• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.73-82
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• 2013

The main objective of this study was to evaluate Representative Concentration Pathways (RCP) scenarios-based flood risk at a Si-Gun level. A bias correction using a quantile mapping method with the Generalized Extreme Value (GEV) distribution was performed to correct future precipitation data provided by the Korea Meteorological Administration (KMA). A series of proxy variables including CN80 (Number of days over 80 mm) and CX3h (Maximum precipitation during 3-hr) etc. were used to carry out flood risk assessment. Indicators were normalized by a Z-score method and weighted by factors estimated by principal component analysis (PCA). Flood risk evaluation was conducted for the four different time periods, i.e. 1990s, 2025s, 2055s, and 2085s, which correspond to 1976~2005, 2011~2040, 2041~2070, and 2071~2100. The average flood risk indices based on RCP4.5 scenario were 0.08, 0.16, 0.22, and 0.13 for the corresponding periods in the order of time, which increased steadily up to 2055s period and decreased. The average indices based on RCP8.5 scenario were 0.08, 0.23, 0.11, and 0.21, which decreased in the 2055s period and then increased again. Considering the average index during entire period of the future, RCP8.5 scenario resulted in greater risk than RCP4.5 scenario.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.203-222
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• 2011

The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2293-2302
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• 2013

Flood inundation map has been used as a fundamental information in flood risk management. However, there are various sources of uncertainty in flood inundation mapping, which can be another risk in preventing damage from flood. Therefore, it is necessary to remove or reduce uncertainty sources to improve the accuracy of flood inundation maps. However, the entire removal of uncertainty source may be impossible and inefficient due to limitations of knowledge and finance. Sensitivity analysis of uncertainty sources allows an efficient flood risk management by considering various conditions in flood inundation mapping because an uncertainty source under different conditions may propagate in different ways. The objectives of this study are (1) to perform sensitivity analysis of uncertainty sources by different conditions on flood inundation map using the FOA method and (2) to find a major contributor to a propagated uncertainty in the flood inundation map in Flatrock at Columbus, U.S.A. Result of this study illustrates that an uncertainty in a variable is differently propagated to flood inundation map by combination with other uncertainty sources. Moreover, elevation error was found to be the most sensitive to uncertainty in the flood inundation map of the study reach.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.236-236
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• 2015

Flood is one of the major natural disasters affecting millions of people. Thailand also, frequently faces with this type of disaster. Especially, 2011 mega flood in Central Thailand, inundated highway severely attributed to the failure of national economic and risk to life. Lesson learned from such an extreme event caused flood monitoring and warning becomes one of the sound mitigations. The highway flood hazard mapping accomplished in this research is one of the strategies. This is due to highway flood is the potential risk to life and limb, and potential damage to property. Monitoring and warning therefore help reducing live and property losses. In this study, degree of highway flood hazard was assessed by weighting factors for each cause of the highway flood using Multi Criteria Analysis (MCA) based Analytic Hierarchy Process (AHP). These weighting factors are the essential information to classify the degree of highway flood hazard to enable pinpoint on flood monitoring and flood warning in hazard areas. The highway flood causes were then investigated. It was found that three major factors influence to the highway flood are namely the highway characteristics, the hydrological characteristics and the land topography characteristics. The weight of importance for each cause of the highway flood in the whole country was assessed by weighting 3 major factors influence to the highway flood. According to the result of MCA analysis, the highway, the hydrological and the land topography characteristics were respectively weighted as 35, 35 and 30 percent influence to the cause of highway flood. These weighting factors were further utilized to classify the degree of highway flood hazard. The Weight Linear Combination (WLC) method was used to compute the total score of all highways according to each factor. This score was later used to categorize highway flood as high, moderate and low degree of hazard levels. Highway flood hazard map accomplished in this research study is applicable to serve as the handy tool for highway flood warning. However, to complete the whole warning process, flood water level monitoring system for example the camera gauge should be installed in the hazard highway. This is expected to serve as a simple flood monitor as part of the warning system during such extreme or critical event.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.97-104
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• 2012

Recent climate change has increased the occurrence of flood disaster. There are two approaches to prevent flooding damage. One is a structural method and the other is a non-structural method. The production and usage of a flood risk map are the example of non-structural way. The flood risk map displays several kinds of information to minimize casualties and property damage caused from flooding. In order to increase the usage of current flood risk maps and improve intuitive recognition of flood information, this paper produced flood risk maps based on geo-spatial information system using three dimensional virtual reality techniques and investigated the applicability of the maps. Because flood information is easily accessed through online, flood risk maps suggested in this paper are regarded as an efficient tool.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.85-97
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• 2022

In this study, a method for an integrated flood risk mapping was proposed that simultaneously considers the flood inundation map indicating the degree of risk and the disaster vulnerability index. This method creates a new disaster map that can be used in actual situations by providing various and specific information on a single map. In order to consider the human, social and economic factors in the disaster map, the study area was divided into exposure, vulnerability, responsiveness, and recovery factors. Then, 7 indicators for each factor were extracted using the GIS tool. The data extracted by each indicator was classified into grades 1 to 5, and the data was selected as a disaster vulnerability index and used for integrated risk mapping by factor. The risk map for each factor, which overlaps the flood inundatoin map and the disaster vulnerability index factor, was used to establish an evacuation plan by considering regional conditions including population, assets, and buildings. In addition, an integrated risk analysis method that considers risks while converting to a single vulnerability through standardization of the disaster vulnerability index was proposed. This is expected to contribute to the establishment of preparedness, response and recovery plans for providing detailed and diverse information that simultaneously considers the flood risk including social, humanistic, and economic factors.

• 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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• 2021.06a
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• pp.139-139
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• 2021

Flooding events often result from extreme precipitations driven by various climate mechanisms, which are often disregarded in flood risk assessments. To bridge this gap, we propose a climate-mechanism-based flood frequency analysis that accommodates the direct linkage between the dominant climate processes and risk management decisions. Several statistical methods have been utilized in this approach including the Markov Chain analysis, K-nearest neighbor (KNN) resampling approach, and Z-score-based jittering method. After that, the impacts of climate change are associated with the modification of the transition matrix (TM) and the application of the quantile mapping approach. For this study, we have selected the Nam River Basin, South Korea, to consider the heterogeneous impacts of the two climate mechanisms, including the Tropical Cyclone (TC) and non-TCs. Based on our results, while both climate mechanisms have significant impacts on future flood extremes, TCs have been observed to bring more significant and immediate impacts on the flood extremes. The results in this study have proven that the proposed approach can lead to a new insights into future flooding management.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.125-133
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• 2019

In this paper, probabilistic flood risk maps were produced for levee break caused by possible flood scenarios. The results of the previous studies were employed for flood stages corresponding to hydrological extreme event quantified uncertainties and then predicted the location of a levee breach. The breach width was estimated by combining empirical equation considered constant width and numerical modeling considered uncertainties on compound geotechnical component. Accordingly, probabilistic breach outflow was computed and probabilistic inundation map was produced by 100 runs of 2D inundation simulation based on reliability analysis. The final probabilistic flood risk map was produced by combining probabilistic inundation map based on flood hazard mapping methodology. The outcomes of the study would be effective in establishing specified emergency actin plan (EAP) and expect to suggest more economical and stable design index.