• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.1-9
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• 2017

Recently, it is increasing the grape farm which is converted from paddy field to orchard. These soil which are poor drainage extremely also can be damaged a lot by excessive water or flooding during heavy rain season on summer. Therefore the aim of this study was carried out to measure the changes of soil water potential and to compare the growth responses of 'Jinok' (Vitis spp.) and 'Campbell Early' (V. labruscana) grapes under three drainage systems (control, conventional drainage, and under drainage). After heavy rain, soil water potential holding times above -15 kpa applied water excessive were 352, 348 and 180 hours in control, conventional, and under drainage systems, respectively. The clay content of the under drainage system was lower than the other systems about 8-12%. The crop water stress index was lowest in the under drainage and highest in the control. Also, photosynthetic rate has showed the opposite result with crop water stress index. It was significant differences between the treatments but, the value has not shown significantly different between the varieties. In addition, leaf area and the trunk growth rate was more effective in under drainage than in the control and conventional drainage.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.729-742
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• 2019

Natural disasters such as floods has been increased in many parts of the world, also Korea is no exception. The biggest part of natural damage in South Korea was caused by the flooding during the rainy season in every summer. The existing flood vulnerability analysis cannot explain the reality because of the repeated changes in topography. Therefore, it is necessary to calculate a new flood vulnerability index in accordance with the changed terrain and socio-economic environment. The priority of the investment for the flood prevention and mitigation has to be determined using the new flood vulnerability index. Total 25 urban districts in Seoul were selected as the study area. Flood vulnerability factors were developed using Pressure-State-Response (PSR) structures. The Pressure Index (PI) includes nine factors such as population density and number of vehicles, and so on. Four factors such as damage of public facilities, etc. for the Status Index (SI) were selected. Finally, seven factors for Response Index (RI) were selected such as the number of evacuation facilities and financial independence, etc. The weights of factors were calculated using AHP method and Fuzzy AHP to implement the uncertainties in the decision making process. As a result, PI and RI were changed, but the ranks in PI and RI were not be changed significantly. However, SI were changed significanlty in terms of the weight method. Flood vulnerability index using Fuzzy AHP shows less vulnerability index in Southern part of Han river. This would be the reason that cost of flood mitigation, number of government workers and Financial self-reliance are high.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.51-59
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• 2021

Due to recent climate change, the flood damage is becoming larger due to the development of localized heavy rains. 2020.12 The Ministry of Environment provides 100-year flood flood map, but in the case of small rivers, river structures are designed at 50-80 years frequency, making it difficult to predict damage and provide evacuation information. This study prepared flood map of Donamcheon district in Geumnam-myeon, Sejong Special Self-Governing Province, which is a small stream and habitual flood zone. The flood level was calculated using HEC-RAS and the flood area was visualized through HEC-GeoRAS. The analysis results showed that property damage such as special crops and roads occurred during the 30-80 year frequency rainfall, and it affected private houses such as general residential areas and public land when the frequency occurred for 100 years. The results of the comparison and analysis of the flood map provided by the Ministry of Environment and the results of the HEC-GeoRAS simulation showed that the flood map provided by the Ministry of Environment did not consider small streams. Further studies on flood flood maps considering the large and small stream are needed in the future.

• Journal of odor and indoor environment
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• v.17 no.4
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• pp.355-361
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• 2018

Mold grows more easily when humidity is higher in indoor spaces, and as such is found more often on wetted areas in housing such as walls, toilets, kitchens, and poorly managed spaces. However, there have been few studies that have specifically assessed the level of mold in the indoor spaces of water-damaged housing in the Republic of Korea. We investigated the levels of airborne mold according to the characteristics of water damage types and explored the correlation between the distribution of mold genera and the characteristics of households. Samplings were performed from January 2016 to June 2018 in 97 housing units with water leakage or condensation, or a history of flooding, and in 61 general housing units in the metropolitan and Busan area, respectively. Airborne mold was collected on MEA (Malt extract agar) at flow rate of 100 L/min for 1 min. After collection, the samples were incubated at $25^{\circ}C$ for 120 hours. The cultured samples were counted and corrected using a positive hole conversion table. The samples were then analyzed by single colony culture, DNA extraction, gene amplification, and sequencing. By type of housing, concentrations of airborne mold were highest in flooded housing, followed by water-leaked or highly condensed housings, and then general housing. In more than 50% of water-damaged housing, the level of airborne mold exceeded the guideline of Korea's Ministry of Environment ($500CFU/m^3$). Of particular concern was the fact that the I/O ratio of water-damaged housing was greater than 1, which could indicate that mold damage may occur indoors. The distribution patterns of the fungal species were as follows: Penicillium spp., Cladosporium spp. (14%), Aspergillus spp. (13%) and Alternaria spp. (3%), but significant differences of their levels in indoor spaces were not found. Our findings indicate that high levels of mold damage were found in housing with water damage, and Aspergillus flavus and Penicillium brevicompactum were more dominant in housing with high water activity. Comprehensive management of flooded or water-damaged housing is necessary to reduce fungal exposure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.5
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• pp.253-264
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• 2019

Storm surges caused by a typhoon occur during the summer season, when the sea-level is higher than the annual average due to steric effect. In this study, we analyzed the sea-level pressure and tidal data collected in 1 h intervals at Incheon, Kunsan, Mokpo, Seogwipo stations on the Yellow Sea coast to analyze the summer season storm surge and wave overtopping. According to our analyses, the summer mean sea-level rise on the west and south coasts is approximately 20 cm and 15 to 20 cm higher than the annual mean sea-level rise. Changes in sea-level rise are closely related to changes in seasonal sea-level pressure, within the range of 1.58 to 1.73 cm/hPa. These correlated mechanisms generates a phase difference of one month or more. The 18.6 year long period tidal constituents indicate that in 2090, the amplitude of the $M_2$ basin peaks on the southwest coast. Therefore, there is a need to analyze the target year for global warming and sea-level rise in 2090. Wave overtopping was simulated considering annual mean sea-level rise, summer sea level rise, the combined effect of nodal factor variation, and 100-year frequency storm surge. As a result, flooding by wave overtopping occurs in the area of Suyong Bay, Busan. In 2090, overtopping discharges are more than doubled than those in Marine City by the recent typhoon Chaba. Adequate coastal design is needed to prepare for flood vulnerability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.257-266
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• 2021

Urban areas can often suffer flood damage because of the more frequent catastrophic rainfall events from climate change. Flood mitigation measures consist of (1) structural and (2) non-structural measures. In this study, the proposed method focused on operating an urban drainage system among non-structural measures. The combined inland-river operation technique estimates the inflow of pump stations based on the water level obtained from a preselected monitoring point, and the pump station expels the stored rainwater to the riverside based on those estimates. In this study, the proposed method was applied to the Mokgam drainage watershed, where catastrophic rainfall events occurred (i.e., 2010- and 2011-years), and severe flood damage was recorded in Seoul. Using the proposed method, the efficiency of flood reduction from the two rainfall events was reduced by 34.9 % and 54.4 %, respectively, compared to the current operation method. Thus, the proposed method can minimize the flood damage in the Mokgam drainage watershed by reserving the additional storage space of a reservoir. In addition, flooding from catastrophic rainfall can be prevented, and citizens' lives and property in urban areas can be protected.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1195-1204
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• 2021

Recently, local torrential rain have become more frequent and severe due to abnormal climate conditions, causing a surge in human and properties damage including infrastructures along the river. In this study, water surface elevation prediction algorithm was developed using the LSTM (Long Short-term Memory) technique specialized for time series data among Machine Learning to estimate and prevent flooding of the facilities. The study area is Jamsu Bridge, the study period is 6 years (2015~2020) of June, July and August and the water surface elevation of the Jamsu Bridge after 3 hours was predicted. Input data set is composed of the water surface elevation of Jamsu Bridge (EL.m), the amount of discharge from Paldang Dam (m³/s), the tide level of Ganghwa Bridge (cm) and the number of tweets in Seoul. Complementary data were constructed by using not only structured data mainly used in precedent research but also unstructured data constructed through wordcloud, and the role of unstructured data was presented through comparison and analysis of whether or not unstructured data was used. When predicting the water surface elevation of the Jamsu Bridge, the accuracy of prediction was improved and realized that complementary data could be conservative alerts to reduce casualties. In this study, it was concluded that the use of complementary data was relatively effective in providing the user's safety and convenience of riverside infrastructure. In the future, more accurate water surface elevation prediction would be expected through the addition of types of unstructured data or detailed pre-processing of input data.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.267-278
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• 2022

Recently Flood damage volume has increased as heavy rain has frequently occurred. Especially urban areas are a vulnerability to flooding damage because of densely concentrated population and property. A local government is preparing to mitigate flood damage through the heavy rain warning issued by Korea Meteorological Administration. This warning classification is identical for a national scale. However, Seoul has 25 administrative districts with different regional characteristics such as climate, topography, disaster prevention state, and flood damage severity. This study considered the regional characteristics of 25 administrative districts to analyze the flood vulnerability using entropy weight and Euclidean distance. The rainfall classification was derived based on probability rainfall and flood damage rainfall that occurred in the past. The result shows the step 2 and step 4 of rainfall classification was not significantly different from the heavy rain classification of the Korea Meteorological Administration. The flood vulnerability is high with high climate exposure and low adaptability to climate change, and the rainfall classification is low in the northern region of Seoul. It is possible to preemptively respond to floods in the northern region of Seoul based on relatively low rainfall classification. In the future, we plan to review the applicability of rainfall forecast data using the rainfall classification of results from this study. These results will contribute to research for preemptive flood response measures.