• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.75-84
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• 2023

Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Journal of the Korean GEO-environmental Society
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• v.25 no.6
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• pp.5-12
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• 2024

Currently, a grouting method that minimizes damage to the reservoir embankment by injecting solidification agent at low pressure is commonly used to ensure waterproofing and safety of the embankment, but the use of solidification agents can cause issues, such as a decrease in durability and a lack of clear method for determining the mixing ratio. In this study, when the base ground and solidification agent were stirred and mixed at various weight mixing ratios, the permeability coefficient and strength of the mixture were confirmed through laboratory tests, and the optimal mixing ratio was suggested through analysis of the test results. The specimen for the laboratory test was produced considering the mixing ratio of the solidification agent. The specimen for the permeability coefficient test was tested by producing one each of cohesionless and cohesive soil for a mixing amount of 1.5 kN/m³ of solidification agent, and the permeability test results confirmed that the water barrier performance was secured below the permeability coefficient value required by various design criteria. A total of 24 specimens for the strength test were produced, 3 for each of 5 mixing amounts for cohesive soil and 3 mixing amounts for cohesionless soil. The strength test results showed that the uniaxial compressive strength tends to increase linearly with increasing curing time for both cohesionless soil and cohesive soil when the mixing amount is less than 2.0 kN/m³. Therefore, the optimal mixing ratio applied to the site is determined to be mixing amount of 1.5 kN/m³ and 2.0 kN/m³. Finally, numerical analysis reflecting test results was conducted on design case for improvement projects for aging reservoirs embankment to verify the water barrier performance and safety improvement effects.

• Journal of Marine Bioscience and Biotechnology
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• v.16 no.1
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• pp.63-86
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• 2024

This study analyzed the distribution, diversity, and density variation of algal clusters in a freshwater reservoir from an oceanic island and a traditional inland water system to gain insights on future marine freshwater resource management. In the Paldang water system (Han River), despite the upstream Paldang Dam and the downstream Jamsil underwater reservoir being in the same meteorological zone, their algae density patterns varied inversely. The distinct algal cluster structure (diversity/dominance) of Paldang was altered in the downstream reservoir, suggesting that physical devices aid algae management in traditional water systems. In contrast, 24 out of 35 genera (63.2%) identified in the Jeolgol Reservoir (Baeknyeong Island) were unique, lacking regulatory mechanisms, and existing in a complex ecotone. The desmid Chlorophyceae Cosmarium, adapted to higher photosynthetic stress and low temperatures, dominated in January (38.04%) and August (86.45%) during the periods of extreme photosynthetic stress. Jeolgol's annual algal cluster structure (H' 2.097; D 0.259; S' 35) demonstrated higher stability than Paldang (H' 1.125; D 0.448; S' 13) and the Jamsil underwater reservoir (H' 1.078; D 0.469; S' 12), maintaining an H' above 1.5 even during midwinters. No evidence of TN/TP inflow from surrounding soils was observed, even during torrential rainfalls, with phosphorus being the limiting factor for algal growth. TOC, BOD, chlorophyll-a, and turbidity peaked during Cosmarium bloom. Future climate change is expected to cause fluctuations in algal clusters and related water quality factors. The complex transitional nature of the Jeolgol Reservoir, its algal diversity, and the interspecies interactions contribute to the high stability of its algal community.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Korean Journal of Environment and Ecology
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• v.38 no.3
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• pp.324-337
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• 2024

Aquatic macrophytes are important factors in determining species diversity and abundance of cladocerans, but the effects of cladocerans on plant species composition or structure have not been fully considered. In South Korea, wetlands and reservoirs that are prone to covering aquatic macrophytes are scattered across the country, so it is necessary to consider on aquatic macrophytes study, when aquatic animals including cladoceran were studied. in this study, the species and abundance of cladocerans community in six microhabitat types are investigated, and based on these results, habitat conservation and efficient management are suggested. The high species numbers and abundance of cladocerans communities were found in mixed plant communities consisting of free-floating, floating-leaved, and submerged plants. The inclusion of submerged plants in plant communities contributes significantly to the complexity of habitat structures, and may increase species and abundance of cladocenran communities. This can be compared to a plant community consisting only of free-floating and floating-leaved plants in the absence of submerged plants, thereby identifying the efficiency of submerged plants. In the mixed plant communities, species diversity was the highest due to the emergence of cladoceran species (Graptoleveris testudinaria, Ilyocryptus spinifer, and Leydigia acanthococcides) absent from other plant communities. The gradual increase in the biomass (g) of submerged plants in the mixed plant communities significantly increased the species numbers and abundance of cladoceran communities (p<0.05). This is strong evidence that the increase of submerged plants in mixed plant communities has a positive effect on efficiency as a habitat for cladocerans. Although submeged plants do not contribute significantly to their landscape/aesthetic value because they are submerged in water, they have the effect of increasing species diversity in terms of biology, so they should be considered important when creating/restoring wetlands.

• Korean Journal of Environmental Agriculture
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• v.22 no.1
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• pp.16-25
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• 2003

Manun Reservoir, located in Andong district has the capacity of 2 million tons in irrigation water supply with the drainage area of $23.8\;km^2$. Manun Reservoir is over fifty year old, and shallow in depth. The ratio of drainage area (DA) to reservoir surface area (SA) as an effective physical parameter on water quality was 56.1 and was higher than those of other agricultural reservoirs. The ratio of reservoir storage (ST) to SA in Manun Reservoir was 4.79, and the mean depth was below 8m. Both ratios of DS/SA, total area (TA)/ST and ST/SA in Manun Reservoir were relatively higher than those in other agricultural reservoir and natural lakes in Korea. These physical parameters in Manun Reservoir, however, had a eutropic potential significance. Average of COD, IN, and TP in Manun Reservoir were 11.1 mg/L 1.426 mg/L, 0.093 mg/L, respectively. In the inflow stream of Manun Reservoir, the TN ($1.426{\sim}3.809\;mg/L$) was higher than those in reservoir. Only Lyngbya spp. was dominant in phytoplankton for this study period and Gymnodinium spp., Peridinium spp., and Cryptomonas spp. were dominant in zooplankton. According to the Carlson's trophic status index, Mnnun Reservoir was eutrophic in 1996, 1997, and 1999, and hypertrophic in 1998.

• 한국석유지질학회:학술대회논문집
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• autumn
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• pp.28-46
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• 2001

Natural gas is a mixture of hydrocarbon gases and impurities such as nitrogen, hydrogen sulfide, and carbon dioxide and a clean energy producing no pollution materials for combustion. Currently, the demand of the natural gas is rapidly increasing due to worldwide environmental problems. According to Hubbert's study in the past, the natural gas was predicted as rapidly depleted resources, and then the results led to high gas price and limitation of usage during 1980s. Afterward, the study of natural gas resources based on geology identified the additional natural gas resources that were not considered in Hubbert's study. They are unconventional gas, additional resources in the existed reservoirs, and natural gas in deep subsurface areas. Such additional resouces made the future of natural gas bright and pormised low and stable gas price in the future. Deep natural gas is defined as the gas existing at or below 15,000ft$(4,752{\cal}m)$ in depth from the surface. According to the study from the U.S. Geological Survey(USGS) in 1995, 1,412 TCF of technically recoverable natural gas was remained to be discovered or developed in the onshore of United States. A significant part of that resource base, 114 TCF, exists at deep sedimentary basins, and it shows wide distribution with various geological environments. In 1995, the deep gas contributed to $6.7\% of total supply amount of natural gas in the United States and is expected to be $18.7\% by 201.5. However, the development of the deep gas is a high risky business due to expensive investment and high portion of dry holes, although it is developed. Thus, for developing the deep gas economically, it is necessary to overcome many technical challenges. In this paper, for increasing success rate of the deep gas, 1) geologic and compositional characteristics, and production cost have been analyzed according to depth, 2) technical problems related to deep gas production have been summarized, and 3) finally future study areas for increasing application of the deep gas have been suggested. For reference, this paper was written based on the study results from USGS and Gas Research Institute(GRI), for the United States is doing the most active R&D in the deep gas area, and thus, has many reliable data.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.80-87
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• 2010

This study was conducted to develop a reservoir modelling workflow to reproduce the heterogeneous distribution of effective permeability that impacts on the performance of SAGD (Steam Assisted Gravity Drainage), the in-situ bitumen recovery technique in the Athabasca Oil Sands. Lithologic facies distribution is the main cause of the heterogeneity in bitumen reservoirs in the study area. The target formation consists of sand with mudstone facies in a fluvial-to-estuary channel system, where the mudstone interrupts fluid flow and reduces effective permeability. In this study, the lithologic facies is classified into three classes having different characteristics of effective permeability, depending on the shapes of mudstones. The reservoir modelling workflow of this study consists of two main modules; facies modelling and permeability modelling. The facies modelling provides an identification of the three lithologic facies, using a stochastic approach, which mainly control the effective permeability. The permeability modelling populates mudstone volume fraction first, then transforms it into effective permeability. A series of flow simulations applied to mini-models of the lithologic facies obtains the transformation functions of the mudstone volume fraction into the effective permeability. Seismic data contribute to the facies modelling via providing prior probability of facies, which is incorporated in the facies models by geostatistical techniques. In particular, this study employs a probabilistic neural network utilising multiple seismic attributes in facies prediction that improves the prior probability of facies. The result of using the improved prior probability in facies modelling is compared to the conventional method using a single seismic attribute to demonstrate the improvement in the facies discrimination. Using P-wave velocity in combination with density in the multiple seismic attributes is the essence of the improved facies discrimination. This paper also discusses sand matrix porosity that makes P-wave velocity differ between the different facies in the study area, where the sand matrix porosity is uniquely evaluated using log-derived porosity, P-wave velocity and photographically-predicted mudstone volume.

• Korean Journal of Environmental Agriculture
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• v.32 no.1
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• pp.9-16
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• 2013

BACKGROUND: Eutrophication occurs occasionally in reservoirs around lake in summer and early autumn. Lakeside macrophyte which is one of internal pollutants effects on water quality when it is submerged during rainy season. To improve water quality of water supply source in Boknae reservoir around Juam lake, characteristics of nutrient(N, P) uptake and release by submerged plants were investigated. METHODS AND RESULTS: In order to establish the management plan of submerged plants in Boknae reservoir around Juam lake, water level, rainfall, flooding and non-flooding areas, biomass of dominant plants, contents of nitrogen and phosphorus were investigated during 7 months(August, 2010 through February, 2011). Dominant plants were Miscanthus sacchariflorus(MISSA) and Carex dimorpholepis(CRXDM) in Boknae reservoir. Total plant area of Boknae reservoir in August, 2010 was 987,872 $m^2$. In Boknae reservoir, flooding occurred from August until February caused by rainfall during rainy season. The total amounts of nitrogen and phosphorus uptakes by MISSA were 247 and 22 kg/total reservoir area, respectively. By CRXDM, the total amounts of nitrogen and phosphorus uptakes were 11,340 and 1,231 kg/total reservoir area, respectively. The total amounts of nitrogen and phosphorus residues by MISSA were 34 and 11 kg/total reservoir area, respectively. By CRXDM, the total amounts of nitrogen and phosphorus residues were 491 and 68 kg/total reservoir area, respectively. CONCLUSION(S): Total amounts of nitrogen and phosphorus releases in Boknae reservoir were 12,212 and 1,324 kg/total reservoir area, respectively. The results demonstrate that total nitrogen and total phosphorus in water were strongly influenced by submerged plants. Therefore, management plan for submerged plants during rainy season will be needed to improve water quality of water supply source in Boknae reservoir around Juam lake.