• 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 Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.59-64
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• 2008

Soil erosion is a major problem in the case of forests in hilly terrains. Soil erosion removes the fertile topsoil, making unsuitable for growth and establishment of vegetation. In the present study, erosion prone areas in a forest region situated in the Moyar sub-watershed of Western ghats was identified using GIS with data collected from India. The thematic layers such as forest cover, slope and drainage density were used for analysis. In the erosion prone map, majority of area (48%) was under medium category, and about 35% of area was under high erosion prone category. Very high erosion prone category occupied 7% of the forest area. This erosion prone map would be an ideal spatial data to take up necessary management actions at appropriate places in this watershed to prevent erosion.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.251-253
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• 2008

Erosion and landslide cause serious damage to forest areas. As a consequence, partial or complete destruction of vegetation occurs, which leads to many cascading problems. In this study, an attempt has been made to identify the forest areas, which are under different risk categories of erosion and landslide, in part of Eastern Ghats of Tamil Nadu. Relevantthematic maps were generated from satellite data, topographical maps, primary and secondary data and weights to each map were assigned appropriately. Weighted overlay analysis was carried out to identify the erosionprone forest areas. The result of erosion and landslide prone model reveals that 4712 ha(17%) of forest area is under high risk category and 15879 ha(58.65%) isunder medium risk category. The results of spatial modeling would be very much useful to the forest officials and conservationist to plan for effective conservation.

• Water Engineering Research
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• v.2 no.1
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• pp.49-61
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• 2001

A grid-based KIneMatic wave soil-water EROsion and deposition Model(KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS(Geographic Information Systems), and generates the distributed results by ASCII-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulated surface and subsurface flow, respectively (Kim, 1998; Kim et al., 1998). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts single overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element for a given time increment. The model was tested to a 162.3 $\textrm{km}^2$ watershed located in the tideland reclaimed ares of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.664-667
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• 2004

This paper is aimed at analyzing the soil erosion hazard zone in farm land. RUSLE was used for an analysis of soil erosion amount, and for the spatial data of basin, soil erosion amount was calculated by extracting the respect topography space related factors of RUSLE using DEM, Landuse, Soil map as base map. As a result of analysis on the calculated soil erosion amount according to land use type, it was analyzed that the most soil erosion occurred in orchard area, i.e., 40.08ton/ha/yr at average. It was classified into 5 classes depending on the calculated soil erosion amount. of which Class V was decided as soil erosion hazard zone, and for this area, 72.5ha or so, $2.4\%$ of the entire farm land was assessed as erosion hazard zone.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.150-150
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• 2021

Soil erosion due to climate change is one of the global environmental issues. Especially, Korea is vulnerable to soil erosion as the frequency of extreme rainfall events and rainfall intensity are increasing. Soil erosion causes various problems such as reduced farmlands, deterioration of water quality in rivers, etc. To these severe problems, understanding the process of soil erosion is the first process. Then, it is necessary to quantify and analyze soil ersoion using an erosion model. Soil erosion models are divided into empirical, conceptual, and physics-based models according to the structures and characteristics of models. This study used GSSHA (Gridded Surface Subsurface Hydrologic Analysis), the physics-based erosion model, running on WMS (Watershed Modeling System) to analyze soil erosion vulnerability of the CheonCheon watershed. In addition, we compared the six sediment transport capacity formulas provided in the model and evaluated the equations fir on this study site. Therefore, this result can be as a primary tool for soil conservation management.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.59-74
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• 2016

The collapses of retaining walls or embankments, the soil erosion and landslides around urban areas are occurring by heavy rainfalls because of the recent climate change. This study conducts the soil erosion modeling, while applying the spatial information such as soil maps, DEM and landcover maps to the RUSLE model. Especially this study draws up the soil erosion grade map and the unit soil erosion grade map by parcels through coupling the soil erosion with the cadastral map, and by that can calculate the number of parcels by soil erosion grades. Also the sediment disaster information system based on the mobile GIS is developed to identify the soil erosion grades of site in the urban plannings and the construction fields. The sediment disaster information system can identify the present conditions of the registers of lands, buildings and roads, and confirm the RUSLE factors, the soil erosion, the sediment disaster grades by parcels. Also it is anticipated that this system can support the sediment disaster work of site effectively through searching the locations and attributes of the specific parcels by Administrative Dong and the soil erosion grades.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.803-814
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• 2020

Managing erosion control dams requires the annual average sediment yield to determine their storage capacity and time to full sediment-fill and dredging. The GeoWEPP (Geo-spatial interface for Water Erosion Prediction Project) model can predict the annual average sediment yield from various land uses and vegetation covers at a watershed scale. This study assessed the GeoWEPP to determine the annual average sediment yield for managing erosion control dams by applying it to five erosion control dams and comparing the results with field observations using ground-based LiDAR (light detection and ranging). The modeling results showed some differences with the observed sediment yields. Therefore, GeoWEPP is not recommended to determine the annual average sediment yield for erosion control dams. Moreover, when using the GeoWEPP, the following is recommended :1) use the US WEPP climate files with similar latitude, elevation and precipitation modified with monthly average climate data in Korea and 2) use soil files based on forest soil maps in Korea. These methods resulted in GeoWEPP predictions and field observations of 0 and 63.3 Mg·yr-1 for the Gangneung, 142.3 and 331.2 Mg·yr-1 for the Bonghwa landslide, 102.0 and 107.8 Mg·yr-1 for the Bonghwa control, 294.7 and 115.0 Mg·yr-1 for the Chilgok forest fire, and 0 and 15.0 Mg·yr-1 for the Chilgok control watersheds. Application of the GeoWEPP in Korea requires 1) building a climate database fit for the WEPP using the meteorological data from Korea and 2) performing further studies on soil and streamside erosion to determine accurate parameter values for Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.25-34
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• 2001

A grid-based KIneMatic wave soil-water EROsion and deposition Model (KIMEROM) that predicts temporal variation and spatial distribution of sediment transport in a watershed was developed. This model uses ASCII-formatted map data supported from the regular gridded map of GRASS (U.S. Army CERL, 1993)-GIS (Geographic Information Systems), and generates the distributed results by ASCIIl-formatted map data. For hydrologic process, the kinematic wave equation and Darcy equation were used to simulate surface and subsurface flow, respectively (Kim, 1798; Kim et al., 1993). For soil erosion process, the physically-based soil erosion concept by Rose and Hairsine (1988) was used to simulate soil-water erosion and deposition. The model adopts sing1e overland flowpath algorithm and simulates surface and subsurface water depth, and sediment concentration at each grid element (or a given time increment. The model was tested to a 162.3 km$^2$ watershed located in the tideland reclaimed area of South Korea. After the hydrologic calibration for two storm events in 1999, the results of sediment transport were presented for the same storm events. The results of temporal variation and spatial distribution of overland flow and sediment areas are shown using GRASS.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.908-912
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• 2006

Geology and terrain of Imha basin has a very weak characteristics to soil erosion, so much soil particles flow into Imha reservoir and bring about high density turbid water when it rains a lot. Especially, since the agricultural area of Imha basin is mainly located in river boundary, Imha reservoir has suffered from turbid water by soil erosion. Therefore, it is important to estimate the influence of soil erosion to establish efficient management of water-pollutant buffering zone for the reduction of turbid water. By applying GIS-based RUSLE model, this study can acquire 12.23% that is the ratio of soil erosion in water-pollutant buffering zone and is higher than area-ratio (9.95%) of water-pollutant buffering zone. This is why the area-ratio of agricultural district (27.24%) in water-pollutant buffering zone is higher than the area-ratio of agricultural district (14.96%) in Imha basin. Also as the result of soil erosion in sub-basin, Daegok basin shows highest soil erosion in water-pollutant buffering zone, second is Banbyeon_10 basin and last is Seosi basin.