• The Korean Journal of Ecology
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• v.23 no.2
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• pp.89-100
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• 2000

On community data. sampled in regular intervals on a long-term basis. artificial neural networks were implemented to extract information on characterizing patterns of community changes. The Adaptive Resonance Theory and Kohonen Network were both utilized in learning benthic macroinvertebrate communities in the Soktae Stream of the Suyong River collected monthly for three years. Initially, by regarding each monthly collection as a separate sample unit, communities were grouped into similar patterns after training with the networks. Subsequently, changes in communities in a sequence of samplings (e.g., two-month, four-month, etc.) were given as input to the networks. After training, it was possible to recognize new data set in line with the sampling procedure. Through the comparative study on benthic macroinvertebrates with these learning processes, patterns of community changes in chironomids diverged while those of the total benthic macro-invertebrates tended to be more stable.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.4
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• pp.91-98
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• 1997

At present, automated monitoring of water quality in Han river has been operated at each water treatment plant. But the automated measurement sites must be choosen newly because water source in Seoul move to the upper stream of Chamshil weir. In this study, automated monitoring sites in Han river were reviewed, and the proper sites for automated monitoring of water quality have been selected by Qual2E model, RMA model, water sampling guidline, Sanders' method and topograpical characteristics of Han river in order to resonable operate. 8 sites have been selected as follows: (1) the site of immediately after Paldang drainage (2) the left site and a right site of $Gu{\check{u}}i$ water intake (3) the left site and a right site at Noryangjin(Han river bridge) (4) the site between Shingok weir and Anyangchun confluence point(Hangju bridge) (5) the site of Chungryangchun downstream(existence) (6) the site of Tanchun downstream(existence) (7) the site of Anyangchun downstream(existence) (8) the site of Wangsukchun downstream. The results proposed resonable operating management of network and economical system built up.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.175-186
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• 2018

Due to global warming, various natural disasters such as floods and localized heavy rains are increasing. If a natural disaster can be detected and analyzed in advance and effectively, it can prevent enormous damage due to natural disasters. Recent development in visual sensor technologies has encouraged various studies on monitoring environments including rivers. In this paper, we propose a method to detect river regions from river images which can be exploited for river surveillance systems using video sensor networks. In the proposed method, we first analyze the color properties of the river region and the background region of a image and then propose a way to select the proper color channel and binarize the image to detect the river region. It is shown by experimental results that the proposed method is simple but detects river regions accurately.

• Journal of Environmental Impact Assessment
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• v.29 no.1
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• pp.61-77
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• 2020

In South Korea, major public waters have been systematic management under national level. Water environment network has been continuous monitoring for change of aquatic ecosystem, river and reservoir. In Water Quality Monitoring Networks, the data have been generally monitored Per eight days or month, while in Automatic Water Quality Monitoring Network the data have been monitored at daily intervals. Therefore, we were compared and analyzed water quality data between the networks using statistic method for same water quality item. Mann-kendall test results confirm that all points in Water Temperature (WT) and DO were not statistically significant. In particular, the result revealed that there is significant variation of TOC in the four different sites, TN in two different sites, TP in three different sites, WT in seven different sites, pH in two different sites between Water Quality Monitoring Network and Automatic Water Quality Monitoring Network. As a result firm LOWESS, TOC and pH clearly shows different trend. Among different sites, the water quality show the significantly positive correlations between at Sinam-Sangju2 and Namgang-Namgang4. Negative correlation significantly appeared in TP (ADD_Lower-AD1 site), TOC (DG-SG site), pH (GR-GR site), TP (JP-CN) and TN, TP, pH, EC, DO (GC-GC2-1 site).

• Journal of Environmental Science International
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• v.25 no.3
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• pp.361-371
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• 2016

Ministry of Environment has been operating water quality monitoring network in order to obtain the basic data for the water environment policies and comprehensively understand the water quality status of public water bodies such as rivers and lakes. The observed water quality data is very important to analyze by applying statistical methods because there are seasonal fluctuations. Typically, monthly water quality data has to analyze that the transition comprise a periodicity since the change has the periodicity according to the change of seasons. In this study, trends, SOM and RDA analysis were performed at the Mulgeum station using water quality data for temperature, BOD, COD, pH, SS, T-N, T-P, Chl-a and Colon-bacterium observed from 1989 to 2013 in the Nakdong River. As a result of trends, SOM and RDA, the Mulgeum station was found that the water quality is improved, but caution is required in order to ensure safe water supply because concentrations in water quality were higher in the early spring(1~3 month) the most.

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.152.3-153
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• 2000

No Abstract, See Full Text

• Journal of Korea Water Resources Association
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• v.54 no.1
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• pp.49-60
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• 2021

This study presents a methodology to estimate two distinct fractal dimensions of natural river basin by using fractal tree concept. To this end, an analysis is performed on fractal features of a complete drainage network which consists of all possible drainage paths within a river basin based on the growth process of fractal tree. The growth process of fractal tree would occur only within the limited drainage paths possessing stream flow features in a river basin. In the case of small river basin, the bifurcation process of network is more sensitive to the growth step of fractal tree than the meandering process of stream segment, so that various bifurcation structures could be generated in a single network. Therefore, fractal dimension of network structure for small river basin should be estimated in the form of a range not a single figure. Furthermore, the network structures with fractal tree from this study might be more useful information than stream networks from a topographic or digital map for analysis of drainage structure on small river basin.

• Water for future
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• v.28 no.1
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• pp.91-106
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• 1995

An investigation into the rainfall variability in time and space in the Nam River dam basin of Korea was made with use of the coefficient of variation and the correlation coefficient. The Nam River dam basin is a small mountainous watershed where the wind direction and orography are the dominant influences on the pattern and distribution of rainfall. It was found that the characteristics of rainfall distribution vary with elevation, position, wind direction. And in the three directions considered, it was found that there is the related formulation dependent on the distance between two stations. The resultrs of this study on the temporal and spatial characteristics of rainfall can be used in the design of raingauge networks, hydrological forecasting, and so on in the Nam River dam basin.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.45-57
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• 2003

An artificial neural network model was developed to analyze and forecast Short-term river runoff from the Naju watershed, in Korea. Error back propagation neural networks (EBPN) of hourly rainfall and runoff data were found to have a high performance In forecasting runoff. The number of hidden nodes were optimized using total error and Bayesian information criterion. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$is greater than 0.99) for calibration and verification data sets. Increasing the time horizon for application data sets, thus mating the model suitable for flood forecasting. decreases the accuracy of the model. The resulting optimal EBPN models for forecasting hourly runoff consists of ten rainfall and four runoff data(ANN0410 model) and ten rainfall and ten runoff data(ANN1010 model). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$is greater than 0.92).

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.83-95
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• 2020

Because sensor nodes have limited resources in wireless sensor networks, data aggregation can efficiently reduce communication overhead and extend the network lifetime. Although many existing methods are particularly useful for data aggregation applications, they incur unbalanced communication cost and waste lots of sensors' energy. In this paper, we propose a privacy-preserving, energy-saving data aggregation scheme (EBPP). Our method can efficiently reduce the communication cost and provide privacy preservation to protect useful information. Meanwhile, the balanced energy of the nodes can extend the network lifetime in our scheme. Through many simulation experiments, we use several performance criteria to evaluate the method. According to the simulation and analysis results, this method can more effectively balance energy dissipation and provide privacy preservation compared to the existing schemes.