
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2020
Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.
Journal of the Korean Society for Marine Environment & Energy
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v.11
no.1
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pp.24-34
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2008
To mitigate the climate change and global warming, various technologies have been internationally proposed for reducing greenhouse gas emissions. Especially, in recent, carbon dioxide capture and storage (CCS) technology is regarded as one of the most promising emission reduction options that $CO_2$ be captured from major point sources (eg., power plant) and transported for storage into the marine geological structure such as deep sea saline aquifer. The purpose of this paper is to review the latest progress on the development of technologies for $CO_2$ storage in marine geological structure and its perspective in republic of Korea. To develop the technologies for $CO_2$ storage in marine geological structure, we carried out relevant R&D project, which cover the initial survey of potentially suitable marine geological structure fur $CO_2$ storage site and monitoring of the stored $CO_2$ behavior, basic design for $CO_2$ transport and storage process including onshore/offshore plant and assessment of potential environmental risk related to $CO_2$ storage in geological structure in republic of Korea. By using the results of the present researches, we can contribute to understanding not only how commercial scale (about 1 $MtCO_2$) deployment of $CO_2$ storage in the marine geological structure of East Sea, Korea, is realized but also how more reliable and safe CCS is achieved. The present study also suggests that it is possible to reduce environmental cost (about 2 trillion Won per year) with developed technology for $CO_2$ storage in marine geological structure until 2050.
Jeong, Do Hyeon;Shin, Hyeon Ho;Jung, Seung Won;Lim, Dhong Il
Korean Journal of Environmental Biology
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v.31
no.1
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pp.19-36
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2013
Physiochemical characters of sea waters during summer flood- and winter dry-seasons and their spatial variations were investigated along the coastal area off the eastern South Sea, Korea. Using the hierarchical clustering method, in this study, we present comprehensive analyses of coastal waters masses and their seasonal variations. The results revealed that the coastal water of the study area was classified into six water masses (A to F). During summer season, the surface water was mainly occupied by the coastal pseudo-estuarine water (water mass B) with low salinity and high nutrients and the river-dominated coastal water (water mass C) with low nutrients, respectively. The bottom water was dominated by cold water (water mass D) with very low temperature, high salinity and high nutrients, compared to masses of surface water. Notably, the water mass B, with high concentrations of nutrients (silicate and nitrogen) and low salinity, which is strongly controlled by the water quality of river freshwater, seems to play an important role in controlling the water quality and further regulating physical processes on ecosystem in the eastern coastal area of South Sea. The water mass D (bottom cold water) coupled with a strong thermocline, which exists in near-bottom layer along the western margin of Korea Strait, has a low temperature, pH and DO, but abundant nutrients. This water mass disappears in winter owing to strong vertical mixing, and subsequently may act as a pool for nutrients during winter dry-season. On the other hand, vertically well-mixed water column during the winter season was typically occupied by the Tsushima (water mass E) and the coastal water (water mass F) with a development of coastal front formed in a transition zone between them. These winter water masses were characterized by low nutrient concentration and balance in N/P ratio, compared with summer season with high nutrient concentrations and strong N-limitation. Accordingly, the analysis of water masses will help one to better chemical and biological processes in coastal area. In most of the study area, characteristically, the growth of phytoplankton community is limited by nitrogen, which is clearly different with coastal environment of West Sea of Korea, with a relative lack of phosphorus. It showed the western and the southern coasts in Korea are substantially different from each other in environmental and ecological characteristics.
Journal of the Korean Society of Hazard Mitigation
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v.9
no.6
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pp.31-39
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2009
This study has found that there is a reverse phase with interdecadal variation in temporal variations of tropical cyclone (TC) genesis frequency (TCGF) between Northwest sector and Southeast sector, based on climatological mean tropical cyclone genesis location over the western North Pacific. The TCGF in the Northwest sector has been increased since the mid 1980s (1986-2005), while TCGF in the Southeast sector was higher until the early 1970s (1951-1970). The analysis of a difference between 1986-2005 and 1951-1970 showed results as follows: i) Through the analysis of vertical wind shear (VWS) and sea surface temperature (SST), less VWS and higher SST in the former (latter) period was located in the Northwest (Southeast) sector. ii) In the analysis of TC passage frequency (TCPF), TCs occurred in the Northwest sector frequently passed from east sea of the Philippines, through East China Sea, to Korea and Japan in the latter period, while TCs in the former period frequently has a lot of influences on South China Sea (SCS). In the case of TCs occurred in the Southeast sector, TCs in the west (east), based on $150^{\circ}E$ had a high passage frequency in the latter (former) period. In particular, TCs during the latter period frequently moved toward from the east sea of the Philippines to SCS and southern China. iii) This difference of TCPF between the two periods was characterized by 500 hPa anomalous pressure pattern. Particularly, anomalous cyclonic circulation strengthened over the East Asian continent caused anomalous southerlies along the East Asian coast line from the east sea of the Philippines to be predominate. These anomalous winds served as steering flows that TC can easily move toward same regions.
Kim, Eun-Sook;Lee, Bora;Kim, Jaebeom;Cho, Nanghyun;Lim, Jong-Hwan
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.
To understand vegetation changes along environmental gradients in the natural forests in the east side of the Cascade Range in Washington state, USA, line transects were used to sample six different forest environments in the Wenatchee National Forest in the north-facing and south-facing sites at 975, 1280 and 1700m elevation. Data were analyzed using ordination by detranded correspondence analysis. Pseudotsuga menziesii was found as one of the dominant species on all the six sites regardless of elevation or aspect, while Pinus ponderosa was dominant on south slopes only. Abies grandis and A. lasiocarpa were dominant species on north slopes at elevations of 1280 and 1700m, respectively. Moisture, as it related to aspect, was identified as one of the most important environmental gradients for explaining the variation of vegetation types. On north-facing slopes, compared to south-facing slopes, where moisture was not as limiting and canopies could grow denser, probably, elevation or competitive interaction was more important. Species diversity tended to decrease with increasing environmental severity, with south slopes having less diversity than north slopes due to extended water stress and harsher temperature extremes on south slopes. The age structure on north-facing and south-facing slopes was different. Light intensity, moisture and climate were different between these two slopes. Large scale disturbances(e.g., big fire or insects) were major causes in changing age structure. Younger trees showed a closer relationship between size and age than adult trees. DBH values of shade intolerant species in south-facing slope were bigger than those of north-facing slope, which suggested that aspect of stands be the most important factor for age and size.
Kim, Gun-Yeob;So, Kyu-Ho;Jeong, Hyun-Cheol;Shim, Kyo-Moon;Lee, Seul-Bi;Lee, Deog-Bae
Korean Journal of Soil Science and Fertilizer
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v.43
no.6
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pp.886-891
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2010
Importance of climate change and its impact on agriculture and environment have increased with a rise of greenhouse gases (GHGs) concentration in Earth's atmosphere, which caus an increase of temperature in Earth. Greenhouse gas emissions such as carbon dioxide ($CO_2$), methane ($CH_4$) and nitrous oxide ($N_2O$) in the Upland field need to be assessed. GHGs fluxes using chamber systems in two upland fields having different soil textures during pepper cultivation (2005) were monitored under different soil textures at the experimental plots of National Academy of Agricultural Science (NAAS), Rural Development Administration (RDA) located in Suwon city, Korea. $CO_2$ emissions were 12.9 tonne $CO_2\;ha^{-1}$ in clay loam soil and 7.6 tonne $CO_2\;ha^{-1}$ in sandy loam soil. $N_2O$ emissions were 35.7 kg $N_2O\;ha^{-1}$ in clay loam soil and 9.2 kg $N_2O\;ha^{-1}$ in sandy loam soil. $CH_4$ emissions were 0.054 kg $CH_4\;ha^{-1}$ in clay loam soil and 0.013 kg $CH_4\;ha^{-1}$ in sandy loam soil. Total emission of GHGs ($CO_2$, $N_2O$, and $CH_4$) during pepper cultivation was converted by Global Warming Potential (GWP). GWP in clay loam soil was higher with 24.0 tonne $CO_2$-eq. $ha^{-1}$ than that in sandy loam soil (10.5 tonne $CO_2$-eq. $ha^{-1}$), which implied more GHGs were emitted in clay loam soil.
Kim, Donghyun;Lee, Haneul;Bae, Younghye;Joo, Hongjun;Kim, Deokhwan;Kim, Hung Soo
Journal of Wetlands Research
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v.23
no.4
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pp.287-295
/
2021
As facilities such as dam reservoir wetlands and agricultural irrigation reservoir wetlands are built, sedimentation occurs over time through erosion, sedimentation transport, and sediment deposition. Sedimentation issues are very important for the maintenance of reservoir wetlands because long-term sedimentation of sediments affects flood and drought control functions. However, research on resignation has been estimated mainly by empirical formulas due to the lack of available data. The purpose of this study was to calculate and compare the sediment deposition rate by developing a multiple regression model along with actual data and empirical formulas. In addition, it was attempted to identify potential causes of collapse by applying it to 64 reservoir wetlands that suffered flood damage due to the long rainy season in 2020 due to reservoir wetland sedimentation and aging. For the target reservoir, 10 locations including the GaGog reservoir located in Miryang city, Gyeongsangnam province in South Korea, where there is actual survey information, were selected. A multiple regression model was developed in consideration of physical and climatic characteristics, and a total of four empirical formulas and sediment deposition rate were calculated. Using this, the error of the sediment deposition rate was compared. As a result of calculating the sediment deposition rate using the multiple regression model, the error was the lowest from 0.21(m3km2/yr) to 2.13(m3km2/yr). Therefore, based on the sediment deposition rate estimated by the multi-regression model, the change in the available capacity of reservoir wetlands was analyzed, and the effective storage capacity was found to have decreased from 0.21(%) to 16.56(%). In addition, the sediment deposition rate of the reservoir where the overflow damage occurred was relatively higher than that of the reservoir where the piping damage occurred. In other words, accumulating sediment deposition rate at the bottom of the reservoir would result in a lack of acceptable effective water capacity and reduced reservoir flood and drought control capabilities, resulting in reservoir collapse damage.
Rapid climate change and oceanic warming have increased the variability of oceanic wave heights over the past several decades. In addition, the extreme wave heights, such as the upper 1% (or 5%) wave heights, have increased more than the heights of the normal waves. This is true for waves both in global oceans as well as in local seas. Satellite altimeters have consistently observed significant wave heights (SWHs) since 1991, and sufficient SWH data have been accumulated to investigate 100-year return period SWH values based on statistical approaches. Satellite altimeter data were used to estimate the extreme SWHs at the Ieodo Ocean Research Station (IORS) for the period from 2005 to 2016. Two representative extreme value analysis (EVA) methods, the Initial Distribution Method (IDM) and Peak over Threshold (PoT) analysis, were applied for SWH measurements from satellite altimeter data and compared with the in situ measurements observed at the IORS. The 100-year return period SWH values estimated by IDM and PoT analysis using IORS measurements were 8.17 and 14.11 m, respectively, and those using satellite altimeter data were 9.21 and 16.49 m, respectively. When compared with the maximum value, the IDM method tended to underestimate the extreme SWH. This result suggests that the extreme SWHs could be reasonably estimated by the PoT method better than by the IDM method. The superiority of the PoT method was supported by the results of the in situ measurements at the IORS, which is affected by typhoons with extreme SWH events. It was also confirmed that the stability of the extreme SWH estimated using the PoT method may decline with a decrease in the quantity of the altimeter data used. Furthermore, this study discusses potential limitations in estimating extreme SWHs using satellite altimeter data, and emphasizes the importance of SWH measurements from the IORS as reference data in the East China Sea to verify satellite altimeter data.
The ecosystem and landscape conservation areas of Seoul were designated according to the Natural Environment Conservation Act and the Natural Environment Conservation Ordinance. With the adoption of the "Rapid Assessment of Wetland Ecosystem Service (RAWES)" approach and the "wetland ecosystem service" for the Ramsar Wetland City Accreditation at the 13th Meeting of the Conference of the Contracting Parties to the Ramsar Convention on Wetlands in 2018, the need for data evaluating wetland ecosystem services has become a necessity. Therefore, in this study, we selected five wetlands from the ecosystem and landscape conservation areas in Seoul, having high ecological conservation values, and evaluated their carbon sequestration and economic value assessment using the InVEST model, which is an ecosystem service evaluation technique. The evaluation results for carbon storage in each wetland are as follows: Tancheon Wetland: 3,674.62 Mg; Bamseom Island in the Hangang River: 1,511.57 Mg; Godeok-dong Wetland: 5,007.21 Mg; Amsa-dong Wetland: 7,108.47 Mg; and Yeouido Wetland: 290.27 Mg. Particularly, the Tancheon Wetland showed the lowest carbon sequestration of 1,130.37 Mg, as compared to the results acquired in 2013, of 4,804.99 Mg. When the average effective carbon rate of $16.06 (US) was applied to the decreased carbon sequestration value, a loss of $15,910.58(US) was calculated. Furthermore, if the average social cost of carbon ($204 (US)) is considered, which includes the impact of climate change on productivity and ecosystems, the total loss is equivalent to $202,101.97 (US). This study aims to examine the natural resource value of urban wetlands by evaluating selected major wetlands in Seoul. This study can be utilized as basic data to plan for the protection and management of the ecosystem and landscape conservation areas. Additionally, because wetland value assessment is considered essential, the results of this study can be used in future research to provide measures for evaluating ecosystem services in the Ramsar Wetland City Certification System. Moreover, this study can be utilized for selecting important wetlands as Ramsar sites, and to raise awareness about the significance of conserving urban wetlands, and for expanding international exchange among the Ramsar Wetland sites.
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