• Smart Media Journal
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• v.11 no.7
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• pp.52-60
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• 2022

Due to global warming and changes in the natural environment, flood damage to agricultural land due to wind and flood damage continues. Although disaster prevention projects have been continuously carried out since the founding of the country, progress has been insufficient compared to the sustained period, and huge costs are still being consumed. Therefore, it is necessary to use predictive simulation for pre-emptive response to inundation of farmland. In this paper, a case of immersion analysis simulation using a GIS(Geospatial Information System) based SWMM model was introduced, and the validity was confirmed through the error rate between our simulation result and the results of other models in the US and Korea. In addition, in the direction of using the simulation for agricultural land inundation, we presented various utilization methods to supplement the current agricultural land inundation-based information policy, such as the creation of flood traces. If simulation results from more regions are accumulated in the form of the flood analysis maps in the future, it is expected that they will be able to be utilized in various applications for preemptive response to and prevention of water disasters at the national level.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.637-640
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• 2008

Flood control and river improvement works are carried out every year for the defense of the flood disaster, it is impossible to avoid the damage when there is a flood exceeding the capacity of hydraulic structures. Therefore, nonstructural counter plans such as the establishment of flood hazard maps, the flood warning systems are essential with structural counter plans. In this study, analysis of the internal inundation effect using rainfall runoff model such as PC-SWMM was applied to Woo Ee experimental stream basin. Also, the design frequency analysis for effects of the external inundation was accomplished by main parameter estimation for conclusive hydraulic routing using HEC-RAS model. Finally, inundated areas for flood hazard map were estimated at Woo Ee downstream basin according to flood frequency using HEC-GeoRAS model linked by Arc View GIS.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.29-29
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• 2023

To mitigate the damaging impacts of floods, accurate prediction of runoff, streamflow and flood inundation is needed. Conventional approach of simulating hydrology and hydraulics using loosely coupled models cannot capture the complex dynamics of surface and sub-surface processes. Additionally, the scarcity of data in ungauged basins and quality of data in gauged basins add uncertainty to model predictions, which need to be quantified. In this presentation, first the role of integrated modeling on creating accurate flood simulations and inundation maps will be presented with specific focus on urban environments. Next, the use of machine learning in producing streamflow predictions will be presented with specific focus on incorporating covariate shift and the application of theory guided machine learning. Finally, a framework to quantify the uncertainty in flood models using Hierarchical Bayesian Modeling Averaging will be presented. Overall, this presentation will highlight that creating accurate information on flood magnitude and extent requires innovation and advancement in different aspects related to hydrologic predictions.

• Journal of the Korean GEO-environmental Society
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• v.15 no.1
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• pp.69-77
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• 2014

The objective of this study is to compare flood inundation models for small stream basin. HEC-RAS model was used for the analysis of one dimensional hydraulics and HEC-GeoRAS, Ras Mapper and RiverCAD models were applied for the flood inundation analysis in Gum Chung stream. Flood inundations are to simulate by flood inundation models using observed data and rainfall on each frequency and to compare with inundation area based on the flood plain maps. The results of this study are as follows; Area of flood inundations by HEC-GeoRAS model is similar to that of flood plain map and appears in order of RAS Mapper and RiverCAD model. Flood inundation area by RiverCAD model is to estimate lager than that of RAS Mapper and HEC-GeoRAS model in flood area on each frequency and the results show that they have a little difference in models of flood inundation analysis at small stream. Comparing the area of flood inundations by flood depth, the results of three models are relatively similar in flood depth as 2.0 m below, and RiverCAD model shows a significant difference in flood depth as 2.0 m or more.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.335-342
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• 2015

In this study, data linking module called GeoSWMM was developed using a typical secondary flooding model SWMM in order to improve the accuracy of the input data of SWMM and to map hourly inundation estimation areas that were not represented in the conventional inundation map. GeoSWMM is a data linking module of GIS and SWMM, which can generate a SWMM project file directly from sewer network GIS data. Utilizing the GeoSWMM the project file of SWMM model was constructed in the study area, Seocho 2-dong, Seoul. The actual flooding has occurred September 21, 2010 and the actual rainfall data were used for flood simulation. As a result, the outflow started from 2 PM due to the lack of water flow capacity of the sewage system. Based on the results, hourly inundation estimation maps were produced and compared with flood train map in 2010. The comparison showed about 66% matching in the overlap of inundation areas. By utilizing GeoSWMM that was developed in this study, it is easy to build the sewer network data for SWMM. In addition, the creation of hourly inundation estimation map using SWMM will be much help to flood disaster prevention plan.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.165-179
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• 2024

It is crucial to have a comprehensive understanding of inundation and water cycle in urban areas for mitigating flood risks and sustainable water resources management. In this study, we developed a Cellular Automata-based integrated Water cycle model (CAW). A comparative analysis with physics-based and conventional cellular automata-based models was performed in an urban watershed in Portland, USA, to evaluate the adequacy of spatiotemporal inundation simulation in the context of a high-resolution setup. A high similarity was found in the maximum inundation maps by CAW and Weighted Cellular Automata 2 Dimension (WCA2D) model presumably due to the same diffuse wave assumption, showing an average Root-Mean-Square-Error (RMSE) value of 1.3 cm and high scores of binary pattern indices (HR 0.91, FAR 0.02, CSI 0.90). Furthermore, through multiple simulation experiments estimating the effects of land cover and soil conditions on inundation and infiltration, as the impermeability rate increased by 41%, the infiltration decreased by 54% (4.16 mm/m²) while the maximum inundation depth increased by 10% (2.19 mm/m²). It was expected that high-resolution integrated inundation and water cycle analysis considering various land cover and soil conditions in urban areas would be feasible using CAW.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.203-213
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• 2018

This study aims to propose the methods for urban flood risk maps which are useful in strengthening urban planning toward disaster prevention by climate change. Selecting the Gwangju city, Gyeonggi-do as study area, it analyzes urban flood at a RCP 8.5 scenario, and develops gridded information regarding risk components such as hazard, exposure, and vulnerability. It turns out that flooding would occur at a bend interval of the Mokhyun stream and also at the joint of the Gyungan and the Mokhyun streams, showing the similarity with the inundation trace map. In particular, the Songjeong dong is analyzed to be seriously exposed and to be highly vulnerable to flood inundation. With all results together, this study concludes that the proposed methods could be used as a basis for strengthening urban planning toward flood disaster prevention system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.937-945
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• 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
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• v.47 no.11
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• pp.1051-1060
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• 2014

This study is attempted to realize an improved computation performance by combining the MPI (Message Passing Interface) Technique, a standard model of the parallel programming in the distributed memory environment, with the DHM(Diffusion Hydrodynamic Model), a inundation analysis model. With parallelizing inundation model, it compared with the existing calculation method about the results of applications to complicate and required long computing time problems. In addition, it attempted to prove the capability to estimate inundation extent, depth and speed-up computing time due to the flooding in protected lowlands and to validate the applicability of the parallel model to the actual flooding analysis by simulating based on various inundation scenarios. To verify the model developed in this study, it was applied to a hypothetical two-dimensional protected land and a real flooding case, and then actually verified the applicability of this model. As a result of this application, this model shows that the improvement effectiveness of calculation time is better up to the maximum of about 41% to 48% in using multi cores than a single core based on the same accuracy. The flood analysis model using the parallel technique in this study can be used for calculating flooding water depth, flooding areas, propagation speed of flooding waves, etc. with a shorter runtime with applying multi cores, and is expected to be actually used for promptly predicting real time flood forecasting and for drawing flood risk maps etc.