• Journal of Korea Water Resources Association
• /
• v.55 no.9
• /
• pp.657-668
• /
• 2022

With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.210-210
• /
• 2022

This study evaluates Japan's Official Development Assistance (ODA) projects in Thailand from 2011 to 2013 by deploying the Sendai Framework for Disaster Risk Reduction (SFDRR) and the Organization for Economic Cooperation Development (OECD) evaluation criteria. Special attention is placed on disaster-related development assistance activities of Japan through reviewing long-term impacts of the projects. The Japan International Cooperation Agency (JICA) has played a crucial role in transferring Japan's experiences on disaster risk management to developing countries, including Thailand. The study highlights two flood risk management projects in Thailand with the support of JICA after the 2011 floods, namely the Project for the Comprehensive Flood Management Plan for the Chao Phraya River Basin and the Project for Flood Countermeasures for Thailand Agriculture Sector. The case studies demonstrate that the projects were efficiently and effectively conducted for meeting Thailand's needs and requirements. JICA provided multi-hazards risk analysis through scientific data as well as local knowledge. However, achievements of the project did not last for long because of a lack of Thai stakeholders' commitment and JICA's post-project management. It is concluded that a development agency should consider impacts and sustainability of flood risk management projects more carefully from the stage of planning, and the practical application of the knowledge, and technologies should also be monitored progressively after the completion of the project.

• Journal of Korea Water Resources Association
• /
• v.48 no.9
• /
• pp.757-768
• /
• 2015

Recently, climate change has affected short time concentrated local rainfall and unexpected heavy rain which is increasingly causing life and property damage. In this research, arithmetic average analysis, weighted average analysis, and principal component analysis are used for predicting flood risk. This research is foundation for application of predicting flood risk based on annals of disaster and status of urban planning. Results obtained by arithmetic average analysis, weighted average analysis, and principal component analysis using many factors affect on flood are compared. In case of arithmetic average analysis, each factor has same weights though it is simple method. In case of weighted average analysis, correlation factors are complex by many variables and multicollinearty problem happen though it has different weights. For solving these problems, principal component analysis (PCA) is used because each factor has different weights and the number of variables is smaller than other methods by combining variables. Finally, flood risk assessment considering flood control ability and urban environment risk in former research is predicted.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.1
• /
• pp.29-39
• /
• 2018

In this study, the applicabilities of flood risk indices using FVI from IPCC, PSR method from OECD, and DPSIR method from EEA, were analyzed. Normalized values of daily maximum rainfall, hourly maximum rainfall, ten minute maximum rainfall, annual precipitation, total days of heavy rainfall (more than 80mm/day), density of population, density of asset, DEM, road statistics, river maintenance ratio, reservoir capacity, supply ratio of water supply and sewerage, and pumping capacity were constructed from 2000 to 2015 for nationwide 113 watersheds, to estimate flood risk indices. The estimated indices were compared to 4 different types of flood damage such as the number of casualties, damage area, the amount of flood damage, and flood frequency. The relationships between flood indices and different flood damage types demonstrated that the flood index using the PSR method shows better results for the amount of flood damage, the number of casualties and damage area, and the flood index using the DPSIR method shows better results for flood frequency.

• Journal of the Korean Society of Safety
• /
• v.29 no.1
• /
• pp.64-69
• /
• 2014

Community-based disaster preparedness approaches are increasingly important elements of vulnerability reduction and disaster strategies. They are associated with a policy trend that values the knowledge and capacities of local people. In this research, we describe the community diagnosis method and develop Flood Disaster Risk Reduction Index(FDRRI) for assessment of flood vulnerability. FDRRI is composed of four indicators such as Flood Exposure Indicator(FEI), Sensitivity Indicator(SI), Risk Reduction Indicator(RRI), and Community Preparedness Indicator(CPI). We anticipate to present the guideline for selection national preparedness projects and uplift community's preparedness capacity.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.195-198
• /
• 2008

In this study we analyzed flood runoff and flood characteristics of an small urban river basin which is in an apartment complex in Yewol-Dong, Buchun-Si, Gyunggi-Do. A little discharge normally flows in the river, however this small river has a relatively high potential of flood damage risk in the flood season due to the high flood level and velocity. Therefore we used the GIS data, cross section data in the river, HEC-RAS model, etc. for investigating safety of a river against flood runoff and also we investigated the stability of hydraulic structures and ability of flood prevention in the river. As the result of investigation, we found that the river had the risk of flood damage occurrence due to the hydraulic structures constructed for various purposes in the river. So we should analyze backwater effect by the structures and consider the risk factors can be occurred by the flood runoff and velocity for more safe design of a small river basin in the residential area such as an apartment complex in the urban area.

• Journal of Korea Water Resources Association
• /
• v.46 no.1
• /
• pp.35-45
• /
• 2013

The aim of study is to present how to estimate and use the FRI (Flood Risk Index) for classifying area zones based on regional flooding risk in terms of the integrated flood risk management. To estimate the FRI at a spatial resolution of city/county/town units for the Nakdong River Watershed, the 17 representative flood indexing factors are carefully selected for the three flood indexes, such as PI (Pressure Index), SI (State Index), and RI (Response Index) under the P-S-R (Pressure-State-Response) classification system. Because flood indexing factors are measured at different scales and units, they are transformed into a common domain by the T-Score normalization technique. The entropy weight coefficient method is also applied to calculate the weight of flood indexing factors in order to reduce subjective judgement on the effect of weight coefficients. The three flood indexes of PI, SI, and RI are integrated for an overall value of the FRI to evaluate the flood risk of districts. To examine the practical application of the proposed FRI, the FRI results with/without the weight coefficients are compared with flooding zones of natural disaster risk areas officially announced in 2010. It is expected that the FRI ensured by full verification can make regional protection plans against flooding disasters with respect to causes and characteristics of past floods.

• Journal of Korea Water Resources Association
• /
• v.53 no.2
• /
• pp.121-129
• /
• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.181-181
• /
• 2023

Flood is a major threat to human society, and scientific assessment of flood risk in human living areas is an important task. In this study, two different methods were used to evaluate the flood in Ulsan City, and the results were comprehensively compared and analyzed. Based on the fuzzy mathematics and VIKOR method of the multi-objective decision system, similar evaluation results were obtained in the study area. The results show that due to the large number of rivers in Ulsan City and the relatively high exposure index, the whole city faces a high risk of flooding. However, fuzzy mathematics theory pays more attention to the negative impact of floods on people, and the adaptability in the Nam-gu District is lower. In contrast, the VIKOR method pays more attention to the positive role of the economy and population in flood protection, and thus obtains a higher score. Both approaches demonstrate that the city of Ulsan faces a high risk of flooding and that its citizens and policymakers need to invest in preventing flood damage.

• Journal of Korea Water Resources Association
• /
• v.52 no.10
• /
• pp.753-761
• /
• 2019

Localized heavy storm is one of the major causes of flood damage in urban regions. According to the recent disaster statistics in South Korea, the frequency of urban flood is increasing more frequently, and the scale is also increasing. However, localized heavy storm is difficult to predict, making it difficult for local government officials to deal with floods. This study aims to construct a Flood risk matrix (FRM) using ensemble weather prediction data and to assess its applicability as a means of reducing damage by securing time for such urban flood response. The FRM is a two-dimensional matrix of potential impacts (X-axis) representing flood risk and likelihood (Y-axis) representing the occurrence probability of dangerous weather events. To this end, a regional FRM was constructed using historical flood damage records and probability precipitation data for basic municipality in Busan and Daegu. Applicability of the regional FRMs was assessed by applying the LENS data of the Korea Meteorological Administration on past heavy rain events. As a result, it was analyzed that the flood risk could be predicted up to 3 days ago, and it would be helpful to reduce the damage by securing the flood response time in practice.