• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• 농업과학연구
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• 제47권2호
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• pp.381-394
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• 2020

Accelerated soil wind erosion still remains to date to cause severe economic and environmental impacts. Revised and updated models to quantitatively evaluate wind induced soil erosion have been made for specific factors in the wind erosion equation (WEQ) framework. Because of increasing quantities of accumulated data, the WEQ, the revised wind erosion equation (RWEQ), the wind erosion prediction system (WEPS), and other soil wind erosion models have been established. These soil wind erosion models provide essential knowledge about where and when wind erosion occurs although naturally, they are less accurate than the field-scale. The WEQ was a good empirical model for comparing the effects of various management practices on potential erosion before the RWEQ and the WEPS showed more realistic estimates of erosion using easily measured local soil and climatic variables as inputs. The significant relationship between the observed and predicted transport capacity and soil loss makes the RWEQ a suitable tool for a large scale prediction of the wind erosion potential. WEPS developed to replace the empirical WEQ can calculate soil loss on a daily basis, provide capability to handle nonuniform areas, and obtain predictions for specific areas of interest. However, the challenge of precisely estimating wind erosion at a specific regional scale still remains to date.

• 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.

• 한국환경농학회지
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• 제27권4호
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• pp.314-320
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• 2008

During the summer season, more than half of the annual precipitation in Korea occurs during the summer season due to the geographical location in the Asian monsoon belt. So, this causes severe soil erosion from croplands, which is directly linked to the deterioration of crop/land productivity and surface water quality. Therefore, much attention has been given to develop accurate estimation tools of soil erosion. The aim of this study is to assess the performance of using the empirical Universal Soil Loss Equation (USLE) and the physical-based model of the Water Erosion Prediction Project (WEPP) to quantify eroded amount of soil from agricultural fields. Input data files, including climate, soil, slope, and cropping management, were modified to fit into Korean conditions. Chuncheon (forest) and Jeonju (level-plain) were selected as two Korean cities with different topographic characteristics for model analysis. The results of this current study indicated that better soil erosion prediction can be achieved using the WEPP model since it has better power to illustrate a higher degree of spatial variability than USLE in topography, precipitation, soils, and crop management practices. These present findings are expected to contribute to the development of the environmental assessment program as well as the conservation of the agricultural environment in Korea.

• 대한공간정보학회지
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• 제15권3호
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• pp.77-85
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• 2007

토양침식의 산정은 많은 비용과 시간을 요구한다. 한 지역에서 토양침식을 예측하기 위한 많은 모형들이 있지만, 범용토양손실공식(USLE, Universal Soil Loss Equation)이 연 토양 침식량 산정을 위한 경험식으로 가장 널리 사용되고 있다. 토양침식은 강우강도, 토양의 종류, 토지 피복과 토지이용, 사면경사와 경사길이, 그리고 토양보전을 위한 시설의 영향을 받는다. 이러한 모든 변수들은 공간적으로 분포되어 있기 때문에 지형정보시스템(GIS)이 토양침식 영향평가에 널리 적용될 수 있다. 본 연구에서는 IHP 대표 유역인 보청천 유역을 대상으로 지형정보시스템(GIS)과 범용토양손실 공식을 연계하여 태풍 루사의 강우에 의한 유역에서의 토양 침식량을 산정하였다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제22권6호
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• 대한토목학회논문집
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• 제26권2D호
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• pp.341-347
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• 2006

임하호는 안동호 유역과 지형학적으로 인접되어 있지만 강우강도에 따른 탁수발생에는 큰 차이를 보이고 있으며 이러한 원인을 밝히는 것은 매우 중요하다. 본 연구에서는 안동호와 임하호 유역을 연구대상지로 선정하여 준경험 토사유실모델인 RUSLE 모델을 이용하여 고탁수 발생에 큰 영향을 미치는 토사유실량을 비교 평가하였다. 먼저, 환경부에서 구축한 토지피복도를 기반으로 토사유실에 가장 민감한 농경지비율을 분석한 결과, 안동호유역은 11.88%, 임하호유역은 14.95%로서 임하호유역이 3.07% 높게 평가되었다. 또한 RUSLE 인자의 분석에서는 경작인자를 제외한 모든 인자들이 임하호유역에서 높게 평가되었으며, 이는 시간적인 변화를 보이는 강우자료를 제외한 토양, 지형 그리고 토지피복상태가 임하호유역이 안동호유역에 비해 토사유실에 취약한 구조를 가지고 있음을 의미한다. 토사유실량 평가에서도 안동호와 임하호유역이 각각 1,275,806 ton과 1,501,608 ton으로서, 임하호유역이 안동호유역에 비해 225,802 ton만큼 높게 평가되었다.

• 한국농공학회논문집
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• 제58권6호
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• pp.55-69
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• 2016

RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associated overland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity and characteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physical schemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed to quantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfall data) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factors calculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those for energy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual R factors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods that would provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, the efforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.774-778
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• 2010

상류에서 유입된 토사는 지표수를 오염시키고 때때로 퇴적이 발생시 심각한 문제들을 야기하게 된다. 본 연구에서는 GIS 기반의 경험적 토사유실모형을 통해 모의된 토사유실량과 관측된 유사량 자료를 이용하여 유사전달률 자료를 구축하였다. 모의된 토사유실량과 관측된 유사량과의 관계를 분석한 결과, 강우량에 의한 결정계수는 동향과 천천에 대해 각각 0.427과 0.667인 반면, 강우 강도에 의한 결정계수는 0.873과 0.927로 높게 나타났다. 자료의 검보정을 위해 2002-2005년도(보정)와 2006-2008년도(검증) 자료로 분류한 후 USLE 모형과 관측된 유사량을 이용하여 SDR을 계산하였다. 동향과 천천유역의 강우량에 의한 SDR의 평균은 각각 6.273과 3.353인 반면 강우강도에 의한 SDR의 평균은 4.799와 2.874로 낮게 나타났으며, 표준편차는 강우량의 3.746과 2.090에 비해 강우강도가 0.930과 0.407로 낮게 나타났다. 따라서 토사유실 모델링시 강우량에 의한 방법보다는 강우강도에 의한 SDR 추정값을 사용하는 것이 더 바람직함을 보여준다.

• 한국측량학회지
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• 제19권1호
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• pp.27-37
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• 2001

강우나 물의 유출에 의한 토양침식은 농업 생산성을 떨어뜨리고 목초지를 손상시키며, 물의 흐름을 방해하는 등의 각종 환경적인 문제를 야기시키고 있다. 환경에 대한 관심이 고조되는 시점에서 토양침식이 매우 중요한 위치를 차지하고 있지만 아직은 체계적인 자료의 정리와 분석이 이루어지지 못하고 있는 실정이다. 본 연구는 최근 부각되고 있는 GSIS를 활용하여 토양침식을 예측하는 모형에 입력되는 인자를 추출하는 기법을 제시하는 것으로 침식모형에는 ANSWER, WEPP RUSLE 등 여러 가지가 있으나 본 연구에서는 GSIS 자료와의 연계가 용이하면서 유역에 대한 일반적인 토양침식을 예측할 수 있는 RUSLE 침식모형을 사용하였다. RUSLE 입력인자에는 강우침식인자 R, 토양침식인자 K, 침식사면의 길이인자 L, 침식사면의 경사인자 S, 식생피복인자 C 그리고 경작인자 P로 구성되어 있다. RUSLE 입력인자 중 L과 S인자 추출에 사용되었던 기존의 식은 대부분 농업지역에 적용된 식으로 유역에 적용시 한계가 있기 때문에 본 연구에서는 GSIS 자료를 통해 격자별로 유역에 적용 가능한 수정된 경험식을 활용하였다. 또한 격자형 RUSLE인자를 유역추출 알고리즘을 이용하여 유역별로 분석함으로서 유역별 RUSLE인자의 최소값, 최대값, 평균 그리고 표준편차를 계산할 수 있었다.