• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.155-166
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• 2020

In this study, we applied the Radar-AWS Rainrates (RAR), weather radar-based quantitative precipitation estimations (QPEs), to the Yongdam study watershed in order to perform the flood runoff simulation and calculate the inflow of the dam during flood events using hydrologic model. Since the Yongdam study watershed is a representative area of the mountainous terrain in South Korea and has a relatively large number of monitoring stations (water level/flow) and data compared to other dam watershed, an accurate analysis of the time and space variability of radar rainfall in the mountainous dam watershed can be examined in the flood modeling. HEC-HMS, which is a relatively simple model for adopting spatially distributed rainfall, was applied to the hydrological simulations using HEC-GeoHMS and ModClark method with a total of eight independent flood events that occurred during the last five years (2014 to 2018). In addition, two NCL and Python script programs are developed to process the radar-based precipitation data for the use of hydrological modeling. The results demonstrate that the RAR QPEs shows rather underestimate trends in larger values for validation against gauged observations (R² 0.86), but is an adequate input to apply flood runoff simulation efficiently for a dam watershed, showing relatively good model performance (E_NS 0.86, R² 0.87, and PBIAS 7.49%) with less requirements for the calibration of transform and routing parameters than the spatially averaged model simulations in HEC-HMS.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1016-1017
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• 2005

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.55-63
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• 2018

This study analyzed the applications of near real-time drought monitoring using satellite rainfall for the Korean Peninsula and un-gaged basins. We used AWS data of Yongdam-Dam, Hoengseong-Dam in Korea area, the meteorological station of Nakhon Rachasima, Pak chong for test-bed to evaluate the validation and the opportunity for un-gaged basins. In addition, we calculated EDI (Effective doought index) using the stations and co-located PERSIANN-CDR, TRMM (Tropical Rainfall Measurement Mission) TMPA (The TRMM Multisatellite Precipitation Analysis), GPM IMERG (the integrated Multi-satellitE Retrievals for GPM) rainfall data and compared the EDI-based station data with satellite data for applications of drought monitoring. The results showed that the correlation coefficient and the determination coefficient were 0.830 and 0.914 in Yongdam-dam, and 0.689 and 0.835 in Hoengseng-Dam respectively. Also, the correlation coefficient were 0.830, 0.914 from TRMM TMPA datasets and compasion with 0.660, 0.660 based on PERSIANN-CDR and TRMM data in nakhon and pakchong station. Our results were confirmed possibility of near real-time drought monitoring using EDI with daily satellite rainfall for un-gaged basins.

• Korean Journal of Ecology and Environment
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• v.44 no.2
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• pp.214-225
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• 2011

The objectives of the study were to evaluate seasonal patterns of epilimnetic water quality, and determine interannual eutrophication patterns at the dam site of Yong-dam Reservoir using long-term data during 2002~2009. Ionic dilutions, based on specific conductivity, occurred in the summer period in response to the intense monsoon rain and inflow, and suspended solid analysis indicated that the reservoir was clear except for the monsoon. Seasonality of nitrogen contents varied depending on the types of nitrogen and responded to ionic dilution; Ammonia-nitrogen ($NH_4$-N) peaked at dry season but nitrate-nitrogen ($NO_3$-N) peaked in the monsoon when the ionic dilution occurred. The maxima of $NO_3$-N seemed to be related with external summer N-loading from the watershed and active nitrogen fixation of bluregreens in the summer. $NO_3$-N was major determinant (>50%) of the total nitrogen pool and relative proportion of $NH_4$-N was minor. Long-term annual $NO_3$-N and TDN showed continuous increasing trends from 2004 to 2009, whereas TP and TDP showed decreasing trends along with chlorophyll-a (CHL) values. Empirical model analysis of log-transformed nutrients and N : P ratios on the CHL showed that the reservoir CHL had a stronger linear function with TP ($R^2$=0.89, p<0.001) than TN ($R^2$=0.35, p=0.120). Overall results suggest that eutrophication progress, based on TP and CHL, is slow down over the study period and this was mainly due to reduced phosphorns, which is considered as primary nutrient by the empirical model.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.1 s.20
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• pp.69-81
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• 2006

The purpose of this study is to identify the downstream influences due to the dam discharge by using 2-dimensional model, SMS(Surface water Modeling System). RMA-2 and SED-2D in SMS were applied to Yongdam multipurpose dam watershed located in Gum river basin. Through the simulation, erosion and deposit quantitative analysis of sinuous channels and scour pattern analysis of bridges have been done. A differences erosion depths between deposit are simulated as $-102.4 mm{\sim}54.2 mm$ at No.176(1.4 km) and $-104.1 mm{\sim}28.9 mm$ at No.146(7.4 km), sinuous channel. The river bed at Kamdong bridge in straight channal is simulated as uniform erosion. However, the river bed at Dumdul bridge in sinuous channal has been shown as different erosion depths at each sides. Consequently, the parts that could not be simulated on the existing 1-dimensional model, can be improved results by using a 2-dimensional model, about weakness points for hydraulic modeling such as extreme bend, tributary confluence.

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.187-194
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• 2002

To improve the accuracy of the areal rainfall estimates over a river basin, the optimal design method of rainfall network was studied using the stochastic characteristics of measured rainfall data. The objective function was constructed with the estimation error of areal rainfall and observation cost of point rainfall and the observation sites with minimum objective function value were selected as the optimal network. As a stochastic variance estimator, kriging model was selected to minimize the error terms. The annual operation cost including the installation cost was considered as the cost terms and an accuracy equivalent parameter was used to combine the error and cost terms. The optimal design method of rainfall network was studied in the Yongdam dam basin whose raingauge numbers need to be enlarged for the optimal rainfall networks of the basin.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.185-193
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• 2004

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONV GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about 7.6％ of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.929-940
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• 2011

In this study, the future expected discharges are analyzed for Daecheong and Yongdam Dam Watershed in Geum River watershed using A1B scenario based RCM with 27 km spatial resolutions from Korea Meteorological Agency and SWAT model. The direct use of GCM and RCM data for water resources impact assessment is practically hard because the spatial and temporal scales are different. In this study, the problems of spatial and temporal scales were settled by the spatial and temporal downscaling from watershed scale to weather station scale and from monthly to daily of RCM grid data. To generate the detailed hydrologic scenarios of the watershed scale, the multi-site non-stationary downscaling method was used to examine the fluctuations of rainfall events according to the future climate change with considerations of non-stationary. The similarity between simulation and observation results of inflows and discharges at the Yongdam Dam and Daecheong Dam was respectively 90.1% and 84.3% which shows a good agreement with observed data using SWAT model from 2001 to 2006. The analysis period of climate change was selected for 80 years from 2011 to 2090 and the discharges are increased 6% in periods of 2011~2030. The seasonal patterns of discharges will be different from the present precipitation patterns because the simulated discharge of summer was decreased and the discharge of fall was increased.

• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.179-190
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• 2019

In this study, a fish survey was conducted to investigate the habitat status of black shinner (Pseudopungtungia nigra) designated as endangered species level from the lower part of Yongdam Dam to the upper part of Daecheong Dam. Biodiversity analysis was performed on the basis of the number of fish emerged, and biological health and physical habitat environment were quantitatively analyzed using collected P. nigra. According to the survey, the habitat range of P. nigra was found from Banguri-myeon, Buri-myeon, Geumsan-gun, downstream of Yongdam Dam. The biodiversity analysis results of all species appeared to be low in overall dominance index and relatively high in species diversity and uniformity index. In addition, P. nigra collected in this study was confirmed to have normal growth and nutritional status by the full-length-weighted relativities and condition factor. The physical habitat environment of P. nigra was 0.3 - 0.6 m in depth, 0.3 - 0.7 m/s in flow rate, and bed materials showed high frequency of occurrence in the range of cobbles (64.0 - 256.0 mm) to boulders (>256.0 mm). These results are expected to be used as data for habitat restoration and management in the future as basic data on the spatial range and preferred physical habitat environment of P. nigra in Geumgang.