• Journal of Wetlands Research
• /
• v.18 no.2
• /
• pp.154-165
• /
• 2016

Recently, the frequency of extreme rainfall event has increased due to climate change and impermeable area also has increased due to rapid urbanization. Therefore, we ought to prepare countermeasures for flood reduction to reduce the damage. To consider climate change, the frequency based rainfall was calculated according to the aimed period(reference : 1971~2010, Target period I : 2011~2040, Target period II : 2041~2070, Target period III : 2071~2100) and the flood discharge was also calculated by climate change using HEC-HMS model. Also, the flood elevation was calculated by each alternative through HEC-RAS model, setting 5 sizes of drainage pumps and reservoirs respectively. The flood map was constructed using topographical data and flood elevation, and the economic analysis was conducted for reduction of flood damage using Multi dimension - Flood Damage Analysis, MD-FDA. As a result of the analysis on the flood control effect, a head of drainage pump was reduced by 0.06m up to 0.44m while it was reduced by 0.01m up to 1.86m in the case of a detention pond. The flooded area shrunk by up to 32.64% from 0.3% and inundation depth also dropped. As a result of a comparison of the Benefit/Cost index estimated by the economic analysis, detention pond E in period I and pump D in period II and III were deemed appropriate as an alternative for climate change. The results are expected to be used as good practices when implementing the flood control works considering climate change.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.3
• /
• pp.119-136
• /
• 2012

The goal of this study is to apply the IPCC(Intergovernmental Panel on Climate Change) concept of vulnerability to climate change and verify the use of a combination of vulnerability index and fuzzy logic to flood vulnerability analysis and mapping in Seoul using GIS. In order to achieve this goal, this study identified indicators influencing floods based on literature review. We include indicators of exposure to climate(daily max rainfall, days of 80mm over), sensitivity(slope, geological, average DEM, impermeability layer, topography and drainage), and adaptive capacity(retarding basin and green-infra). Also, this research used fuzzy model for aggregating indicators, and utilized frequency ratio to decide fuzzy membership values. Results show that the number of days of precipitation above 80mm, the distance from river and impervious surface have comparatively strong influence on flood damage. Furthermore, when precipitation is over 269mm, areas with scare flood mitigation capacities, industrial land use, elevation of 16~20m, within 50m distance from rivers are quite vulnerable to floods. Yeongdeungpo-gu, Yongsan-gu, Mapo-gu include comparatively large vulnerable areas. This study improved previous flood vulnerability assessment methodology by adopting fuzzy model. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing flood mitigation policies.

• Geotechnical Engineering
• /
• v.2 no.1
• /
• pp.27-44
• /
• 1986

The measured soil data are analyzed to the descriptive statistics and classified into the four models of uncorrelated-normal (UNNO), uncorrelated-nonnormal (VNNN), correlatedonnormal(CONN), and correlated-nonnormal(CONN) . This paper presents the comparisons of reliability index and check points using the advanced first-order second-moment method with respect to the four models as well as BASIC Program. A sin91e-mode Performance function is consisted of the basic design variables of bearing capacity and settlements on shallow foundations and input the above analyzed soil informations. The main conclusions obtained in this study are summarized as follows: 1. In the bearing capacity mode, cohesion and bearing-capacity factors by C-U test are accepted for normal and lognormal distribution, respectively, and negatively low correlated to each other. Since the reliability index of the CONN model is the lowest one of the four model, which could be recommended a reliability.based design, whereas the other model might overestimate the geotechnical conditions. 2. In the case of settlements mode, the virgin compression ratio and preccnsolidation pressure are fitted for normal and lognormal distribution, respectively. Constraining settlements to the lower ones computed by deterministic method, The CONN model is the lowest reliability of the four models.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.3
• /
• pp.579-588
• /
• 2015

Recent climage changes have resulted in increases in rainfall intensity and flood frequency as well as the risk of flood damage due to typhoons during the summer season. Water-friendly facilities such as ecological parks and sports facilities have been established on floodplains of rivers since the river improvement project was implemented and increases in the flood levels of rivers due to typhoons can lead to direct flood damage to such facilities. To analyze the hydraulic influence of these water-friendly facilities on floodplains or to evaluate their stability, numerical analysis should be performed in advance. In addition, it is crucial to address the drying and wetting processes generated by water level fluctuations. This study uses a Nays2D model, which analyzes drying and wetting, to examine its applicability to simple terrain in which such fluctuations occur and to natural rivers in which drying occurs. The results of applying this model to sites of actual typhoon events are compared with values measured at water level observatories. Through this comparison, it is determined that values of coefficient of determination ($R^2$), mean absolute error (MAE), and root-mean-square error (RMSE) are 0.988, 0.208, and 0.239, respectively, thus showing a statistically high correlation. In addition, the results are used to calculate flood risk indices for evaluation of such risk for water-friendly facilities constructed on floodplains.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.1
• /
• pp.64-79
• /
• 2016

The purpose of this study is to find the relationship between precipitation deficit, SPI(standardized precipitation index)-12 month, agricultural reservoir water storage deficit and agricultural drought-related big data, and to evaluate the usefulness of agricultural risk management through big data. For the long term drought (from January 2014 to September 2015), each data was collected and analysed with monthly and Provincial base. The minimum SPI-12 and maximum reservoir water storage deficit compared to normal year were occurred at the same time of July 2014, and August and September 2015. The maximum frequency of big data was occurred at June and July of 2014, and March and June to September of 2015. The maximum big data was occurred 1 month advanced in 2014 and 2 months advanced in 2015 than the maximum reservoir water storage deficit. The occurrence of big data was sensitive to spring drought from March, late Jangma of June, dry Jangma of July and the rainfall deficit of September 2015. The big data was closely related with the meteorological drought and agricultural drought. Because the big data is the in situ feeling drought, it is proved as a useful indicator for agricultural risk management.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.4
• /
• pp.264-272
• /
• 2013

Climate changes have caused not only changes in the frequency and intensity of extreme climate events, but also temperature and precipitation. The damages on agricultural production system will be increased by heavy rainfall and snow. In this study we assessed vulnerability of crop cultivation facility and animal husbandry facility by heavy rain in 232 agricultural districts. The climate data of 2000 years were used for vulnerability analysis on present status and the data derived from A1B scenario were used for the assessment in the years of 2020, 2050 and 2100, respectively. Vulnerability of local districts was evaluated by three indices such as climate exposure, sensitivity and adaptive capacity, and each index was determined from selected alternative variables. Collected data were normalized and then multiplied by weight value that was elicited in delphi investigation. Jeonla-do and Gangwon-do showed higher climate exposures than the other provinces. The higher sensitivity to abnormal weather was observed from the regions that have large-scale cultivation facility complex compared to the other regions and vulnerability to abnormal weather also was higher at these provinces. In the projected estimation based on the SRES A1B, the vulnerability of controlled agricultural facility in Korea totally increased, especially was dramatic between 2000's and 2020 year.