• Korean Journal of Soil Science and Fertilizer
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• v.40 no.3
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• pp.208-213
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• 2007

When overland flow water is small and slow, it moves down a stream slowly and we use it as available resource. However, it could not only be good for nothing but arouse an inundation if a lot of runoff pour down to stream at a torrential rain. So it is important to know how much water to flow out and be stored in soil and on land in order to predict a flood and conserve soil and water quality. We intended to develop the prediction model of runoff in upland at a torrential rain and conducted lysimeter study in soybean cultivation and bare soil with 3 slopeness, 3 slope length and 5 soil texture from 1985 to 1991. The data of rainfall and runoff were used when daily rainfall was over 80 mm, the level of torrential rain warning. Minimum rainfall occurring runoff (MROR) was dependent on surface coverage and slope length. However soil texture and slopeness had a little influence on MROR. Runoff after MROR increased in proportion to precipitation which depended on surface coverage, soil texture and slope. Runoff ratio was larger in fine texture and bare soil than coarse soil and soybean coverage. Runoff ratio was in proportion to a square root of slope angle(radian) and reduced with slope length to converge a certain value. From these basis, we developed the prediction model following as $$Runoff(mm)=a(s^{0.5}+l^b)(Rainfall(mm)-80(1-e^{-bl}))$$ where a is a coefficient relevant soil hydraulic properties, b is a surface coverage coefficient, s is a slope angle and l is a slope length. The coefficient a was 0.5 in sandy loam and 0.6 in clay, and b was 0.06 in bare soil and 0.5 in soybean cultivation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.307-318
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• 2015

In this study, the efficiency of two-dimensional inundation analysis using road network was demonstrated in order to reduce the simulation time of numerical model in urban area. For this objective, three simulation conditions were set up: Case 1 considered only inundation within road zone, while Case 2 and 3 considered inundation within road and building zone together. Accordingly, Case 1 used grids generated based on road network, while Case 2 and 3 used uniform and non-uniform grids for whole study area, respectively. Three simulation conditions were applied to Samsung drainage where flood damage occurred due to storm event on Sep. 21, 2010. The efficiency of suggested method in this study was verified by comparison the accuracy and simulation time of Case 1 and those of Case 2 and 3. The results presented that the simulation time was fast in the order of Case 1, 2 and 3, and the fit of inundation area between each case was more than 85% within road zone. Additionally, inundation area of building zone estimated from inundation rating index gave a similar agreement under each case. As a result, it is helpful for study on real-time inundation forecast warning to use a proposed method based on road network and inundation rating index for building zone.