• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.71-84
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• 2022

The objective of this study is to develop a two-dimensional (2D) flood model that can perform accurate flood analysis with simple input data. The 2D flood inundation models currently used to create flood forecast maps require complex input data and grid generation tools. This sometimes requires a lot of time and effort for flood modeling, and there may be difficulties in constructing input data depending on the situation. In order to compensate for these shortcomings, in this study, a grid-based model that can derive accurate and rapid flood analysis by reflecting correct topography as simple input data was developed. The calculation efficiency was improved by extending the existing 2×2 sub-grid model to a 5×5. In order to examine the accuracy and applicability of the model, it was applied to the Gamcheon Basin where both urban and river flooding occurred due to Typhoon Rusa. For efficient flood analysis according to user's selection, flood wave propagation patterns, accuracy and execution time according to grid size and number of sub-grids were investigated. The developed model is expected to be highly useful for flood disaster mapping as it can present the results of flooding analysis for various situations, from the flood inundation map showing accurate flooding to the flood risk map showing only approximate flooding.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.991-998
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• 2022

The purpose of this study is to develop GPU (Graphics Processing Unit) acceleration technique for 2-dimensional model and to assess the effectiveness for high resolution flood simulation in wide area In this study, GPU acceleration technique was implemented in the G2D (Grid based 2-Dimensional land surface flood model) model, using implicit scheme and uniform square grid, by using CUDA. The technique was applied to flood simulation in Jinju-si. The spatial resolution of the simulation domain is 10 m × 10 m, and the number of cells to calculate is 5,090,611. Flood period by typhoon Mitag, December 2019, was simulated. Rainfall radar data was applied to source term and measured discharge of Namgang-Dam (Ilryu-moon) and measured stream flow of Jinju-si (Oksan-gyo) were applied to boundary conditions. From this study, 2-dimensional flood model could be implemented to reproduce the measured water level in Nam-gang (Riv.). The results of GPU acceleration technique showed more faster flood simulation than the serial and parallel simulation using CPU (Central Processing Unit). This study can contribute to the study of developing GPU acceleration technique for 2-dimensional flood model using implicit scheme and simulating land surface flood in wide area.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.316-316
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• 2023

2022년 8월 수도권 이상폭우로 인해 서울 도심지역의 지하시설, 도로, 주택 등에 침수가 발생하면서 인명 및 재산피해가 발생하였으며, 특히 동서로 가로지르는 정체전선으로 좁고 긴 비구름이 집중되면서 국지적으로 피해가 집중되었다. 서울시의 경우 도시화에 따른 불투수지역 증가 및 내수배제 불량에 따른 빗물 역류로 인한 피해가 지속적으로 발생하고 있으며, 최근에는 기후변화에 따른 방재성능목표 강우량을 초과하는 빈도의 이상폭우로 인해 하천범람과 내수배제 불량에 따른 복합적인 원인으로 침수피해 가중되고 있는 실정이다. 또한 서울시의 경우 전체 자연적, 사회적, 경제적, 환경적 요인 등의 지역적 편차가 매우 큰 도시로 지형적인 특성뿐만 아니라 취약시설(병원, 학교 등), 수방시설물(하천, 배수시설, 빗물펌프장 등) 및 방재시설(대피소, 구호소 등) 밀도 등에 따른 침수 취약성 및 위험성 등의 편차가 매우 크기 때문에 지역특성에 대한 피해사례가 다원화 되고 있는 실정이다. 본 연구에서는 30년 이상의 종관기상관측(ASOS)과 서울시 자치구별 20년 이상의 방재기상관측(AWS)자료를 기반으로 CMIP6 SSP(Shared Socioeconomic Pathways, 공통사회 경제경로)시나리오에 따른 극한기후 지수(강수강도, 호우일수, 지속기간, 1일 최대강수량, 95퍼센타일 강수일수 등)에 대한 재현성을 평가하고 공간자기상관분석 등 시공간적인 강우특성에 대한 변화를 전망하였다. 특히 여름철 강우의 경우 자치구별 편차가 크게 나타났고 이를 통해 대도시의 도심지역의 경우 세분화하여 지역의 정확한 강우특성을 파악하는 것이 필요하다는 것을 확인할 수 있었다. 본 연구의 결과는 도심지의 방재성능 초과강우 정의와 기준을 수립하고, 장기적인 수자원 및 도시계획 차원의 대책을 마련하는데 활용될 수 있을 것으로 판단된다. 기후위기에 따른 기록적인 호우(지역별 방재성능을 초과하는 강우)에 따른 재해는 구조적인 대책을 통해 모두 저감할 수 없는 한계가 있다. 하지만 인명피해를 최소화하는 것을 목표로 기후위기에 대한 적응단계로 인식하고 수리·수문학적, 사회경제학적 등 지역특성에 따른 방재성능목표 강우량에 대한 재검토와 더불어 법제도(풍수해보험, 저류조설치 의무화 등), 개인별 재해예방, 취약계층 안전망 확보, 반지하주택 침수안전대책, 재해지도 개선 등 구조적/비구조적인 대책을 통합 수립 및 보완하는 것이 필요한 시점이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3B
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• pp.271-281
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• 2008

To determine the flood protection elevation (FPE) in urban built-up areas, this study examines four possible methods: using the highest flood elevation in the past, extending base flood elevations of nearby watercourse to inland, and two simulation methods of inland flood under the same rainfall used in the watercourse planning nearby. According to the case study of the Jang-An Drainage Area, Seoul, the highest flood elevation in the past and simulation results of inland flood under the same rainfall in the watercourse planning nearby tend to get similar results, while extending base flood elevations of nearby watercourse to inland shows much higher elevations than other results. Meanwhile, cost-benefit analysis, when regulating residential/commercial uses below the FPE by each of four methods, suggest that planners need to consider carefully the economic feasibility of FPE used to choose appropriate methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3B
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• pp.261-270
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• 2008

Even though there is a great deal of progress in a numerical method of high caliber like SPH, it is very rarely deployed in a water resources community. Despite the great stride in computing environment, depth averaged approach like a nonlinear shallow equation is still efficient tool for flood routing in large watershed, but it can give some misleading information like the inundation height of flood. In this rationale, we numerically simulate the flow into the dry channel, dry channel with an obstacle triggered by the collapse of a two dimensional water column using SPH (Smoothed Particle Hydrodynamics) in order to boost the application of numerical method of high caliber like SPH in a water resources community. As a most severe test of the robustness of SPH, we also carry out the simulation of the flow through a clearance into the wet channel driven by the rapid removal of a water gate. As a hydrodynamic model, we used the Navier-Stokes equation, a numerical integration of which was carried out using SPH. To verify the validity of newly proposed numerical model, we compare the numerically simulated flow with the others in the literature mainly from VOF and MAC, and hydraulic experiments by Martin and Moyce (1952), Koshizuka et al. (1995) and Janosi et al. (2004). It was shown that agreements between the numerical results in this study and hydraulic experiments are remarkable.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.501-509
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• 2006

The safety of levee that depends on the river flood elevation has been regarded as very important keys to build up various flood prevention systems. However, deterministic methods for computation of water surface profile cannot reflect the effect of possible inaccuracies in the input parameters. The purpose of this study is to develop a methodology of uncertainty computation of design flood level based on steady flow analysis and Monte Carlo simulation. This study addresses the uncertainty of water surface elevation by Manning's coefficients, design discharges, river cross sections and boundary condition. Monte Carlo simulation with the variations of these parameters is performed to quantify the variations of water surface elevations in a river. The proposed model has been applied to the Kumho-river. The reliability analysis was performed within 38.5 km (95 sections) reach considered the variations of the above-mentioned parameters. Overtopping risks were evaluated by comparing the elevations of the flood condition with the those of the levees. The results show that there is a necessity which will raise the levee elevation between 1 cm and 56 cm at 7 sections. The model can be used for preparing flood risk maps, flood forecasting systems and establishing flood disaster mitigation plans as well as complement of conventional levee design.