• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.176-176
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• 2023

The Tonle Sap is the richest and diverseness of freshwater ecosystem in Southeast Asia, receiving nurturing water flows from the Mekong and its immediate basin. In addition, the rapid development in the Tonle Sap Lake (TSL) Basin, and flood inundation may threaten the natural diversities and characteristics. The impacts of flood inundation in 11 sub-basins contributing to the Tonle Sap Lake were assessed using the Rainfall-Runoff-Inundation (RRI) model to quantify the potential magnitude and extent of the flooding. The RRI model is set up by using gauged rainfall data to simulate the information of river discharge and flood inundation of huge possible flood events. Moreover, two satellite precipitation products (SPPs), CHIRPS and GSMaP, within respectively spatial resolutions of 0.05° and 0.1°, are utilized as an input for the RRI model to simulate river discharge, flood depth, and flood extent for the great TSL Basin of Cambodia. This study used statistical indicators such as NSE, PBIAS, RSR, and R2 as crucial indices to evaluate the performance of the RRI model. Therefore, the findings of this study could provide promising guidance in hydrological modeling and the significant implications for flood risk management and disaster preparedness in the region.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.140-148
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• 2010

The Taihu Basin is located in the east coast of China, where the threats of frequent floods have induced construction of massive, complex, hierarchical flood defense systems over the interconnected river networks. Digital modeling of flooding processes and quantitative damage assessment still remain challenging due to such complexity. The current research uses an integrated approach to meet this challenge by combining multiple types of models within a GIS platform. A new algorithm is introduced to simulate the impacts of the flood defense systems, especially the large number of polders, on floods distributions and damages.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.247-253
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• 2017

Accurate flood frequency and magnitude estimation has a critical role in flood risk management and damage reduction. In United States, Log Pearson Type-III (LP-III) distribution with method of moments for parameter estimation has been uniformly and consistently employed in estimating design floods. After the first version of flood frequency guidelines (Bulletin 15) was published in 1967, the revised version Bulletin 17B has been employed since 1982 up to now. A new version of flood frequency guidelines, Bulletin 17C, is prepared and about to come out soon. In the current study, we analyzed the new features of the upcoming Bulletin 17C and presented case studies applying its new features. From the presented results, we see what critical components in the new design flood frequency guideline we could learn.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.167-167
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• 2020

Annual sediment deposition in reservoirs behind weirs poses flood risk, while its accurate prediction remains a challenge. Sediment management by hydraulic flushing is an effective method to maintain reservoir storage. In this study, an integrated approach to predict sediment inflow and sediment flushing simulation in reservoirs is presented. The annual sediment inflow prediction was carried out with Artificial Neural Networks (ANN) modelling. RESCON model was applied for quantification of sediment flushing feasibility criteria. The integrated approach was applied on Sangju Weir and also on estuary of Nakdong River (NREB). The mean annual sediment inflow predicted at Sangju Weir and NREB was 400,000 ㎥ and 170,000 ㎥, respectively. The sediment characteristics gathered were used to setup RESCON model and sediment balance ratio (SBR) and long term capacity ratio (LTCR) were used as flushing efficiency indicators. For Sangju Weir, the flushing discharge, Q_f = 140 ㎥/s with a drawdown of 5 m, and flushing duration, T_f = 10 days was necessary for efficient flushing. At NREB site, the parameters for efficient flushing were Q_f = 80 ㎥/s, T_f = 5 days, N = 1, El_f = 2.24 m. The hydraulic flushing was concluded feasible for sediment management at both Sangju Weir and NREB.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.342-346
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• 2009

홍수피해를 발생시키는 외부적인 요소 측면에서 과거와는 다른 강우특성이 뚜렷이 나타나고 있고, 홍수 피해의 측면에서 홍수에 의한 피해 잠재성이 매우 커지고 있는 시점에서 치수대책은 내 외부적인 여건변화에 민감하게 대처해야 한다. 수자원장기종합계획보고서(국토해양부, 2006)에서는 과거와 같은 제방위주의 치수대책으로는 변화하고 있는 강우상황에 대처할 수 없을 뿐만 아니라 급증하는 홍수피해를 줄이기에는 한계가 있다고 강조하고 있다. 따라서 이와 같은 내 외부적인 환경변화에 대응하기 위해 새로운 패러다임의 홍수대책의 수립이 필요하고, 급변하는 기후변동에 의한 유역의 홍수취약성을 파악하기 위한 지표를 개발하여 치수 정책과 관련 사업의 의사결정을 지원할 수 있는 체계가 뒷받침 되어야 한다. 본 연구에서는 P(Pressure, 압력)-S(State, 현상)-R(Response, 대책) 구성체계를 기반으로 홍수위험지수(Flood Risk Index, FRI)를 개발하여 유역 간 홍수의 취약성 비교 분석을 하고 해당 지역의 주된 취약요인을 파악하여 정부 및 지자체의 치수관련 정책 결정을 효과적으로 지원할 수 있도록 하는데 목적이 있다.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.103-111
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• 2013

This paper discusses how to manage supply chain disruption risks from natural disasters or other low-likelihood-high-impact risk drivers. After the catastrophic earthquake in Eastern Japan and the severe flood in Thailand, most companies have been attempting to re-establish the business continuity plan to prevent their supply chain from disruption. However, the challenges for managers and individual risks are often interrelated, and thus, actions that mitigate one risk can end up being no contribution as a whole. In this paper, we describe a framework for assessing how much impact individual mitigation strategies have on the entire supply chain protection against disruption, using network reliability. We propose three categories of risk-mitigation approaches: Stabilization, Absorption, and Duplication. We analyze the situation under which each of these strategies is the best suitable. With a clear understanding of relations between these mitigation strategies and the entire supply chain risks, managers can select effective risk-reduction approaches to their supply chain.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.771-783
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• 2023

This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.

• 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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• 2005.09a
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• pp.730-730
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• 2005