• Journal of Korea Water Resources Association
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• v.37 no.8
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• pp.631-641
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• 2004

The objective of this study is to test the applicability of SLURP (Semi-distributed Land Use-based Runoff Process) on Soyanggang-dam watershed. SLURP model is a conceptual semi-distributed form model that can be used to examine irrigation plan and the effects of proposed changes in water management within a basin or to see what effects external factors such as climate change or changing land cover might have on various water users. Topographical parameters were derived from DEM using TOPAZ and SLURPAZ. Monthly NDVIs were calculated from multi-temporal NOAA/AVHRR images during four years (1998 ∼ 2001). Weather elements (dew-point temperature, solar radiation, maximum/minimum temperature and relative humidify) were obtained from five meteorological stations within and near the study area. To simulate daily hydrograph during 1998 ∼ 2001, the model parameters of each land cover class were optimized by sensitivity analysis and SCE-UA method. Test result of SLURP was summarized by various statistics method (WMO volume error, Nash-Sutcliffe efficiency, mean error and coefficient of variation).

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.867-880
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• 2006

Hydrological models with many parameters and complex model structures require a powerful and detailed model calibration/validation scheme. In this study, we proposed a multi-variable and multi-site calibration and validation framework for the Soil Water Assessment Tool (SWAT) model applied in the Gap-cheon catchment located downstream of the Geum river basin. The sensitivity analysis conducted before main calibration helped understand various hydrological processes and the characteristics of subcatchments by identifying sensitive parameters in the model. In addition, the model's parameters were estimated based on existing data prior to calibration in order to increase the validity of model. The Nash-Sutcliffe coefficients and correlation coefficient were used to estimate compare model output with the observed streamflow data: $R_{eff}\;and\;R^2$ ranged 0.41-0.84 and 0.5-0.86, respectively, at the Heuduck station. Model reproduced baseflow estimated using recursive digital filter except for 2-5% overestimation at the Sindae and Boksu stations. Model also reproduced the temporal variability and fluctuation magnitude of observed groundwater levels with $R^2$ of 0.71 except for certain periods. Therefore, it was concluded that the use of multi-variable and multi-site method provided high confidence for the structure and estimated parameter values of the model.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.155-155
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• 2019

The Agricultural Policy/Environmental eXtender (APEX) models have been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. National Academy of Agricultural Sciences, Wanju, Korea, has modified a key component of APEX application, named APEX-Paddy for simulating water quality with considering appropriate paddy management practices, such as puddling and flood irrigation management. Calibration and validation are an anticipated step before any model application. Simple techniques are essential to assess whether or not a parameter should be adjusted for calibration. However, very few study has been done to evaluate the ability of APEX-Paddy to simulate the impact of multiple management scenarios on nutrients loss. In this study, the observation data from experimental fields at Iksan in South Kora was used in calibration and evaluation process during 2013-2015. The APEX auto- calibration tool (APEX-CUTE) was used for model calibration and sensitivity analysis. Four quantitative statistics, the coefficient of determination ($R^2$),Nash-Sutcliffe(NSE),percentbias(PBIAS)androotmeansquareerror(RMSE)were used in model evaluation. In this study, the hydrological process of the modified model, APEX-Paddy, is being calibrated and tested in predicting runoff discharge rate and nutrient yield. Field-scale calibration and validation processes are described with an emphasis on essential calibration parameters and direction regarding logical sequences of calibration steps. This study helps to understand the calibration and validation way is further provided for applications of APEX-Paddy at the field scales.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.9-19
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• 2023

Drought is a natural disaster that can have serious social impacts. Drought's impact ranges from water supply for humans to ecosystems, but the impact of drought on river water quality requires careful investigation. In general, drought occurs meteorologically and is classified as agricultural drought, hydrological drought, and environmental drought. In this study, the BOD environmental drought is defined using the bivariate copula joint probability distribution model between the meteorological drought index and the river BOD, and based on this, the environmental drought condition index (EDCI-BOD) was proposed. The results of examining the proposed index using past precipitation and BOD observation data showed that EDCI-BOD expressed environmental drought well in terms of river BOD water quality. In addition, by classifying the calculated EDCI-BOD into four levels, namely, 'attention', 'caution', 'alert', and 'seriousness', a practical monitoring stage for environmental drought of BOD was constructed. We further estimated the sensitivity of the stream BOD to meteorological drought, and through this, we could identify the stream section in which the stream BOD responded relatively more sensitively to the occurrence of meteorological drought. The results of this study are expected to provide information necessary for river BOD management in the event of meteorological droughts.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.36-51
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• 2012

The demand for a climatological dataset with a regular spaced grid is increasing in diverse fields such as ecological and hydrological modeling as well as regional climate impact studies. PRISM(Precipitation-Elevation Regressions on Independent Slopes Model) is a useful method to estimate high-altitude precipitation. However, it is not well discussed over the optimization of PRISM parameters and DEM(Digital Elevation Model) resolution in South Korea. This study developed the PRISM and then optimized parameters of the model and DEM resolution for producing a gridded annual average precipitation data of South Korea with 1km spatial resolution during the period 2000-2005. SCE-UA (Shuffled Complex Evolution-University of Arizona) method employed for the optimization. In addition, sensitivity analysis investigates the change in the model output with respect to the parameter and the DEM spatial resolution variations. The study result shows that maximum radius within which station search will be conducted is 67km. Minimum radius within which all stations are included is 31km. Minimum number of stations required for cell precipitation and elevation regression calculation is four. Optimizing DEM resolution is $1{\times}1km$. This study also shows that the PRISM output very sensitive to DEM spatial resolution variations. This study contributes to improving the accuracy of PRISM technique as it applies to South Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.43-54
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• 2023

Due to climate change, drought and flood occurrences have been increasing. Accurate projections of watershed discharges are imperative to effectively manage natural disasters caused by climate change. However, climate change and hydrological model uncertainty can lead to imprecise analysis. To address this issues, we used two lumped models, IHACRES and GR4J, to compare and analyze the changes in discharges under climate stress scenarios. The Hapcheon and Seomjingang dam basins were the study site, and the Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) were used for parameter optimizations. Twenty years of discharge, precipitation, and temperature (1995-2014) data were used and divided into training and testing data sets with a 70/30 split. The accuracies of the modeled results were relatively high during the training and testing periods (NSE>0.74, KGE>0.75), indicating that both models could reproduce the previously observed discharges. To explore the impacts of climate change on modeled discharges, we developed climate stress scenarios by changing precipitation from -50 % to +50 % by 1 % and temperature from 0 ℃ to 8 ℃ by 0.1 ℃ based on two decades of weather data, which resulted in 8,181 climate stress scenarios. We analyzed the yearly maximum, abundant, and ordinary discharges projected by the two lumped models. We found that the trends of the maximum and abundant discharges modeled by IHACRES and GR4J became pronounced as changes in precipitation and temperature increased. The opposite was true for the case of ordinary water levels. Our study demonstrated that the quantitative evaluations of the model uncertainty were important to reduce the impacts of climate change on water resources.