• Korean Journal of Environmental Agriculture
• /
• v.25 no.2
• /
• pp.138-146
• /
• 2006

To understand the status of water quality and work out a suitable countermeasures in Seonakdong watershed which has poor agro- environmental condition because of severe point and non-point source pollution by popularized city and near sea, we investigated the pollution sources and water quality from '03 and '05 and the result were mapped with GIS and RS for end-users's convenient comprehense and conjunction of water quality and geological data. The most degraded tributary was Hogeo stream which was affected directly by highly popularized Gimhae city, the main pollution source of the watershed. The pollution of tributaries in watershed increased the T-N of main body that reached over 4 mg/L during dry season. Pyeonggang stream and the lower part of main water way were suffered from high salt contents induced near sea and the EC value of those area were increased to 2.25 dS/m. The delivered loads of T-N and T-P were largest in Joman river as 56% and 61% of total delivered loads 1mm tributaries because of lots of stream flow. When Management mandate for irrigation water in Seonakdong river watershed was mapped for estimating integrated water quality as the basis of classification of EC and T-N contents in water, Hogeo and Shineo catchments were showed the requiring countermeasures none against nutrients hazard and Pyeonggang catchment was the vulnerable zone against nutrients and salts hazard. As the result, Seonakdong watershed had very various status of water quality by characteristics of catchments and countermeasures for improving water quality and crop productivity safely should changed depend on that.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.6-7
• /
• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Journal of Environmental Impact Assessment
• /
• v.8 no.4
• /
• pp.1-12
• /
• 1999

The purpose of this study is to develop a Water Quality Management System(WQMS), which calculates pollutant discharge and forecasts water quality with a water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView 3.1 was used to enter or edit geographic data and attribute data, and Avenue Script was used to customize the user interface. PCI, a remote sensing software, was used to derive land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, database subsystem and modelling subsystem. The database subsystem consisted of watershed data from digital maps, remote sensing data, government reports, census data and so on. The modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model) and SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. These two subsystems were connected through a graphic display module. This system has been calibrated for and applied to Mokhyun Stream watershed.

• Journal of Environmental Health Sciences
• /
• v.8 no.1
• /
• pp.1-11
• /
• 1982

A study on the water pollution of Gumho river by the relationship between physio-chemical conditions and water quality level by phytoplankton was examined at 7 sampling positions during the period from Aug. 1 to Nov. 30, 1981. Examination of physio-chemicat water analysis such as temperature, pH, DO, BOD, and biological analysis are as follows: 1. pH was in the range of 6.6-7.3. 2. At all positions DO was0.5-11.9 mg/l. But at Shinchun bridge and Gangchang was 0.5-3.9 mg/l. 3. BOD was in the range of 3.4-29.2 mg/l. Banyawol, Dongchon and Gumdan was shown good condition. But at Shinchun bridge was 21.1-29.2 mg/l. 4. The plankton identification in this study period showed, Cyanophyceae is 7 genera 13 species, Bacillariophyceae is 11 genera 32 species, and Chlorophceae is 17 genera 27 species: total 35 genera 72 species. 5. In the point of phytoplankton classification, upper stream of Banyawol, Dongchon and Gumdan which BOD was 3.4-8.7 mg/l, dominant phytoplanktons were Synedra ulna, Ulothrix sp., Oscillatoria sp. and Frusturia rhomboides. At Shinchun bridge which BOD was 21.1-29.2 mg/l, Microcystis aeruginosa, Closterium acerosum and Oscillatoria sp were found a small. At 3rd gongdan which BOD was 9.2-12.5 mg/l, dominant species were Synedra ulna, Hormidium sp and Actinastrum hantzschii. At Paldal which BOD was 7.8-9.2 mg/l, dominant species were Nitzschia palea, Synedra ulna and Scenedesmus bijuga. At Gangchang of down stream which BOD was 6.9-9.2 mg/l, dominant phytoplanktons were Closterium acerosum, Microcystis aeruginosa and Actnastrum hantzschii. 6. The results of biological water analysis by saprobic system were as follows: Banyawol was from oligosaprobic to $\beta$-mesosaprobic, Dongchon and Gumdan was from $\beta$-mesosaprobic to $\beta$-mesosaprobic, Shinchun bridge was polysaprobic, 3rd gongdan was from $\alpha$-mesosaprobic to $\beta$-polysaprobic, Paldal was $\beta$-polysaprobic and Gangchang was $\alpha$-polysaprobic.

• Journal of the Korean Geographical Society
• /
• v.44 no.1
• /
• pp.31-55
• /
• 2009

This research aims 1) to characterize the spatial distribution of low relief landforms (plains) via analyses of a Digital Elevation Model (DEM), 2) to classify plains according to morphological and genetic similarity, and 3) to develop a model to explain forming processes of plains in the Korean peninsula. Plains can easily be separated from high relief mountaneous areas by analyzing the DEM. The overall morphological and locational characteristics of plains can be categorized into lava plains, fluvial-marine plains, erosional plains, intermontane basins, and higher ground plains. It is concluded that the characteristic of each plain type is decided by base-level changes caused by tectonic uplift and sea-level changes, and topological relationship of different rock types. Different plain types do not exist independently, but connected with each others along stream networks. The model developed is able to combine the morphological characteristics of plains with the channel network to conceptualize characteristics and development pathways of plains in the Korean Peninsula.

• The Journal of Engineering Geology
• /
• v.28 no.4
• /
• pp.583-592
• /
• 2018

Recently, concern has arisen regarding the lowering of groundwater levels in the hinterland caused by the development of high-capacity radial collector wells in riverbank filtration areas. In this study, groundwater levels are estimated using Modflow software in relation to the water volume pumped by the radial collector well in Anseongcheon Stream. Using the water volume data, an artificial neural network (ANN) model is developed to determine the amount of water that can be withdrawn while minimizing the reduction of groundwater level. We estimate that increasing the pumping rate of the horizontal well HW-6, which is drilled parallel to the stream direction, is necessary to minimize the reduction of groundwater levels in wells OW-7 and OB-11. We also note that the number of input data and the classification of training and test data affect the results of the ANN model. This type of approach, which supplements ANN modeling with observed data, should contribute to the future groundwater management of hinterland areas.

• Journal of Korean Society on Water Environment
• /
• v.35 no.2
• /
• pp.152-164
• /
• 2019

In this study, a Benthic Macroinvertebrates Family Index (BMFI) was developed using 100 indicator groups (99 families including Chironomidae with 2 phena). Families were assigned a score between 1 and 10 depending on their sensitivity to organic pollution. The BMFI was composed of the sensitivity and relative abundance of the indicator taxa. Sensitivity values of each group were generally similar to Biological Monitoring Working Party (BMWP) scores or Walley, Hawkes, Paisley, Trigg (WHPT) scores of UK, Japanese BMWP scores, and the FBI tolerance values of North America. However, sensitivity values of some taxa were significantly different from those of foreign countries, which seemed to have resulted from discrepancy in species composition, difference of taxonomic classification system, or methodological difference for estimation of sensitivity. As an annual average level, BMFI showed significant correlation with concentration of 5-day biochemical oxygen demand (BOD5) (correlation coefficient r = -0.80, n = 569 sites), total suspended solids (r = -0.68), and total phosphorus (r = -0.79). In addition, BMFI revealed strong correlation with Shannon-Weaver's species diversity (r = 0.85), Margalef's species richness (r = 0.85) and McNaughton's dominance (r = -0.84). Correlation between BMFI and water quality parameters or community indices such as species diversity did not show significant difference compared to that of species-level indices such as BMI (Benthic Macroinvertebrates Index). This means that BMFI is a more useful indicator in terms of easy identification of organisms. BMFI was used to assess the environmental status of 3,017 sites of Stream Ecosystem Survey conducted by the Korean Ministry of Environment between 2016 and 2018. As a result, about half of all sites appeared to be in good condition, and a quarter in poor condition.

• Journal of Internet Computing and Services
• /
• v.19 no.5
• /
• pp.67-75
• /
• 2018

According to Symantec's Internet Security Threat Report(2018), Internet security threats such as Cryptojackings, Ransomwares, and Mobile malwares are rapidly increasing and diversifying. It means that detection of malwares requires not only the detection accuracy but also versatility. In the past, malware detection technology focused on qualitative performance due to the problems such as encryption and obfuscation. However, nowadays, considering the diversity of malware, versatility is required in detecting various malwares. Additionally the optimization is required in terms of computing power for detecting malware. In this paper, we present Stream Order(SO)-CNN and Incremental Coordinate(IC)-CNN, which are malware detection schemes using CNN(Convolutional Neural Network) that effectively detect intelligent and diversified malwares. The proposed methods visualize each malware binary file onto a fixed sized image. The visualized malware binaries are learned through GoogLeNet to form a deep learning model. Our model detects and classifies malwares. The proposed method reveals better performance than the conventional method.

• Korean Journal of Environment and Ecology
• /
• v.17 no.2
• /
• pp.153-168
• /
• 2003

Wangpicheon, which is located in Uljin-Gun, Korea, is threatened with various developments plan recently. To investigate the forest structure, actual vegetation and degree of green naturality(DGN) in Wangpicheon, survey was carried out within about 1km width from the stream. In the analysis of actual vegetation, the forest type around Wangpicheon is differentiated into 26 vegetation ones. In these, six Pinus densiflora - dominated vegetation types are appeared a great many of them. In DGN analysis, 70.8% of total area is covered by DGN 8 and 0.3% of total area is covered by DGN 9. According to the analysis of classification by TWINSPAN, the community was divided by three types of Pinus densiflora community and two types of Quercus spp. community i.e. Quercus mongolica and Q. vuliabitis community. The structure of communities were analyzed using importance percentage, and species and individuals, DBH distribution and similarity analysis were executed.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.16 no.2
• /
• pp.93-104
• /
• 2013

The purpose of this study was to develop a list of plants that adapted to the aquatic environment in urban areas based on the list of plants surveyed through literature review and field surveys, and to classify the types of vegetation according to the five categories of plant distributions set by the U.S. Fish and Wildlife Service (1988) in the aspect of the adaptability of plants to the aquatic environment. Results of the classification by category according to the adaptability to the aquatic environment for the plant species surveyed through literature review and field surveys showed that there are 45 species of OBL, 96 species of FACW, 66 species of FAC, and 94 species of FACU, totaling 650 species. In addition, a total of 50 species excluding exotic species, endangered species, and naturally introduced plants are proposed as appropriate plants for the urban aquatic environment that will be artificially constructed. The results of the study can be utilized as the basic information for maintaining diversity and stability of the ecosystem during the restoration of water ecology; they can serve as useful data for the development of an optimum vegetation model when planting in water spaces in the future and preparing proper planting plans for each space. In addition, it is believed that the information will be useful in wetland identification and evaluation by observing plant species that appear only in wetlands.