# Estimating Flood Inundation in Urban Areas Using a Scenario Generation Method and Inundation Graphs
## 3 Application Results  
The field target area of study is the Gampo Sewage Treatment Plant, which is located near Gyeongju City as the first sewage treatment plant built as a pilot project for sewerage advancement. There is a small river to the north of the sewage treatment plant, so areas where flooding may occur in the event of flooding are analyzed. The buildings and areas that would be later used for the inundation graph creation are depicted in Figure 2.  
The runoff of the target area corresponding to the calculated rainfall was estimated using an empirical rational formula. Then, the scenario generation method was applied to  
Figure 1: Scenario creation methodology and database storage to graph. Figure 2: The field target area for the application. create input values and boundary conditions for the flow model for inundation analysis. Flood risk and flood vulnerability of each urban area were evaluated based on the input data from the scenarios and the results of the flood analysis. For this field target area, the scenario generation used return periods of 50, 100, 200, and 500 years, based on the regional rainfall data that was collected using local hydrologic data from the Flood Control Offices. After collecting the maximum rainfall data by year of the rainfall station in the target area up to 57 years, these data were used as sample data to estimate the variables for the theoretical distributions, which was used for rainfall estimation for higher return periods up to 500 years. The Gumbel and GEV distribution suitable for the rainfall data of the observation station was constructed, and the rainfall in the designated return period for each scenario was calculated. The distribution functions for the measured precipitation for the target area, for time scales of 9 h of rainfall, were compared with the observed rainfall using the Weibull plotting position in Figure 3.  
The comparison with observed data showed the mean absolute percentage error was 13.3% and 4.8% for the Gumbel and GEV distribution. Also, the coefficients of determination from the two distribution functions were 0.79 and 0.88 for the Gumbel and GEV distribution. The results show that both Gumbel and GEV distributions are appropriate for modeling, but the GEV had better accuracy. Next, the flow-time distribution using [PERSON]'s third-quartile classification of rainfall intensity profiles was also created. Finally, the rational method for runoff [35] was utilized to estimate the flow rate in the target area shown in Figure 4.  
The discharge boundary conditions for the two-dimensional flow model for inundation analysis used the time-discharge values from the estimated flow rate. For the river overflow conditions for the water surface elevation, the conventional power function equation \(Q=C(h-h_{0})^{m}\) were applied to the ungauged small river which was located in the north part of the target area shown in Figure 5, using similar \(C\) values from stage-discharge  
Figure 4: Estimated flow rate for the return period scenarios. Figure 3: Gumbel and GEV Distribution function plots compared to observed rainfall data. equations developed in a nearby city since actual measured stage data at the river in the model was not available. Then for the flow model, a triangular mesh was constructed using topographical data from the site, which consisted of 6684 elements and 3558 nodes shown in Figure 5.  
Using the flow rates from the return period scenarios, the two-dimensional flow simulation was conducted through several cases of scenarios. The results of the estimated depth were then stored in the inundation graph. Originally, the results of running the two-dimensional flow model in various cases would have looked similar to those in Figure 6, which depicts all the scenarios with 50-200-year flood frequency based on the theoretical functions of Gumbel and GEV. Although this is the typical result for two-dimensional simulation, the target area of interest may be located in a specific area of the constructed mesh.