• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.687-699
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• 2001

A 2-dimensional numerical sediment transport model has been developed by using erosion rates observed by SEDFLUME. The model un boundary-fitted coordinate can reduce inaccuracy of sediment model with accurate erosion data. Suspended transport and bed load transport are included in the model together. The model results gave good agreement with particle size distributions in 1-d channel and was more accurate than that of HIDAS of 1-dimensional model. The model applied to an enlarging channel to check model performance in 2-dimensional domain. Bed coarsening reduced erosion and deposition.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.4
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• pp.235-238
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• 2008

The Water Erosion Prediction Project (WEPP) was initiated in August 1985 to develop new generation water erosion prediction technology for federal agencies involved in soil and water conservation and environmental planning and assessment. Developed by USDA-ARS as a replacement for empirical erosion prediction technologies, the WEPP model simulates many of the physical processes important in soil erosion, including infiltration, runoff, raindrop detachment, flow detachment, sediment transport, deposition, plant growth and residue decomposition. The WEPP included an extensive field experimental program conducted on cropland, rangeland, and disturbed forest sites to obtain data required to parameterize and test the model. A large team effort at numerous research locations, ARS laboratories, and cooperating land-grant universities was needed to develop this state-of-the-art simulation model. The WEPP model is used for hillslope applications or on small watersheds. Because it is physically based, the model has been successfully used in the evaluation of important natural resources issues throughout the United State and in several other countries. Recent model enhancements include a graphical Windows interface and integration of WEPP with GIS software. A combined wind and water erosion prediction system with easily accessible databases and a common interface is planned for the future.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.357-360
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• 2005

Soil loss is widely recognized as a threat to farm livelihoods and ecosystem integrity worldwide. Soil loss prediction models can help address long-range land management planning under natural and agricultural conditions. Even though it is hard to find a model that considers all forms of erosion, some models were developed specifically to aid conservation planners in identifying areas where introducing soil conservation measures will have the most impact on reducing soil loss. Revised Universal Soil Loss Equation (RUSLE) computes the average annual erosion expected on hillslopes by multiplying several factors together: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and support practice (P). The value of these factors is determined from field and laboratory experiments. This study calculated soil erosion using GIS-based RUSLE model in Imha basin and examined soil erosion source area using SPOT 5 high-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area applying field survey method in common areas (dry field & orchard area) that are difficult to confirm soil erosion source area using satellite image.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1295-1299
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices (BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation (USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield from the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool (SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)$\sim$-54.5%(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)$\sim$+3.8%(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.1
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• pp.3-12
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• 2008

Soil erosion is a natural process and has been occurring in most areas in the watershed. However, accelerated soil erosion rates have been causing numerous environmental impacts in recent years. To reduce soil erosion and sediment inflow into the water bodies, site-specific soil erosion best management practices(BMPs) need to be established and implemented. The most commonly used soil erosion model is the Universal Soil Loss Equation(USLE), which have been used in many countries over 30 years. The Sediment Assessment Tool for Effective Erosion Control(SATEEC) ArcView GIS system has been developed and enhanced to estimate the soil erosion and sediment yield trom the watershed using the USLE input data. In the last decade, the Soil and Water Assessment Tool(SWAT) model also has been widely used to estimate soil erosion and sediment yield at a watershed scale. The SATEEC system estimates the LS factor using the equation suggested by Moore and Burch, while the SWAT model estimates the LS factor based on the relationship between sub watershed average slope and slope length. Thus the SATEEC and SWAT estimated soil erosion values were compared in this study. The differences in LS factor estimation methods in the SATEEC and SWAT caused significant difference in estimated soil erosion. In this study, the difference was -51.9%(default threshold)${\sim}-54.5%$(min. threshold) between SATEEC and non-patched SWAT, and -7.8%(default threshold)${\sim}+3.8%$(min. threshold) between SATEEC and patched SWAT estimated soil erosion.

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.637-647
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• 2010

The Universal Soil Loss Equation (USLE)-based modeling systems have been widely used to simulate soil erosion studies. However the GIS-based USLE modeling systems have limitation in gully erosion evaluation which is one of the most important factor in soil erosion estimation. In this study, the integrated soil erosion evaluation system using with Sediment Assessment Tool for Effective Erosion Control (SATEEC) system, nLS and Unit Stream Power-based Erosion/Deposition (USPED) model was developed to simulate gully erosion. Gully head location using nLS model, USPED for gully erosion, and the SATEEC estimated sheet and rill erosion were evaluated and combined together with the integrated soil erosion evaluation system. This system was applied to the Haean-myeon watershed, annual average sediment-yield considering sheet, rill and gully erosion was simulated as 101,933 ton/year at the study watershed. if the integrated soil erosion evaluation system is calibrated and validated with the measured data, this system could be efficiently used in developing site-specific soil erosion best management system to reduce soil erosion and muddy water inflow into the receiving waterbody.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.454-458
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• 2007

Nonpoint source (NPS) pollution is a serious problem causing the degradation of soil and water quality. Concentrated overland flow is the primary transport mechanism for a large amount of NPS pollutants from hillslope areas to downslope areas in a watershed. In this study, a soil erosion model, nLS model, to identify transitional overland flow regions (i.e., ephemeral gully head areas) was developed using the kinematic wave overland flow theory. Spatial data, including digital elevation models (DEMs), soil, and landcover, were used in the GIS-based model algorithm. The model was calibrated and validated using gully head locations in a large agricultural watershed, which were identified using 1-m aerial photography. The model performance was better than two previous approaches; the overall accuracy of the nLS model was 72 % to 87 % in one calibration subwatershed and the mean overall accuracy was 75 to 89 % in four validation subwatersheds, showing that the model well predicted potential transitional erosion areas at different watersheds. However, the user accuracy in calibration and validation was still low. To improve the user accuracy and study the effects of DEM resolution, finer resolution DEMs may be preferred because DEM grid is strongly sensitive to estimating model parameters. Information gained from this study can improve assessing soil erosion process due to concentrated overland flow as well as analyze the effect of microtopographic landscapes, such as riparian buffer areas, in NPS control.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.316-316
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• 2021

Erosion in a watershed is one of the main sources of sediment inflow in dams. While sediment management practices can be performed to reduce and manage sedimentation in reservoirs, managing the sediment inflow before it reaches the reservoir should also be consider. The accurate location of areas with high erosion and deposition rates should be determined in order to propose an appropriate sediment management procedure such as the construction of check dams. In this study, the projected rainfall from HadGEMRA-3 for RCP 8.5, was used in C-SEM, a distributed rainfall-erosion model, to determine the projected spatial erosion patterns in Cheoncheon catchment, which is located in the upstream part of Yongdam Dam.

• Journal of Ocean Engineering and Technology
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• v.31 no.1
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• pp.14-21
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• 2017

The erosion of solid particles in a pipe elbow was numerically investigated. A numerical procedure to estimate the sand erosion rate, as well as the particle motion, in the pipe elbow flow was introduced. This procedure was performed based on the combined empirical erosion model and computational fluid dynamics (CFD) analysis to consider the interaction between the particle motion and the eroded surface. The underlying turbulent flow on an Eulerian frame is described by the Reynolds averaged Navier-Stokes (RANS) equations with a $k-{\epsilon}$ turbulent model. The one-way coupled Eulerian-Lagrangian motion of the air flow and sand particles is employed to simulate the particle trajectories and particle-wall interactions on the pipe surfaces. The predicted CFD erosion magnitudes are compared with experimental data from pipe elbows. The erosion rate results do not reveal a good accordance between the simulation and experimental results. It seems that the CFD shows a slightly over-predicted erosion ratio.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.526-534
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• 2019

The average coastline and the erosion control line introduced as the management coastline, and the average shoreline (MSL) was established from the observed coastline. Also, the median grain size and the wave height of 30-years return period were applied. The erosion control line (ECL) was established through the model, HaeSaBeeN. These two lines set the coastline for evaluation. Based on the observed monitoring data along the coastline, the 1-day variation according to the normal distribution was used to estimate the regional variation, and the width of the erosion was calculated by applying the median grain size (D₅₀) and the wave height of 30-years return period through the high-wave coastal erosion width model, i.e., HaeSaBeeN.