• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1315-1319
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• 2008

본 연구에서는 WEP 모형을 통해 판교신도시 개발 전의 물순환을 해석하였다. 정밀한 해석을 위해 대상유역을 30m 크기의 정방형 격자로 구분하고 기상 조건, 지표면 조건, 하천, 토양, 지하대수층, 농업용수 이용 등 물순환에 관련된 광범위한 입력자료를 기존 측정 자료 및 관련 문헌, 현장 조사를 통해 각각 구축하였다. 물순환 해석 결과는 개발 전 모의에 대해 하천유출, 유황곡선 및 물수지, 수문요소 공간분포 분석을 통해 수행하였다. 모의 결과의 전 후처리는 WEP+(Water and Energy transfer Process model Plus)를 통해 수행되었으며, WEP+는 WEP 모형의 방대한 양의 입력자료를 효과적으로 구축하고, 다양한 시계열 및 공간분포 출력자료를 효과적으로 분석할 수 있는 인터페이스를 지닌 전 후처리 프로그램이다(한국건설기술연구원, 2007). 향후 판교신도시 개발후의 물순환 특성 변화를 평가하여 개발전후의 수문요소의 변화를 정량적으로 비교분석 함으로써 효율적인 저감 대책의 수립에 활용할 계획이다. 즉 도시개발로 인해 변화되는 지형, 토지이용, 토양, 지하대수층, 용수이용 등의 각 요소들을 모형에 적용하여 각 매개변수들이 수문순환 요소에 미치는 영향을 분석할 계획이다.

• Journal of the Korean association of regional geographers
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• v.17 no.2
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• pp.245-258
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• 2011

Best management practices (BMPs) are widely accepted and implemented as a mitigation method for soil erosion and non-point source problems. Estimating the amount of soil erosion and the effectiveness of BMPs using hydrological models help to understand the condition, identify the problems, and make plans for conservation practices in an area, typically a watershed. However, the accuracy and reliability of assessment of BMP impacts estimated by hydrological models can be often questionable due to the uncertainties from various sources including GIS(Geographic Information System) data, scale, and model. This study reviewed the development and the background of hydrological models, and the modeling issues such as the selection of models, scale, and uncertainties of data and models. This study also discussed the advantage of a small scale and spatially distributed model to estimate the impacts of BMPs.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.209-220
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• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• Journal of Environmental Impact Assessment
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• v.10 no.3
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• pp.235-243
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• 2001

Since the middle of 1990s, in Korea a few researches on the optimal management technologies combining numerical model and GIS for the management of water environment in drinking watershed area and reservoir such as Paldang Lake have been carried out. In this study, the integrated water environment management system was been suggested to efficiently reflect the public awareness of the environment by integrating the web based distributed data collection system, GIS, public hearing system and water quality model. As all the components of the system have been developed using the World Wide Web and all data have been collected from the relevant agencies through the Internet, the water quality model could be implemented on the web directly. In consequence, the environmental geographic information in Paldang Lake could be acquired and analyzed through the Internet. The system can rapidly respond to the public right to know on environment, so the public will willingly participate in the governmental projects on environment. To verify the usability of the developed system, it has been applied to Paldang Lake. Especially when the web based model has been used, users can easily and confidentially get the prediction results by applying the minimum number of parameters for the water quality model. This model will provide clearness and scientific bases in the process of water quality prediction for the sensitive sites where there are critical conflicts between the residents and the developers. In this study, rapid water environment management technique without spatial and time limit has been suggested, which can contribute to the efforts on the government and the public participation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.495-504
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• 2008

Evapotranspiration (ET) is an important state variable while simulating daily streamflow in hydrological models. In the estimation of ET, for example, when using FAO Penman Monteith equation, the LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAI from MODIS satellite data is available, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. Four years (2001-2004) of MODIS LAI was prepared for the evaluation of Penman Monteith ET in the continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungju watershed ($6661.3km^2$) located in the upstream of Han river basin. For four years (2001-2004) dam inflow data and meteorological data, the model was calibrated and verified using MODIS LAI data. The average Nash-Sutcliffe model efficiency was 0.66. The 4 years watershed average Penman Monteith ETs of deciduous, coniferous, and mixed forest were 639.1, 422.4, and 631.6 mm for average MODIS LAI values of 3.64, 3.50, and 3.63 respectively.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.887-898
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• 2007

A physically based semi-distributed model, SWAT was applied to the Chungju Dam upstream watershed in order to investigate the spatial and temporal characteristics of watershed sediment yields. For this, general features of the SWAT and sediment simulation algorithm within the model were described briefly, and watershed sediment modeling system was constructed after calibration and validation of parameters related to the runoff and sediment. With this modeling system, temporal and spatial variation of soil loss and sediment yields according to watershed scales, land uses, and reaches was analyzed. Sediment yield rates with drainage areas resulted in $0.5{\sim}0.6ton/ha/yr$ excluding some upstream sub-watersheds and showed around 0.51 ton/ha/yr above the areas of $1,000km^2$. Annual average soil loss according to land use represented the higher values in upland areas, but relatively lower in paddy and forest areas which were similar to the previous results from other researchers. Among the upstream reaches, Pyeongchanggang and Jucheongang showed higher sediment yields which was thought to be caused by larger area and higher fraction of upland than other upstream sub-areas. Monthly sediment yields at the main outlet showed same trend with seasonal rainfall distribution, that is, approximately 62% of annual yield was generated during July to August and the amount was about 208 ton/yr. From the results, we could obtain the uniform value of sediment yield rate and could roughly evaluate the effect of soil loss with land uses, and also could analyze the temporal and spatial characteristics of sediment yields from each reach and monthly variation for the Chungju Dam upstream watershed.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.39-58
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• 2019

This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R²) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R², and VCI results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.529-536
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• 2013

The semi-distributed rainfall runoff model of SWAT is applied to the Seom-river experimental watershed. The simulations of various antecedent periods before the targeted simulation periods of 2002 to 2009 are not necessary despite of the slight appearance of corresponding changes in simulated total runoff. The simulated results of total runoff by using various numbers of soil layer maps have little differentiated nevertheless the slight changes in simulated results have been appeared. The 7 parameters of CANMX, $CN_2$, ESCO, GW_REVAP, SOL_ALB, SOL_AWC, and SOL_K greatly govern the rainfall runoff are confirmed and their sensitivity analyses have been carried out. The optimal parameters used in SWAT are derived by SUFI-2 of SWAT-CUP. The NS and $R^2$ are 0.99 and 0.98, respectively which is shown the good agreement between the observed and the simulated results. The uncertainty factors of P-factor and R-factor are 0.85 and 0.06, respectively which is also shown the high efficiency of the model. The high applicability is also shown with improving the RMSE in SWAT model simulation using the parameters estimated by SUFI-2 of SWAT-CUP.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.63-72
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• 2000

The objective of this study was to identify the applicability of AGNPS(Agricultural Nonpoint Source Pollution) model using RS data; Landsat TM merged by KOMPSAT EOC and GIS data. AGNPS model which is well-known distributed nonpoint source pollution model was used as the assessment tool. This model has the capability to adjust the level of pollutant load from farmstead and the fertilization level of upland field. A small agricultural watershed($4.12km^2$) which has 20 livestock farmhouses located in Gosan-myun, Ansung-gun was selected. AGNPS data were prepared by using Arc/Info, GRASS, ER-Mapper and Idrisi. Four storm events in 1999 were used for runoff calibration, and 2 storm events which were measured in hourly-base at 4 locations along the stream were used for water quality(TN, TP) calibration.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.