• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.131-140
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• 2022

The magnitude and frequency of extreme floods are increasing owing to the effects of climate change. Therefore, multipurpose flood management techniques incorporating nature-based solutions have been introduced to mitigate the limitations of flood management and river design methods relying on existing observation data. Nature-based solutions to prepare for such extreme flooding events include ways to retreat the embankment, expand the floodplain, and reduce flood damage. To apply these technologies, adopting appropriate location selection methods based on various evaluation factors, such as flood damage reduction effects, sustainable ecological environments, river connectivity, and physical channel structure enhancements, should be prioritized. Therefore, in this study, the optimal location for implementing the multipurpose floodplain construction project was determined by selecting the location of the floodplain expansion with objectivity in the river waterfront area upstream of Daecheong Dam to downstream of Yongdam Dam. Through the final location determination, the Dongdaeje and Jeogokje sections were included in the optimal location considering both flood damage reduction and water environment improvement.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.999-1009
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• 2022

The Chuncheon Mullori area is an underprivileged area for water welfare that does not have a local water supply system. Here, water is supplied to the village by using a small-scale water supply facility that uses underground water and underground water as the source. To solve the problem of water shortage during drought and to prepare for the increasing water demand, a sand dam was installed near the valley river, and this facility has been operating since May 2022. In this study, in order to evaluate the reliability of water supply when a sand dam is assumed during a drought in the past, groundwater runoff simulation results using MODFLOW were used to generate inflow data from 2011 to 2020, an unmeasured period. After performing SWAT-K basin hydrologic modeling for the watershed upstream of the existing water intake source and the sand dam, the groundwater runoff was calculated, and the relative ratio of the monthly groundwater runoff for the previous 10 years to the monthly groundwater runoff in 2021 was obtained. By applying this ratio to the 2021 inflow time series data, historical inflow data from 2011 to 2020 were generated. As a result of analyzing the availability of water supply during extreme drought in the past for three cases of demand 20 m³/day, 50 m³/day, and 100 m³/day, it can be confirmed that the reliability of water supply increases with the installation of sand dams. In the case of 100 m³/day, it was analyzed that the reliability exceeded 90% only when the existing water intake source and the sand dam were operated in conjunction. All three operating conditions were evaluated to satisfy 50 m³/day or more of demand based on 95% reliability of water supply and 30 m³/day or more of demand based on 99% of reliability.

• Journal of Korea Water Resources Association
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• v.47 no.7
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• pp.599-614
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• 2014

In this study, two dimensional finite volume model was parallelized to improve computing time, which has been developed to be able to apply for the mixed meshes of triangle and quadrilateral. MPI scheme which is free from limitation of the number of cores was applied, and non-blocking point-to-point communication was used for fluxes and time steps calculation domain. The developed model is applied to analyze dam break in a L-shaped experimental channel with $90^{\circ}$ bend and Malpasset dam breach event to calibrate the consistency between parallelized model and existing model and examine the speed-up and efficiency of computing time. Computational speed-up about the size of the input data was considered by simulating 4 cases classified by the number of meshes, Consequently, the simulation results reached a satisfactory accuracy compared to measured data and the results from existing model, and achieved more than 3 times benefit of computational speed-up against computing time of existing model. Simulation results of 3 cases classified by the size of input data lead us to the conclusion that it is important to use proper size of input data and the number of process in order to minimize the communication overhead.

• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.155-169
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• 2013

This study proposes proper forms of empirical formulas for the concentration time and storage coefficient based on their theoretical backgrounds and evaluates several existing empirical formulas by comparing them with the formula proposed in this study. Additionally, empirical formulas for the concentration time and storage coefficient of the Chungju Dam basin were derived using the forms proposed by considering their theoretical backgrounds, and compared with exiting empirical formulas. The results derived are summarized as follows. (1) The concentration time of a basin is proportional to the square of the main channel length, but inversely proportional to the channel slope, as the flood flow is generally turbulent. (2) The storage coefficient is proportional to the concentration time. (3) The comparison results with existing empirical formulas for the concentration time indicates that the empirical formulas like the Kirpich, Kraven (I), Kraven (II), California DoT, Kerby, SCS, and Morgali & Linsley are in line with the form proposed in this study. Among existing empirical formulas for the storage coefficient, the Clak, Russell, Sabol and Jung are found to be well matched to this study. (4) The application results to Chungju Dam basin indicates that among empirical formulas for the concentration time, the Jung, Yoon, Kraven (I), and Kraven (II) show relatively similar results to the observed in this study, but the Rziha shows abnormal results. Among the empirical formulas for the storage coefficient, the Yoon and Hong, Jung, Lee, and Yoon show somewhat reasonable results, but the Sabol shows abnormal results. In conclusion, the empirical formulas for the concentration time and storage coefficient developed in Korea are found to reflect the basin characteristics of Korea better.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.1-11
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• 2018

Probable Maximum Flood (PMF) is mostly applied for the designs of large-scale hydraulic structures and it is estimated by computing the runoff hydrograph where Probable Maximum Precipitation (PMP) is inserted as design rainfall. The existing PMP is estimated by transferring the heavy rainfall from all watersheds of korea to the design watershed, however, in this study, PMP was analyzed by selecting only rainfall events occurred in the design watershed. And then, Catchment-scale Soil Erosion Model (CSEM) was used to estimate the PMF and sediment-runoff yield according to the watershed-based estimated PMP. Although the PMF estimated in this study was lower than the existing estimated PMF in the Yongdam-dam basin, it was estimated to be higher than the 200-year frequency design flood discharge. In addition, sediment-runoff yield was estimated with a 0.05 cm of the maximum erosion and a 0.06 cm of the maximum deposition, and a total sediment-runoff yield of 168,391 tons according to 24-hour PMP duration.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.143-152
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• 2003

This paper suggests the improvement of the Sumjinkang for the estimation of areal averages of heavy rainfall events based on the optimal network and three existing networks. The problem consists of minimizing an objective function which includes both the accuracy of the areal mean estimation as expressed by the Kriging variance and the economic cost of the data collection. The wellknown geostatistical variance-reduction method is used in combination with SATS which is an algorithm of minimization. At the first stage, two kinds of optimal solutions are obtained by two trade-off coefficients. One of them is a optimal solution, the other is an alternative. At the second stage, a quasi optimal network and a quasi alternative are suggested so that the existing raingages near to the selected optimal raingages are included in the two solutions instead of gages of new gages.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.301-316
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• 2012

Two models, TANK and SWAT (Soil and Water Assessment Tool) were compared for simulating natural flows in the Paldang Dam upstream areas of the Han River basin in order to understand the limitations of TANK and to review the applicability and capability of SWAT. For comparison, simulation results from the previous research work were used. In the results for the calibrated watersheds (Chungju Dam and Soyanggang Dam), two models provided promising results for forecasting of daily flows with the Nash-Sutcliffe model efficiency of around 0.8. TANK simulated observations during some peak flood seasons better than SWAT, while it showed poor results during dry seasons, especially its simulations did not fall down under a certain value. It can be explained that TANK was calibrated for relatively larger flows than smaller ones. SWAT results showed a relatively good agreement with observed flows except some flood flows, and simulated inflows at the Paldang Dam considering discharges from upper dams coincided with observations with the model efficiency of around 0.9. This accounts for SWAT applicability with higher accuracy in predicting natural flows without dam operation or artificial water uses, and in assessing flow variations before and after dam development. Also, two model results were compared for other watersheds such as Pyeongchang-A, Dalcheon-B, Seomgang-B, Inbuk-A, Hangang-D, and Hongcheon-A to which calibrated TANK parameters were applied. The results were similar to the case of calibrated watersheds, that TANK simulated poor smaller flows except some flood flows and had same problem of keeping on over a certain value in dry seasons. This indicates that TANK application may have fatal uncertainties in estimating low flows used as an important index in water resources planning and management. Therefore, in order to reflect actually complex and complicated physical characteristics of Korean watersheds, and to manage efficiently water resources according to the land use and water use changes with urbanization or climate change in the future, it is necessary to utilize a physically based watershed model like SWAT rather than an existing conceptual lumped model like TANK.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.165-169
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• 2009

The effect of the Dirichlet boundary condition for the redistance equation of level set method on the solutionof sloshing problem is investigated by adopting four Dirichlet boundary conditions. For the solution of the incompressible Navier-Stokes equations, P1P1 four-step fractional finite element method is employed and a least-square finite element method is used for the solutions of the two hyperbolic type equations of level set method; advection and redistance equation. ALE (Arbitrary Lagrangian Eulerian) method is used to deal with a moving computational domain. It has been shown that the free surface motion in a sloshing tank is strongly dependent on the type of the Dirichlet boundary condition and the results of broken dam and sloshing problems using various Dirichlet boundary conditions are discussed and compared with the existing experimental results.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.994-996
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• 2003

GRAM++ is a collection of software packages for geographic information system (GIS) applications, developed indigenously at the Centre of Studies in Resources Engineering (CSRE), Indian Institute of Technology (IIT), Bombay. This software is now being used for a number of GIS applications that assist decision makers in taking informed decisions. Some of these applications include simulation of the spatial impact of raising height of dam and assessment of the costs and benefits; identifying sites suitable for inland aquaculture and validation with existing sites; developing resource profiles and computation of human development indices for prioritized development; land suitability analysis for agriculture applications.