• Water Engineering Research
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• v.5 no.2
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• pp.81-99
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• 2004

Long term streamflow regime under virtual climate change scenario was examined. Rainfall forecast simulation of the Canadian Global Coupled Model (CGCM2) of the Canadian Climate Center for modeling and analysis for the IPCC SRES B2 scenario was used for analysis. The B2 scenario envisions slower population growth (10.4 billion by 2010) with a more rapidly evolving economy and more emphasis on environmental protection. The relatively large scale of GCM hinders the accurate computation of the important streamflow characteristics such as the peak flow rate and lag time, etc. The GCM rainfall with more than 100km scale was downscaled to 2km-scale using the space-time stochastic random cascade model. The HEC-HMS was used for distributed hydrologic model which can take the grid rainfall as input data. The result illustrates that the annual variation of the total runoff and the peak flow can be much greater than rainfall variation, which means actual impact of rainfall variation for the available water resources can be much greater than the extent of the rainfall variation.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.39-50
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• 2022

In this study, we suggested the optimal training period for predicting the streamflow using the LSTM (Long Short-Term Memory) model based on the deep learning and CMIP5 (The fifth phase of the Couple Model Intercomparison Project) future climate scenarios. To validate the model performance of LSTM, the Jinan-gun (Seongsan-ri) site was selected in this study. We comfirmed that the LSTM-based streamflow was highly comparable to the measurements during the calibration (2000 to 2002/2014 to 2015) and validation (2003 to 2005/2016 to 2017) periods. Additionally, we compared the LSTM-based streamflow to the SWAT-based output during the calibration (2000~2015) and validation (2016~2019) periods. The results supported that the LSTM model also performed well in simulating streamflow during the long-term period, although small uncertainties exist. Then the SWAT-based daily streamflow was forecasted using the CMIP5 climate scenario forcing data in 2011~2100. We tested and determined the optimal training period for the LSTM model by comparing the LSTM-/SWAT-based streamflow with various scenarios. Note that the SWAT-based streamflow values were assumed as the observation because of no measurements in future (2011~2100). Our results showed that the LSTM-based streamflow was similar to the SWAT-based streamflow when the training data over the 30 years were used. These findings indicated that training periods more than 30 years were required to obtain LSTM-based reliable streamflow forecasts using climate change scenarios.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.88-96
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• 2013

Much attention has been needed in water resource management at the watershed due to drought and flooding issues caused by climate change in recent years. Increase in air temperature and changes in precipitation patterns due to climate change are affecting hydrologic cycles, such as evaporation and soil moisture. Thus, these phenomena result in increased runoff at the watershed. The Soil and Water Assessment Tool (SWAT) model has been used to evaluate rainfall-runoff at the watershed reflecting effects on hydrology of various weather data such as rainfall, temperature, humidity, solar radiation, wind speed. For bias-correction of RCP data, at least 30 year data are needed. However, for most gaging stations, only precipitation data have been recorded and very little stations have recorded other weather data. In addition, the RCP scenario does not provide all weather data for the SWAT model. In this study, two scenarios were made to evaluate whether it would be possible to estimate streamflow using measured precipitation and long-term average values of other weather data required for running the SWAT. With measured long-term weather data (scenario 1) and with long-term average values of weather data except precipitation (scenario 2), the estimate streamflow values were almost the same with NSE value of 0.99. Increase/decrease by ${\pm}2%$, ${\pm}4%$ in temperature and humidity data did not affect streamflow. Thus, the RCP precipitation data for Hongcheon watershed were bias-corrected with measured long-term precipitation data to evaluate effects of climate change on streamflow. The results revealed that estimated streamflow for 2055s was the greatest among data for 2025s, 2055s, and 2085s. However, estimated streamflow for 2085s decreased by 9%. In addition, streamflow for Spring would be expected to increase compared with current data and streamflow for Summer will be decreased with RCP data. The results obtained in this study indicate that the streamflow could be estimated with long-term precipitation data only and effects of climate change could be evaluated using precipitation data as shown in this study.

• Water Engineering Research
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• v.1 no.3
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• pp.233-242
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• 2000

A system for regularly appraising the reliability of streamflow data, KORSAS (KOwaco's Regular Streamflow Appraising System) was developed on PC based Windows for hydrological specialists and engineers working in the Korea Water Resources Corporation (KOWACO). The reliability of streamflow rates can be evaluated with KORSAS in various as pects according to the evaluation duration and method. The former being selected as short term (event based) or long term(continus based), and the latter being classified into comparison methods of flow measurement, other stations results, and simulation. Rainfall-runoff models can be used together with KORSAS in order to evaluate the reliability of observed flow data by comparing with simulated flow data. The objective of this study is to develop a systematic methodology in various aspects to evaluate the reliability of streamflow data regularly.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.967-974
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• 2011

Based on daily time series from RDAPS numerical weather forecast, Streamflow prediction was simulated and the result of ESP analysis was implemented considering quantitative mid- and long-term forecast to compare the results and review applicability. The result of ESP, ESP considering quantitative weather forecast, and flow forecast from RDAPS numerical weather forecast were compared and analyzed with average observed streamflow in Guem River Basin. Through this process, the improvement effect per method was estimated. The result of ESP considering weather information was satisfactory relatively based on long-term flow forecast simulation result. Discrepancy ratio analysis for estimating accuracy of probability forecast had similar result. It is expected to simulate more accurate flow forecast for RDAPS numerical weather forecast with improved daily scenario including time resolution, which is able to accumulate 3 hours rainfall or continuous simulation estimation.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.19-27
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• 2017

Recently, the hydrological model Soil Water Assessment Tool (SWAT) has been applied in many watersheds in South Korea. This study estimated parameters in SWAT for calibrating streamflow in long-term drought periods. Therefore, we focused on the continuous severe drought periods 2014~2015, and understand the model calibrated parameters. The SWAT was applied to a $366.5km^2$ Gongdo watershed by using 14 years (2002~2015) daily observed streamflow (Q) including two years extreme drought period of 2014~2015. The 9 parameters of CN2, CANMX, ESCO, SOL_K, SLSOIL, LAT_TIME, GW_DELAY, GWQMN, ALPHA_BF were selected for model calibration. The SWAT result by focusing on 5 normal years (2002~2006) calibration showed the 14 years average Nash-Sutcliffe model efficiency (NSE) for Q and 1/Q with 0.78 and 0.58 respectively. On the other hand, the 14 years average NSEs of Q and 1/Q by focusing on 2 drought years (2014~2015) calibration were 0.86 and 0.76 respectively. Thus, we could infer that the SWAT calibration trial by focusing on drought periods data can be a good approach to calibrate both high flow and low flow by controlling the 9 drought affected parameters.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.629-642
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• 2021

Land-use change has an important role in the hydrologic characteristics of watersheds because it alters various hydrologic components such as interception, infiltration, and evapotranspiration. For example, rapid urbanization in a watershed reduces infiltration rates and increases peak flow which lead to changes in the hydrologic responses. In this study, a physical hydrologic model the soil and water assessment tool (SWAT) was used to assess long-term continuous daily streamflow corresponding to land-use changes that occurred in the Naesungchun river watershed. For a 30-year model simulation, 3 different land-use maps of the 1990s, 2000s, and 2010s were used to identify the impacts of the land-use changes. Using SWAT-CUP (calibration and uncertainty program), an automated parameter calibration tool, 23 parameters were selected, optimized and compared with the daily streamflow data observed at the upstream, midstream and downstream locations of the watershed. The statistical indexes used for the model calibration and validation show that the model performance is improved at the downstream location of the Naesungchun river. The simulated streamflow in the mainstream considering land-use change increases up to -2 - 30 cm compared with the results simulated with the single land-use map. However, the difference was not significant in the tributaries with or without the impact of land-use change.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.245-250
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• 2001

• Journal of Wetlands Research
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• v.10 no.1
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• pp.1-9
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• 2008

This study describes the WASMOD, water balance model which can consider the snowmelting. The pilot study basin is the Soyang River basin with outlet at Soyang Dam Site and compute long-term monthly streamflow, The advantage of the WASMOD is that the input data is simple and the user can operate easily. To optimize for the parameters of the model, the WASMOD used VA05A of automatic fitting technique. The observed and simulated monthly streamflow hydrographs were compared. The model performance on corrleation coefficient between the observed and the simulated streamflow for the verification periods was above 0.89. It was shown that the WASMOD reproduces the observed monthly streamflow hydrographs very well. This evidence suggests that the WASMOD might be appropriate for the simulation of monthly streamflow

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.60-67
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• 2014

In this study, four methods for calculation of continuous daily flow was suggested using short-term or partial recording station of streamflow including missing data. Using these methods, standard flows at the outlet of unit/small basins for the management of total maximum daily loads (TMDLs) in Namgang dam basin were estimated from full-period flow duration curve (FDC). Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and maintenance of variance extension types 1 and 2 (MOVE.1, MOVE.2). In these methods, the continuous daily flow was calculated using extension equation based on correlation analysis, after conducting the correlation analysis between historic record of streamflow and long-term recording station (a base station). Finally the best optimal method was selected as the MOVE.2, and the standard flows in the abundant, ordinary, low and drought flow estimated from FDC was evaluated using MOVE.2 in unit/small basins.