• Asian Journal of Atmospheric Environment
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• 제10권1호
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• pp.42-50
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• 2016

This study presents a performance evaluation of four different land surface models (LSM) available in Weather Forecast Research (WRF). The research site was located in Haean Basin in South Korea. The basin is very unique by its geomorphology and topography. For a better representation of the complex terrain in the mesoscale model were used a high resolution topography data with a spatial resolution of 30 meters. Additionally, land-use layer was corrected by ground mapping data-sets. The observation equipments used in the study were an ultrasonic anemometer with a gas analyzer, an automatic weather station and a tethered balloon sonde. The model simulation covers a four-day period during autumn. The result shows significant impact of LSM on meteorological simulation. The best agreement between observation and simulation was found in the case of WRF with Noah LSM (WRF-Noah). The WRF with Rapid Update Cycle LSM (WRF-RUC) has a very good agreement with temperature profiles due to successfully predicted fog which appeared during measurements and affected the radiation budget at the basin floor. The WRF with Pleim and Xiu LSM (WRF-PX) and WRF with Thermal Diffusion LSM (WRF-TD) performed insufficiently for simulation of heat fluxes. Both overestimated the sensible and underestimated the latent heat fluxes during the daytime.

• 환경영향평가
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• 제21권1호
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• pp.105-117
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• 2012

Future climate according to land-use change was simulated by regional climate model. The goal of study was to predict the distribution of meteorological elements using the Weather Research & Forecasting Model (WRF). The KME (Korea Ministry of Environment) medium-category land-use classification was used as dominant vegetation types. Meteorological modeling requires higher and more sophisticated land-use and initialization data. The WRF model simulations with HyTAG land-use indicated certain change in potential vegetation distribution in the future (2086-2088). Compared to the past (1986-1988) distribution, coniferous forest area was decreased in metropolitan and areas with complex terrain. The research shows a possibility to simulate regional climate with high resolution. As a result, the future climate was predicted to $4.5^{\circ}$ which was $0.5^{\circ}$ higher than prediction by Meteorological Administration. To improve future prediction of regional area, regional climate model with HyTAG as well as high resolution initial values such as urban growth and CO2 flux simulation would be desirable.

• 한국농공학회논문집
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• 제59권6호
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• pp.29-37
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• 2017

In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

• 대한환경공학회지
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• 제36권3호
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• pp.162-171
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• 2014

본 연구에서는 수질오염총량제의 토지계 발생부하량 산정 방식에서의 지목 단순화로 인한 불확실성을 분석하고, 23 개 중분류 토지피복도를 기존 산정방식에 적용하여 지목 확장을 할 수 있도록 개선하였으며 이를 L-THIA 모형을 이용하여 검증하였다. 진위천 유역에 대하여 지목이 단순화된 기존 방식(시나리오 1)과 23개 중분류 토지피복도를 이용한 방식(시나리 오 2)으로 산정된 TP 부하량을 비교한 결과 기존 방식의 불확실성이 높다는 것이 나타났으며, 시나리오 2에 의한 분석 결과 같은 대지 분류에 속하는 토지피복들에서 T-P 발생부하량의 편차가 3.45 kg/day~56.69 kg/day로 약 16배의 차이를 보였다. 시 나리오 2를 수질오염총량제에 적용할 수 있도록 23개 중분류 토지피복을 지적도 기반 지목으로 매칭하여 TP 발생부하량을 산정하였다(시나리오 3). 개선된 방식(시나리오 3)의 토지계 T-P 발생부하량 산정의 정확도를 검증하기 위해 L-THIA 모형의 결과와 비교하였으며 모형 예측 대비 약 10% 정도로 차이가 매우 적게 나타났다. 본 연구결과는 향후 수질오염총량제의 토 지계 발생부하량 산정의 정확도를 높이는데 있어 기초자료로 사용될 수 있을 것이라 기대된다.

• 대한원격탐사학회지
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• 제39권5_1호
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• pp.729-741
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• 2023

Operational Linescan System (OLS) 센서는 Defense Meteorological Satellite Program (DMSP) 프로그램을 통해 발사된 위성체에 탑재된 센서로, 야간에 방출되는 가시광 및 적외선대의 빛을 감지한다. 여러 연구자들의 연구를 통해 OLS 센서를 통해 획득한 야간광 자료와 국내 총생산(gross domestic product, GDP) 값에는 높은 상관관계가 존재함이 밝혀졌다. 본 연구에서는 경제 발전과 관련된 다양한 지표 중 하나인 개별 공시지가 총액과 야간광 자료의 상관관계에 대한 연구를 진행하였다. 연구 결과 대다수의 시, 도에서 0.7 이상의 상관계수로 높은 상관관계를 보였으며 남한 전체의 개별 공시지가 총액과 야간광 자료 간에도 상관계수는 0.7837로 높은 상관관계를 보였다. 그러나 타 시, 도와 달리 서울특별시의 경우 야간광과 개별 공시지가 총액은 상관계수가 0.5648로 낮은 상관계수를 보였는데, 이는 서울특별시의 digital number (DN) 값은 OLS 센서의 최대 DN 값에 가깝게 나타나 그 이상의 변화를 나타낼 수 없는 것이 원인으로 분석되었다. 본 연구를 통해 향후 공시지가가 체계적으로 정리되지 않은 지역의 공시지가를 파악하고, 이를 이용한 지역의 토지이용 변화 등을 분석하는 데 도움이 될 것으로 기대한다.

• 지질공학
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• 제32권4호
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• pp.483-498
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• 2022

토양수분은 불포화대의 공극 내에 존재하는 물로 정의되며, 다양한 수문학적 과정과 밀접하게 연관되어 있다. 본 연구에서는 지하수에 대한 의존도가 높은 농촌지역인 연구지역을 덮고 있는 6가지의 토지이용에 따른 토양수분 함량 및 토양 투수성 비교를 통해 토양수분에 영향을 미치는 요인을 파악하여 향후 연구에 유용한 자료를 제공하는 것을 목적으로 한다. 시계열 자료를 이용하여 자기상관분석, 스펙트럼 밀도분석 및 교차상관분석을 수행하였다. 토양수분 함량은 약한 자기상관성 및 기억효과를 가지며, 강수량이 토양수분 함량에 상당한 영향을 미치는 것으로 사료된다. 토지이용 변화에 따라 포화 수리전도도는 크게 변화하지 않으며, 대신 불균질한 토양의 구조에 의하여 영향을 받는 것으로 보인다.

• 한국농공학회지
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• 제37권E호
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• pp.63-71
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• 1995

Three types of land use were investigated to describe the effect of land use on both surface and ground water quality. Typical land uses of a grazing pasture, Sudan grass field and paddy in Kangwon province were selected and flumes and monitoring wells were installed. Land managements were carefully monitored, water samples were collected periodically and analyzed with respect to nitrate, TP and TKN at a laboratory of Kangwon Provincial Institute of Health and Environment from August, 1993 to May, 1994. Runoff from the pasture was formed mostly with seeping subsurface flow in the lower areas of the pasture. A few overland flows were observed during heavy storms, and when it occurred, runoff increased sharply. For the Sudan grass field, runoff was formed with overland flow. Nitrate concentration in runoff from both land uses seemed not affected by runoff and ranged from 0.241 to 4.137mg'/1. TP and TKN concentrations from the pasture were affected by overland flow. When overland flow occurred, TP and TKN concentrations abruptly increased to 5.726 and 12.841mg/1, respectively, from less than 1.0mg/l. However, these concentrations from the Sudan grass field were quite stable ranging from 0.191 to 0.674mg/l for TP and 0A70 and 1.650mg/l for TKN. Nitrate concentration was significantly affected by land use(Sudan grass field) and the concentration increase reached about 2mg/l per lOOm ground water flow. Nitrate concentration from a well located in the middle of rice fields also was significantly higher than that measured from a well located relatively undisturbed mountain toe area. TP and TKN concentrations in shallow ground water affected by the depth of the monitoring wells. The deeper the monitoring wells, the less TP and TKN concentrations were measured.

• 환경영향평가
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• 제14권3호
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• pp.97-107
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• 2005

The purpose of this study is to develop a system, which estimates watershed pollutant loading rate through the combination of GIS and computational mode. Also, the applicability of this study was estimated by the application of the above system for Chuncheon City. The detailed results of these studies are as follows; The pollutant loading estimation system was developed for more convenient estimation of pollutant loading rate in watershed, and the system load was minimized by the separation of estimation module for point and non-point source. This system on the basis of GIS is very economical and efficient because it can be applied to other watershed with the watershed map. System modification is not needed. The pollutant loading estimation system for point source was developed to estimate the pollutant loading rate in watershed through the extraction of the proper data from all districts and yearly data and the execution of spatial analysis which is main function of GIS. From the verification result of spatial analysis, real watershed area and the administrative districtarea extracted by spatial analysis were $1,114,893,340.15m^2$ and $1,114,878,683.68m^2$, respectively. It shows that the spatial analysis results were very exact with only 0.001% error. The pollutant loading estimation system for non-point source was developed to calculate the pollutant loading rate through the overlaying of land-use and watershed map after the construction of new land-use map using the land register database with most exact land use classification. Application result for Chuncheon City shows that the proposed system results in one percent land use error while the statistical method results in five percent. More exact nonpoint source pollutant loading was estimated from this system.

• 한국농공학회지
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• 제45권4호
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• pp.78-88
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• 2003

The land use changes from non-urban areas to urban areas lead to the increased impervious areas, consequently increased direct runoff and higher peak runoff. Urban areas have also been recognized as significant sources of Nonpoint Source (NPS) pollution, while agricultural activities have been known as the primary sources of NPS pollution. Many features of the L-THIA/NPS GIS, L-THIA/NPS WWW system have been enhanced to provide easy-to-use system. The L-THIA model was applied to the Little Eagle Creek (LEC) watershed in Indiana to evaluate the accuracy of the model. The L-THIA/NPS GIS estimated yearly direct runoff values match the direct runoff separated from U.S. Geological Survey stream flow data reasonably. The $R^2$ and Nash-Sutcliffe values are 0.67 and 0.60, respectively. The L-THIA estimated runoff volume and total nitrogen loading for each land use classification in the LEC watershed were computed. The estimated runoff volume and total nitrogen loading in the LEC watershed increased by 180% and 270% for the 20 years. Urbanized areas -"Commercial", "High Density Residential", and "Low Density Residential"- of the LEC watershed made up around 68% of the 1991 total land areas, however contributed more than 92% of average annual runoff and 86% of total nitrogen loading. Therefore, it is essential to consider the impacts of land use change on hydrology and water quality in land use planning of urbanizing watershed.nning of urbanizing watershed.

• 한국물환경학회지
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• 제30권2호
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• pp.212-219
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• 2014

In this study, a land pollutant load calculation method in TMDLs was improved to consider climate change scenarios. In order to evaluate the new method, future change in rainfall patterns was predicted by using SRES A1B climate change scenarios and then post-processing methods such as change factor (CF) and quantile mapping (QM) were applied to correct the bias between the predicted and the observed rainfall patterns. Also, future land pollutant loads were estimated by using both the bias corrected rainfall patterns and the enhanced method. For the results of bias correction, both methods (CF and QM) predicted the temporal trend of the past rainfall patterns and QM method showed future daily average precipitation in the range of 1.1~7.5 mm and CF showed it in the range of 1.3~6.8 mm from 2014 to 2100. Also, in the result of the estimation of future land pollutant loads using the enhanced method (2020, 2040, 2100), TN loads were in the range of 4316.6~6138.6 kg/day and TP loads were in the range of 457.0~716.5 kg/day. However, each result of TN and TP loads in 2020, 2040, 2100 was the same with the original method. The enhanced method in this study will be useful to predict land pollutant loads under the influence of climate change because it can reflect future change in rainfall patterns. Also, it is expected that the results of this study are used as a base data of TMDLs in case of applying for climate change scenarios.