• Korean Journal of Environment and Ecology
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• v.38 no.3
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• pp.246-262
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• 2024

The survey conducted from 2018 to 2020 aimed to investigate the changes in fish fauna and community characteristics in the upper reaches of the Seomgang River, Korea. During the survey period, 35 sites were selected, resulting in the collection of 7,817 fish belonging to 12 families and 40 species. The dominant species was Zacco koreanus, with a relative abundance of 34.5%, followed by Z. platypus at 28.7%. Other significant species included Rhynchocypris oxycephalus (10.2%), Pungtungia herzi (5.3%), and Squalidus gracilis majimae (4.3%). Notably, four protected species - Acheilognathus signifer, Gobiobotia brevibarba, and Cottus koreanus, designated as class II endangered wildlife by the Ministry of Environment- were identified. These species predominantly inhabit the middle and lower reaches, except for Gobiobotia brevibarba, which is found in the upper reaches. Nineteen species, accounting for a 47.5% endemism rate, were endemic to Korea. The study also noted the presence of one climate-sensitive species, Cottus koreanus, and two exotic species, Carassius cuvieri and Micropterus salmoides. Community analysis indicated a trend of decreasing dominance and increasing diversity and richness from upstream to downstream, with a distinct division into uppermost reaches, upper reaches, middle and lower reaches, and lakes. The construction of the Hwaseong Dam has had a significant direct and indirect impact on the fish community. The habitat and abundance of endangered species such as R. pseudosericeus, A. signifer, and G. brevibarba decreased dramatically immediately after the dam's construction, transforming the submerged area from lotic to lentic environments. Approximately 20 years later, the habitats have stabilized, leading to an increase in the fish population and a recovery of the previously diminished endangered species. The river health (FAI) was also evaluated, with 27 sites rated as very good (A), seven as good (B), and one as fair (C). However, endangered species such as A. signifer continue to face threats from dam and river construction, while C. Koreanus has experienced a severe population decline due to river works. Additionally, the presence of the ecosystem-disrupting species M. salmoides in Hwaseong Lake raises concerns. To ensure a stable habitat for fish in the upper reaches of the Seomgang River, it is crucial to avoid indiscriminate river construction, urgently implement restoration policies for endangered species such as A. signifer, and develop management strategies to control the spread of invasive species such as bass.

• Journal of The Korean Association For Science Education
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• v.44 no.4
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• pp.325-341
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• 2024

This study examined how specific aspects of epistemic cognition are developed in elementary students during modeling activities, using the Apt-AIR framework. The study focused on a class unit titled 'Shall We Find Out What the Landscape of a Riverside Looks Like?' which is part of the land chapter in the third-grade Korean elementary science curriculum. Ambitious Science Teaching (AST) was applied as a teaching strategy to enhance students' model construction. Seven science classes were conducted in line with the core practices of AST, with 29 elementary school students participating in the study. The classes were organized into four stages: initial model composition, inquiry activity, group model composition-sharing, and final model construction. The class activities at each stage were analyzed using both the AIR model, i.e., epistemic aim and value (A), epistemic ideals (I), and reliable epistemic processes (R), and the multi-faceted framework for epistemic thinking from the Apt-AIR framework. The results of the study revealed that in science classes emphasizing modeling activities based on the core practices of AST, the elementary students progressively developed more sophisticated explanatory models that included causal relationships explaining the topographic differences between the upstream and downstream sections of a river. This result was due to their engagement in constructing initial models to describe phenomena, supplementing the initial models using data collected in the model experiment, and participating in discussions to share and evaluate group models. Additionally, from the perspective of the Apt-AIR framework, the aspects of epistemic cognition demonstrated by the elementary students in their modeling activities were appropriate for engaging with cognitive processes related to epistemic aims and values, epistemic ideals, and reliable processes. The other four aspects of the Apt-AIR framework, however, were not performed as effectively. In particular, the application of reliable epistemic processes for knowledge construction required more improvement.

• Journal of Global Scholars of Marketing Science
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• v.19 no.1
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• pp.37-46
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• 2009

The Census Bureau of the Department of Commerce announced in May 2008 that U.S. retail e-commerce sales for 2006 reached $ 107 billion, up from $ 87 billion in 2005 - an increase of 22 percent. From 2001 to 2006, retail e-sales increased at an average annual growth rate of 25.4 percent. The explosive growth of E-Commerce has caused profound changes in marketing channel relationships and structures in many industries. Despite the great potential implications for both academicians and practitioners, there still exists a great deal of uncertainty about the impact of the Internet channel introduction on distribution channel management. The purpose of this study is to investigate how the ownership of the new Internet channel affects the existing channel members and consumers. To explore the above research questions, this study conducts well-controlled mathematical experiments to isolate the impact of the Internet channel by comparing before and after the Internet channel entry. The model consists of a monopolist manufacturer selling its product through a channel system including one independent physical store before the entry of an Internet store. The addition of the Internet store to this channel system results in a mixed channel comprised of two different types of channels. The new Internet store can be launched by the independent physical store such as Bestbuy. In this case, the physical retailer coordinates the two types of stores to maximize the joint profits from the two stores. The Internet store also can be introduced by an independent Internet retailer such as Amazon. In this case, a retail level competition occurs between the two types of stores. Although the manufacturer sells only one product, consumers view each product-outlet pair as a unique offering. Thus, the introduction of the Internet channel provides two product offerings for consumers. The channel structures analyzed in this study are illustrated in Fig.1. It is assumed that the manufacturer plays as a Stackelberg leader maximizing its own profits with the foresight of the independent retailer's optimal responses as typically assumed in previous analytical channel studies. As a Stackelberg follower, the independent physical retailer or independent Internet retailer maximizes its own profits, conditional on the manufacturer's wholesale price. The price competition between two the independent retailers is assumed to be a Bertrand Nash game. For simplicity, the marginal cost is set at zero, as typically assumed in this type of study. In order to explore the research questions above, this study develops a game theoretic model that possesses the following three key characteristics. First, the model explicitly captures the fact that an Internet channel and a physical store exist in two independent dimensions (one in physical space and the other in cyber space). This enables this model to demonstrate that the effect of adding an Internet store is different from that of adding another physical store. Second, the model reflects the fact that consumers are heterogeneous in their preferences for using a physical store and for using an Internet channel. Third, the model captures the vertical strategic interactions between an upstream manufacturer and a downstream retailer, making it possible to analyze the channel structure issues discussed in this paper. Although numerous previous models capture this vertical dimension of marketing channels, none simultaneously incorporates the three characteristics reflected in this model. The analysis results are summarized in Table 1. When the new Internet channel is introduced by the existing physical retailer and the retailer coordinates both types of stores to maximize the joint profits from the both stores, retail prices increase due to a combination of the coordination of the retail prices and the wider market coverage. The quantity sold does not significantly increase despite the wider market coverage, because the excessively high retail prices alleviate the market coverage effect to a degree. Interestingly, the coordinated total retail profits are lower than the combined retail profits of two competing independent retailers. This implies that when a physical retailer opens an Internet channel, the retailers could be better off managing the two channels separately rather than coordinating them, unless they have the foresight of the manufacturer's pricing behavior. It is also found that the introduction of an Internet channel affects the power balance of the channel. The retail competition is strong when an independent Internet store joins a channel with an independent physical retailer. This implies that each retailer in this structure has weak channel power. Due to intense retail competition, the manufacturer uses its channel power to increase its wholesale price to extract more profits from the total channel profit. However, the retailers cannot increase retail prices accordingly because of the intense retail level competition, leading to lower channel power. In this case, consumer welfare increases due to the wider market coverage and lower retail prices caused by the retail competition. The model employed for this study is not designed to capture all the characteristics of the Internet channel. The theoretical model in this study can also be applied for any stores that are not geographically constrained such as TV home shopping or catalog sales via mail. The reasons the model in this study is names as "Internet" are as follows: first, the most representative example of the stores that are not geographically constrained is the Internet. Second, catalog sales usually determine the target markets using the pre-specified mailing lists. In this aspect, the model used in this study is closer to the Internet than catalog sales. However, it would be a desirable future research direction to mathematically and theoretically distinguish the core differences among the stores that are not geographically constrained. The model is simplified by a set of assumptions to obtain mathematical traceability. First, this study assumes the price is the only strategic tool for competition. In the real world, however, various marketing variables can be used for competition. Therefore, a more realistic model can be designed if a model incorporates other various marketing variables such as service levels or operation costs. Second, this study assumes the market with one monopoly manufacturer. Therefore, the results from this study should be carefully interpreted considering this limitation. Future research could extend this limitation by introducing manufacturer level competition. Finally, some of the results are drawn from the assumption that the monopoly manufacturer is the Stackelberg leader. Although this is a standard assumption among game theoretic studies of this kind, we could gain deeper understanding and generalize our findings beyond this assumption if the model is analyzed by different game rules.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.174-189
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• 2015

The objective of this study was to reconstruct spatial information using the results of the investigation and evaluation of the health of the living organisms, habitat, and water quality at the investigation points for the aquatic ecosystem health of the Nakdong River basin, to support the rational decision making of the aquatic ecosystem preservation and restoration policies of the Nakdong River basin using spatial analysis techniques, and to present efficient management methods. To analyze the aquatic ecosystem health of the Nakdong River basin, punctiform data were constructed based on the position information of each point with the aquatic ecosystem health investigation and evaluation results of 250 investigation sections. To apply the spatial analysis technique, the data need to be reconstructed into areal data. For this purpose, spatial influence and trends were analyzed using the Kriging interpolation(ArcGIS 10.1, Geostatistical Analysis), and were reconstructed into areal data. To analyze the spatial distribution characteristics of the Nakdong River basin health based on these analytical results, hotspot(Getis-Ord Gi, $G^*_i$), LISA(Local Indicator of Spatial Association), and standard deviational ellipse analyses were used. The hotspot analysis results showed that the hotspot basins of the biotic indices(TDI, BMI, FAI) were the Andong Dam upstream, Wangpicheon, and the Imha Dam basin, and that the health grades of their biotic indices were good. The coldspot basins were Nakdong River Namhae, the Nakdong River mouth, and the Suyeong River basin. The LISA analysis results showed that the exceptional areas were Gahwacheon, the Hapcheon Dam, and the Yeong River upstream basin. These areas had high bio-health indices, but their surrounding basins were low and required management for aquatic ecosystem health. The hotspot basins of the physicochemical factor(BOD) were the Nakdong River downstream basin, Suyeong River, Hoeya River, and the Nakdong River Namhae basin, whereas the coldspot basins were the upstream basins of the Nakdong River tributaries, including Andong Dam, Imha Dam, and Yeong River. The hotspots of the habitat and riverside environment factor(HRI) were different from the hotspots and coldspots of each factor in the LISA analysis results. In general, the habitat and riverside environment of the Nakdong River mainstream and tributaries, including the Nakdong river upstream, Andong Dam, Imha Dam, and the Hapcheon Dam basin, had good health. The coldspot basins of the habitat and riverside environment also showed low health indices of the biotic indices and physicochemical factors, thus requiring management of the habitat and riverside environment. As a result of the time-series analysis with a standard deviation ellipsoid, the areas with good aquatic ecosystem health of the organisms, habitat, and riverside environment showed a tendency to move northward, and the BOD results showed different directions and concentrations by the year of investigation. These aquatic ecosystem health analysis results can provide not only the health management information for each investigation spot but also information for managing the aquatic ecosystem in the catchment unit for the working research staff as well as for the water environment researchers in the future, based on spatial information.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.40-46
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• 2009

The applicability of a well-type autotrophic sulfur-oxidizing reactive barrier (L $\times$ W $\times$ D = $3m\;{\times}\;4\;m\;{\times}\;2\;m$) as a long-term treatment option for nitrate removal in groundwater was evaluated. Pilot-scale (L $\times$ W $\times$ D = $8m\;{\times}\;4\;m\;{\times}\;2\;m$) flow-tank experiments were conducted to examine remedial efficacy of the well-type reactive barrier. A total of 80 kg sulfur granules as an electron donor and Thiobacillus denitrificans as an active bacterial species were prepared. Thiobacillus denitrificans was successfully colonized on the surface of the sulfur granules and the microflora transformed nitrate with removal efficiency of ~12% (0.07 mM) for 11 days, ~24% (1.3 mM) for 18 days, ~45% (2.4 mM) for 32 days, and ~52% (2.8 mM) for 60 days. Sulfur granules attached to Thiobacillus denitrificans were used to construct the well-type reactive barrier comprising three discrete barriers installed at 1-m interval downstream. Average initial nitrate concentrations were 181 mg/L for the first 28 days and 281 mg/L for the next 14 days. For the 181 mg/L (2.9 mM) plume, nitrate concentrations decreased by ~2% (0.06 mM), ~9% (0.27 mM), and ~15% (0.44 mM) after $1^{st}$, $2^{nd}$, and $3^{rd}$ barriers, respectively. For the 281 mg/L (4.5 mM) plume, nitrate concentrations decreased by ~1% (0.02 mM), ~6% (0.27 mM), and ~8% (0.37 mM) after $1^{st}$, $2^{nd}$, and $3^{rd}$ barriers, respectively. Nitrate plume was flowed through the flow-tank for 49 days by supplying $1.24\;m^3/d$ of nitrate solution. During nitrate treatment, flow velocity (0.44 m/d), pH (6.7 to 8.3), and DO (0.9~2.8 mg/L) showed little variations. Incomplete destruction of nitrate plume was attributed to the lack of retention time, rarely transverse dispersion, and inhibiting the activity of denitrification enzymes caused by relatively high DO concentrations. For field applications, it should be considered increments of retention time, modification of well placements, and intrinsic DO concentration.

• Journal of Preventive Medicine and Public Health
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• v.4 no.1
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• pp.65-76
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• 1971

In view of ever rising water pollution problems of river in the vicinity of large urban communities, the author has made an investigation on the pollution of water sampled from Han River (Seoul area) and Nakdong River (Daegu city area) during the period from July to December, 1970. The water samples were taken twice a month during the study period of 6 months from 7 points (locations) along the main stream of Han River at Seoul city and 5 points of Nakdong River at Daegu city. The samples ware measured and analyzed in accordance with the recognized methods in the 'Standard Methods for Examination of Water and waste' by American Public Health Association. The obtained results are as follows : I. Han River. 1. Average turbidity was 5.1 units ranging from 1 to 10 units and the turbidity of down stream was higher than that of the upper stream. 2. pH value showed slight alkalinity (mean;7.2) except Yunchang-Dong (6.9). 3. The mean value of Dissolved Oxygen contents (D.O) was 7.2 ppm. (range of 3.4-10.5ppm.). D.O. of the upper stream (8.2 ppm. at Walker Hill boating place, 8.0 ppm. at the Gwangzang Bridge and Ddookdo) was higher than that of he downstream (5.6ppm. at Yumchang-Dong, 6.4 ppm. at the 2nd Han River Bridge), and D.O. in the winter season was higher than that in the summer season, respectively. 4 The mean value of the Biochemical Oxygen Demand (B.O.D.) was 28.3 ppm. (range of 6.2-64.8 ppm.). The mean value of B.O.D. was 48.7 ppm. at Yumchang-Dong, 42.3 ppm. at the 2nd Han River Bridge, 34.0 ppm. at the 1st nan River Bridge, 28.5 ppm. at the 3rd Han River Bridge, 19.2 ppm. at Dookdo, 13.2 ppm. at the Gwangzang Bridge, and 10.2 ppm. at the Walker Hill boating place in order of value. B.O.D. in July and August (35.6 and 34.5 ppm.) were the highest and that in November and December (18.6 and 21.2 ppm.) were the lowest. 5. Suspended Solids (SS) were from 15.0 to 667.0 ppm. with the mean of 222.1 ppm. 'Suspended Solids' of the water samples at Yumchang-Dong and the 2nd Han River Bridge were found to be 378.1 ppm. and 283.9 ppm. respectively which were higher than at the Gwangzang Bridge (134.1 ppm.) and at Walker Hill boating place (79.3ppm.). 6. Coliform colonies counting of the water samples ranged from $0-2,500{\times}10/100ml$. with the mean value of $205.6{\times}10/100ml$. The most contaminated water sample by coliform were from the point of the 2nd Han River Bridge with $640.8{\times}10/100ml$ while the lowest ones were from Walker Hill boating place with $17.2{\times}10/100ml$. There was also a seasonal variation in coliform contamination that is the higher in summer and the lower in winter. II. Nakdong River 1. The mean value of turbidity was 2.3 units with range of 0 to 9.0 units. The highest point was at Geumho River (7.2 units). and the lowest point was at Gangzung and Moonsan (0.45 and 0.41 units). 2. The mean value of pH was 7.5 (range of 7.1-8.5) and highest point was Geumho River with 8.5. 3. The mean value of D.O. was 8.1 ppm. (range of 3.4-11.2 ppm.). D.O. of the upper stream showed higher value than that of the down stream, and the winter season than the summer season. 4. B.O.D. ranged from 2.6 to 57.0 ppm. (mean; 20.4ppm.). The water sample at Geumho River showed the highest value (41.5 ppm.) while at Moonsan and Gangzung showed the lowest (4.6 and 4.7 ppm.). 5. The mean value of suspended solids was 48.7 ppm. (range of 4.0-182.0 ppm.). The highest month was July (63.7ppm.) and August (62.1 ppm.) and the lowest month was October (37.0 ppm.) and December (24.4 ppm.). 6. The mean value of the coliform colonies was $22.7{\times}10/100ml$. (range of $0-243{\times}10/100ml$.). The highest number of the colonies was found in the sample water at the Whawon recreation area ($50.5{\times}10/100ml$.) followed by the Geumho River ($33.9{\times}10/100ml$.), the Goryung Bridge ($28.3{\times}10/100ml$.), Gangzung($0.7{\times}10/100ml$), and Moonsan ($0.6{\times}10/100ml$.).

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.14 no.2
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• pp.47-58
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• 1981

Relationships between the electrical conductivity and the contents of the chloride, sulfate, calcium, magnesium, sodium, potassium and total major inorganic ions, and between each, chemical conservative constituents were calculated with the data which sampled at the lesions of Mulgeum and between Namji and Wondong from March 1974 to April 1980. Semilogarithmic relations were found between the electrical conductivity and the contents of monovalent ions, and logarithmic relations were found between the electrical conductivity and the contents of divalent ions at the both regions. The relational equations between the electrical conductivity $\lambda_{25}$and the contents of the major inorganic ions at Mulgeum are as follows: $log\;Cl(ppm)\;=\;2.37{\cdot}\lambda_{25}(m{\mho}/cm)+0.733{\pm}0.141$, $log\;SO_4(ppm)=1.12{\cdot}log\lambda_{25}(m{\mho}/cm)+2.14{\pm}0.18$, $log\;Ca(ppm)=0.615{\cdot}log\lambda_{25}(m{\mho}/cm)+1.67{\pm}0.12$, $log\;Mg(ppm)=0.756{\cdot}log\lambda_{25}(m{\mho}/cm)+1.27{\pm}0.11$, $log\;Na(ppm)=2.82{\cdot}\lambda_{25}(m{\mho}/cm)+0.551{\pm}0.133$, $log\;K(ppm)=1.33{\cdot}\lambda_{25}(m{\mho}/cm)+0.136{\pm}0.095$, and total inorganic ions $C(ppm)=399{\cdot}\lambda_{25}(m{\mho}/cm)-0.9{\pm}14.6$. The relational equations between the electrical conductivity ($\lambda_{25}$) and the contents of the major inorganic ions at the region between Namji and Wondong a.e as follows: $log\;Cl(ppm)=4.27{\cdot}\lambda_{25}(m{\mho}/cm)+0.380{\pm}0.138$, $log\;SO_4(ppm)=0.915{\cdot}log\lambda_{25}(m{\mho}/cm)+1.95{\pm}0.18$, $log\;Ca(ppm)=0.756{\cdot}log\lambda_{25}(m{\mho}/cm)+1.74{\pm}0.12$, $log\;Mg(ppm)=1.00{\cdot}log\lambda_{25}(m{\mho}/cm)+1.41{\pm}0.10$. $log\;Na(ppm)=2.47{\cdot}\lambda_{25}(m{\mho}/cm)+0.614{\pm}0.065$, $log\;K(ppm)=1.62{\cdot}\lambda_{25}(m{\mho}/cm)+0.030{\pm}0.060$, and total inorganic ions $C(ppm)=323{\cdot}\lambda_{25}(m{\mho}/cm)+11.7{\pm}9.3$. Logarithmic relations were found between each chemical conservative constituents at Mulgeum and the equations are as follows: $log\;Cl(ppm)=0.711{\cdot}log\;SO_4(ppm)+0.488{\pm}0.206$, $log\;Cl(ppm)=0.337{\cdot}log\;Ca(ppm)+0.822{\pm}0.130$, $log\;Cl(ppm)=0.605{\cdot}log\;Mg(ppm)-0.017{\pm}0.154$, $Cl(ppm)=0.676{\cdot}Na(ppm)+2.31{\pm}4.67$, $log\;Cl(ppm)=0.406{\cdot}log\;K(ppm)-0.092{\pm}0.112$, $log\;SO_4(ppm)=0.378{\cdot}log\;Ca(ppm)+0.721{\pm}0.125$, $log\;SO_4(ppm)=0.462{\cdot}log\;Mg(ppm)+0.107{\pm}0.118$, $log\;SO_4(ppm)=0.592{\cdot}log\;Na(ppm)+0.313{\pm}0.191$, $log\;SO_4(ppm)=0.308{\cdot}log\;K(ppm)-0.019{\pm}0.120$, $Ca(ppm)=0.262{\cdot}Mg(ppm)+0.74{\pm}1.71$. $log\;Ca(ppm)=1.10{\cdot}log\;Na(ppm)-0.243{\pm}0.239$, $Ca(ppm)=0.0737{\cdot}K(ppm)+1.26{\pm}0.73$, $log\;Mg(ppm)=0.0950{\cdot}Na(ppm)+0.587{\pm}0.159$, $log\;Mg(ppm)=0.0518{\cdot}K(ppm)+0.111{\pm}0.102$, and $Na(ppm)=0.0771{\cdot}K(ppm)+1.49{\pm}0.59$. Logarithmic relations were found between each chemical conservative constituents except a relationship between the chloride and calcium contents at the region between Namji and Wondong, and the equations are as follows : $log\;Cl(ppm)=0.312{\cdot}log\;SO_4(ppm)+0.907{\pm}0.210$, $log\;Cl(ppm)=0.458{\cdot}log\;Mg(ppm)+0.135{\pm}0.130$, $Cl(ppm)=0.484{\cdot}logNa(ppm)+0.507{\pm}0.081$, $Cl(ppm)=0.0476{\cdot}K(ppm)+1.41{\pm}0.34$, $log\;SO_4(ppm)=0.886{\cdot}log\;Ca(ppm)+0.046{\pm}0.050$, $log\;SO_4(ppm)=0.422{\cdot}log\;Mg(ppm)+0.139{\pm}0.161$, $log\;SO_4(ppm)=0.374{\cdot}log\;Na(ppm)+0.603{\pm}0.140$, $log\;SO_4(ppm)=0.245{\cdot}log\;K(ppm)+0.023{\pm}0.102$, $log\;Ca(ppm)=0.587{\cdot}log\;Mg(ppm)+0.003{\pm}0.088$, $log\;Ca(ppm)=0.892{\cdot}log\;Na(ppm)+0.028{\pm}0.109$, $log\;Ca(ppm)=0.294{\cdot}log\;K(ppm)-0.001{\pm}0.085$, $log\;Mg(ppm)=0.600{\cdot}log\;Na(ppm)+0.674{\pm}0.120$, $log\;Mg(ppm)=0.440{\cdot}log\;K(ppm)+0.038{\pm}0.081$, and $log\;Na(ppm)=0.522{\cdot}log\;K(ppm)-0.260{\pm}0.072$.