• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.410-413
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• 2008

We constructed the regional flood risk and damage magnitude using hazard and vulnerabilities which are climatic, hydrological, socio-economic, countermeasure, disaster probability components for DB construction on the GIS system. Also we developed the Excess Flood Vulnerability index estimation System(EFVS). By the construction of the System, we can perform the scientific flood management for the flood prevention and optional extreme flood defenses according to regional characteristics. In order to evaluate the performance of system, we applied EFVS to Anseong-chen in Korea, and the system's stabilization is appropriate to flood damage analysis.

• Journal of Wetlands Research
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• v.22 no.4
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• pp.302-311
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• 2020

There are limitations to cope with flood damage by structural strategies alone because both frequency and intensity of floods are increasing due to climate change. Therefore, it is one of the necessary factors in the nonstructural countermeasures to collect and analyze historical flood damage records for the future flood damage assessments. In order to estimate flood damage costs in Gyeongsangbuk-do where severe flood damage occurs frequently due to geographical and climatic effects, this paper has performed the regression analysis on flood damage records over the past 20 years (1999-2018) by rainfall characteristics, which is one of the major causes of flood damage. This paper has then examined the relationship between the terrain features and rainfall characteristics in the regional regression functions, and also estimated the flood damage risk for 100-year rainfall by using the regional regression functions presented for the 22 administrative districts in Gyeongsangbuk-do excluding Ulleung-gun. The flood damage assessment shows that the relatively high damage risk is estimated for county areas adjacent to the eastern coast in Gyeongsangbuk-do. The regional damage estimate functions in this paper are expected to be used as one of the nonstructural countermeasures to estimate flood damage risk for the design or forecasting rainfall data.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.345-357
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• 2007

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.549-557
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• 2013

An flood inundation map is able to convey spatial distribution of inundation to a decision maker for flood risk management. A roughness coefficient with unclear values and a discharge obtained from the stage-discharge rating equation are key sources of uncertainty in flood inundation mapping by using a hydraulic model. Also, the uncertainty analysis needs an observation for the flood inundation, and satellite images is useful to obtain spatial distribution of flood. Accordingly, the objective of this study is to quantify uncertainty arising roughness and discharge in flood inundation mapping by using a hydraulic model and a satellite image. To perform this, flood inundations were simulated by HEC-RAS and terrain analysis, and ISODATA (Iterative Self-Organizing Data Analysis) was used to classify waterbody from Landsat 5TM imagery. The classified waterbody was used as an observation to calculate F-statistic (likelihood measure) in GLUE (Generalized Likelihood Uncertainty Estimation). The results from GLUE show that flood inundation areas are 74.59 $km^2$ for lower 5 % uncertainty bound and 151.95 $km^2$ for upper 95% uncertainty bound, respectively. The quantification of uncertainty in flood inundation mapping will play a significant role in realizing the efficient flood risk management.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.160-160
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• 2022

Floods are the most common natural disasters and are annually causing severe destructions worldwide. Human activities, along with expected increased extreme precipitation patterns as a result of climate change enhance the future potential of floods. There are proven evidence that infrastructure based responses to flood disaster is no longer achieving optimum mitigation and have created a false sense of security. Nature-based solutions(NBS) is a widely accepted sustainable and efficient approach for disaster risk reduction and involves the protection, restoration, or management of natural and semi-natural ecosystems to tackle the climate and natural crisis. Adoption of NBS in decision-making, especially in developing nations is limited due to a lack of sufficient scenario-based studies, research, and technical knowledge. This study explores the knowledge gap and challenges on NBS adoption with case study of developing nation, specially for flood management, by the study of multiple scenario analysis in the context of climate, land-use change, and policies. Identification and quantification of the strength of natural ecosystems for flood resilience and water management can help to prioritize NBS in policymaking leading to sustainable measures for integrated flood management.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.758-763
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• 2006

Statistical concepts and methods are routinely utilized in a number of design and management problems in engineering hydrology. This is because most of hydrological processes have some degree of randomness and uncertainty. Thus, the concepts of risk and uncertainty are commonly utilized for designing and evaluating hydraulic structures such as spillways and dikes. Therefore, in this study, uncertainty analysis considering the variance of design floods is performed to evaluate the uncertainty of the hydrologic risk of flood related hydraulic structures using frequency analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1441-1444
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• 2007

It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.423-428
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• 2004

Flooding is one of the main causes of loss of lives and properties among various natural disasters in Korea. Flood risk maps are currently being produced in Korea but the progress is slow considering the necessity to map at nationwide scale. In this study, GIS-based multi-criteria decision making process which is normally used for resource management and site analysis was applied to locate flood vulnerable areas. Past records of flooding maps were analysed to extract topographic characteristics of flooded areas. The extracted characteristics were then set as criteria for flooding analysis using the Fuzzy and Analytic Hierarchy Process(AHP) methodology. Results from this study showed that an improved phased action plan was possible, because the flood vulnerable areas are shown in varying degrees of uncertainty unlike the conventional Boolean type GIS layer superimposition analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.74-88
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• 2010

In this study, the points of LiDAR were modified in order to generate various DEM resolutions by applying LiDAR data in Ulsan. Since the LiDAR data have points with 1m intervals, the number of points for each resolution was modified to the size of 1, 5, 10, 30, 50, 100m by uniformly eliminating the points. A runoff analysis was performed on Taehwa river and its tributary, Dongcheon, with 200 year rainfall exceedance probability. 2-dimensional inundation analysis was performed based on the density of LiDAR data using FLUMEN, which was used to establish domestic flood risk map. Once DEM data obtained from LiDAR survey are used, it is expected that the study results can be used as data in determining optimal grid spacing, which is economical, effective and accurate in establishing flood defence plans including the creation of flood risk map.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.691-698
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• 1997

The risk assessment model for dam and levee is applied to a river where two adjacent dams are located in the upstream of the watershed. "A" dam is proven to be safe with 200-year precipitation and unsafe with PMP condition, whereas "B" dam to be safe with 200-year precipitation and PMP condition. The computed risk considering the uncertainties of the runoff coefficient. initial water depth and relevant data of the dam and spillway turn out to be equivalent results in Monte-Carlo and AFOSM method. In levee risk model, this study addresses the uncertainty of water surface elevation by Manning's equation. Monte-Carlo simulation with the variations of Manning's roughness coefficient is calculated by assuming that it follows atriangular distribution. The model can be used for preparing flood risk maps, flood warning systems, and establishing nation's flood disaster protection plan.