• Geomechanics and Engineering
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• v.18 no.5
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.

• Korean Journal of Soil Science and Fertilizer
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• v.38 no.2
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• pp.59-65
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• 2005

This study was performed to estimate the soil loss on a national scale and grade regions with the potential risk of soil erosion. Universal soil loss equation (USLE) for rainfall and runoff erosivity factors (R), cover management factors (C) and support practice factors (P) and revised USLE for soil erodibility factors (K) and topographic factors (LS) were used. To estimate the soil loss, the whole nation was divided into 21,337 groups according to city county, soil phase and land use type. The R factors were high in the southern coast of Gyeongnam and Jeonnam and part of the western coast of Gyeonggi and low in the inland and eastern coast of Gyeongbuk. The K factors were higher in the regions located on the lower streams of rivers and the plain lands of the western coast of Chungnam and Jeonbuk. The average slope of upland areas in Pyeongchang-gun was the steepest of 30.1%. The foot-slope areas from the Taebaek Mountains to the Sobaek Mountains had steep uplands. Total soil loss of Korea was estimated as $50{\times}10^6Mg$ in 2004. The potential risk of soil erosion in upland was the severest in Gyeongnam and the amount of soil erosion was the greatest in Jeonnam. The regions in which annual soil loss was estimated over $50Mg\;ha^{-1}$ were graded as "the very severe" and their acreage was $168{\times}10^3ha$ in 2004. The soil erosion maps of city/county of Korea were made based on digital soil maps with 1:25,000 scale.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.123-128
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• 2015

This study conducted a series of field experiments using soil conditioners, Polyacrylamide(PAM) and gypsum, to evaluate their effects in reducing sediment loss and surface runoff. In addition, the correction factors (K-alpha) for the erodibility factor (K) were determined to reflect the effects of PAM and PAM+gypsum in applying the USLE equation. Experimental erosion plots individually sized $10m^2$ (5 m long, 2 m wide and 1 m deep) have different slopes (10, 20 and 30%). Erosion plots were prepared for one control (C; no PAM and gypsum) and two treatments (P; PAM 20 kg/ha, PG; PAM 20 kg/ha+gypsum 3,000 kg/ha). The amounts of soil eroded and runoff were continuously monitored from July $1^{st}$ to Oct. $31^{st}$ in 2010 and compared to each other. The amount of sediment loss from a control plot was 399.2 ton/ha and the relative reduction of sediment loss were 11.4% and 33.4% for PAM-treated and PAM+gypsum treated plots, respectively. This study also determined the K-alpha factors in the USLE equation to account for the erosion control effectiveness of PAM and gypsum application. The K-alpha factors were calculated as 0.92 for PAM-treated plot and 0.69 for PAM+gypsum-treated plot. The findings of this study revealed that soil conditioners (PAM and gypsum) could play a significant role in controlling soil erosion. In addition, the modified USLE equation using the K-alpha could provide valuable information to make better decision on establishment of best management practice for soil erosion control in agriculture.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.363-377
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• 2006

Mean annual soil loss was calculated and critical soil erosion areas were identified for the Congaree River Basin in South Carolina, USA using the Revised Universal Soil Loss Equation (RUSLE) model. In the RUSLE model, the mean annual soil loss (A) can be calculated by multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), crop-management (C), and support practice (P) factors. The critical soil erosion areas can be identified as the areas with soil loss amounts (A) greater than the soil loss tolerance (T) factor More than 10% of the total area was identified as a critical soil erosion area. Among seven subwatersheds within the Congaree River Basin, the urban areas of the Congaree Creek and the Gills Creek subwatersheds as well as the agricultural area of the Cedar Creek subwatershed appeared to be exposed to the risk of severe soil loss. As a prototype model for examining future effect of human and/or nature-induced changes on soil erosion, the RUSLE model customized for the area was embedded into ESRI ArcGIS ArcMap 9.0 using Visual Basic for Applications. Using the embedded model, users can modify C, LS, and P-factor values for each subwatershed by changing conditions such as land cover, canopy type, ground cover type, slope, type of agriculture, and agricultural practice types. The result mean annual soil loss and critical soil erosion areas can be compared to the ones with existing conditions and used for further soil loss management for the area.

• Korean Journal of Soil Science and Fertilizer
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• v.35 no.6
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• pp.361-371
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• 2002

Multifunctionality of agriculture has been an important international issue in terms of environmental benefits and public concerns. We calculated soil loss mass in national basis using the USLE, and attempted to evaluate its economical benefits by replacement cost method. Soil loss mass ranged from 1.4 to $18MT\;ha^{-1}\;yr^{-1}$ was fairly fitted to measured values for 13 cropping systems. In national basis, the factors in USLE were evaluated as: 429.4 for rainfall and runoff factor. R, 0.15 for soil erodibility factor, K, 1.72 for topographic factor, LS, 0.275 for cover and management factor, C, and 0.856 for support practice factor, P. The soil loss estimated from upland farming using the USLE was $26.1MT\;ha^{-1}\;yr^{-1}$, but soil loss from the bare soil was $110.8MT\;ha^{-1}\;yr^{-1}$, the ratio of soil loss from upland farming to bare soil was 23 percents. Function of reducing soil loss in comparison with the bare soil was $84.7MT\;ha^{-1}\;yr^{-1}$, of which national soil loss mass was 62.6 million MT per annum in south Korea. Agriculture economic replacement cost of soil loss reduction was 497 billion Wons(398 million dollars) for the cost of upland soil dressing. For conservational purposes to increase the environmental benefits of upland farming, the agricultural practice including contour, strip cropping, terracing and division ditches should be implemented.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.789-792
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• 2010

Major impacts of climate change expert that soil erosion rate may increase during the $21^{st}$ century. This study was conducted to assess the potential impacts of climate change on soil erosion by water in Korea. The soil loss was estimated for regions with the potential risk of soil erosion on a national scale. For computation, Universal Soil Loss Equation (USLE) with rainfall and runoff erosivity factors (R), cover management factors (C), support practice factors (P) and revised USLE with soil erodibility factors (K) and topographic factors (LS) were used. RUSLE, the revised version of USLE, was modified for Korean conditions and re-evaluate to estimate the national-scale of soil loss based on the digital soil maps for Korea. The change of precipitation for 2010 to 2090s were predicted under A1B scenarios made by National Institute of Meteorological Research in Korea. Future soil loss was predicted based on a change of R factor. As results, the predicted precipitations were increased by 6.7% for 2010 to 2030s, 9.5% for 2040 to 2060s and 190% for 2070 to 2090s, respectively. The total soil loss from uplands in 2005 was estimated approximately $28{\times}10^6$ ton. Total soil losses were estimated as $31{\times}10^6$ ton in 2010 to 2030s, $31{\times}10^6$ ton in 2040 to 2060s and $33{\times}10^6$ ton in 2070 to 2090s, respectively. As precipitation increased by 17% in the end of $21^{st}$ century, the total soil loss was increased by 12.9%. Overall, these results emphasize the significance of precipitation. However, it should be noted that when precipitation becomes insignificant, the results may turn out to be complex due to the large interaction among plant biomass, runoff and erosion. This may cause increase or decrease the overall erosion.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.1024-1034
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• 2010

In order to select the demonstration farm site for agricultural investment by Korean fund, 14 sites were investigated by soil morphological characteristics and were evaluated by rating method in the Oudomxai province of Laos. Land evaluation was carried out by using eight factors, such as site accessibility, soil erosion susceptibility, easiness of farm mechanization, irrigation water obtainability, suitability of soil physical and chemical properties for crop growth, cost for establishment of farm foundation and land obtainability. In addition, one site to have been highly ranked was soil physico-chemically studied for farm planning. The site of heavy clayey soil has hydraulic conductivity of 26.27~40.64 cm $day^{-1}$, organic content of lower than 14 g $kg^{-1}$, available phosphate content of lower than 3 mg $kg^{-1}$, exchangeable cations of lower than 0.38, 11 and 3.1 cmolc $kg^{-1}$ in K, Ca and Mg, respectively. Major important limitations for establishment of demonstration farm were concluded as heavy soil-texture, high soil erodibility, low organic matter and phosphate contents, and insufficient irrigation water in the Oudomxai province of Laos.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.1
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• pp.121-130
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• 1993

The major objective of this study is to develop practical methods for estimating sediment yield rates of medium size watersheds of which areas range from 200 to $2,000km^2$. For this purpose, this study adopts an empirical method of statistical approach and another empirical method of weighting the watershed characteristics factors. A total of 13 data points for sediment yield rate, including five data points from reservoir deposit data and eight data points from sampled river-sediment data have been collected. Meanwhile, seven factors that may affect the sediment yield rate of a watershed have been selected. They are drainage density, rainfall erosivity, ground cover and land use, soil erodibility, topography, river-bed material characteristics, and watershed area. In the companion paper following this paper, methods for estimating sediment yield rate are to be developed using the 13 data points collected and seven watershed characteristics factors selected in this study.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.199-206
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• 2004

Factors of universal soil loss equation, USLE, and its revised version, RUSLE for Korean soils were reevaluated to estimate the national scale of soil loss based on digital soil maps. Rainfall erosivity factor, R, of 158 locations of cities and counties were spacially interpolated by the inverse distance weight method. Soil erodibility factor, K, of 1321 soil phases of 390 soil series were calculated using the data of soil survey and agri-environmental quality monitoring. Topographic factor, LS, was estimated using soil map of 1:25,000 scale with soil phase and land use type. Cover management factor, C, of major crops and support practice factor, P, were summarized by analyzing the data of lysimeter and field experiments for 27 years (1975-2001) in the National Institute of Agricultural Science and Technology. R factor varied between 2322 and 6408 MJ mm $ha^{-1}$ $yr^{-1}$ $hr^{-1}$ and the average value was 4276 MJ mm $ha^{-1}$ $yr^{-1}$ $hr^{-1}$. The average K value was evaluated as 0.027 MT hr $MJ^{-1}$ $mm^{-1}$. The highest K factor was found in paddy rice fields, 0.034 MT hr $MJ^{-1}$ $mm^{-1}$, and K factors in upland fields, grassland, and forest were 0.026, 0.019, and 0.020 MT hr $MJ^{-1}$ $mm^{-1}$, respectively. C factors of upland crops ranged from 0.06 to 0.45 and that of grassland was 0.003. P factor varied between 0.01 and 0.85.