• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.3
• /
• pp.937-945
• /
• 2013

The accuracy of flood inundation maps is determined by the uncertainty propagated from all variables involved in the overall process including input data, model parameters and modeling approaches. This study investigated the uncertainty arising from key variables (flow condition and Manning's n) among model variables in flood inundation mapping for the Missouri River near Boonville, Missouri, USA. Methodology of this study involves the generalized likelihood uncertainty estimation (GLUE) to quantify the uncertainty bounds of flood inundation area. Uncertainty bounds in the GLUE procedure are evaluated by selecting two likelihood functions, which is two statistic (inverse of sum of squared error (1/SAE) and inverse of sum of absolute error (1/SSE)) based on an observed water surface elevation and simulated water surface elevations. The results from GLUE show that likelihood measure based on 1/SSE is more sensitive on observation than likelihood measure based on 1/SAE, and that the uncertainty propagated from two variables produces an uncertainty bound of about 2% in the inundation area compared to observed inundation. Based on the results obtained form this study, it is expected that this study will be useful to identify the characteristic of flood.

• Journal of Korea Water Resources Association
• /
• v.51 no.6
• /
• pp.481-490
• /
• 2018

Recently, the spatiotemporal patterns of flood disasters have become more complex and unpredictable due to climate change. Flood hazard map including information on flood risk level has been widely used as an unstructured measure against flooding damages. In order to product a high-precision flood hazard map by combination of hydrologic and hydraulic modeling, huge digital information such as topography, geology, climate, landuse and various database related to social economic are required. However, in some areas, especially in developing countries, flood hazard mapping is difficult or impossible and its accuracy is insufficient because such data is lacking or inaccessible. Therefore, this study suggests a method to delineate large scale flood-prone area based on topographic factors produced by linear binary classifier and ROC (Receiver Operation Characteristics) using globally-available geographic data such as ASTER or SRTM. We applied the proposed methodology to five different countries: North Korea Bangladesh, Indonesia, Thailand and Myanmar. The results show that model performances on flood area detection ranges from 38% (Bangladesh) to 78% (Thailand). The flood-prone area detection based on the topographical factors has a great advantage in order to easily distinguish the large-scale inundation-potent area using only digital elevation model (DEM) for ungauged watersheds.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.411-412
• /
• 2023

The purpose of this research and development is to develop a structure module that improves the efficiency and constructability of the layout structure as well as the design development of rainwater permeable storage tank blocks using inorganic binders and aggregates with the aim of reducing greenhouse gas (CO₂) with eco-friendly materials. In addition, for the efficient response to flooding of the developed permeable storage structure, we present a technical solution for combining drone mapping technology and flood monitoring technology that can analyze topographical factors in detail.

• Journal of Cadastre & Land InformatiX
• /
• v.45 no.2
• /
• pp.87-100
• /
• 2015

Currently, Korea government has strongly recommended the storm and flood insurance system to reduce the damage caused by natural disasters. The storm and flood insurance operated by private insurance company is the type of policy insurance. and is supervised by Minister of Public Safety and Security. It is the advanced disaster management system which is able to protect the public interests through unexpected natural disaster by assisting some part of the insurance premium from a central or local government. The main purpose of the present investigation is to build the insurance object GIS DB which should be necessary to calculate the premium rate in the map for storm and flood insurance, and also, to perform GIS analysis. The service model in this study is aimed to general single house, apartment and green house. The service management plan targeting the whole country has been investigated in terms of building DB and service operation.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.6_2
• /
• pp.1043-1050
• /
• 2020

In this study, a study was presented on the monitoring technique of landslide area using UAV. In the case of disaster investigation using drone mapping, it can be used at various disaster sites. The mission can be carried out at various disaster sites, including surveys of damage to mountainous areas caused by landslides, building collapses surveys of flood damage, typhoons, earthquakes. The damage investigation plan using drone mapping is expected to be highly utilized at disaster sites where investigators cannot access it like in mountainous areas and where it is difficult to conduct direct damage investigations at the site. Drone mapping technology has many advantages in terms of disaster follow-up, such as recovery. Compared to the existing survey system, which was mainly carried out manually, the investigation time can be drastically reduced, and it can also respond to disaster sites that are difficult to carry out or are difficult to access directly. In addition, it is possible to establish and guide spatial data at the disaster site based on accurate mapping data from the time of the disaster, which has considerable strength in managing the situation of the disaster site, selecting priority areas for recovery, and establishing recovery plans. As such, drone mapping is a technology that can be used in a wide range of sites along with natural disasters and social disasters. If a damage investigation system is established through this, it is believed that it will contribute significantly to the rapid establishment of recovery plans along with the investigation of disaster response time and extent of damage recovery.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.6
• /
• pp.155-163
• /
• 2010

The past researches on flood inundation simulation mainly focused on development of numerical models based on unstructured mesh networks to improve model performances. However, despite the accurate simulation results, such models are not suitable for real-time flood inundation forecasting due to a huge computational burden in terms of geographic data processing. In addition, even though various types of vector and raster data are available to be compatible with flood inundation models for post-processes such as flood hazard mapping and flood inundation risk analysis, the unstructured mesh-based models are not effective to fully use such information due to data incommensurability. Therefore, this study aims to develop a raster-based two-dimensional inundation model; it guarantees computational efficiency because of direct application of DEM for flood inundation modeling and also has a good compatibility with various types of raster data, compared to a commercial model such as FLUMEN. We applied the model to simulate the BaekSan levee break in the Nam river during a flood period from August 10 to 13, 2002. The simulation results showed a good agreement with the field-surveyed inundation area and were also very similar with results from the FLUMEN. Moreover, the model provided physically-acceptable velocity vectors with respect to inundating and returning flows due to the difference of water level between channel and lowland.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.4
• /
• pp.726-733
• /
• 2016

Recently, the flood frequency and magnitude have increased due to heavy rainfall. Considering the present condition, a flood risk map has been published in many countries to raise awareness about flood damage to people. A flood inundation analysis model, which is used to publish the flood risk map, can be classified as river and inland inundation models according to the inundation cause. Although a variety of flood inundation analysis models are utilized both domestically and overseas, their usability is limited by the expensive price, except for the HEC-RAS model developed by U.S. Army Corps of Engineers (USACE). In the situation, the USACE has developed a 2-D HEC-RAS model that can be linked to the existing 1-D model. This model has been released as a beta version under the name, HEC-RAS 5.0. In this study, the HEC-RAS 5.0 model's features, usability, applicability, and accuracy were evaluated by comparing the performances on Gokgyo-cheon with the FLUMEN model, which is used for domestic flood risk mapping. The results of this study will contribute to river inundation analysis in many different ways after the HEC-RAS 5.0 model is stabilized.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.122-126
• /
• 2010

This paper elaborates on difficulties when ones tried to apply domestically developed technology to other countries from both technical and sociological aspects. Next, the author proposes possible solutions to expand the applicability of domestic technology. The main one is breaking down a technology to smaller components so that anybody can clarify the applicability of each component. The author presents an example of this methodology to flood hazard mapping.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.6
• /
• pp.1011-1021
• /
• 2016

This study performs the potential flood hazard analysis by applying elevation data, soil data and land use data. The susceptibility maps linked to elevation, soil and land use are combined to develop the new types of flood hazard map such as runoff production map and runoff accumulation map. For the development of the runoff production map, land use, soil thickness, permeability, soil erosion and slope data are used as runoff indices. For the runoff accumulation map, elevation, knick point and lowland analysis data are used. To derive an integrated type of flood potential hazard, a TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) technique, which is widely applied in MCDM (Multi-Criteria Decision Making) process, is adopted. The indices applied to the runoff production and accumulation maps are considered as criteria, and the cells of analysis area are considered as alternatives for TOPSIS technique. The model is applied to Gamcheon watershed to evaluate the flood potential hazards. Validation with large scale data shows the good agreements between historical data and runoff accumulation data. The analysis procedure presented in this study will contribute to make preliminary flood hazard map for the public information and for finding flood mitigation measures in the watershed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.208-208
• /
• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.