• Journal of Environmental Science International
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• v.9 no.6
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Korean Journal of Environmental Biology
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• v.24 no.2 s.62
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• pp.160-165
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• 2006

The purpose of this study was to ascertain the prey composition and utilization of the Eurasian otter, Lutra lutra, in the ecosystem conservation region of the Seomjin River. The study was conducted for a 12-month period from March 2003 to February 2004 by spraints analysis and an investigation using artificial holts. We found seasonal variation in the number of spraints and composition of prey items. Fish were the main prey items throughout the period (82%), and other prey items included birds (14%), amphibians (2%) and arthropods (1%). In addition to prey identification, we investigated habitat utilization by otters through spraints distribution. The traces of otters were discovered in five of the six total artificial holts. However, the utilization of the artificial holts in the study area seemed to be limited as evidenced by the low frequency of traces in the holts.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.1023-1036
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• 2015

A reliable streamflow forecasting is essential for flood disaster prevention, reservoir operation, water supply and water resources management. This study proposes a hybrid model for river stage forecasting and investigates its accuracy. The proposed model is the wavelet packet-based artificial neural network(WPANN). Wavelet packet transform(WPT) module in WPANN model is employed to decompose an input time series into approximation and detail components. The decomposed time series are then used as inputs of artificial neural network(ANN) module in WPANN model. Based on model performance indexes, WPANN models are found to produce better efficiency than ANN model. WPANN-sym10 model yields the best performance among all other models. It is found that WPT improves the accuracy of ANN model. The results obtained from this study indicate that the conjunction of WPT and ANN can improve the efficiency of ANN model and can be a potential tool for forecasting river stage more accurately.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.185-185
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• 2011

Mapping of artificial levee lines, one of major tasks in river zone mapping, is critical to prevention of river flood, protection of environments and eco systems in river zones. Thus, mapping of artificial levee lines is essential for management and development of river zones. Coastal mapping including river zone mapping has been historically carried out using surveying technologies. Photogrammetry, one of the surveying technologies, is recently used technology for national river zone mapping in Korea. Airborne laser scanning has been used in most advanced countries for coastal mapping due to its ability to penetrate shallow water and its high vertical accuracy. Due to these advantages, use of LiDAR data in coastal mapping is efficient for monitoring and predicting significant topographic change in river zones. This paper introduces a method for construction of a 3D artificial levee line using a set of LiDAR points that uses normal vectors. Multiple steps are involved in this method. First, a 2.5-dimensional Delaunay triangle mesh is generated based on three nearest-neighbor points in the LiDAR data. Second, a median filtering is applied to minimize noise. Third, edge selection algorithms are applied to extract break edges from a Delaunay triangle mesh using two normal vectors. In this research, two methods for edge selection algorithms using hypothesis testing are used to extract break edges. Fourth, intersection edges which are extracted using both methods at the same range are selected as the intersection edge group. Fifth, among intersection edge group, some linear feature edges which are not suitable to compose a levee line are removed as much as possible considering vertical distance, slope and connectivity of an edge. Sixth, with all line segments which are suitable to constitute a levee line, one river levee line segment is connected to another river levee line segment with the end points of both river levee line segments located nearest horizontally and vertically to each other. After linkage of all the river levee line segments, the initial river levee line is generated. Since the initial river levee line consists of the LiDAR points, the pattern of the initial river levee line is being zigzag along the river levee. Thus, for the last step, a algorithm for smoothing the initial river levee line is applied to fit the initial river levee line into the reference line, and the final 3D river levee line is constructed. After the algorithm is completed, the proposed algorithm is applied to construct the 3D river levee line in Zng-San levee nearby Ham-Ahn Bo in Nak-Dong river. Statistical results show that the constructed river levee line generated using a proposed method has high accuracy in comparison to the ground truth. This paper shows that use of LiDAR data for construction of the 3D river levee line for river zone mapping is useful and efficient; and, as a result, it can be replaced with ground surveying method for construction of the 3D river levee line.

• Water Engineering Research
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• v.6 no.1
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• pp.17-30
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• 2005

The bed evolution of the stretch of the River Rhine between km-812.5 and km-821.5 is characterised by general bed degradation as a result of the river training works and dredging activities of the last two centuries. The degradation of the river bed affects the water levels, and so the navigation conditions. To combat the erosion of the river bed with the aim to keep up the shipping traffic and to avoid the ecological system damages due to water level reductions, sand-gravel-mixtures were added to the river (so called artificial grain feeding activities). This paper presents the results of an application of a graded sediment transport model in order to study morpholodynamical characteristics due to artificial grain feeding activities in the river stretch. The finite element code TELEMAC2D was used for flow calculation by solving the 2D shallow water equation on non-structured grids. The sediment transport module SISYPHE has been developed for graded sediment transport using a multiple layer model. The needs to apply such graded sediment transport approaches to study morphological processes in the domain are discussed. The calculations have been carried out for the case of middle water flow and different size-fraction distributions. The results show that the grain feeding process could be well simulated by the model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.3
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• pp.83-97
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• 2009

The objects of study is to propose criteria for physical river disturbance assessment and as case study to show the application results for river improvement. For this purpose, the river disturbance assessment method for past disturbance process and the present-day potential natural state of stream is proposed. To assess the disturbance of the Youngcheon River caused by river improvement, One ares of Nam River was selected for the reference reach and two areas of Youngcheon River were selected for the comparison reach. And these reaches were surveyed and analyzed according to applying criteria of the river disturbances assessment. The assessment indices were physical factors as like epifaunal (bottom), embededness, velocity/depth regime, sediment deposition, channel flow status, channel alteration, frequency of riffles, bank stability, vegetative protection and riparian zone etc. The results showed that physical river environment in Youngcheon River area was disturbed by artificial revetment and bed excavation, consequently this disturbance give rise to impact of ecosystem in river. Hereafter, the criteria for river disturbance assessment are needed to consider various river characters as bed materials and bed slop etc.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.3
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• pp.14-24
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• 2007

The purpose of this study was to investigate how the landscape characteristics and the physical factors of landscape would affect the preference for the Gapcheon in Daejeon Metropolitan City. The Gapcheon was divided in three sections of the outskirts, Expopark areas, and residential complexes. After selecting seven landscape points where the sections could be expressed best, photographs were taken both in the upstream and downstream direction. The questionnaire used to evaluate the river's landscape included 20 items of adverbs that described the form of the river and one item to rate the overall preference. By analyzing the 14 pictures taken, the occupancy rates of the landscape elements in terms of the sky, river, vegetation of the river, mountain, and artificial structures. Image factor analysis was conducted for each of the sections in order to analyze the landscape characteristics of the Gapcheon, and then regression analysis was conducted in order to analyze the relationships among the physical factors influencing the preference of the landscapes. The results were as follows : Factors that compose the visual characters of urban river were classified be the aesthetic factor, the emotional factor and the situation factor. These 3 factors showed a 65.8% total variance. The river landscape with the biggest preference was the one from the Daedeok Grand Bridge as the occupancy area of the mountain, sky, and river was large and distributed evenly and the vegetation of the river was in a good harmony with the surroundings. After carrying out regression analysis to examine the relationships between the visual preference of Gapcheon and the physical factors of landscape(the sky, river, vegetation of the river, mountain, and artificial structure), the following regressions model was made : PRE=5.906+0.017(river)-0.053(artificial structure)-0.060(vegetation of the river) (R-square=0.48).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.198-203
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• 2020

In this paper, we propose an artificial water level prediction system for small river flood prediction. River level prediction can be a measure to reduce flood damage. However, it is difficult to build a flood model in river because of the inherent nature of the river or rainfall that affects river flooding. In general, the downstream water level is affected by the water level at adjacent upstream. Therefore, in this study, we constructed an artificial intelligence model using Recurrent Neural Network(LSTM) that predicts the water level of downstream with the water level of two upstream points. The proposed artificial intelligence system designed a water level meter and built a server using Nodejs. The proposed neural network hardware system can predict the water level every 6 hours in the real river.

• Journal of Environmental Science International
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• v.7 no.5
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• pp.591-598
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• 1998

This study was conducted to evaluate water quality in the Keum River estuary using principal component analysis. The results was summarized as follow; Water quality in the Keum River estuary could be explained up to 70.40% by three factors which were included in the inffluent loading by the Keum River and Kyungpo cheon(38.99%), seasonal variation and organic matter pollution(19.05%), sediment resuspension and internal metabolism(12.35%). For spatial variation of factor score, artificial pollutant loading is highest at st.1, below Keum River barrage, and decreases toward the outer sea. For annual variation of factor score, factor 1 was highly related to artificial pollutant leading, and it was gently increased in 1994. Also, organic matter pollution, sediment resuspension and internal metabolism were increased to every year. It is necessary to control the nutrient leading by Keum river and Kyongpo cheon for Water quality management of estuary.

• Journal of Korean Society on Water Environment
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• v.23 no.3
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• pp.339-347
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• 2007

Zooplankton community dynamics were studied after establishment of an artificial vegetation island (AVI) in Lake Paldang, from April 2005 to November 2006. There were distinct seasonal and inter-annual changes of total zooplankton abundance at the survey site. Total zooplankton abundance rapidly increased in spring and fall, while it remained low throughout winter. During summer, the dynamics of zooplankton community seemed to be largely affected by hydrological parameters such as, precipitation and inflow. Total zooplankton abundance and biomass below AVI was much higher than that of pelagic zone (L1) in Lake Paldang. Copepoda and cladocera represented the main bulk of the zooplankton community from summer to fall at the both sites. Copepods were more dominant at AVI area, while cladocera were more dominant at pelagic zone (L1). Water quality, prey and habitat condition, species competition between zooplankton seemed to play important roles in dominance of the copepoda and cladocera in zooplankton community at AVI area. Our results conclude that artificial vegetation island provide the stable habitat and besides phytoplankton, diverse food to zooplankton, and consequently influence the diversity and richness of zooplankton community.