• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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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.

• 대한공간정보학회지
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• 제16권3호
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• pp.59-64
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• 2008

토양침식은 산악지역에서 산림조성에 중요한 문제를 일으키며 비옥한 토양을 침식시켜 식생의 성장을 저해시키며 인도에서 수집한 자료와 GIS를 이용하여 인도의 서부산맥 모야유역의 토양침식을 분석하였다. 주제도의 레이어로 산림, 지형경사, 배수 등에 대한 자료가 사용되었으며 토양침식 지도분석에서 48%의 지역이 중간정도의 침식을 보였다. 또한 35%지역은 높은 침식을 보였으며 가장 높은 침식은 식생지역의 7%를 차지하였다. 이러한 토양침식 분석도는 유역에서의 토양침식을 방지하기 위한 대책을 수립하는데 주요한 자료가 될 것으로 판단된다.

• 농업과학연구
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• 제51권3호
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• pp.375-389
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• 2024

Soil erosion, a critical environmental issue primarily driven by water and wind, has severe consequences, including the loss of fertile agricultural land, degradation of water quality, and sediment accumulation in riverbeds. This study utilized the SSEM (surface soil erosion model), a physically-based distributed model, to simulate the rainfall-runoff-sediment dynamics associated with short-term rainfall events in the Naerin River basin. A spatial analysis of erosion and deposition was conducted, taking into account topographical factors such as local slope and overland flow length. The study area was segmented into six sub-catchments using Strahler's stream order method to examine the correlation between geographic factors and erosion or deposition. The findings revealed that erosion was predominant within flow path distances of 0 - 1 km (adjacent to the river) and 3 - 4 km (in the upper catchment areas). Notably, deposition did not occur in areas beyond 2.5 km from the river. Furthermore, it was observed that average erosion depth increased on steeper slopes (exceeding 0.3 - 0.4 degrees), whereas deposition was absent in these steep slope classes.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2008년도 공동추계학술대회
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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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• 제2권1호
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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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.

• 지적과 국토정보
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• 제46권1호
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• pp.59-74
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• 2016

최근 기후변화에 따른 집중호우로 인해 도심지 옹벽 및 축대붕괴, 토사유실 그리고 산사태가 발생하고 있다. 본 연구에서는 토양도, DEM, 토지피복도와 같은 공간정보를 RUSLE 모델에 적용하여 토사유실모델링을 수행하였다. 특히 토사유실량을 지적도와 연계하여 필지별로 토사유실 및 단위토사유실 등급도를 작성하였으며, 토사유실 등급별로 필지수를 계산할 수 있었다. 또한 도시계획이나 건설 분야에서 토사유실 등급을 현장에서 확인할 수 있도록 모바일 GIS 기반의 토사재해정보시스템을 개발하였다. 토사재해정보시스템을 통해 토지대장, 건축물대장 그리고 도로구간대장에 대한 현황을 확인할 수 있으며, 필지별로 RUSLE 인자와 토사유실량 그리고 토사재해등급을 확인할 수 있었다. 또한 행정동과 토사유실등급별로 해당 필지의 위치와 속성을 검색함으로써 현장에서 토사재해업무를 효과적으로 지원할 수 있을 것으로 판단된다.

• 농업과학연구
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• 제47권4호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2001년도 학술발표회 논문집(I)
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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.