• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.605-616
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• 2005

In this paper, runoff curve numbers (CN's) for a small forested mountainous catchment are estimated using rainfall-runoff data measured at Sulma experimental catchment every 10 minutes and a new guideline for applying the antecedent rainfall conditions (ARC's) for small mountainous watersheds in Korea is proposed. Sulma experimental catchment is a typical natural mountainous basin with $97\%$ of forested land cover and CN's are estimated to be in the range between 51 and 89 with median value of 72. The test hypothesis stating as 1-day ARC is better than 5-day ARC in determining CN's for a small mountainous watershed is shown to be acceptable. Also, linear regression equations for the estimation of CN's for small mountainous catchments are proposed. As there is no significant investigations available on CN's for small mountainous catchments, the newly proposed relationships between CN's and ARC may be used as a preliminary guideline to assign CN's for the estimation of floods from rainfall data on mountainous regions.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.228-231
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• 2006

유출계수(Runoff Curve Number, CN)란 강수량으로부터 대상유역의 유출량과 우수 잠재능(stormwater potential) 평가에 이용하는 수문학 변수로, 미국 자연자원 보존국(Natural Resources Conservation Service; NRCS)이 제안한 방법이다. 유출계수를 평가하기 위해서는 토지피복, 토양형, 토양 습윤 조건에 대한 정보를 조합하여 분석해야 한다. 본 연구의 목적은 미국 North Carolina의 Raleigh와 Cary시를 관통하는 Walnut Creek 유역 서부지역의 토지 피복도를 제작하여, 이 유역의 유출계수를 산정하는 것이다. 이를 위해서, 첫째 위의 불투수면 레이어와 정사항공사진을 기초자료로, ArcGIS와 Feature Analyst를 이용하여 서부 Walnut Creek 유역의 토지피복도를 제작하였다. 둘째, 제작된 토지 피복도와 본 유역의 수문학적 토양 분류체계도(Hydrologic Soil Group Map)를 중첩하여 이 유역의 유출계수도를 제작하였다.

• Korean Journal of Remote Sensing
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• v.2 no.2
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• pp.117-131
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• 1986

The purpose of this study was to develop techniques acquiring hydrologic parameters that affect runoff conditions from Landsat imagery. Runoff conditions in a study area were analyzed by employing the U.S. Soil Conservation Service(SCS) Method. SCS runoff curve numbers(CN) were estimated by the computer analysis of Landsat imagery and digiral terrain model(DTM) data. The SCS Method requires land use/cover and soil conditions of the area as input parameters. A land use/cover map of 5 hydrological classes was produced from the Landsat multi-spectral scannerr imagery. Slope-gradient and contour and contour maps were also made using the DTM topographic data. Inundation areas depending on reservoir levels were able to be mapped on the Landsat scene by combining the contour data.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.759-767
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• 2017

Two main parameters of NRCS-CN method are curve numbers and intial loss ratio. They are generally selected according to the guideline of US National Engineering Handbook, however, they might cause errors on estimated runoff in Korea because there are differences between soil types and hydrological characteristics of Korean watersheds and those of United States. In this study, applying asymptotic CN regression method, we suggested eight modified NRCS-CN models to decide optimum runoff estimation model for Korean watersheds. RSR (RMSE-observations standard deviation ratio) and NSE (Nash-Sutcliffe efficiency) were used to evaluate model performance, consequently M6 for gauged basins (Avg. RSR was 0.76, Avg. NSE was 0.39) and M7 for ungauged basins (Avg. RSR was 0.82, Avg. NSE was 0.31) were selected. Furthermore it was observed that initial loss ratios ranging from 0.01 to 0.10 were more adequate than the fixed ${\lambda}=0.20$ in most of basins.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.381-392
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• 2011

Pollutant loads calculated with unit factor method can not identity seasonal variations of pollutant inputs. Estimation of pollutant loads considering rainfall runoff can overcome these limits. SCS curve number method was applied to estimate runoff of each event of Koeup watershed of Koheung estuary lake. SCS curve numbers were calculated based upon land use, soil types of the catchment using GIS. Point and nonpoint source pollutant loads were summed up for total loads estimation. Those from nonpoint source were estimated by multiplying the calculated runoff and expected mean concentrations (EMC) presented by the Minister of Environment of Korea. DEM can present three dimensional views of a terrain, identity stream networks and flow accumulation. Furthermore, it can examine accumulated pollutant loads of specific point of a catchment. Therefore, cell based pollutant load estimation was attempted using DEM. ArcView was utilized to collect, store and manipulate spatial and attribute data of pollutant sources and features of the catchment. Cell-based DEM which was established by the GRID module of ARC/INFO was employed to estimate flows and pollutant loads.