## 3 Urban Inundation Simulation Using the Rainfall Simulator  
### Runoff Descriptions  
The runoff patterns against rainfall intensities were analyzed from the runoff velocity and the inundation depth. Every measured data was converted to real scale values based on the Froude similitude defined as  
\[\mathrm{Fr}_{r}\ =\ \frac{v_{r}}{\sqrt{h_{r}}}\ =\ 1 \tag{2}\]  
where \(\mathrm{Fr}_{r}\) is the Froude number ratio defined as 1; \(v_{r}\) is the velocity ratio; \(h_{r}\) is the length scale defined as 1/200 in this study. Figure 6 shows time-averaged contours of the flow velocity according to rainfall intensity. The slope of the target area gradually decreased toward the north from the Namtaeryeong hill in the south. Thus, the flow accumulated in relatively low lands where the crossroad, Road A (Covered road over the Sadang-cheon), and Road B (Dongjak-daero) are located. The rainwater from the southern hill was rushed to the crossroad which has eight entrances to the underground space of Sadang station, and the velocity increased especially on the east side of the crossroad. The flood water running off the crossroad divided onto Road A and Road B. The rainwater from the residential areas also flowed to these roads. Thus, the flow velocity locally increased near the confluence of the main roads and the residential areas. The elevation on Road C is relatively higher than other areas, and the flow velocity was not observed because the inundation depth on this road was not high enough to transport particles for the LSPIV analysis. The aforementioned flow characteristics can be clearly observed according to increase of rainfall intensity.  
Figure 5: Flow measurements using Large-Scale Particle Image Velocimetry (LSPIV) and tape ruler: (**a**) runoff velocity measurement; (**b**) inundation depth measurement.  
The maximum velocity on Roads A and B occurred at the points depicted in Figure 6a. Point 1 is a confluence of Road A and a small street connected from the residential area. The flow direction between the two roads have an acute angle, and thus the flow velocity was more accelerated than other confluences. In case of point 2, the point is located where the width of the corridor for rainwater abruptly decreased the flow onto Road B from the crossroad. In addition, a structure of the entrance of the Sadang station near point 2 further decreased the flow area, and the runoff velocity increased more than another region of Road B. Point 3 is at the bottom of the mountain hill and the relatively steep slope in the crossroad caused the increase of the runoff velocity. The velocity at point 3 rarely increased when the rainfall intensity was over than 160 mm/h because the inundation depth sharply rose.  
Figure 7 shows distributions of the measured inundation depth according to the rainfall intensity. From the velocity measurement results, one can know that most flood accumulated in the crossroad and Roads A and B. The inundation depth also increased in these three regions. The eastern part of the crossroad was more inundated than the western region. The depth on Road A was higher than that on Road B due to the narrower road width. Previous research conducting numerical simulations in the Sadang area also show that the inundation depth increased through the crossroad and Roads A and B [1]. They concluded that the flood in the crossroad was caused by the rainwater flowing from the mountain hill and insufficient sewer system capacity. The depth slowly increased between 80 mm/h  
Figure 6: Runoff velocity distributions according to rainfall intensity: (**a**) 80 mm/h; (**b**) 130 mm/h; (**c**) 160 mm/h; (**d**) 185 mm/h.  
and 130 mm/h. When the rainfall intensity exceeded 160 mm/h, the inundation depth in the crossroad and Road A noticeably increased, and then the patterns turned to a slow rise again.