• Korean Journal of Ecology and Environment
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• v.55 no.2
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• pp.132-144
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• 2022

The fish community in the Seomjin River-Seomjin River Estuary-Gwangyang Bay coast continuum was investigated three times from March 2019 to October 2019. The collected species at the eight sites during the survey period were 49 species belonging to 31 families, including two endangered species. According to Bray-Curtis similarities, observations were divided into four groups based on the fish community composition; two groups (group 1, 2) and two uncategorized groups (group 3, 4). ANOSIM based on spatial and temporal groupings indicated that the spatial differences in fish communities (R=0.398, P=0.001) were relatively more important than the temporal differences (analysis of similarities, R=0.273, P=0.002). In particular, there were significant differences between groups 1 and 2 (analysis of similarities, R=0.556, P=0.001), and similarity percentage analysis revealed that Argyrosomus argentatus (9.4%), Favonigobius gymnauchen (6.9%) and Konosirus punctatus (5.9%) contributed to these differences of fish assemblages for each group. The fish fauna distributed in the Seomjin River-Gwangyang Bay ecosystem were spatially divided and the number of species and number of individuals showed seasonal differences. This study could be a basis for understanding changes in the fish community and implementing conservation and management strategies on major species within a continuous environment of the river-estuary-ocean continuum.

• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.235-250
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• 2023

This study was carried out to identify the vascular flora of Mt. Bonghwa in the Baekdudaegan Mountain range, located on the border between Namwon City and Jangsu Country in Jeollabuk Province and Hamyang Country in Gyeongsangnam Province and use them as basic data for the conservation of plant diversity and prevention of the spread of alien plants. Specimens deposited at the Herbarium of Korea National Arboretum (KH) were reexamined, and 15 field surveys were conducted from April 2020 to July 2023. The result revealed a total of 466 taxa, consisting of 97 families, 279 genera, 409 species, 16 subspecies, 32 varieties and 9 forms, Of which, eight taxa were endemic plants, and one taxon, Aconitum coreanum (H.Lév.), belonged to the vulnerable (VU) on the national red list species. Moreover, there were 57 floristic target species, including 1 taxon of grade V, 9 taxa of grade III, 14 taxa of grade II, and 33 taxa of grade I, whereas there were 24 taxa of alien plants and 1 taxon of ecosystem disturbance species. In the usefulness survey, 353 taxa were for food, 3 for textiles, 71 for medicinal use, 21 for ornamental use, 108 for pasture use, 2 for industrial use, 7 for miscellaneous use, and 11 for timber plants.

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

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.321-327
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• 2006

In Korea, there is a growing competitive for water resources between industrial, domestic and agricultural consumer, and the environment as many other OECD countries. The demand on water use is also affecting aquatic ecosystems particularly where withdrawals are in excess of minimum environmental needs for rivers, lakes and wetland habits. OECD developed three indicators related to water use by the agriculture in above contexts : the first is a water use intensity indicator, which is expressed as the quantity or share of agricultural water use in total national water utilization; the second is a water stress indicator, which is expressed as the proportion of rivers (in length) subject to diversion or regulation for irrigation without reserving a minimum of limiting reference flow; and the third is a water use efficiency indicator designated as the technical and the economic efficiency. These indicators have different meanings in the aspect of water resource conservation and sustainable water use. So, it will be more significant that the indicators should reflect the intrinsic meanings of them. The problem is that the aspect of an overall water flow in the agro-ecosystem and recycling of water use not considered in the assessment of agricultural water use needed for calculation of these water use indicators. Namely, regional or meteorological characteristics and site-specific farming practices were not considered in the calculation of these indicators. In this paper, we tried to calculate water use indicators suggested in OECD and to modify some other indicators considering our situation because water use pattern and water cycling in Korea where paddy rice farming is dominant in the monsoon region are quite different from those of semi-arid regions. In the calculation of water use intensity, we excluded the amount of water restored through the ground from the total agricultural water use because a large amount of water supplied to the farm was discharged into the stream or the ground water. The resultant water use intensity was 22.9% in 2001. As for water stress indicator, Korea has not defined nor monitored reference levels of minimum flow rate for rivers subject to diversion of water for irrigation. So, we calculated the water stress indicator in a different way from OECD method. The water stress indicator was calculated using data on the degree of water storage in agricultural water reservoirs because 87% of water for irrigation was taken from the agricultural water reservoirs. Water use technical efficiency was calculated as the reverse of the ratio of irrigation water to a standard water requirement of the paddy rice. The efficiency in 2001 was better than in 1990 and 1998. As for the economic efficiency for water use, we think that there are a lot of things to be taken into considerations to make a useful indicator to reflect socio-economic values of agricultural products resulted from the water use. Conclusively, site-specific, regional or meteorogical characteristics as in Korea were not considered in the calculation of water use indicators by methods suggested in OECD(Volume 3, 2001). So, it is needed to develop a new indicators for the indicators to be more widely applicable in the world.