• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.67-74
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• 2005

The Doam watershed is located at alpine areas and the annual average precipitation, including snow accumulation, is significant higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. Also, extremely torrential rainfall, such as the typhoons 'RUSA' in 2002 and 'MAEMI' in 2003, caused significant amounts of soil erosion and sediment at the Doam watershed. However, the USLE model cannot simulate impacts on soil erosion of freezing and thaw of the soil. It cannot estimate sediment yield from a single torrential rainfall event. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The R$^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it is found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Two typhoons in 2002 and 2003, MAEMI and RUSA, caused 33% and 22% of total sediment yields at the Doam watershed, respectively. Thus, it is recommended that the SWAT model, capable of simulating snow melt, sediment yield from a single storm event, and long-term weather data, needs to be used in estimating soil erosion at alpine agricultural areas to develop successful soil erosion management instead of the USLE.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.749-762
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• 2020

Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.491-500
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• 2017

Stream water quantity is the most basic, fundamental and important element for stream water quality and for conservation of ecological environment. This study aims to analyze causes of changes in stream water quantity based on the percentage of impervious surface area (%ISA) in urban streams of Gyeonggi-do, and also to present a method to secure water quantity of urban streams in Gyeonggi-do and data to be applied to River Management Policy. For this purpose, the Anyangcheon watershed, the Tancheon watershed, and the Osancheon watershed were selected as samples of the urban streams. In addition, the stream water quantity and the changes in stream water quality which were based on the amount of ISA, and methods to directly and indirectly secure stream water quantity were investigated. The results are as follows. The amounts of ISA of the Anyangcheon watershed, of the Tancheon watershed, and of the Osancheon watershed showed a 5.32%, 6.32%, and 7.22% increase, respectively, from 2014 which was approximately 10 years ago. The runoff coefficient generally increased as the amount of ISA was increased. Water reuse quantity of stream in the Tanchon watershed had a positive effect on securing stream water quantity, but both in the Anyangcheon watershed and in the Osancheon watershed, it did not have a positive effect on that. However, water reuse quantity of stream improved the water quality of each stream.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.104-118
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• 2018

This study is to evaluate the accuracy improvement of the model using SWAT(Soil and Water Assessment Tool) model and multi - point hydrological observation data. The watershed is located in the Yongdam Dam($930.4km^2$), the Donghyang($165.5km^2$), the Chuncheon($290.9km^2$), the Juchun($57.8km^2$) and the Seokjeong($80.5km^2$). The watershed covers 70.0 % forest. In order to improve the accuracy of the model, precipitation data were used from two weather stations(Jangsu, Geumsan) and 16 AWS stations daily precipitation data(2003~2011) managed by KMA, MLIT, and K-water. Based on the reliable data of the Yongam test basin in 2003~2011, the runoff of single point (Yongdam dam) and multi-point (Donghyang, Chuncheon, Jucheon, Seokjeong). Simulation results show that the $R^2$ of the single subwatershed (Donghyang, Chuncheon, Jucheon, Seokjeong) is single point(0.84) and multipoint(0.88). For model efficiency coefficient of Nash-Sutcliffe at single point(0.45) and multipoint(0.70).

• Korean Journal of Environmental Agriculture
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• v.29 no.3
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• pp.273-281
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• 2010

Concentration of antibiotics including a tetracycline group (TCs) of tetracycline (TC), chlortetracycline (CTC), and oxytetracycline (OTC), a sulfonamide group (SAs) of sulfamethoxazole (SMX), sulfathiazole (STZ), and sulfamethazine (SMT), an ionophore group (IPs) of lasalocid (LSL), monensin (MNS), and salinomycin (SLM), and a macrolide group (MLs) of tylosin (TYL) was determined from samples collected from the agricultural soil, stream water, and sediment. For the agricultural soil samples, the concentration of TCs had the highest value among all tested antibiotic's groups due to its high accumulation rate on the surface soils. The lower concentrations of SAs in the agricultural soils may be resulted from its lower usage and lower distribution coefficient (Kd) compared to TCs. The concentration of TCs in stream water was significantly increased through June to September. It would be likely due to soil loss during an intensive rainfall event and a reduction of water level after the monsoon season. A significant amount of TCs in the sediment was also detected due to its accumulation from runoff, which occurred by complexation of divalent cations, ion exchange, and hydrogen bonding among humic acid molecules. To ensure environmental or human safety, continuous monitoring of antibiotics residues in surrounding ecosystems and systematic approach to the occurrence mechanism of antibiotic resistant bacteria are required.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1039-1049
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• 2015

The inflow estimation at large multipurpose dam reservoir is carried out by considering the water balance among the discharge, the storage change during unit time interval obtained from the observed water level near dam structure and area-volume curve. This method can be ideal for level pool reservoir but include potential errors when the inflow is influenced by the water level slope due to backwater effects from upstream flood inflows and strong wind induced by typhoon. In addition, the other uncertainties arisen from the storage reduction due to sedimentation after the dam construction and water level noise due to mechanical vibration transmitted from the electric power generator. These uncertainties impedes the accurate hydraulic inflow measurement requiring exquisite hydrometric data arrangement for reservoir waterbody. In this study, the distributed hydrologic model using UBC-3P boundary setting was applied and its feasibility was evaluated. Finally, the modeling performance has been verified since the calculated determination coefficient has been in between 0.96 to 0.99 after comparing with observed peak inflow and total inflow at Namgang dam reservoir.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.291-295
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• 2007

강수진단모형을 이용하여 저수지 이수운영을 위한 실시간 유량예측기법을 개발하였다. 강수진단모형은 현재 기상청 현업에서 수행중인 강우수치예보를 기반으로 상세 지역의 지형 효과에 의한 강수를 예측하는 정량강수예측모형(QPM; Quantitative Precipitation Model)으로서 부경대학교 환경대기과학과에서 개발된 모형이다. QPM은 중규모 예측 모형으로부터 계산된 수평 바람, 고도, 기온, 강우 강도, 그리고 상대습도 등의 예측 자료를 이용하고, 소규모 상세지형 효과를 고려함으로써 중규모 예측 모형에서 생산된 강수량 예측 값을 상세 지역의 지형을 고려한 강수량 예측 값으로 재구성하여 결과적으로 3km 간격의 상세지역 강우산출과 지형에 따른 강수량의 분포 파악이 용이할 뿐만 아니라 계산 효율성을 개선된 모형이다. QPM 검증을 위하여 기상학적 평가와 수문학적 평가를 수행하였다. 호우 사례별 일강수량의 시공간 분포로 부터, QPM을 활용한 시스템에 의한 예측결과가 원시자료 RDAPS 보다 고해상도의 예측 및 지형효과의 반영도가 높았으며, AWS의 관측자료와 비교하여 보다 높은 예측성을 보여 주었다. 대상기간인 2006년 1월 1일부터 6월 20일까지 관측강우는 총 391.5mm 였으며 RQPM은 실적강우에 비하여 119.5mm 정도 과소산정하고 있으나 분위사상과정을 거치게 되면 351.7mm로서 실적강우에 불과 10.2% 못미치고 있다. 이는 고무적인 결과로 볼 수 있으며 현업에서의 활용성이 기대되는 수준이라 볼 수 있다. 강우-유출모의를 위한 QPM신뢰도를 높이기 위하여 분위사상법(Quantile Mapping)을 이용하여 QPM모의에 존재할 수 있는 계통오차에 대한 추가적인 보정을 수행하였다. 수문학적 평가를 위하여는 장기연속유출모형인 SSARR모형을 기반으로 개발된 RRFS(Rainfall-Runoff Forecast System)을 이용하여 2006년 1월${\sim}$9월까지의 용담댐 유입량에 대하여 모의예측결과와 관측유입량 비교를 통한 검증을 수행하였다. 위 기간중 예측유입량의 RMSE(Root Mean Squared Error), COE(Sutcliffe Coefficient of Efficiency), MAE(Mean Absolute Error), $R^2$값은 각각 7.50, 0.68, 2.59, 0.69 값을 보이고 있다. 본 연구에서는 QPM에 의한 예측성의 향상 및 구축된 시스템에 의한 일강수량의 장기예측 가능성을 확인하였고, 향후 시스템을 현업에 활용하기 위해서 생산된 예측자료의 보다 장기적인 검증을 통한 시스템의 안정화가 필요할 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.30 no.2
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• pp.165-175
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• 1997

This is to study the characteristics of available water resources (AWR) of the eastern coastal area in Korea. A rating curve was suggested at Yangyang water level station of the Yangyangnamdai river. Annual mean precipitation of this area is 1365.8mm. Annual mean precipitation in central and northern area of eastern coastal area is more than that of southern area because of orographic precipitation occurred by the north-easterly air flow from the East sea. By the correlation analysis of monthly rainfall depths between rainfall gauging stations it is presented that the rainfall gauging stations located in coastal region have the regional representativity, but the rainfall gauging stations located in the westward of mountains have a strong locality. AWR of eastern coastal area by the application of runoff coefficient 0.665 is 1134.5X106m3 and 28.6 percentage for total water resources. In each watershed AWR is 193.7X106m3 in the Yangyangnamdai river, 109X106m3 in the Kangnungnamdai river, and 146.0X106m3 in the Samcheokosip river. The seasonal changes of 30/3% in summer and 19.1% in water, and those of the AWR to total water resources are 86.3% in winter, 60.1% in spring, 50.1% in autumn, and 25.7% in summer. The results of this study may be used to establish the water resources planning of eastern coastal area.

• Spatial Information Research
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• v.20 no.3
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• pp.39-50
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• 2012

The objective of this study is the quantitative analysis of climate change effects by performing several statistical analyses with hydrometeorological data sets for past 30 years in Geum river watershed. Temperature, precipitation, relative humidity data sets were collected from eight observation stations for 37 years(1973~2009) in Geum river watershed. River level data was collected from Gongju and Gyuam gauge stations for 36 years(1973~2008) considering rating curve credibility problems and future long-term runoff modeling. Annual and seasonal year-to-year variation of hydrometeorological components were analyzed by calculating the average, standard deviation, skewness, and coefficient of variation. The results show precipitation has the strongest variability. Run test, Turning point test, and Anderson Exact test were performed to check if there is randomness in the data sets. Temperature and precipitation data have randomness and relative humidity and river level data have regularity. Groundwater level data has both aspects(randomness and regularity). Linear regression and Mann-Kendal test were performed for trend test. Temperature is increasing yearly and seasonally and precipitation is increasing in summer. Relative humidity is obviously decreasing. The results of this study can be used for the evaluation of the effects of climate change on water resources and the establishment of future water resources management technique development plan.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.569-583
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• 2013

This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon ($8.54km^2$) mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination ($R^2$) from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from $0.9^{\circ}C$ to $4.2^{\circ}C$ and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.