• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.775-778
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• 2008

In general, forecast tsunami heights announced for tsunami warning are computed by using a linear tsunami model with coarse grids which leads the underestimation of inundation area. Thus, an accurate tsunami inundation map corresponding to the forecast tsunami height is indispensible for an emergency evacuation plan. A practical way to construct a relatively accurate tsunami inundation map was proposed in this study for the quantitative forecast of inundation area. This procedure can be introduced as in the followings: The fault dislocations of potential tsunami sources generating a specific tsunami height near an interested area are found by using a linear tsunami model. Based on these fault dislocations, maximum inundation envelops of the interested area are computed and illustrated by using nonlinear inundation numerical model. In this study, the tsunami inundation map for Imwon area was constructed according to 11 potential tsunami sources, and the validity of this process was examined.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.1-15
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• 2013

Great loss of life and property has been occurred by the severe flood globally. In Korea, a flood inundation map is used as one of the non-structural measures for reducing flood damage, and various inundation models have been studied for flood inundation analysis. This study applies LiDAR data and LISFLOOD model for flood inundation analysis and discusses the the modeling results from levee breaching scenarios for evaluating the applicability of the model to stream inundation modeling. In the results of LISFLOOD modeling, maximum inundation area was similar to the inundation map by HEC-RAS model just less than 4%. The inundation area by each levee breaching scenario showed the difference from 0.2% to 6.5%. Inundation processes were different each other according to the position of levee breach point, and maximum inundation area and depth were changed by the flow direction of stream and flood plain. This study shows that LISFLOOD model can be applied properly to stream inundation analysis using various inundation scenarios.

• Journal of Environmental Science International
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• v.13 no.1
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• pp.19-26
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• 2004

The purpose of the study was to construct a forecast system of flood inundation area at natural stream channels. The study built the system to interpret the flood inundation area in four stages ; constructing topography data around the stream channel, interpreting flood discharge, interpreting flood elevation in the stream channel, and interpreting the flood inundation and mapping. According to the result of the analysis, as for the characteristic of flood inundation around the area within the purview of this study, although there were areas where flood inundation over a bank caused a flooded area, the failure of the internal drainage in the ground lower than flood elevation caused more serious problems. Rather than the existing method where only the estimated flood elevation data is used based on the hydrographical stream channel trace model(such as the HEC-RAS model) to establish the flood inundation area, if the procedure introduced in this study was applied to interpret the floodplain, actual flood inundation area could be visibly confirmed.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.579-582
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• 2007

In this paper, the inundation simulations were carried out by using GIS tools for the analysis of detention efficiency based on the results of runoff analysis according to location and scale of regional detention facilities. The inundation maps could be drawn by the inundation simulations, and the locations and magnitude of inundation areas could be estimated through the inundation maps. The inundation simulations with GIS tools are approved to be the one of the useful method in designing optimized location and scale of regional detention facilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.33-43
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• 2020

In order to reduce damage from farmland inundation caused by recent climate change, it is necessary to predict the risk of farmland inundation accurately. Inundation modeling should be performed by considering multiple time distributions of possible rainfalls, as digital forecasts of Korea Meteorological Administration is provided on a six-hour basis. As building multiple inputs and creating inundation models take a lot of time, it is necessary to shorten the forecast time by building a data base (DB) of farmland inundation probability. Therefore, the objective of this study is to establish a DB of farmland inundation probability in accordance with forecasted rainfalls. In this study, historical data of the digital forecasts was collected and used for time division. Inundation modeling was performed 100 times for each rainfall event. Time disaggregation of forecasted rainfall was performed by applying the Multiplicative Random Cascade (MRC) model, which uses consistency of fractal characteristics to six-hour rainfall data. To analyze the inundation of farmland, the river level was simulated using the Hydrologic Engineering Center - River Analysis System (HEC-RAS). The level of farmland was calculated by applying a simulation technique based on the water balance equation. The inundation probability was calculated by extracting the number of inundation occurrences out of the total number of simulations, and the results were stored in the DB of farmland inundation probability. The results of this study can be used to quickly predict the risk of farmland inundation, and to prepare measures to reduce damage from inundation.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.2
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• pp.164-173
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• 2009

MIKE21, a commercial hydrodynamic model, was applied at the Masan Bay to evaluate the model's applicability of simulating the inundation phenomena. A storm surge/inundation model which adopts overflow computation scheme was applied together for comparison. The results of both models show correspondence with not only observed inundation area but also inundation water depth to prove their ability as inundation models. Especially, the accuracy of the MIKE21 model, which just adopts wetting/drying scheme, does not seem to be behind the inundation model. Moreover, an inundation simulation of the virtual MAEMI which was generated at preceding study, was conducted. The inundation area of the virtual MAEMI is similar to that of the real MAEMI, but inundation water depth is deeper than the real MAEMI.

• Atmosphere
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• v.27 no.2
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• pp.189-197
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• 2017

Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.88-100
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• 2009

An inundation analysis was performed on Hwapocheon, one of the tributaries of Nakdong River, which was inundated by heavy rain in August, 2002 with overtopping and levee break. The results of the developed model, 2D diffusion wave inundation analysis model, was compared with inundation trace map as well as inundation depth in terms of time and maximum inundated area calculated from FLUMEN model for the assessment of model applicability. The results from the developed model showed high fitness of 88.61% in comparison with observed data. Also maximum inundated area and spatial distribution of inundation zone were also found to be consistent with the results of FLUMEN model. Therefore, inundation zone and maximum inundation area calculated over a period of time by adopting 2D diffusion wave inundation analysis model can be used as a database for identifying high risk areas of inundation and establishing flood damage reduction measures.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.87-96
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• 2019

The objective of this study was to develop a general inundation modeling technique considering the effect of drainage delay in the paddy field districts. In most studies, farmland inundation simulations have been conducted using previously developed watershed models. However, the water cycle in the paddy fields has a different structure from that of the general watershed, and the effect of the drainage delay should be considered. In this study, the drainage delay algorithm was developed using water balance equation, and the inundation modeling was performed for inundation-prone paddy fields located near Doowol stream. As a result, the depth of inundation was 43.1 cm and 45.2 cm, respectively, due to the 100-year and 200-year frequency rainfall. With the operation of drainage pump ($0.1m^3/s$), inundation depths decreased by 5.8 cm and 6.0 cm, respectively, and inundation time reduced by 20 hours and 21 hours, respectively for the 100-year and 200-year frequency rainfall. The result showed that the general inundation modeling technique developed in this study could reflect the effect of drainage delay due to the rise of external water level and the flooding reduction effect by operation of drainage pump. The results of this study are expected to be useful to establish measures for damage caused by farmland inundation.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.49-66
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• 2024

Extreme rainfall will become intense due to climate change, increasing inundation risk to agricultural land. Hydrological and hydraulic simulations for the entire watershed were conducted to analyze the impact of climate change. Rainfall data was collected based on past weather observation and SSP (Shared Socio-economic Pathway)5-8.5 climate change scenarios. Simulation for flood volume, reservoir operation, river level, and inundation of agricultural land was conducted through K-HAS (KRC Hydraulics & Hydrology Analysis System) and HEC-RAS (Hydrologic Engineering Center - River Analysis System). Various scenarios were selected, encompassing different periods of rainfall data, including the observed period (1973-2022), near-term future (2021-2050), mid-term future (2051-2080), and long-term future (2081-2100), in addition to probabilistic precipitation events with return periods of 20 years and 100 years. The inundation area of the Aho-Buin district was visualized through GIS (Geographic Information System) based on the results of the flooding analysis. The probabilistic precipitation of climate change scenarios was calculated higher than that of past observations, which affected the increase in reservoir inflow, river level, inundation time, and inundation area. The inundation area and inundation time were higher in the 100-year frequency. Inundation risk was high in the order of long-term future, near-term future, mid-term future, and observed period. It was also shown that the Aho and Buin districts were vulnerable to inundation. These results are expected to be used as fundamental data for assessing the risk of flooding for agricultural land and downstream watersheds under climate change, guiding drainage improvement projects, and making flood risk maps.