• 한국관개배수회지
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• no.18
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• pp.21-23
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• 1997

From March 20 to 25, 1997, Dr. Rodenhuis, on the invitation of KCID, visited Korea for the International Symposium on the $\ulcorner$Efficient Operation and Management of Fresh Water Reservoir and Environmental Considerations on the Reservoir W

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4B
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• pp.221-232
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• 2012

In this study, the model enhancing the safety of reservoirs and reducing the downstream flood damage by reservoirs system operation during abnormal flood was developed. Linear programming was used for the optimal reservoirs system operation during an abnormal flood and fuzzy inference system was introduced to solve the uncertainty problem which is included in hydrological factors like inflow, water level and inflow variation of reservoir operation. The linear programming model determined the optimal reservoir system operation rules and could be used in situation where water demands varies rapidly during the abnormal flood events using fuzzy control technique. In this study, the optimal reservoirs system operation for Andong and Imha reservoirs located in the upper basin of Nakdong river was performed in order that the design flood discharge at Andong city would not be exceeded for the design flood of 100 year and PMF(Probable Maximum Flood). And the model that determines the release according to the downstream flow discharge, the reservoir storage, the inflow and the inflow variation of each reservoir was developed using the optimal system operation result and fuzzy control technique. The developed model consisted of 224 fuzzy rules according to the conditions of Andong reservoir, Imha reservoir and Andong city. And the release from each reservoir could be determined when the current data are used as input data through the developed GUI.

• Journal of Environmental Impact Assessment
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• v.8 no.1
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• pp.107-120
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• 1999

This study was performed to survey the general feature of reservoir sediment in Daecheong, Sapkyo and Kumkang reservoir. For investigations, sediments were sampled at four sites in Dae-Cheong and two sites in SapKyo and Kumkang in June and October. The items for investigation are as follows; water content, loss on ignition(IG), porosity of sediment, contents of element such as hydrogen, nitrogen, carbon, phosphorus contents and nutrient release rates. Loss on ignition was measured to determine the contents of organic substance. And its ranges were determined 2.4~16.2% in Daecheong reservoir, 5.6~27.9% in Sapkyo and 4.8~18.7% in Kumkang reservoir. And, total phosphorus contents in sediments were measured $677{\sim}5,238{\mu}g/g$ in Daecheong, $780{\sim}1,417{\mu}g/g$ in Sapkyo and $604{\sim}1,452{\mu}g/g$ in Kumkang reservoir. And release rates of nutrients were calculated $0.05{\sim}8.63mgP/m^2day$ and $4.99{\sim}36.56mgN/m^2day$ in Daecheong, $1.83{\times}10^{-3}{\sim}3.23{\times}10^{-2}mgP/m^2day$ and $1.97{\sim}.22mgN/m^2day$ in Sapkyo, $8.31{\times}10^{-3}{\sim}6.51{\times}10^{-2}mgP/m^2day$ and $0.89{\sim}4.42mgN/m^2day$ in Kumkang reservoir, respectively. And this study attempted to determine the humus level of sediments. As a result of elemental analysis, C/N ratio was determined 3.0~13.1 in Daecheong reservoir, 6.5~13.0 in Sapkyo and 3.6~12.6 in Kumkang reservoir, respectively. From the elemental analysis, humus levels of reservoirs were changed from mesohumic to oligohumic state in all reservoirs.

• Journal of Environmental Science International
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• v.2 no.2
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• pp.123-133
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• 1993

Shingal reservoir is a relatively small (211ha) and shallow impoundment, and approximately 25 ha of its sediment is exposed after spring drawdown. At least 14 vascular p13n1 species germinate on the exposed sediment, but Persimria vulgaris Webb et Moq. quickly dominates the vegetation. In order to estimate the role of the vegetation in the dynamics of heavy metal pollutants in the reservoir, Cu concentration of water, fallout particles, exposed sediment, and tissues of p. vulgaris, Ivas analyzed. Cu content in reservoir water decreased from $13.10mg/m^2$ on May 15 (before dralvdown) to $3.08mg/m^2$ in June 1 (after drawdown), mainly due to the loiwering of water level. Average atmospheric deposition of Cu by fallout particles was $10.84 {\mu}g/m^2/day$. Cu content in the surface 15cm of exposed sediment decreased from $5.094g1m^2$ right after drawdown, to $0.530g/m^2$ in 41 days, which is a 89.6% decrease. Therefore up to 99.7% of Cu in the reservoir appears to exist in the sediment. only 0.3% in water If the rate of atmospheric Input by fallout particles is assumed to have been the same since 1958, when the reservoir was completed, cumulative input of Cu during the 38 years would have been $150.35mg/m^2$, which is only 3.0% of Cu content in sediment right after drawdown. Therefore, most of Cu in the Shingal reservoir must have been transported by the Shingal-chun flowing into the reservoir, Standing crop of vegetation on the exposed sediment 41 days after drawdown was $730.67g/m^2$, of which 630.91g/m2 was p. vulgaris alone, and Cu content in P vulgaris at this time was $6.612mg/m^2$. This was only 0.13% of Cu in the exposed sediment, but was 50.5% of Cu in water before drawdown, or 167% of the average annual input of Cu by atmospheric deposition. If other plants were assumed to absorb Cu to the same concentration as p. vulgaris, total amount of Cu absorbed in 41 days by vegetation on the exposed sediment is estimated to be 1913.3 g, which is a considerable contribution to the purification of the reservoir water.

• Journal of Environmental Science International
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• v.2 no.2
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• pp.29-29
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• 1993

Shingal reservoir is a relatively small (211ha) and shallow impoundment, and approximately 25 ha of its sediment is exposed after spring drawdown. At least 14 vascular p13n1 species germinate on the exposed sediment, but Persimria vulgaris Webb et Moq. quickly dominates the vegetation. In order to estimate the role of the vegetation in the dynamics of heavy metal pollutants in the reservoir, Cu concentration of water, fallout particles, exposed sediment, and tissues of p. vulgaris, Ivas analyzed. Cu content in reservoir water decreased from $13.10mg/m^2$ on May 15 (before dralvdown) to $3.08mg/m^2$ in June 1 (after drawdown), mainly due to the loiwering of water level. Average atmospheric deposition of Cu by fallout particles was $10.84 {\mu}g/m^2/day$. Cu content in the surface 15cm of exposed sediment decreased from $5.094g1m^2$ right after drawdown, to $0.530g/m^2$ in 41 days, which is a 89.6% decrease. Therefore up to 99.7% of Cu in the reservoir appears to exist in the sediment. only 0.3% in water If the rate of atmospheric Input by fallout particles is assumed to have been the same since 1958, when the reservoir was completed, cumulative input of Cu during the 38 years would have been $150.35mg/m^2$, which is only 3.0% of Cu content in sediment right after drawdown. Therefore, most of Cu in the Shingal reservoir must have been transported by the Shingal-chun flowing into the reservoir, Standing crop of vegetation on the exposed sediment 41 days after drawdown was $730.67g/m^2$, of which 630.91g/m2 was p. vulgaris alone, and Cu content in P vulgaris at this time was $6.612mg/m^2$. This was only 0.13% of Cu in the exposed sediment, but was 50.5% of Cu in water before drawdown, or 167% of the average annual input of Cu by atmospheric deposition. If other plants were assumed to absorb Cu to the same concentration as p. vulgaris, total amount of Cu absorbed in 41 days by vegetation on the exposed sediment is estimated to be 1913.3 g, which is a considerable contribution to the purification of the reservoir water.

• ALGAE
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• v.18 no.2
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• pp.145-156
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• 2003

Seasonal investigations were conducted to determine the major aquatic environmental factors and the variation of phytoplankton in Pyeongtaek Reservoir in March, June, September, and December 2000. Heavy rainfall mainly occurs from late June to mid-September, and water quality of reservoir was high in the influent zone of stream and riverine zone of reservoir. The biomass of phytoplankton was related to aquatic environmental factors. In particular, its value increased where nutrient concentration was high. Likewise, the increase of turbidity was found to have anthropogenic effects on the varying quantity of phytoplankton. The phytoplankton composition in quantitative survey identified into 43 genera and 71 species. Species numbers of Bacillariophyceae, Cyanophyceae, and Chlorophyceae accounted for 17%, 15%, and 49%, respectively, with the remainder constituting less than 3-7%. The distribution of such phyla also significantly varied according to seasons, accounting for 25%, 37%, 61%, and 14% in March, June, September, and December, respectively. Bacillariophyceae and Chlorophyceae were observed throughout the year, while Cyanophyceae proliferated in June and September. Euglenophyceae and Dinophyceae were prevalent in March and September, while Cryptophyceae occurred in March and December. The succession trend of phytoplankton showed the maximum cell density was followed by Bacillariophyceae (6.8$\times$$10^3$ cells ${\cdot}$ml)$\rightarrow$ Chlorophyceae (3.7$\times$$10^3$ cells ${\cdot}$ml)$\rightarrow$Cyanophyceae (1.3$\times$$10^4$ cells ${\cdot}$ml)$\rightarrow$Cryptophyceae (1.2$\times$$10^3$ cells ${\cdot}$ml). The cell density was the highest in the upstream. Dominant species were composed of Aulacoseira ambigua, Stephanodiscus hantzschii f. tenuis of Bacillariophyceae, Anabaena spiroides var. crassa, Microcystis aeruginosa, Oscillatoria amphibia of Cyanophyceae, Actinastrum hantzschii var. fluviatile, Pediastrum duplex var. reticulatum of Chlorophyceae, Euglena gracilis, Trachelomonas spp. of Euglenophyceae, and Chroomonas spp., Cryptomonas spp. of Cryptophyceae. As a results, seasonal variation of phytoplankton in Pyeongtaek Reservoir was evident in spite of inflow the high concentration of nutrients from watershed streams, because hydrological control and anthropogenic disturbance in reservoir were found to have major effects on the retention time of water.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.185-190
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• 2005

This study is to determine an optimal reservoir among many alternative proposals in order to obtain the maximized efficiency under the limited budget. There are many alternative proposals which deal with problems to assign reservoir such as water conversion establishment construction, subterranean water, reservoir, submarine pipeline, water bort, and marine water saving base construction. In this paper, the new model to assign the most reasonable alternative is introduced using 0-1 integer programming. This proposed model has not been applied in the optimal reservoir selection problem yet. This paper will contribute to determine the most reasonable alternative to minimize budget under constraints. Also, this proposal model can be applied to other reservoir selection problem in other regions.

• Journal of Environmental Science International
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• v.11 no.12
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• pp.1217-1226
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• 2002

This study aims at the effective estimation of water supply capacity of small scale reservoir and the proposal of the data which is necessary to establish the water resources management plan of down stream area of the reservoir in the future by comparison and examination about reservoir operation technique for the security of agricultural water in small scale reservoir. The result of flow calculation by Tank model is used for the input data as the inflow data which is needed for the analysis of water supply capacity. Stochastic method, simulation method, and optimization method are used to examine the water supply capacity, and water security amount is compared with each method. From the analyses of water supply capacities by each method, slightly different results are shown in spite of the effort to compare them equally using input data such as inflow data under equal conditions, and the comparison of water supply capacities by each method are as follows; linear planning method, simulation method, and transition probability matrix method in the order of amount from the largest. It is thought that the simulation method in which comparatively reasonable application of the inflow data is possible and is simulated in successive time series dam operation of the three methods used in this study thus, simulation model is proper to estimate the water supply capacity of agricultural small scale reservoir. And it is judged that the heightening of efficiency of water resources utilization according to the development of downstream area of dam may be possible using the upward readjusted water supply amount of $55.18{\tiems}10^6ton$ and $63.7{\times}10^6ton$ at 95% and 90% supply reliability respectively which are above the planning water supply amount of $50.0{\times}10^6$ton when the simulation method is introduced as the standard.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.69-76
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• 1981

The predictive equations for reservoir sedimentation rate now in use are extensively reviewed, and the equation of multiple regression type, in which the reservoir sedimentation rate is related with the watershed area and the trap-efficiency, is proposed based on the 113 irrigation reservoir resurvey data. The predictive relation so obtained proved to be a reasonable measure for the estimation of reservoir sedimentation rate. The relationship of sediment yield with the watershed area and with the reservoir trap efficiency is also analyzed. The variations of sedimentation rate and of the annual reservoir capacity loss rate was shown to heavily depend on the trap-efficiency of a reservoir. Besides, the effect of sedimentation on stream channels is confirmed and quantified based on the predictive equation derived in the present study.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.79-86
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• 2020

Purpose: In this study, a model was developed to estimate the storage in Cheonan reservoir using images taken by Sentinel-1 satellite. Method: A total of three reservoirs were studied. All three reservoirs are small reservoirs whose water level is being measured. The preprocessing of Sentinel-1 images was done using SNAP distributed by the European Space Agency(ESA), and the storage was estimated by classifying water surface by the threshold classification method. The estimated reservoir area was compared with satellite and drones images taken on the same day. The correlation was derived by comparing the estimated reservoir area with the actual measurement. Results and Conclusions: The storage values estimated by satellite image analysis showed similar values to the actual measurement data. However, because of the underestimation of the reservoir area due to green algae and Epilithic diatom of summer reservoirs and the low resolution of satellite images, it is dificult to detect reservoir area by satellite images less than 10,000㎡.