• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.2
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• pp.73-82
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• 1989

When the flood occurs in the alluvial rivers, the rivers adjust to the flood by means of the mechanism of the river bed variations and its morphological changes to pass that safely, the numerical model was developed to simulate the process of the alluvial river bed variation due to flood wave and carried out by the flood routing for flood wave and the sediment routing for river bed variation. The flood wave, river bed variation, and bed material size distribution may be analysed and predicted by this model. The ability of this model to predict the process of river bed response was proved by the application to the reach from Paldang dam to Indogyo site. In view of the flood analysis considering the sediment process, the effects of river bed variation for the flood routing may be negligible because the river bed variation is smaller than the unsteady flow variation during the same period. By the application of this model, it is shown that, in occurring of sequential flood events, the variation of the river bed and bed material size distribution due to flood wave is more dependent on the first flood event than the latter flood events, and that the river bed variation in this reach of the downstream Han river is dependent on the degradation and the coarsening of bed materials.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.873-884
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• 2013

In Korea, the rainfall is concentrated in summer under the influence of monsoon climate. Thus, even a small climate change can be significant problems in water resources. As a result, a lot of attention has been focused on climate changes and a number of researches have been conducted in a manner commensurate with the attention to the climate change. This study is intended to forecast the changes in the flow and water quality of the Nam river resulting from the future climate changes in the Nam river basin using a watershed and water quality model. An SWAT model, as a watershed hydrologic model, was established after estimating a climate scenario using an artificial neural network method, and the established model was verified and adjusted using date from the Ministry of Environment to evaluate the applicability of the model. As a consequence, $R^2$ showed more than 0.7 in the simulation test, which satisfies the minimum required level. Results from the SWAT model and the future Namgang dam discharge calculated by HEC-ResSIM is used as input date for QUALKO. The results showed a huge variation in BOD depending on the annual flow of the river, which recorded a maximum difference of 2 mg/L between a rainy season and a dry season. It can be deduced that because rainfall and the runoff of a basin significantly account for the water quality of a river, higher water concentrations are recorded in a dry season in which the flow is not as much as that in a rainy season. It also can be said that water should be reserved in advance to secure water in the Nam river downstream for a dry season and be controlled in an effective and efficient manner to provide better water quality.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.363-376
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• 2011

1-D hydrodynamic numerical models have been most widely used in the field of flood analysis. The model's input data are upstream/downstream boundaries, roughness coefficients, cross-sections, and so on, and computational distance step and time step are the most important factors in order to guarantee the computational accuracy, stability, and efficiency. In this study, a theoretical explanation is presented for the basis of the previous empirical selection criteria of cross-section's location; also, the estimation technique of computationally variable distance step is proposed to reflect the properties of flow at every computational time step. Combining this technique with 1-D unsteady numerical model, it was applied to two events of Teton dam failure flood and the Han River flood. The numerical experimental results demonstrate that the accuracy and stability is increased when used more interpolated cross-sections and show that the proposed technique of computationally variable distance step has the same order of accuracy with smaller numbers of cross-section than previous empirical selection criteria. The practical use of this technique will be possible to analyze the river floods with high efficiency as well as accuracy and stability.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.201-210
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• 2017

This study proposes a numerical model which is able to simulate turbidity currents intruding into a reservoir and resulting sediment depositions. The proposed model is applied to laboratory experiments by Toniolo and Schultz (2005), and propagation of turbidity currents, morphological change, and trap of suspended sediment are simulated. It is simulated that the turbidity current after plunging at the foreset of the model delta, propagates along the bottom. The thickness of the turbidity current increases significantly after being blocked by the dam, and this effect is propagated in the upstream direction. In addition, it is simulated that the foreset moves in the downstream direction due to both the bedload and suspended load and the thickness of the bottom set increases due to the suspended load. It is found that the height of the intake affects the thickness of the turbidity current and the location of the internal hydraulic jump. The impact of the height of the intake on the trap efficiency is not clear in the experimental results, however, overall trap efficiency is predicted quite successfully by the model. Also, sensitivity analysis is carried out, and the results indicates that the particle size affects the trap efficiency most.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.12-26
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• 2017

The objective of this study was to develop a runoff analysis system of the Nakdong River watershed using the GRM (Grid-based Rainfall-runoff Model), a physically-based distributed rainfall-runoff model, and to assess the system run time performance according to Microsoft Azure VM (Virtual Machine) settings. Nakdong River watershed was divided into 20 sub-watersheds, and GRM model was constructed for each subwatershed. Runoff analysis of each watershed was calculated in separated CPU process that maintained the upstream and downstream topology. MoLIT (Ministry of Land, Infrastructure and Transport) real-time radar rainfall and dam discharge data were applied to the analysis. Runoff analysis system was run in Azure environment, and simulation results were displayed through web page. Based on this study, the Nakdong River real-time runoff analysis system, which consisted of a real-time data server, calculation node (Azure), and user PC, could be developed. The system performance was more dependent on the CPU than RAM. Disk I/O and calculation bottlenecks could be resolved by distributing disk I/O and calculation processes, respectively, and simulation runtime could thereby be decreased. The study results could be referenced to construct a large watershed runoff analysis system using a distributed model with high resolution spatial and hydrological data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.507-514
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• 2011

A numerical model has been developed by employing a finite element method to simulate the depth-averaged 2-D dispersion of the heat pollutant, which is an important pollutant material in natural streams. Among the finite element methods, the Streamline Upwind/Petrov Galerkin (SUPG) method was applied. Also both linear and quadratic elements can be applied so that irregular river boundaries can be easily represented. To show the movement of heat pollutants, the reaction term describing heat transfer was represented as an equation in which sink/source term is proportional to the difference between the equilibrium temperature and water surface temperature. The equation was expressed so that the water surface temperature changes according to the temperature transfer coefficient and the equilibrium temperature. For the calibration of the model developed, analytic and numerical results from a case of rectangular channel with full width continuous injection have been compared in a steady state. The comparisons showed that the numerical results were in good agreement with analytical solutions. The application site was selected from the downstream of Paldang dam to Jamsil submerged weir, and overall length of this site is about 22.5 km. The change of water temperature caused by the discharge from the Guri sewage treatment plant has been simulated, and results were similar to the observed data. Overall it is concluded that the developed model can represent the water temperature changes due to heat transport accurately. But the verification using observed data will further enhance the validity of the model.

• Journal of Korea Water Resources Association
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• v.45 no.2
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• pp.229-242
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• 2012

This study presents a physical habitat modeling of adult Zacco platypus in a reach of the Dalcheon Stream located downstream of the Goesaan Dam. CASiMiR model is used to estimate habitat suitability index based on the fuzzy logic. Results are compared with those from River2D model, which uses habitat preference curve for habitat suitability index. Hydraulic data simulated by River2D are used as input data for CASiMiR model after verification against field measurements. The result shows that the habitat suitability of the adult Zacco platypus is maximum around the riffle area located upstream of the bend. CASiMiR and River2D estimate the maximum weighted usable areas at the discharge rates of 7.23 $m^3/s$ and 9.0 $m^3/s$, respectively. Overall comparison of the two models employed in this study indicates that CASiMiR model overestimates the weighted usable area by 0.3~25.3% compared with River2D model in condition of drought flow (Q355), low flow (Q275), normal flow (Q185), and average-wet flow (Q95).

• Korean Journal of Ecology and Environment
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• v.35 no.1 s.97
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• pp.21-27
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• 2002

The frequent occurrence of excessive phytoplankton populations in the downstream Nakdong River has been an important water quality problem in recent years. The limnological survey of the Nakdong River was conducted from January 1997 to December 1999 on once or twice per month. A typical phenomenon of eutrophication appears with the persistent algal bloom due to high nutrients in the mid-lower part of the river. This study showed that the point at which Chl. a concentration reaches maximum was affected by the water temperature and the flow rate. For example, Chl. a concentration reached maximum after around 380, 240 and 120 hours which were estimated from the time of flow at low (${\le}10^{\circ}C$), mean ($10{\sim}20^{\circ}C$) and high (${\ge}20^{\circ}C$) water temperature conditions, respectively. It was estimated that increase coefficients of phytoplankton (Chl. a) on the water temperature are 0.201, 0.254 and $0.289\;day^{-1}$, on the contrary, decrease coefficients are -0.012, -0.128 and $-0.193\;day^{-1}$ in low, mean and high water temperature. Therefore, to prevent formation of Chl. a maximum concentration in the specific water resource, it is necessary to increase the discharge of dam as well as to decrease.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1207-1216
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• 2018

Discharge or water level predictions at tidally affected river reaches are currently still a great challenge in hydrological practices. This research aims to predict water level of the tide dominated site, Jamsu bridge in the Han River downstream. Physics-based hydrodynamic approaches are sometimes not applicable for water level prediction in such a tidal river due to uncertainty sources like rainfall forecasting data. In this study, TensorFlow deep learning framework was used to build a deep neural network based LSTM model and its applications. The LSTM model was trained based on 3 data sets having 10-min temporal resolution: Paldang dam release, Jamsu bridge water level, predicted tidal level for 6 years (2011~2016) and then predict the water level time series given the six lead times: 1, 3, 6, 9, 12, 24 hours. The optimal hyper-parameters of LSTM model were set up as follows: 6 hidden layers number, 0.01 learning rate, 3000 iterations. In addition, we changed the key parameter of LSTM model, sequence length, ranging from 1 to 6 hours to test its affect to prediction results. The LSTM model with the 1 hr sequence length led to the best performing prediction results for the all cases. In particular, it resulted in very accurate prediction: RMSE (0.065 cm) and NSE (0.99) for the 1 hr lead time prediction case. However, as the lead time became longer, the RMSE increased from 0.08 m (1 hr lead time) to 0.28 m (24 hrs lead time) and the NSE decreased from 0.99 (1 hr lead time) to 0.74 (24 hrs lead time), respectively.