• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.29-36
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• 2017

Universal soil loss equation (USLE) has been frequently employed to estimate potential soil loss in land since it was developed based on the statewide data measured and collected in the United States. The equation is an empirical model mainly used for U.S. soil, thus it has been recently modified to reflect Korean soil conditions and named as Korean Soil Loss Equation (KORSLE). The modified equation was implemented in ArcGIS software, and used for estimation of potential soil loss from 2003 to 2016 in the thirty-eight Water Protection Districts. Five out of the thirty-eight districts were identified as the area of potential soil erosion most severly. In those five districts, potential soil erosion were estimated to be more than 50 Mg/ha/year that requires site investigation under supervision of the Korean Ministry of Environment. Distinctive site characteristics were found in the potential soil loss estimation such that the districts of low potential soil loss had low five factors in the aggregate. However, if one of more factors are dominantly large, the potential soil loss significantly increased. This study provides a useful tool to identify the potential areas for soil erosion and the important factors that play an important role in the estimation process.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.269-270
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• 2009

This study builds a sediment rating curve using the measured sediment yield and the simulated soil erosion by a GIS-embedded empirical model. Then the structured sediment rating curve is used to determine the SDR on a basin scale in southern Korea. The whole data(year of 2002-2008) are divided into two groups and the first group(year of 2002-2005) is used for calibration, while the other is used for validation. Two cases(rainfall amount and rainfall intensity) are analyzed to consider the rainfall runoff erosivity factor in simulating soil erosion. The results show the derived SDR provides reasonable accuracy and rainfall intensity gives better performance in calculating soil erosion than rainfall amount.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.151-151
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• 2022

The impact of raindrops on the soil surface causes soil detachment, which may be estimated by measuring the kinetic energy (KE) of the raindrops. Since direct measurements of rainfall force on ground surfaces are not generally available, empirical equations are an alternative option to estimate KE from rainfall intensity (I), which has the greatest influence over soil erosion and is easily accessible. Establishing the optimal formulation for the relationship between kinetic energy and rainfall intensity has proven to be difficult. Thus, this research considered thirty-seven rainfall events observed from June 2020 to December 2021 using a laster optical disdrometer erected in Kyungpook National University to examine the characteristics of KE-I relationships. We concentrated our discussion on the formation of two different expressions of the KE, including KE expenditure (KE_exp) and KE content (KE_con). The following conclusions were drawn: (1) We employed statistical analysis to demonstrate that the KE_exp is more suitable expression for establishing an empirical rule between KE and I than the KE_con. (2) A power-law model was used to find the best correlation between KE_exp-I relationship, whereas the best match between KE_con and I were found using an exponential equation.

• Journal of Environmental Policy
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• v.9 no.2
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• pp.41-55
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• 2010

This paper analyzes optimal watershed management focusing on reservoir-level sediment removal techniques. Although dams and reservoirs provide several benefits, sedimentation may reduce their storage capacity. As of today, the Aswan High Dam (AHD) in Egypt faces approximately 76% reduced life of the reservoir. Since the AHD is the major fresh water source in Egypt, sustainable use of this resource is extremely important. A model is developed to simultaneously determine optimal sediment removal strategies for upstream soil conservation efforts and reservoir-level sediment control. Two sediment removal techniques are considered: mechanical dredging and hydro-suction sediment removal system (HSRS). Moreover, different levels of upstream soil conservation efforts have introduced to control soil erosion, which is a major contributor of reservoir storage capacity reduction. We compare a baseline case, which implies no management alternative, to non-cooperative and social planners' solution. Our empirical results indicate that the socially optimal sediment removal technique is a mechanical dredging with unconstrained amount with providing a sustainable life of the reservoir. From the empirical results, we find that social welfare can be as high as $151.01 billion, and is sensitive to interest rates and agricultural soil loss.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.3
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• pp.337-343
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• 2011

A particular empirical equation for rainfall kinetic energy is needed to compute rainfall erosivity, calculated by the annual sum of the product of total rainfall energy and maximum 30-min rainfall intensity. If rainfall kinetic energy equation was different, rainfall erosivity will be produced differently. However, the previous studies in Korea had little concern about rainfall kinetic energy equation and it was not clear which rainfall kinetic energy is suitable for Korea. The purpose of this study is to analyze and evaluate the difference of the rainfall erosivity based on different rainfall kinetic energy equations obtained from previous studies. This study introduced new rainfall erosivity factors based on rainfall kinetic energy equation of Noe and Kwon (1984) that is only regression model developed in Korea. Data of annual rainfall erosivity for 21 weather stations in 1980~1999 were used in this study. The result showed that rainfall erosivity factors by the previous equations had been about 10~20% overestimated than rainfall erosivity by Noe and Kwon (1984)'s equation in Korea.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.351-362
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• 2009

The Soil and Water Assessment Tool (SWAT) model, semi-distributed model, first divides the watershed into multiple subwatersheds, and then extracts the basic computation element, called the Hydrologic Response Unit (HRU). In the process of HRU generation, the spatial information of land use and soil maps within each subwatershed is lost. The SWAT model estimates the HRU topographic data based on the average slope of each subwatershed, and then use this topographic datum for all HRUs within the subwatershed. To improve the SWAT capabilities for various watershed scenarios, the Spatially Distributed-HRU (SD-HRU) pre-processor module was developed in this study to simulate site-specific topographic data. The SD-HRU was applied to the Hae-an watershed, where field slope lengths and slopes are measured for all agricultural fields. The analysis revealed that the SD-HRU pre-processor module needs to be applied in SWAT sediment simulation for accurate analysis of soil erosion and sediment behaviors. If the SD-HRU pre-processor module is not applied in SWAT runs, the other SWAT factors may be over or under estimated, resulting in errors in physical and empirical computation modules although the SWAT estimated flow and sediment values match the measured data reasonably well.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.132-143
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• 2017

It is essential to obtain periodic sediment discharge data in a river in order to minimize problems that may arise from the erosion, transport, and deposition of sediment. However, it is difficult to estimate sediment discharge by the sediment discharge measurement plan in Korea at present, and empirical fomulas or numerical models are used to replace them. This paper has applied the K-DRUM model, a grid-based rainfall-runoff-sediment model, to estimate sediment discharge and ensure the continuity of the data in the watershed. Discharge and sediment load in 17 watersheds were estimated and the applicability of the model was analyzed through comparisons with measured data. For quantitative evaluation, NSE, PBIAS and RSR items were used, and discharge results reflected the tendency of rainfall and showed high statistical value. In case of sediment discharge, the soil erosion process of the watershed is physically well reflected. When the calibration was performed using the measure data, the applicability seems to be excellent in estimating the continuous sediment discharge data in the real watershed.