• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.237-250
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• 2023

Orthophotos and DEMs were generated by UAV-based aerial photogrammetry and an attempt was made to apply them to detailed investigations for the production of flood traces. The cultivated area located in Goa-eup, Gumi, where the embankment collapsed and inundated inundation occurred due to the impact of 6th Typhoon Sanba in 2012, was selected as rhe target area. To obtain optimal accuracy of UAV photogrammetry performance, the UAV images were taken under the optimal placement of 19 GCPs and then point cloud, DEM, and orthoimages were generated through image processing using Pix4Dmapper software. After applying CloudCompare's CSF Filtering to separate the point cloud into ground elements and non-ground elements, a finally corrected DEM was created using only non-ground elements in GRASS GIS software. The flood level and flood depth data extracted from the final generated DEM were compared and presented with the flood level and flood depth data from existing data as of 2012 provided through the public data portal site of the Korea Land and Geospatial Informatix Corporation(LX).

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1153-1162
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• 2008

The use of radar rainfall for hydrological appraisal has been a challenge due to the limitations in raw data generation followed by the complex analysis needed to come up with precise data interpretation. In this study, RAIDOM (RAdar Image DigitalizatiOn Method) has been developed to convert synthetic radar CAPPI(Constant Altitude Plan Position Indicator) image data from Korea Meteorological Administration into digital format in order to come up with a more practical and useful radar image data. RAIDOM was used to examine a severe local rainstorm that occurred in July 2006 as well as two other separate events that caused heavy floods on both upper and mid parts of the HanRiver basin. A distributed model was developed based on the available radar rainfall data. The Flood Hydrograph simulation has been found consistent with actual values. The results show the potentials of RAIDOM and the distributed model as tools for flood prediction. Furthermore, these findings are expected to extend the usefulness of radar rainfall data in hydrological appraisal.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.351-362
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• 2017

Recently, analysis techniques to extract new meanings using big data analysis and various services using them have been developed. A disaster safety service among such services has been paid attention as the most important service. In this paper, we design and implement a flood disaster safety system using real time weather big data. The proposed system retrieves and processes vast amounts of information being collected in real time. In addition, it analyzes risk factors by aggregating the collected real time and past data and then provides users with prediction information. The proposed system also provides users with the risk prediction information by processing real time data such as user messages and news, and by analyzing disaster risk factors such a typhoon and a flood. As a result, users can prepare for potential disaster safety risks through the proposed system.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.1023-1034
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• 2008

The size and frequency of the natural disaster related to the severe storms are increased for recent decades in all over the globe. The damage from natural disasters such as typhoon, storm and local severe rainfall is very serious in Korea since they are concentrated on summer season. These phenomena will be more frequent in the future because of the impact of climate change related to increment of $CO_2$ concentration and the global warming. To reduce the damage from severe storms, a short-range precipitation forecasting model using a weather radar was developed. The study was conducted as following four tasks: conversion three-dimensional radar data to two-dimensional CAPPI(Constant Altitude Plan Position Indicator) efficiently, prediction of motion direction and velocity of a weather system, estimation of two-dimensional rainfall using operational calibration. Results demonstrated that two-dimensional estimation using weather radar is useful to analyze the spatial characteristics of local storms. If the precipitation forecasting system is linked to the flood prediction system, it should contribute the flood management and the mitigation of flood damages.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.227-238
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• 2024

This study addresses the escalating flood damages prompted by recent climate shifts characterized by extreme weather events and proposes rainwater infiltration blocks as a potential solution. Recognizing the limitations inherent in existing inundation simulation methods, we advocate for the integration of novel functionalities, particularly leveraging drone technology. Our research endeavors encompass experimental assessments of inundation and flooding simulation technologies. These evaluations are conducted within areas where rainwater infiltration storage blocks have been implemented, juxtaposed against existing programs utilizing Digital Elevation Models(DEM) and Digital Surface Models(DSM). Through this comparative analysis and a meticulous scrutiny of the adaptability of inundation and flooding simulation to real-world deployment scenarios, we ascertain the efficacy of the simulation program as a decision-making tool for identifying optimal sites for rainwater infiltration storage block installation.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Journal of the Society of Disaster Information
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• v.12 no.1
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• pp.74-88
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• 2016

Predicting and estimating the disaster characteristics are very important for disaster planning such as prevention, preparedness, response, and recovery. Especially, if we can predict the flood damage before flooding, the predicted or estimated damage will be a very good information to the decision maker for the response and recovery. However, most of the researches, have been performed for calculating disaster damages only after disasters had already happened and there are few studies that are related to the prediction of the damages before disaster. Therefore, the objective of this study was to predict and estimate the flood damages rapidly considering the damage scale and effect before the flood disaster, For this the relationship of rainfall and damage had been suggested using nonlinear regression equation so that it is able to predict the damages according to rainfall. We compared the estimated damages and the actual ones. As a result, the damages were underestimated in 14.16% for Suwon-city and 15.81% for Yangpyeong-town but the damage was overestimated in 37.33% for Icheon-city. The underestimated and overestimated results could be occurred due to the uncertainties involved in natural phenomenon and no considerations of the 4 disaster steps such as prevention, preparedness, response, and recovery which were already performed.. Therefore, we may need the continuous study in this area for reducing various uncertainties and considering various factors related to disasters.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.11-18
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• 2016

The objective of this study was to develop the simple method to estimate ungauged river section for flood stage analysis. Damage prediction should be prioritized using hydrological modeling to reduce flood risk. Mostly, the geographical data using hydrological modeling depends on national river cross-section survey. However because of the lack of measured data, it is difficult to apply to many local streams or small watersheds. For this reason, this study suggest the method to estimate unguaged river cross-section. Simple regression equations were derived and used to estimate river cross-section by analyzing the correlation between the river cross-sectional characteristics (width, height and area). The estimated cross-sections were used to simulate flood level by HEC-RAS (Hydrologic Engineering Center's River Analysis System). The applicability of this method was verified by comparing simulated flood level between measured and estimated cross-section. The water surface elevation of the flood stage analysis was 6.56-7.24 m, 5.33-5.95 m and 6.12-6.75 m for measured cross section, for estimated cross section and for estimated cross section based on DEM elevation, respectively. Further study should consider other factors for more accurate flood stage analysis. This study might be used one of the guidelines to estimate ungauged river section for flood stage analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.381-389
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• 2019

It is important to estimate flood overflow because adverse weather phenomena are frequently occurring in recent years. In order to cope with such abnormal floods, it is essential to perform flood inundation simulations for constructing flood inundation maps as nonstructural countermeasures. However, there is no quantitative evaluation method and criterion for flood inundation prediction. In this study, the Receiver Operation Characteristics (ROC) and Lee Sallee Shape Index (LSSI) were employed to quantitatively evaluate the accuracy of flood inundation maps for 10 administrative districts. Comparing predicted inundation maps with actual inundation trace maps, the ROC score was 0.631 and the LSSI was 25.16 %. Using the ROC and the LSSI, we proposed an evaluation criterion for flood inundation map. The average score was set as an intermediate score and distributed into 5 intervals. The validity of the evaluation criterion was investigated by applying to the XP-SWMM model, which has been verified and corrected. The ROC analysis result was 0.8496 and the LSSI was 51.92 %. It is considered that the proposed evaluation criteria can be applied to flood inundation maps.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.101-110
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• 2010

The increased occurrence of flooding due to typhoons and local rainfall has necessitated damage prevention through the systematic construction of damage history and quantitative analysis of flood prediction data. In this study, we constructed a disaster information map for practical use by combining digital images and continuous cadastral maps of damaged areas using a geographic information system to provide basic data and attribute information. In addition, we predicted the areas at risk of flash floods by calculating the flood capacity of the study area for different rainfall frequencies through flood inundation simulation, which was used to obtain comprehensive disaster information. Further, we calculated the extent of the flooded area and the damage rate for different rainfall frequencies using cadastral information. Flood inundation simulation in the case of heavy rainfall was found to help improve the ability to react to a flood and enhance the efficiency of rescue work by supporting decision-making for disaster management.