• Korean Journal of Hydrosciences
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• v.10
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• pp.73-83
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• 1999

The intake towers of Buyeo W.T.P. in Keum river have being suffered from the sedimentation problems since the beginning of the operation. Impellers of the intake pumps have to the frequently changed due to the serious surface erosion. Thousands tons of sands are entrapped in the intake towers and equalization chambers of W.T.P. every year. Site surveying and numerical analysis were carried out to suggest an appropriate solution by understanding the general sedimentation regime of Keum river and causes of the sedimentation in the intake towers. Origin of the sediment could be found by the desk and site inspections. The validity of the used numerical models was examined by comparisons between the calculated bydraulic values and the measured ones during the specific periods. The design flow rate for the prediction of the future sedimentation regime of the rever was studied. The efficiency of the sediment control measures was also examined with the verified numerical models. Finally, it was found that the best solution could be a combination of three sediment control measures; increase the clearance between river bed and inlet, construct jetties at 2 kilometers upstream from the intake towers, and put vanes at the right side of the intake towers.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.37 no.4
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• pp.323-329
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• 2004

In situ particle size and volume concentration of suspended sediment was measured at the mouth of Seomjin River Estuary In February 2001, using an optical instrument, 'LISST-100'. Time variation of in situ particle size and concentration shows: (1) during ebb tide, Seomjin River supplies relatively fine-grained particles with less-fluctuated, compared to during flood tide, and well-behaved concentrations following the tidal cycle; and (2) during flood tide, relatively coarse-grained particles with highly variable in size distribution and concentration flow upstream from Kwangyang Bay. This explains a poor correlation $(r^{2}=0.10)$ between sediment concentration and beam attenuation coefficient during flood and a high degree of correlation $(r^{2}=0.80)$ during ebb tide. Relatively fine grained and well defined, monotonous size distribution may promote the correlation between concentration and beam attenuation coefficient due to optical homogeneity of particles during ebb tide. Abundance of large aggregates with time-varying size and shape distributions may be mainly responsible for variations in optical properties of the sediment during flood tide, and thus may confound the relationship between the two variables. The difference in particle sizes and shapes between flood and ebb tides can also be observed on SEM images.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Journal of Environmental Impact Assessment
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• v.17 no.6
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• pp.373-380
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• 2008

The Ministry of Environment plans to improve quality of water which is achieved over 85% in rivers and 94% in lakes of the whole country as "Good Water" until 2015. Also, the law of evaluation of water quality and water quality goal were made newly. So, the water quality has evaluated by using new law since 2007. This study evaluated whether "Good Water" and" Water Quality Goal" were achieved or not in 22 middle-sized districts and major 10 lakes of Geum river. The achievement rates of rivers decreased and the achievement rates of lakes mostly were the same for 5 years. In 2007, the achievement rates of "Good Water" were 50% in rivers and 50% in lakes. The achievement rate of "Water Quality Goal" were 59.1% in rivers and 20% in lakes. The water quality in 2007 was evaluated worse than last year in case of rivers. The evaluations of Korea-Comprehensive Water Quality Index(K-CWQI) showed that achievement rates of "Water Quality Goal" were 81.8% in rivers and 0% in lakes. The statistical correlation analysis showed that correlations between BOD and COD were meaningful at the downstream, compared to upstream, generally. In case of lakes, correlations between COD and temperature were meaningful. Also, correlations between COD and Chl-a were meaningful. The Trophic State Index ($TSI_{KO}$) showed that the half of lakes are major over eutrophic status in lakes. These analytical methods such as K-CWQI, $TSI_{KO}$, statistical correlation analysis could be additionally helpful for evaluation of water quality and provide basis data for understanding characteristics of watershed in Geum river.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.542-550
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• 2017

The estimations of flow characteristics and river-bed erosion or sedimentation are very important for hydraulic structure design, floodplain management, and especially, river management. The objective of the study is therefore to estimate the change of flow characteristics and river-bed change due to a hydraulic structure construction. With 11.65 km study area of the Geum River which are located in downstream of Daecheong Dam, flow characteristics and river-bed change were estimated based on the RMA2 and SED2D model. As the result of the study, the increase of river-bed sedimentation in upstream and river-bed erosion in downstream were occurred by the construction of hydraulic structure.

• Journal of Wetlands Research
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• v.16 no.4
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• pp.389-402
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• 2014

In this study, simulation technique with multi-dimensional model(EFDC), coupled with COSFIM and FLDWAV, has been applied to the upstream and downstream of weirs for hydraulic characteristics analysis through development of system and was performed for 8 multi-function weirs on Nakdong river using developed system. COSFIM, FLDWAV and EFDC can utilize suitable model in situation because they have pros and cons according to practical use purpose. Developed technique can offers spatial and grid unit information as well as line and section unit information from 1-D modeling. It is considered that the coupling simulation technique can provide useful hydraulic information for river management and treatment.

• Journal of Korea Water Resources Association
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• v.52 no.spc2
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• pp.875-885
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• 2019

The expansion of riparian vegetation in middle size rivers in Korea had been analyzed in this study. Seom River with dam, Cheongmi River without dam, and Naesung River with no operating dam in the upstream was investigated for the 1 km to identify the expansion of riparian vegetation through the aerial photograph analysis. As a results, we found that the rate of vegetation area is 54.7% in Seom River, 77.5% in Cheongmi River, and 49.7% in Naesung River. The vegetation area had been increased in 3 rivers, and the expansion rate since 2010 is very high nearly up to 2 times (17 times in Naesung River). Sandbar and open-water area, however, have been decreased in the same rate with the riparian vegetation expansion. It could be concluded that vegetation increase trend is clear in rivers regardless of location and dam existence. Further researches are necessary to find out the causes to establish the countermeasures because the increase of vegetation will change the physical system as well as biological system of river.

• Ecology and Resilient Infrastructure
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• v.6 no.1
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• pp.12-22
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• 2019

This study investigated the spatial and temporal water circulation characteristics of Paldang Reservoir by continuous hydraulic and water temperature survey. Due to differences in water temperature and discharge pattern of Ipo Weir and Cheongpyeong Dam, the flow and temperature fluctuations were different in sections of Namhan River and Bukhan River in Paldang Reservoir. At the stratification period, the water temperature of the discharge of Ipo Weir was higher than that of the Cheongpyeong Dam. Therefore, in the surface layer of the downstream of Bukhan River, relatively high temperature water is located and back water phenomenon occurred, and convergence zone is formed. In the downstream section of Namhan River, low-temperature water was distributed in the middle and lower layers, and the upstream flow appeared to be difficult to mix with the surface layer.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.131-131
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• 2021

Deep learning models, especially those based on long short-term memory (LSTM), have presented their superiority in addressing time series data issues recently. This study aims to comprehensively evaluate the performance of deep learning models that belong to the supervised learning category in streamflow prediction. Therefore, six deep learning models-standard LSTM, standard gated recurrent unit (GRU), stacked LSTM, bidirectional LSTM (BiLSTM), feed-forward neural network (FFNN), and convolutional neural network (CNN) models-were of interest in this study. The Red River system, one of the largest river basins in Vietnam, was adopted as a case study. In addition, deep learning models were designed to forecast flowrate for one- and two-day ahead at Son Tay hydrological station on the Red River using a series of observed flowrate data at seven hydrological stations on three major river branches of the Red River system-Thao River, Da River, and Lo River-as the input data for training, validation, and testing. The comparison results have indicated that the four LSTM-based models exhibit significantly better performance and maintain stability than the FFNN and CNN models. Moreover, LSTM-based models may reach impressive predictions even in the presence of upstream reservoirs and dams. In the case of the stacked LSTM and BiLSTM models, the complexity of these models is not accompanied by performance improvement because their respective performance is not higher than the two standard models (LSTM and GRU). As a result, we realized that in the context of hydrological forecasting problems, simple architectural models such as LSTM and GRU (with one hidden layer) are sufficient to produce highly reliable forecasts while minimizing computation time because of the sequential data nature.

• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.486-494
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• 2011

River bed change due to various factors in watershed and/or river environment would one of the most important issues in river management. To judge whether the river bed was aggrading or degrading, normally we use the change in thalweg or average bed, calculated using the design flood of the river. The present study is to figure out the problems of the existing methods and to propose a new concept of average river bed using annual maximum flood. To evaluate the new method, it was applied to the Nakdong River. We use the river bed data surveyed in 1983, 1993, and 2005. The results showed that there were no significant river bed change during 1983 and 1993, while the river bed was degraded significantly during 1993 and 2005. In the latter period, the river had severe degradations, 2~3 m in average sense and 5 m for the maximum in the middle reach(120~200 km from river mouth), and 1~2 m in average in the upper reach(200~240 km from river mouth). For the upstream reach of the confluence of the Naesung River(about 240 km from river mouth), most of the river bed change seemed to be only local phenomena. The main cause of the river bed change in the Nakdong River seems to be massive gravel mining in the middle reach of the river.