• New & Renewable Energy
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• v.5 no.4
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• pp.39-43
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• 2009

The variation of inflow at stream and hydrologic performance for small scale hydro power(SSHP) plants due to climate change have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for SSHP plants is established. Monthly inflow data measured at Andong dam for 32 years were analyzed. The existing SSHP plant located in upstream of Andong dam was selected and analyzed hydrologic performance characteristics. The predicted results from the developed models show that the data were in good agreement with measured results of long term inflow at Andong dam and the existing SSHP plant. Inflow and ideal hydro power potential had increased greatly in recent years, however, these did not lead annual energy production increment of existing SSHP plant. As a results, it was found that the models represented in this study can be used to predict the primary design specifications and inflow of SSHP plants effectively.

• KCID journal
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• v.8 no.2
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• pp.81-86
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• 2001

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.200-205
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• 2001

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.106-111
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• 2000

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.3
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• pp.52-63
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• 1997

A CELTHYM(CEll-based Long-Term HYdrologic Model), a pre-processor and a post processor that can be integrated with geographic information system ( GIS) were developed to predict the stream flow of the small watershed. The CELTHYM was calibrated and verified with measured runoff data at the WS # 1 and WS # 3 that are testing water sheds of Seoul Nat' 1 Univ., dept. of agricultural engineering, in Ansan city, Kyunggi province, South Korea. The results of tests are in good agreement with measured data and usable for other application, but the component of direct runoff and water balance on paddy fields need more study.

• Journal of Environmental Science International
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• v.27 no.2
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• pp.135-141
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• 2018

The specification of surface vegetation is essential for simulating actual evapotranspiration of water resources. The availability of land cover maps based on remotely collected data makes the specification of surface vegetation easier. The spatial resolution of hydrologic models rarely matches the spatial scales of the vegetation data needed, and remotely collected vegetation data often are upscaled up to conform to the hydrologic model scale. In this study, the effects of the grid scale of of surface vegetation on the results of actual evapotranspiration were examined. The results show that the coarser resolution causes larger error in relative terms and that a more realistic description of area-averaged vegetation nature and characteristics needs to be considered when calculating actual evapotranspiration.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1439-1442
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• 2010

Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.75-84
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• 2011

The objective of this study is to evaluate the hydrologic impacts of climate and land use changes in a rural small watershed. HadCM3 (Hadley Centre Coupled Model, ver.3) A2 scenario and LARS-WG (Long Ashton Research Station - Weather Generator) were used to generate future climatic data. Future land use data were also generated by the CA-Markov (Cellular Automata-Markov) method. The Soil and Water Assessment Tool (SWAT) model was used to evaluate hydrologic impacts. The SWAT model was calibrated and validated with stream flow measured at the Baran watershed in Korea. The SWAT model simulation results agreed well with observed values during the calibration and validation periods. In this study, hydrologic impacts were analyzed according to three scenarios: future climate change (Scenario I), future land use change (Scenario II), and both future climate and land use changes (Scenario III). For Scenario I, the comparison results between a 30-year baseline period (1997~2004) and a future 30-year period (2011~2040) indicated that the total runoff, surface runoff, lateral subsurface runoff, groundwater discharge, and evapotranspiration increased as precipitation and temperature for the future 30-year period increased. The monthly variation analysis results showed that the monthly runoff for all months except September increased compared to the baseline period. For Scenario II, both the total and surface runoff increased as the built-up area, including the impervious surface, increased, while the groundwater discharge and evapotranspiration decreased. The monthly variation analysis results indicated that the total runoff increased in the summer season, when the precipitation was concentrated. In Scenario III, the results showed a similar trend to that of Scenario II. The monthly runoff for all months except October increased compared to the baseline period.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.393-398
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• 2010

The variation of inflow at stream and hydrologic performance for small scale hydro power (SSHP) plants due to variation of inflow have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for SSHP plants is established. Monthly inflow data measured at Andong dam for 32 years were analyzed. The existing SSHP plant located in upstream of Andong dam was selected and analyzed hydrologic performance characteristics. The predicted results from the developed models in this study show that the data were in good agreement with measured results of long term inflow at Andong dam and the existing SSHP plant. Inflow and ideal hydro power potential had increased greatly in recent years, however, these did not lead annual energy production increment of existing SSHP plant. As a results, it was found that the models developed in this study can be used to predict the primary design specifications and inflow of SSHP plants effectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.309-319
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• 2023

Recently, the frequency and intensity of meteorological disasters have increased due to climate change. In South Korea, there are regional differences in vulnerability and response capability to cope with climate change because of regional climate characteristics. In particular, drought results from various factors and is linked to extensive meteorological, hydrological, and agricultural impacts. Therefore, in order to effectively cope with drought, it is necessary to use a composite drought index that can take into account various factors, and to evaluate future droughts comprehensively considering climate change. This study evaluated hydrologic risk(${\bar{R}}$) of future drought in the Nakdong River basin based on the Dynamic Naive Bayesian Classification (DNBC)-based composite drought index, which was calculated by applying Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), Evaporate Stress Index (ESI) and Water Supply Capacity Index (WSCI) to the DNBC. The indices used in the DNBC were calculated using observation data and climate scenario data. A bivariate frequency analysis was performed for the severity and duration of the composite drought. Then using the estimated bivariate return periods, hydrologic risks of drought were calculated for observation and future periods. The overall results indicated that there were the highest risks during the future period (2021-2040) (${\bar{R}}$=0.572), and Miryang River (#2021) had the highest risk (${\bar{R}}$=0.940) on average. The hydrologic risk of the Nakdong River basin will increase highly in the near future (2021-2040). During the far future (2041-2099), the hydrologic risk decreased in the northern basins, and increased in the southern basins.