• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.234-238
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• 2008

The energy conservation theory is introduced for investigating processes of runoff and soil erosion on the hillslope system changed vegetation condition by wildfire The rainfall energy, input energy consisted of kinetic and potential energy, is influenced by vegetation coverage and height. Output energy at the outlet of hillslope is decided as the kinetic energy of runoff and erosion soil, and mechanical work according to moving water and soil is influenced dominantly by the work rather than the kinetic energy. Relationship between output and input energy is possible to calculate the energy loss in the runoff and erosion process. The absolute value of the energy loss is controlled by the input energy size of rainfall because energy losses of runoff increase as many rainfall pass through the hillslope system. The energy coefficient which is dimensionless is defined as the ratio of input energy of rainfall to output energy of runoff water and erosion soil such as runoff coefficient. The energy coefficient and runoff coefficient showed the highest correlation coefficient with the vegetation coverage. Maximum energy coefficient is about 0.5 in the hillslope system. The energy theory for output energy of runoff and soil erosion is presented by the energy coefficient theory associated with vegetation factor. Also runoff and erosion soil resulting output energy have the relation of power function and the rates of these increase with rainfall.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.93-106
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• 2011

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.6
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• pp.635-645
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• 2014

The changes of rainfall pattern and impervious covers have increased disaster risks in urbanized areas. Impervious covers such as roads and building roofs have been dramatically increased. So, it is falling the ability safety of flood defense equipments to exist. Runoff coefficient means ratio of runoff by whole rainfall which is able to directly contribute at surface runoff during rainfall event. The application of accurate runoff coefficients is very important in sewer pipelines design. This study has been performed to estimate runoff characteristics change which are applicable to the process of sewer pipelines design or various public facilities design. It has used the SHER model, a long-term runoff model, to analyze the impact of a rising impervious covers on runoff coefficient change. It thus analyzed the long-term runoff to analyze rainfall basins extraction. Consequently, it was found that impervious surfaces could be a important factor for urban flood control. We could suggest the application of accurate runoff coefficients in accordance to the land Impervious covers. The average increase rates of runoff coefficients increased 0.011 for 1% increase of impervious covers. By having the application of the results, we could improve plans for facilities design.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.403-414
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• 2015

This study is daytime and nighttime runoff image data caused by heavy rain on May 27, 2013 at Oedo Water Treatment Plant of Oedo-Stream, Jeju to compute runoff by applying Surface image velocimeter (SIV) and analyzing correlation according to current. At the same time, current was comparatively analyzed using ADCP observation data and fixed electromagnetic surface current meter (Kalesto) observed at the runoff site. As a result of comparison on resolutions of daytime and nighttime runoff images collected, correlation coefficient corresponding to the range of 0.6~0.7 was 6.8% higher for nighttime runoff image compared to daytime runoff image. On the contrary, correlation coefficient corresponding to the range of 0.9~1.0 was 17% lower. This result implies that nighttime runoff image has lower image quality than daytime runoff image. In the process of computing current using SIV, a rational filtering process for correlation coefficient is needed according to images obtained.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.191-200
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• 2015

This study was carried out to investigate coefficient and exponent of runoff energy in MUSLE for small forest watershed, Hwachoen watershed in Gangwon-do. For 15 rainfall events, runoff volume, peak discharge and sediment yield were measured and these data were used to calculate coefficient and exponent of runoff energy. The results of this study showed that $LS{\bullet}K{\bullet}C{\bullet}P$ factors of MUSLE were affected by slope steepness. The coefficient and exponent of runoff energy were validated with coefficient of efficiency of 0.92 and these values were suggested to 0.002 and 0.81 respectively. The comparison of the coefficients and exponents between Hwacheon and other forest watersheds showed that these values would reflect the effect of forest management within watershed.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.2
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• pp.251-259
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• 2013

Among various Green Infrastructure measures for urban stormwater management, effects of porous pavement were quantitatively examined in terms of hydrological cycle. Different scenarios for porous pavement were introduced on a SWMM model and the effects were compared and analysed using discharge hydrographs. Two types of pavements having different runoff coefficients (0.05 & 0.5) were introduced to cover different ratio of entire road areas (100 %, 77.5 % and 40.4 %) and these made up in total 6 different scenarios. Total runoff volume was reduced and peak flow was significantly decreased by applying the porous pavement. The highest reduction for total runoff was shown from S-6(covering area: 100 %, runoff coefficient: 0.05) as 19 % followed by S-5(covering area: 77.5 %, runoff coefficient: 0.05, 16 %), while that of S-2(covering area: 40.4 %, runoff coefficient: 0.05) and S-1(covering area: 40.4 %, runoff coefficient: 0.5) were the lowest with 8 % and 5 %. This proved that the application of porous pavement would improve urban hydrological cycle.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.209-217
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• 2016

The rational method is formed area, rainfall intensity and runoff coefficient that is representation of land use or surface type. A runoff coefficient is a range for a each surface conditions. Drainage Sewer Design Guideline revised at 2011 proposes return periods 10~30 year instead of 5~10 year for increasing design flood. Ponce and ASCE refer higher values of runoff coefficient require for higher values of rainfall intensity and return period, therefore runoff coefficient had to be corrected but not. In case of park, land use and surface type are different from Korea and U.S, so impervious area ratio is different. The runoff coefficient for park is estimated considering with impervious area ratio and return period. 1,004's parks in 20 cities are randomly selected for impervious area ratio and runoff coefficient is estimated. And a proportion of 30 year return period runoff coefficient to 10 year return period with rainfall duration is calculated for 69 weather stations. The estimated runoff coefficient is 0.43~0.54 for return period 10~30 year and the difference of region and rainfall duration is not significant.

• Journal of Environmental Health Sciences
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• v.22 no.4
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• pp.33-42
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• 1996

This research is to show the application of runoff model and runoff analysis of urban storm drainage network. the runoff models that were used for this research were RRL, ILLUDAS, and SWMM applicative object basin were Geucknak-chun and Sangmu drainage basin located in Seo-Gu, Kwangju. The runoff analysis employed the design storm that distributed the rainfall intensity according to the return period after the huff's method. The result from the comparative analysis of the three runoff models was as follows The difference of peak runoff by return period was 20-30% at Sangmu drainage area of $3.17 Km^2$, while less than 10% at Geucknak-chun drainage area of $12.7 Km^2$. The peak runoff were similar to all models. At the runoff hydrograph the times between rising and descending points were in the sequence of RRL, ILLUDAS and SWMM, but the peak times were similar to all models. The conveyance coefficient to examine the conveyance of the existing drainage network was 0.94-1.37, which means insecure, in Geucknak-chun drainage basin and 0.69-1.16, which means secure, in sangmu drainage basin.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.231-240
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• 2002

The rational method of estimating peak flow is used largely for the simplicity. But the accuracy of rational method is not easy to estimate, because the rational method is analyzed by the deterministic point or view and the runoff coefficients of the rational method are proposed from other countries. In this study the rational method is analyzed by the probabilistic way to be a more reliable method. The runoff coefficient is regarded to parameter that changes the probabilistic rainfall to the peak flow. The runoff coeffient for each return period is analyzed to be a reliable index which is used to estimate the peak flow of ungauged natural catchments.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.474-481
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• 2007

With population growth, industrialization, and urbanization within the watershed, the hydrologic response changed dramatically, resulting in increases in peak flow with lesser time to peak and total runoff with shortened time of concentration. Infiltration is directly affected by initial soil moisture condition, which is a key element to determine runoff. Influence of the initial soil moisture condition on hydrograph analysis should be evaluated to assess land use change impacts on runoff and non-point source pollution characteristics. The Long-Term Hydrologic Impact Assessment (L-THIA) model has been widely used for the estimation of the direct runoff worldwide. The L-THIA model was applied to the Little Eagle Creek (LEC) watershed and Its estimated direct runoff values were compared with the BFLOW filtered direct runoff values by other researchers. The $R^2$ value Was 0.68 and the Nash-Sutcliffe coefficient value was 0.64. Also, the L-THIA estimates were compared with those separated using optimized $BFI_{max}$ value for the Eckhardt filter. The $R^2$ value and the Nash-Sutcliffe coefficient value were 0.66 and 0.63, respectively. Although these higher statistics could indicate that the L-THIA model is good in estimating the direct runoff reasonably well, the Antecedent Moisture Condition (AMC) was not adjusted in that study, which might be responsible for mismatches in peak flow between the L-THIA estimated and the measured peak values. In this study, the L-THIA model was run with AMC adjustment for direct runoff estimation. The $R^2$ value was 0.80 and the Nash-Sutcliffe coefficient value was 0.78 for the comparison of L-THIA simulated direct runoff with the filtered direct runoff. However there was 42.44% differences in the L-THIA estimated direct runoff and filtered direct runoff. This can be explained in that about 80% of the simulation period is classified as 'AMC I' condition, which caused lower CN values and lower direct runoff estimation. Thus, the coefficients of the equation to adjust CN II to CN I and CN III depending on AMC condition were modified to minimize adjustments impacts on runoff estimation. The $R^2$ and the Nash-Sutcliffe coefficient values increase, 0.80 and 0.80 respectively. The difference in the estimated and filtered direct runoff decreased from 42.44% to 7.99%. The results obtained in this study indicate the AMC needs to be considered for accurate direct runoff estimation using the L-THIA model. Also, more researches are needed for realistic adjustment of the AMC in the L-THIA model.