• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.04a
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• pp.163-166
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• 2002

The concurrent injection of cosolvent and air, a cosolvent-air (CA) flood was recently suggested for a dense nonaqueous phase liquid (DNAPL) remediation technology. The objectives of this study were to elucidate the DNAPL removal mechanisms of the CA flood and to quantify mass transfer rate coefficients during CA flooding. DNAPL removal mechanisms were examined by evaluating the effects of air flow rate and DNAPL solubility and visually documented at a pore-scale. Two serial processes, immiscible displacement and dissolution, were experimentally and visually documented during CA flooding. Mass transfer rate coefficients (K) were computed from the data showing PCE saturation versus time. Results showed that CA floods exhibited higher K values than cosolvent floods without concurrent air injection. (This document has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.)

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.21-29
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• 2010

In this study, characteristics of natural disaster and damage in North Korea are examined by using CRED(Centre for Research on the Epidemiology of Disasters) data from 1980 to 2008. Result shows that most natural disasters are caused by summertime typhoon and floods with typical floods of 1995 and 2007. Also, synoptic weather condition associated with heavy rainfall in North Korea is analyzed by using satellite image and weather chart provided by JMA(Japan Meteorological Agency). The heavy rainfalls associated with flood in North Korea are mainly related to the effect of Changma front, abrupt development of southeastward moving low over Yellow Sea, convective instability at the edge of North Pacific high and passage of weakened tropical cyclone(typhoon).

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.5
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• pp.39-47
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• 2000

This study is to investigate the conditions closely related to the establishment of vegetation in the riparian zone: the soil condition, an important factor along with climate and light. Especially, the soil structure of the microtopographical formations in the specific area known as the riparian microtopographical zone investigated. In addition, the effect of the riparian microtopographical features on the ground water level, soil moisture content, and vegetation was studied. The results of this study are as follows; 1) At all sample sites, below the sand layer, a gravel layer is always present. This is the result of past floods. 2) Although Salix koreensis experiences frequent disturbances such as increase in river level and floods, this vegetation establishes itself in the most secure are in the microtopographical zone. 3) The growth of Phragmites japonica is closely related to the underground water level. 4) It is clear that Miscanthus sacchariflorus grows concentrated in dry areas. 5) The soil accumulation conditions differ according to the soil moisture content of each microtopgraphical feature. Accordingly, the moisture content of the soil is clearly different within the microtopographical zone. The continuous and long-term investigation and research on the relation of riparian reproduction and the relevance with location surrounding factors are necessary in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.3
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• pp.133-139
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• 1987

Three disastrous floods experienced over the tidal reaches of the Han River are investigated numerically with the use of one-dimensional finite-difference tidal flow model. The hindcast scheme involves processing flood hydrograph at Indogyo to provide the necessary discharge variation at upstream boundary and predicting tidal elevations at downstream boundary that computes the response in terms of flood levels and discharges within the tidal reaches. Computed results of 1925, 1972 and 1984 floods are presented and discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.2
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• pp.141-150
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• 1992

In this study, six gaging stations(T/M bureau) in the Han River basin were selected for flood frequency analysis and was carried out frequency analysis by POT(peaks Over a Threshold) model where existing flood data of short record length are available. Frequency and magnitudes of each station floods in the river basins were estimated by POT model based on statistical method, and also were compared with standard errors to verify applicability of the estimates by POT model. Furthermore, in order to evaluate for the adequate design flood which is needed for the design of the hydrologic structures in the ungaged watersheds, it is considered to be possible to develop the statistical regionalized model by regional frequency analysis.

• Journal of Environmental Impact Assessment
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• v.18 no.6
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• pp.347-357
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• 2009

This study conducted a vulnerability assessment on Korea's physical infrastructure to provide base data for developing strategies to strengthen Korea's ability to adapt to climate change. The assessment was conducted by surveying professionals in the field of infrastructure and climate change science. A vulnerability assessment was carried out for seven climate change events: average temperature increases, sea level rise, typhoons and storm surges, floods and heavy rain, drought, severe cold, and heat waves. The survey asked respondents questions with respect to the consequences of each climate change event, the urgency of adaptation to climate change, and the scale of investment for adaptation to each climate change event. Thereafter, management priorities for infrastructure were devised and implications for policy development were suggested. The results showed that respondents expected the possibility of "typhoons and storm surges" and "floods and heavy rain" to be the most high. Respondents indicated that infrastructure related to water, transportation, and the built environment were more vulnerable to climate change. The most vulnerable facilities included river related facilities such as dams and riverbanks in the "water" category and seaports and roads in the "transport and communication" category. The results found were consistent with the history of natural disasters in Korea.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.415-424
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• 2015

As global warming has accelerated to weather in recent years, and The frequent floods are creating heavy rains and typhoons followed by considerable damage in Jeju. This study estimated design flood discharges and flood stage in Jeju, considering climate change in connection with RCP scenario, the 5th IPCC Report recently published. It also analyzed the period which might be subject to the risk of flooding in downstream of Oedo Stream. As a result, it has analyzed that there might be a risk of flooding when there were 80 years or more rainfall events in 35 years that rainfall would have increased by 10%, 69 years that 100 years or more heavy rain and rainfall would have increased by 20%, and 104 years that 100 years or more heavy rain and rainfall would have increased by 20%. It is expected that this study results of rainfall increasing trend caused by climate change will be helpful to minimize the damage of floods which will secure the future of Jeju.

• International Journal of Contents
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• v.13 no.4
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• pp.23-28
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• 2017

Of the total economic loss caused by disasters, 40% are due to floods and floods have a severe impact on human health and life. So, it is important to monitor the water level of a river and to issue a flood warning during unfavorable circumstances. In this paper, we propose a modified error function to improve a hydrological modeling using a multi-layer perceptron (MLP) neural network. When MLP's are trained to minimize the conventional mean-squared error function, the prediction performance is poor because MLP's are highly tunned to training data. Our goal is achieved by preventing overspecialization to training data, which is the main reason for performance degradation for rare or test data. Based on the modified error function, an MLP is trained to predict the water level with rainfall data at upper reaches. Through simulations to predict the water level of Nakdong River near a UNESCO World Heritage Site "Hahoe Village," we verified that the prediction performance of MLP with the modified error function is superior to that with the conventional mean-squared error function, especially maximum error of 40.85cm vs. 55.51cm.

• Advances in environmental research
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• v.10 no.1
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• pp.1-15
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• 2021

Rising urban flood patterns are a universal phenomenon and a significant challenge for city government and urban planners worldwide. Urban flood problems range from relatively localized incidents to substantial incidents, which lead to cities being flooded for a few hours to several days. Therefore, the effect may be widespread, such as the temporary displacement of individuals, disruption to civic facilities, water quality degradation and the possibility of epidemics. The problems raised by urban flooding are highly challengeable and compound by ongoing climate change, with adverse implications for changes in rainfall and gaps in intra-urban rainfall distribution. Unplanned construction and invasions of large houses along rivers and watercourses have interfered in natural rivers and watercourses. As a result, the runoff has risen in proportion to the urbanization of the urban floods. The location of the relief camp and the priority for evacuation were determined, and the safest route to avoid floods were established. This method can be used for emergency planning in future flood incidents, and it will help plan disaster preparedness for Panchayat. This study will promote the flood plain's potential use for disaster management and land use planning virtually.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.