• Journal of Ocean Engineering and Technology
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• v.21 no.6
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• pp.87-94
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• 2007

This study used POM (Princeton ocean model) improved for applying to coastal area in order to predict the distribution of thermal waste water. This model was applied to the coastal circulation and the effect of thermal waste water of Cheonsu-Bay. So this study compared the discharge of thermal waste water with each layer and section. The tidal current was about 1.5 m/sec at surface level and 0.9 m/sec on bottom level at flood tide; tidal current was about 1.3 m/sec on surface level and 0.8 m/sec on bottom level at ebb tide. The method discharging the thermal waste water in the nearshore region (case 1) accelerates the diffusion of the thermal waste water in the north-south direction(longshore direction). However, the method discharge the thermal waster water in the offshore region (case 2) reduced the diffusion of the thermal waste water over the coastal region. According th the diffusion region of the thermal waste water with case 1 and case 2 at three different layers (surface, middle, bottom), the diffusion region by case 1 discharge method generally influenced wider region (twice) than the one by case 2 discharge method with lower temperature between $1^{\circ}C\;and\;2^{\circ}C$, whereas the case 2 discharge method influenced the deeper region (middle and botton layers) with higher change of the water temperature ($1{\sim}3^{\circ}C$).

• Archives of design research
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• v.19 no.1 s.63
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• pp.273-282
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• 2006

This study has evaluated the visual preference factor of Keum river sceneries which could vary according to the change of water level while other scenic environment near by the river did not change. 1) At Gap Cheon site, the variances of the visual preferences for river scenery at different water level are determined as emotional, physical, aesthetic and individual factor. At Mujoo site, the variances of the visual preferences are determined as only two factors such as emotional and physical factors. Those factors show significant relations. All of the visual preferences are increased as the increase of preference factors. Also decreasing of preference factors result in decreasing of visual preferences. 2) In multiple regression model, both the Gap cheon site and Mujoo site show that the increase of emotional factor affect most to visual preference when other conditions are fixed. The physical factor affect less than the emotional factor. At Gap cheon site, the relative importance level which the preference factors contribute to the visual preference appears as the order of emotional, physical, aesthetic and individual factor. Emotional factor's importance level is 4.2 times greater than individual factor. At Mujoo site, the relative importance level which the preference factors contribute to the visual preference appears as the order of emotional and physical factor. The emotional factor's importance level is 1.1 times greater than physical factor. It is clearly indicate that the emotional factor is most important preference factor in both study sites. The factor analysis results of Keum river scenery at different water level using the visual evaluation method affect a lot to the quantification of river instream flow and water level.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.5
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• pp.572-581
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• 2005

This research is conducted to develop predictable method of real scale nanofiltration treatability with small scale nanofiltration experiments. As a result of comparing calculated values with measured values, they are in a good agreement for the concentrations in filtered water and concentrated water. The results of that are not affected by change of system recovery from 20% to 95%. The proposed method is produced using constant recovery of elements, that is, no considering the pressure change. we can predict filtrated flux and contaminant concentrations with the method. The method has the following steps. (1) Calculate recovery of each element with water quality level after fixing recovery elements, (2) Predict system recovery with recovery of elements in 1, 2, 3, and 4 banks, (3) Run small scale nanofiltration experiments in predicted water quality and (4) Simulate large scale nanofiltration system for forecasting actual water quality. As the cost for nanofiltration pretest will reduced if we use the proposed method, it will be a promising method for introducing nanofiltration to supply safe drinking water.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05b
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• pp.45-48
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• 2009

The performance of concrete mainly depend upon its water-cement ratio. If water percentage is excess in concrete, it may cause the degradation of performance. Because of these reasons, the change of water content is managed by using various evaluation method of unit water content. And criterion for the change of water content is regulated and used. However the criterion is set only considering production error and measurement error but criterion does not consider performance degradation of concrete. Therefore this study tries to investigate degradation of performance while adding extra water by artificial manipulation or management error in concrete, The contents of extra water for tests are set as 0, 20, 40, 60kg/m3, to examine the performance degradation of concrete, strength, shrinkage, cracks, carbonation are tested This study conclude that, when extra water content is excess than 20kg/m3 in concrete, then performance level of concrete declined rapidly. 80 it is very important to maintain quality of concrete for its better performance.

• Journal of Korean Society on Water Environment
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• v.38 no.1
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• pp.1-9
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• 2022

The Yeongsan River, one of the four major rivers in Korea, shows the highest degree of water pollution compared to the other major rivers. The construction and opening of two weirs, Seungchon and Juksan, induced fluctuations in the hydrologic conditions and water quality of the river. To investigate the water quality changes caused by the opening of the weir in 2017, this study analyzed the water quality data using the non-parametric Wilcoxon signed-rank test and the three-dimensional spatiotemporal plots. The non-parametric statistical test results showed that the concentration of all parameters has increased after 2017 at a significance level of 0.05. For the parameters that showed the highest degree of change, chlorophyll-a and suspended solids, the median values have increased by more than 30% after weir opening. Visual analysis additionally showed the spatial changes in the Yeongsan River. Generally, the sites above the Seungchon weir showed higher pollution levels than those above the Juksan weir. In time series, visual analysis results also showed the trend of rising concentration for all water quality parameters, indicating that the opening of two weirs had a significant effect on the change in water quality of the Yeongsan River.

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.631-641
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• 2014

Characteristics of water-level changes in the Temporary Gulpocheon Discharge Channel were identified by observing and analyzing changes in the subterranean water level induced by hydrological stresses the underground aquifer. The subterranean water level refers to the level at which the pressure of subterranean water passing through the corresponding position has an equipotential value that is in equilibrium with the atmospheric pressure at that location. This water level is not fixed but changes in response to hydrological stress. It can be identified by repeatedly measuring the distance from the observation point to the surface of the subterranean water. The subterranean water-level change equation and the variance range of the hydrological curve of subterranean water over 24 hours at the Gimpo-Gimpo National Groundwater Monitoring Network (NGMN) were used as assessment factors. The variance characteristics of the subterranean water at the 18 monitoring system locations were classified into three impact, observational wish, and non-impact. The impact type accounted for 50% of the subterranean water of and accurately reflected the water-level changes due to hydrological stress, showing that distance is the major controlling factor. The observational wish type accounted for 27.8% of the subterranean water, and one of the two assessment factors did not meet the assessment factors. The nonimpact type accounted for 22.2% of the subterranean water. This type satisfied the two assessment factors and represents subterranean water-level changes response to precipitation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.3
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• pp.461-473
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• 2015

Jinhae Bay located in the southern of Korean Peninsular is an important spawning area in Korea. By some preliminary studies it was measured several times that adult Pacific codes (Gadus microcephalus) were passed (swimming layer: 15 to 18 m) over a submerged sea tunnel (sea bottom: about 30 m) rather than another immigration route when the Pacific codes were tagged surgically with an acoustic transmitters and released inside of the Bay. There is a possibility that the Pacific codes and the other fishes use the route on the sea tunnel as an immigration route are affected by a human-generated underwater noise around the sea tunnel due to the sea tunnel traffic. On this study the 25-hour measurements of the underwater noise level by water layer were conducted with a hydrophone attached on a portable CTD and an underwater noise level meter during four seasons, and the acoustical characteristics of the underwater noise was analyzed. The mean traffic volume for one hour at the sea tunnel on the spring was shown the largest value of 1,408 [standard deviation (SD): 855] vehicles among four seasons measurement. The next one was ordered on the autumn [1,145 (SD: 764)], winter [947 (SD: 598)] and summer [931 (SD: 558)] vehicles. Small size vehicle was formed 84.3% of the traffic volume, and ultra-small size, medium size, large size and extra-large size of the vehicle were taken possession of 8.7%, 3.2%, 2.0% and 1.8%, respectively. On the daily change of the noise level in vertical during four seasons the noise level of 5 m-layer was shown the highest value of 121.2 (SD: 3.6) dB (re $1{\mu}Pa$), the next one was 10 m-layer [120.7 (SD: 3.5)], 2 m- and 15 m-layer [120.3 (SD: 3.5 to 3.7)] and 1 m-layer [119.2 (SD: 3.6)] dB (re $1{\mu}Pa$). In relation with the seasonal change of the noise level the average noise level measured during autumn was shown the highest value of 123.9 (SD: 2.6) dB (re $1{\mu}Pa$), the next was during summer [121.4 (SD: 3.2)], spring [118.0 (SD: 3.4)] and winter [116.5 (SD: 5.1)] dB (re $1{\mu}Pa$). In results of eigenray computation when the real bathymetry data (complicate shape of sea bed) was applied the average number of eigenray was 2.68 times (eigenrays: 11.03 rays) higher than those of model bathymetry (flat and slightly sloped sea bottom). When the real bathymetric data toward inside (water depth becomes shallow according to a distance between the source of noise and hydrophone) of the Bay was applied on the eigenrays calculation the number of the eigenray was 1.31 times (eigenrays: 12.49 rays) larger than the real bathymetric data toward outside (water depth becomes deep with respect to the distance). But when the model bathymetric data toward inside of the Bay was applied the number of the eigenray was 1.05 times (eigenrays: 4.21 rays) larger than the model bathymetric data toward outside.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.929-937
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• 2023

This study aims to develop rules for the Determination of Drought Stages at the Local Level based on the drought cases in Gwangju and Jeollanam-do in 2022-2023. Among the eight drought indicators provided, six indicators (Agricultural drought stage (for paddy), Residential & industrial drought stage, SPI-12, Relative agricultural water storage, Residential water consumption change (for domestic use), Residential water consumption change (for non-domestic use) were confirmed to have statistical correlations with the perceptions of local government officials and experts. Additionally, this drought indicator was applied to a decision tree algorithm to develop rules for determining the severity of drought. Although it presented results similar to those of the existing method presented in previous studies, it showed a significant comparative advantage in explaining the temporal and spatial patterns of drought in the Gwangju and Jeollanam-do.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.301-310
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• 2024

The spatial and temporal non-uniform distribution of precipitation makes water management difficult. Due to climate change, nonuniform distribution of precipitation is worsening, and droughts and floods are occurring frequently. Additionally, the intensity of droughts and floods is intensifying, making existing water management systems difficult. From June 2022 to June 2023, most of the water storage rates of major dams in the Yeongsan river and Seomjin river basin were below 30%. In the case of Juam dam, which is the most dependent on water use in the basin, the water storage rate fell to 20.3%, the lowest ever. Pyeongnim dam recorded the lowest water storage rate of 27.3% on May 4, 2023. Due to a lack of precipitation starting in the spring of 2022, Pyeongnim dam was placed at a drought concern level on June 19, 2022, and entered the severe drought level on August 21. Pyeongrim dam and Suyangje(dam) have different operating institutions. Nevertheless, the low water level was not reached at Pyeongnim dam through organic linkage operation in a drought situation. Pyeongnim dam was able to stably supply water to 63,000 people in three counties. In order to maximize the use of limited water resources, we must review ways to move water smoothly between basins and water sources, and prepare for water shortages caused by climate change by establishing a consumer-centered water supply system.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.1-13
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• 2024

This study assessed the efficacy of improving the accuracy of reservoir water level prediction models by employing automated machine learning models and efficient cross-validation methods for time-series data. Considering the inherent complexity and non-linearity of time-series data related to reservoir water levels, we proposed an optimized approach for model selection and training. The performance of twelve models was evaluated for the Obong Reservoir in Gangneung, Gangwon Province, using the TPOT (Tree-based Pipeline Optimization Tool) and four cross-validation methods, which led to the determination of the optimal pipeline model. The pipeline model consisting of Extra Tree, Stacking Ridge Regression, and Simple Ridge Regression showed outstanding predictive performance for both training and test data, with an R² (Coefficient of determination) and NSE (Nash-Sutcliffe Efficiency) exceeding 0.93. On the other hand, for predictions of water levels 12 hours later, the pipeline model selected through time-series split cross-validation accurately captured the change pattern of time-series water level data during the test period, with an NSE exceeding 0.99. The methodology proposed in this study is expected to greatly contribute to the efficient generation of reservoir water level predictions in regions with high rainfall variability.