• Economic and Environmental Geology
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• v.40 no.1 s.182
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• pp.103-113
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• 2007

The empirical USLE and the physically-based GeoWEPP which were distributed model linked with GIS (Geographical Information System) were applied to small natural catchment located in Icheon-si, Gyeonggi-do, South Korea. The results using by two models were total sediment yield from study catchment between January, 2004 and January, 2005. During the study period, the observed total sediment yield was 270.54 ton and the total sediment yield computed by USLE and GeoWEPP model were 358.1 ton and 283.30 ton, respectively. Each of results computed by USLE and GeoWEPP overestimated more than the observed total sediment yield, but, based on the results, the total sediment yield computed by GeoWEPP approximated to the observed result. We suggest that the reason why the total sediment yield using by models overestimated was that computed amounts by two models did not contain the amount of suspended sediment flowed over the weir.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.525-531
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• 2016

This study integrates the Universal Soil Loss Equation(USLE) with GIS method to assess the soil erosion for national land cover map between 2007 and 2014. The land cover change map and C factors of USLE were applied to the estimation of spatial distribution of sediment yield. However, they generated distinct results because of differences in their applied methods and calculation processes of national land cover map. To generate the USLE model, C factors of MOE(Ministry of Environment) were compared with soil erosion of Inje stadium development area at the Naerin watershed in Gangwon province to 2014. The several thematic maps of research area such as land cover map, topographic and soil maps, together with tabular precipitation data used for soil erosion calculation. The land cover change were carried with level-2 and high level land cover map of MOE and estimated maximum double of soil erosion.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.515-515
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• 2015

토양유실량을 산정하기 위한 모델로 Universsal Soil Loss Equation(USLE)가 전 세계적으로 가장 많이 사용되고 있다. USLE 모형은 농경지에서 면상침식(Sheet erosion)과 세류침식(Rill erosion)을 모의할 수 있는 시험포단위 모형(Field-scale)으로 농경지에서 유실된 토양이 하류 하천으로 얼마나 흘러 들어가 하류 수계의 탁수발생과 이에 따른 수질악화에 얼마나 기여하는지, 즉, 유역단위의 토양유실량을 평가하는데 이용될 수 없다. 이러한 단점을 극복하기 위하여 Sediment Assessment Tool for Effective Erosion Control (SATEEC) ArcView 시스템이 개발되어 사용되고 있다. SATEEC ArcView 시스템은 USLE모형의 입력자료와 DEM만으로 유역면적에 따른 유달률을 산정하여 유역에서 유실된 토양이 얼마만큼 하류로 유달되는지를 모의할 수 있으며, 유역 경사도에 의한 유달률도 산정할 수 있어 지형적인 특성을 좀 더 다양하게 분석 할 수 있게 개발 되었다. 그러나 ArcView는 출시한지 오래되어 사용자가 많지 않고, 프로그램상의 오류가 많고, 대용량의 데이터 처리가 가능한 64비트 운영체제에서는 설치가 불가능한 단점이 있다. 또한, ArcView의 프로그래밍 언어인 Avenue는 클래스를 정의한다거나 상속을 한다거나 하는 문법을 제공하지 않기 때문에 객체지향 언어로 보기에는 부족하다고 할 수 있다. 또한, 최근의 ArcGIS 기반의 많은 모델들이 서로 연계하여 사용하고 있으나, Avenue는 기타 다른 프로그래밍 언어와 연계하여 사용하기가 쉽지 않은 단점이 있다. 그러나 최근 ArcGIS 버전들의 프로그래밍 언어인 Python은 간결하고 확장성이 좋으며, 다른 언어와의 연계가 쉽다. 또한, ArcGIS 10.x버전부터 제공되는 arcpy 모듈은 사용자와의 접근성이 매우 향상되었다. 따라서 SATEEC ArcView 버전을 ArcGIS 10.1 기반의 Python 으로 재개발하여 기존의 불편한 접근성과 대용량 데이터의 처리가 불가능했던 부분을 개선하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.450-450
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• 2021

기후변화 보고서에 따르면 집중 호우의 강도 및 빈도 증가가 향후 몇 년동안 지속될 것이라 제시하였다. 이러한 집중호우가 빈번히 발생하게 된다면 강우 침식성이 증가하여 표토 침식에 더 취약하게 발생된다. Universal Soil Loss Equation (USLE) 입력 매개 변수 중 하나인 강우침식능인자는 토양 유실을 예측할때 강우 강도의 미치는 영향을 제시하는 인자이다. 선행 연구에서 USLE 방법을 사용하여 강우침식능인자를 산정하였지만, 60분 단위 강우자료를 이용하였기 때문에 정확한 30분 최대 강우강도 산정을 고려하지 못하는 한계점이 있다. 본 연구의 목적은 강우침식능인자를 이전의 진행된 방법보다 더 빠르고 정확하게 예측하는 머신러닝 모델을 개발하며, 총 월별 강우량, 최대 일 강우량 및 최대 시간별 강우량 데이터만 있어도 산정이 가능하도록 하였다. 이를 위해 본 연구에서는 강우침식능인자의 산정 값의 정확도를 높이기 위해 1분 간격 강우 데이터를 사용하며, 최근 강우 패턴을 반영하기 위해서 2013-2019년 자료로 이용했다. 우선, 월별 특성을 파악하기 위해 USLE 계산 방법을 사용하여 월별 강우침식능인자를 산정하였고, 국내 50개 지점을 대상으로 계산된 월별 강우침식능인자를 실측 값으로 정하여, 머신러닝 모델을 통하여 강우침식능인자 예측하도록 학습시켜 분석하였다. 이 연구에 사용된 머신러닝 모델들은 Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, eXtreme Gradient Boost 및 Deep Neural Network을 이용하였다. 또한, 교차 검증을 통해서 모델 중 Deep Neural Network이 강우침식능인자 예측 정확도가 가장 높게 산정하였다. Deep Neural Network은 Nash-Sutcliffe Efficiency (NSE) 와 Coefficient of determination (R²)의 결과값이 0.87로서 모델의 예측성을 입증하였으며, 검증 모델을 테스트 하기 위해 국내 6개 지점을 무작위로 선별하여 강우침식능인자를 분석하였다. 본 연구 결과에서 나온 Deep Neural Network을 이용하면, 훨씬 적은 노력과 시간으로 원하는 지점에서 월별 강우침식능인자를 예측할 수 있으며, 한국 강우 패턴을 효율적으로 분석 할 수 있을 것이라 판단된다. 이를 통해 향후 토양 침식 위험을 지표화하는 것뿐만 아니라 토양 보전 계획을 수립할 수 있으며, 위험 지역을 우선적으로 선별하고 제시하는데 유용하게 사용 될 것이라 사료된다.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.3-10
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• 2010

The development of various spatial information and GIS has led to the research on interpretation of natural phenomena and correlational studies. This study is aimed to analyze the correlation between RUSLE(Revised Universal Soil Loss Equation) around Nakdong River area during the period of 1955 to 2005 and the amount of area change in the islets at the estuary terrain calculated in the study "Change Detection at the Nakdong Estuary Delta using Satellite Image and GIS". For the calculation of RUSLE, The 'Revised-USLE' model, a modified USLE model commonly used in Korea was used. For the rainfall erosion factor to calculate and compare the area of islets, the actual observation data for one year before the observation of satellite image from all observatories across Korea was used. The correlation coefficient between RUSLE and area change of islets was 0.57 for Jinwoo Islet; 0.7 for Sinja Islet; 0.87 for Doyodeung. This results showed that there was a great influence from Doyodeung where the main water way of Nakdong River runs. This study showed that the study using USLE for various fields and through identifying the characteristics of each factor is useful to understand natural phenomenon in practice.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.783-793
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• 2018

The purpose of this study to present updated regional annual mean rainfall erosivity data in the Republic of Korea. In 2012, Ministry of Environment in Korea published the notice about investigation and survey procedure for the amount of topsoil erosion and adopted USLE (Universal Soil Loss Equation) model to predict the amount of national-scale soil erosion in Korea. In the notice, regional rainfall erosivity values for 158 sites, which is essential to apply the USLE, were included, however, these values came from the data made before 1997 and need to be updated. This study collected, classified and combined annual mean rainfall erosivity data from the literature review to analyze the data. We presented that new iso-erodent map, interpolated by IDW (Inverse Distance Weighted) method and extracted updated regional annual mean rainfall erosivity data at 167 regions for 1961~2015. These values will be used as updated rainfall erosivity data to predict the amount of topsoil erosion in Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.173-173
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• 2016

토양유실은 수생태계에 악영향을 미칠 뿐만 아니라 상수원과 수계를 오염시키는 대표적인 오염원으로 간주되고 있다. 이러한 토양유실에 대한 문제를 해결하기 위해서는 무엇보다 토양유실 발생 현황을 파악하는 것이 중요하다. 토양유실 발생 현황을 파악하기 위하여 SWAT, SATEEC, APEX 등 다양한 수문모형 모델들이 개발되어 왔다. 그러나 각각의 수문모형 모델에서 어떠한 토양유실 산정 공식을 사용하였는지에 따라 모의 결과에서 다소 차이를 보이게 된다. 이에 본 연구에서는 우리나라의 필지나 유역을 대상으로 토양유실량을 산정함에 있어 어떠한 공식이 토양유실에 미치는 영향인자를 가장 잘 모의하는지 분석하여 적용하고자 하였다. 본 연구에서는 분지 특성의 유역으로, 유역 내 경작지가 집약적으로 모여 있어 토양유실 문제가 심각한 양구군 해안면 유역을 대상으로 시범 적용하였다. 토양유실량을 모의하기 위한 모델은 USLE, AOF, RUSLE, MUSLE, MUST, MUSS, MUSI의 공식 중에서 사용자가 지정한 공식에 따라 모의가 가능한 APEX 모델로 선정하였다. 본 연구에서는 양구군 해안면의 실측 유량자료를 기반으로 각 공식에 따른 토양유실량에 대하여 검정 작업을 진행하였으며, 이를 양구군 해안면의 토양유실 실측값과 비교 분석하여 해안면 유역에서 토양유실에 미치는 영향인자를 가장 잘 반영할 수 있는 공식이 무엇인지 확인하였다. 본 연구결과를 통해 양구군 해안면 유역에서 발생하는 토양유실량을 예측할 수 있는 최적의 공식을 확인함으로써 토양유실 관련 연구에 기여할 수 있을 것으로 기대된다. 그러나 본 연구에서는 양구군 해안면 유역을 대상으로 최적의 토양유실 산정공식을 찾았지만, 타 유역의 토양유실량을 평가하기에는 한계가 있다. 따라서 APEX를 이용한 전국단위 토양유실량 평가를 통해 범용화 할 수 있는 공식을 찾는 추가적인 연구를 진행한다면 보다 정밀한 토양유실량 산정이 가능하게 되어 향후 우리나라 토양유실 관련 연구에 큰 기여를 할 것으로 기대된다.

• Spatial Information Research
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• v.10 no.1
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• pp.139-152
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• 2002

The purpose of this study is to estimate temporal soil loss change according to long-term land cover changes using G1S and RS. Revised USLE(Universal Soil Loss Equation) factors were prepared by using point rainfall data, DEM(Digital Elevation Model), soil map and land cover map. During the past two decades, land cover changes were traced by using Landsat MSS and TM data. As a result, forest area in 2000 has decreased 25.3 $km^2$ compared with that in 1990. Soil loss has decreased 3751.2 tou/yr. On the other hand, upland area has increased 22.5 $km^2$. Soil loss of upland has increased 5395.4 to/yr. Therefore, soil loss in 2000 increased 6.3 kg/$m^2$/yr compared with that in 1990. This was mainly caused by the increased upland area.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.467-473
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• 2007

Although the dominant land use at the Imha-dam watershed is forest areas, soil erosion has been increasing because of intensive agricultural activities performed at the fields located along the stream for easy-access to water supply and relatively favorable topography. In addition, steep topography at the Imha-dam watershed is also contributing increased soil erosion and sediment loads. At the Imha-dam watershed, outflow has increased sharply by the typhoons Rusa and Maemi in 2002, 2003 respectively. In this study, the Soil and Water Assessment Tool (SWAT) model was evaluated for simulation of flow and sediment behaviors with long-term temporal and spatial conditions. The precipitation data from eight precipitation observatories, located at Ilwol, Subi and etc., were used. There was no significant difference in monthly rainfall for 8 locations. However, there was slight differences in rainfall amounts and patterns in 2003 and 2004. The topographical map at 1:5000 scale from the National Geographic Information Institute was used to define watershed boundaries, the detailed soil map at 1:25,000 scale from the National Institute of Highland Agriculture and the land cover data from the Korea Institute of Water and Environment were used to simulate the hydrologic response and soil erosion and sediment behaviors. To evaluate hydrologic component of the SWAT model, calibration was performed for the period from Jan. 2002 to Dec. 2003, and validation for Jan. 2004 to Apr. 2005. The $R^2$ value and El value were 0.93 and 0.90 respectively for calibration period, and the $R^2$ value and El value for validation were 0.73 and 0.68 respectively. The $R^2$ value and El value of sediment yield data with the calibrated parameters was 0.89 and 0.84 respectively. The comparisons with the measured data showed that the SWAT model is applicable to simulate hydrology and sediment behaviors at Imha dam watershed. With proper representation of the Best Management Practices (BM Ps) in the SWAT model, the SWAT can be used for pre-evaluation of the cost-effective and sustainable soil erosion BMPs to solve sediment issues at the Imha-dam watershed. In Korea, the Universal Soil Loss Equation (USLE) has been used to estimate the soil loss for over 30 years. However, there are limitations in the field scale mdel, USLE when applied for watershed. Also, the soil loss changes temporarily and spatially, for example, the Imha-dam watershed. Thus, the SW AT model, capable of simulating hydrologic and soil erosion/sediment behaviors temporarily and spatially at watershed scale, should be used to solve the muddy water issues at the Imha-dam watershed to establish more effective muddy water reduction countermeasure.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.383-391
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• 2007

This study was conducted for an assessment through the estimation of soil loss by each catchment classified by soil catena. Ten catchments, which are Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01, Gyongancheon02, Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02, Youngsangang08, were selected from the hydrologic unit map and the detailed soil digital map (1:25,000) for this study. The catchments like Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01 and Gyongancheon02 were mainly composed with soils originated from gneiss. The catchments like Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 and Youngsangang08 were mainly composed with soils originated from granites. The grades, which are divided into seven grades with A(very tolerable), B(tolerable), C(moderate), D(low), E(high), F(severe), G(very severe), of soil erosion estimated by USLE in catchments were distributed in most A and B because of paddy land and forestry. In detailed, the soil erosion grade of catchments mainly distributing soils originated from gneiss showed more the distribution of B and C than it of catchments mainly distributing soils originated from granites. The reason of results would be derived from topographic characteristics of soils originated from gneiss located at mountainous. The soil loss according to soil catena linked with Songsan and Jigok series, which are soils originated from gneiss was calculated with $7.66ton\;ha^{-1}\;yr^{-1}$. The soil loss of Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 which have the soil catena linked with Samgak and Sangju soil series originated from granite, was calculated with $5.55ton\;ha^{-1}\;yr^{-1}$. The soil loss of Youngsangang08 which have the soil catena linked with Songjung and Baeksan soil series originated from granite was calculated with $9.6ton\;ha^{-1}\;yr^{-1}$, but the conclusion on soil loss in this kind of soil catena would be drawn from the analysis of more catchments. In conclusion, the results of this study inform that the classification of soil catena by catchments and estimation of soil loss according to soil catena would be effective for analysis on the grade of non-point pollution by soil erosion in a catchment.