• International Journal of Highway Engineering
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• v.13 no.2
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• pp.133-138
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• 2011

This study aims to compare hydraulic & hydrologic design characteristics by examining generated on weak points for road drainage poor sites. More appropriated methodology of rainfall-intensity calculated is to consider minutely rainfall-intensity decision method for road drainage basins. To use non-uniform flow analysis methodology for road surface drainage facilities inlet spacing decision methods is better than present experience inlet spacing decision equations.

• Journal of Korea Water Resources Association
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• v.45 no.4
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• pp.419-430
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• 2012

Due to the calculation difficulty on the hydraulic and hydrologic analysis for road drainage facilities design, these analysis techniques are not applicable. This study's result are development of minutely rainfall-intensity equation suitable for road drainage area, verification of rainfall-runoff model joining kinematic wave theory for road drainage area, computational model based GUI for road surface drainage facilities spacing and culvert's size decision and various road drainage channel design. Applicable test on the developed model is proceed, result that in case of road surface dranage facilities spacing is narrower 6~65% than present spacing calculation method, in other case of road cross dranage facilities size is bigger 6~140% than present size decision method.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.55-69
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• 2016

RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associated overland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity and characteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physical schemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed to quantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfall data) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factors calculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those for energy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual R factors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods that would provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, the efforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.