• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.37-44
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• 2018

Universal soil loss equation (USLE) had been employed to estimate potential soil loss since it was developed from the statewide data measured and collected in the United States. The equation had an origin in average annual soil loss estimation though, it was modified or improved to provide better opportunities of soil loss estimation outside the United States. The equation has five factors, most studies modifying them to adapt regional status were focused on rainfall erosivity factor and cover management factor. While the conservation practice factor (USLE P factor) is to represent distinct features in agricultural fields, it is challenging to find studies regarding the factor improvements. Moreover, the factor is typically defined using slopes. The factor defining approach was suggested in the study, the approach is a step-by-step method allowing USLE P factor definition with given condition. The minimum condition is slope and field location to provide an opportunity for using in any GIS software and to reflect regionally distinct features. If watershed location, slope, crop type, and mulching type on furrows are given, detailed definition of the factors are possible. The approach was developed from field survey in South-Korea, it is expected to be used for potential soil loss using USLE in South-Korea.

• Geomechanics and Engineering
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• v.28 no.1
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• pp.77-87
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• 2022

Many geotechnical analyses require the investigation of water flow within partially saturated soil zone to incorporate the effect of climatic conditions. It is widely understood that the hydraulic properties of the partially saturated soil should be included in the transient seepage analyses. However, the characteristics of dual porosity soils with dual-mode water retention curve are normally modelled using single-mode mathematical equation for simplification of the analysis. In reality, the rainwater flow can be affected significantly by the dual-mode hydraulic properties of the soil. This paper presents the variations of safety factor for dual porosity soil slope with dual-mode water retention curve and dual-mode unsaturated permeability. This paper includes the development of the new dual-mode unsaturated permeability to represent the characteristics of soil with the dual-mode water retention curve. The finite element analyses were conducted to examine the role of dual-mode water retention curve and dual-mode unsaturated permeability on the variations of safety factor under rainfall loading. The results indicate that the safety factor variations of dual porosity soil slope modelled using the dual-mode water retention curve and the unsaturated permeability equation are lower than those of dual porosity slope modelled using single-mode water retention curve and unsaturated permeability equations.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.712-723
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• 2015

This study was conducted to develop the SWCC estimation equation using scaling technique, and to investigate relative sensitivity of the SWCC according to the soil water tension, for the four kinds of soil texture such as Sand [S], Sandy Loam [SL], Loam [L] and Clay Loam [CL]. The SWCC estimation equation of scale factor [${\Theta}sc$] (Eq. 1) was developed based on the log function (Eq. 2) and exponential function (Eq. 3). ${\Theta}sc=[({\Theta}-{\Theta}r)/({\Theta}s-{\Theta}r)]$ (Eq. 1) ${\Theta}sc=-0.196ln(H)+0.4888$ (Eq. 2) ${\Theta}sc=0.3804(H)^{(-0.448)}$ (Eq. 3) where, ${\Theta}$: water content (g/g %), ${\Theta}s$: water content at 0.1bar, ${\Theta}r$: water content at 15bar, H: soil water tension (matric potential) (bar) Relative sensitivity of soil water content was decreased as increase soil water tension, those according to soil water tension were 0.952~0.620 compared to 0.1bar case. Relative sensitivity of scale factor was also decreased as increase soil water tension, those according to soil water tension were 0.890~0.577 compared to 0.2bar case.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.86-88
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• 2002

The mathematical model was proposed to simulate ozone transport and remediation in unsaturated soils contaminated with phenanthrene. Soil column experiments were also carried out to calibrate the mathematical model. The experimental results successfully matched with the modeling results in various soil conditions. The model proposed nondimensional fraction factor to reveal reactivity between phenanthrene and gas phase ozone and liquid phase ozone. From sensitivity analysis, the fraction factor and stoichiometric coefficient decreased as water content increased. Simulation results showed increased SOM content retarded the ozone transport and the phenanthrene removal due to increased ozone consumption.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.162-177
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• 1998

Conentionally, LS factor for the USLE suggested by Wischmeier has been computed manually on topographic maps based on one dimensional approach. But outcomes of the equation could be severely affected by the convergence and divergence of surface runoff at complex terrains. Thus the objective of this research are to develop a method to automatically compute LS factor based on the multiple flow algorithm, and to test the accuracy of this method by comparing outcomes of this method to previous measurements or estimations of soil erosion. The program for the automatic calculation of LS factor was developed by utilizing Fox Pro 4.5, and outcomes of the program is designed to input to IDRISI. The accuracy test of LS factor was carried out by comparing the actual measurements of soil loss at two test sites in and around of Suwon. The calculated volume of soil erosion at Buju mountain, Mokpo, was also compared to the outcome of a previous research based on the LS factor calculated by the conventional onedimensional approach. The outcomes of this research are as follows. First, the computed L based on the multiple flow algorithm for concae slopes are greater than those of convex slopes,. Second, the estimated soil loss based on this method at the test site in Mokpo is much greater than the outcomes based on the conventional one-dimensional approach. It can e concluded that the application of this automatic calculation method of LS factor can improve the accuracy of USLE and facilitate soil erosion prevention methods.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.631-640
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• 2024

In the traditional slope stability analysis, ignoring the spatial variability of slope soil will lead to inaccurate analysis. In this paper, the K-L series expansion method is adopted to simulate random field of soil strength parameters. Based on Random Limit Equilibrium Method (RLEM), the influence of variation coefficient and fluctuation range on reliability of soil slope supported by micro-pile is investigated. The results show that the fluctuation ranges and the variation coefficients significantly influence the failure probability of soil slope supported by micro-pile. With the increase of fluctuation range of soil strength parameters, the mean safety factor of the slope increases slightly. The failure probability of the soil slope increases with the increase of fluctuation range when the mean safety factor of the slope is greater than 1. The failure probability of the slope increases by nearly 8.5% when the fluctuation range is increased from δ_v=2 m to δ_v =8 m. With the increase of the variation coefficient of soil strength parameters, the mean safety factor of the slope decreases slightly, and the probability of failure of soil slope increases accordingly. The failure probability of the slope increases by nearly 31% when the variation coefficient increases from COV_c=0.2, COV_φ=0.05 to COV_c=0.5, COV_φ=0.2.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.1
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• pp.27-37
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• 2001

Soil erosion by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. As the interest in environment is increasing lately, soil erosion is considered as a serious problem, whereas the systematic regulation and analysis for that have not established yet. This research shows the method of extracting factor entered model which expects soil erosion by GSIS. There are several erosion model such as ANSWER, WEPP, RUSLE. The research used RUSLE erosion model which could expect general soil erosion connected easily with GSIS data. RUSLE's input factors are composed of rainfall runoff factor(R). soil erodibility factor(K), slope length factor(L), slope steepness factor(S), cover management factor(C) and support practice factor(P). The general equation used to extract L, S factor on the RUSLE to be oriented for agricultural area has some limitation to apply whole watershed. So, on this study we used a revised empirical equation applicable to the watershed by grid on the GSIS. Also, we analyzed RUSLE factors by watershed being analyzed with watershed extraction algorithm. Then we could calculate the minimum, maximum. mean and standard deviation of RUSLE factors by watershed.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.119-124
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• 2009

In this study, the characteristics of estimating methodology for RUSLE factors such as soil erodibility factor, slope length-steepness factor, and cover management factor were reviewed and then the relative error according to each methodology was analyzed. RUSLE was applied to experimental watershed for 42 storm events and their results were compared with measured sediment yield to examine the applicability of RUSLE. As a result, this paper found that it should be necessary to consider vegetation effect for forest application of RUSLE as cover management was the most sensitive factor. Also, soil erodbility factor was calculated from data of soil series by National Academy of Agricultural Science caused sediment yield to be overestimated because there were big differences between the soil series and on-site soil texture. The 22.7% of maximum relative error was shown according to selecting the rain energy equation. In addition, it will be necessary to verify the RUSLE factors with more data in order to improve their accuracy.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.55-65
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• 2019

Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models' backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.112-117
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• 2012

The Revised Universal Soil Loss Equation (RUSLE) is a revision of the Universal Soil Loss Equation (USLE). However, changes for each factor of the USLE have been made in RUSLE which can be used to compute soil loss on areas only where significant overland flow occurs. RUSLE which requires standardized methods to satisfy new data requirements estimates soil movement at a particular site by utilizing the same factorial approach employed by the USLE. The rainfall erosivity in the RUSLE expressed through the R-factor to quantify the effect of raindrop impact and to reflect the amount and rate of runoff likely is associated with the rain. Calculating the R-factor value in the RUSLE equation to predict the related soil loss may be possible to analyse the variability of rainfall erosivity with long time-series of concerned rainfall data. However, daily time step models cannot return proper estimates when run on other specific rainfall patters such as storm and daily cumulative precipitation. Therefore, it is desirable that cross-checking is carried out amongst different time-aggregations typical rainfall event may cause error in estimating the potential soil loss in definite conditions.