• Korean Journal of Ecology and Environment
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• v.39 no.2 s.116
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• pp.145-156
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• 2006

The objective of this study was to evaluate biological health conditions and physicochemical status using multi-metric models at five sites of the Keum-Ho River during August 2004 and June 2005. The research approach was based on a qualitative habitat evaluation index (QHEI), index of biological integrity (IBI) using fish assemblage, and long-term chemical data (1995 ${\sim}$ 2004), which was obtained from the Ministry of Environment, Korea. For the biological health assessments, regional model of the IBI in Korea (An,2003), was applied for this study. Mean IBI in the river was 30 and varied from 23 to 48 depending on the sampling sites. The river health was judged to be "fair condition", according to the stream health criteria of US EPA (1993) and Barbour et al. (1999). According to the analysis of the chemical water quality data of the river, BOD, COD, conductivity, TP, TN, and TSS largely varied epending on the sampling sites, seasons and years. Variabilities of some parameters including BOD, COD, TP, TN, and conductivity were greater in the downstream than in the upstream reach. This phenomenon was evident in the dilution by the rain during the monsoon. This indicates that precipitation is a very important factor of the chemical variations of water quality. Community analyses showed that species diversity index was highest (H=0.78) in the site 1, while community dominance index was highest in the site 3, where Opsariichthys uncirostris largely dominated. In contrast, the proportions of omnivore and tolerant species were greater in the downstream reach, than in the upstream reach. Overall, this study suggests that some sites in the downstream reach may need to restore the aquatic ecosystem for better biological health.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.147-152
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• 2015

Nitrogen (N) loading from domestic, agricultural and industrial sources can lead to excessive growth of macrophytes or phytoplankton in aquatic environment. Many studies have used nitrogen stable isotope ratios to identify anthropogenic nitrogen in aquatic systems as a useful method for studying nitrogen cycle. In this study to evaluate the precision and accuracy of Kjeldahl processes, two reference materials (IAEA-NO-3, N-1) were analyzed repeatedly. Measured the ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ values of IAEA-NO-3 and IAEA-N-1 were $4.7{\pm}0.2$‰ and $0.4{\pm}0.3$‰, respectively, which are within recommended values of analytical uncertainties. Also, we investigated spatial patterns of ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ in effluent plumes from a waste water treatment plant in Han River, Korea. ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ values are enriched at downstream areas of water treatment plant suggesting that dissolved nitrogen in effluent plumes should be one of the main N sources in those areas. The current study clarifies the reliability of Kjeldahl analytical method and the usefulness of stable isotopic techniques to trace the contamination source of dissolved nitrogen such as nitrate and ammonia.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.