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적용 기법에 따른 강우침식인자 산정 결과의 시공간적 불확실성Spatiotemporal Uncertainty of Rainfall Erosivity Factor Estimated Using Different Methodologies

Other Titles
Spatiotemporal Uncertainty of Rainfall Erosivity Factor Estimated Using Different Methodologies
Authors
황세운김동현신상민유승환
Issue Date
Nov-2016
Publisher
한국농공학회
Keywords
RUSLE; Rainfall-Erosivity Factor; Soil Erosion; Rainfall Kinetic Energy
Citation
한국농공학회논문집, v.58, no.6, pp 55 - 69
Pages
15
Indexed
KCI
Journal Title
한국농공학회논문집
Volume
58
Number
6
Start Page
55
End Page
69
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/16570
DOI
10.5389/KSAE.2016.58.6.055
ISSN
1738-3692
2093-7709
Abstract
RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associatedoverland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity andcharacteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physicalschemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed toquantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfalldata) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factorscalculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those forenergy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual Rfactors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods thatwould provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, theefforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.
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