• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.719-730
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• 2021

The objective of this study is to develop the water quality and aquatic ecosystem model for Andong lake using SWAT-WET (Soil and Water Assessment Tool-Water Ecosystem Tool) and to evaluate the applicability of WET. To quantify the pollutants load flowing into Andong lake, a watershed model of SWAT was constructed for Andong Dam basin (1,584 km²). The calibration results for Dam inflow and water quality loads (SS, T-N, T-P) were analyzed that average R² was more than 0.76, 0.69, 0.84, and 0.60 respectively. The calibrated SWAT results of streamflow and nutrients concentration was used into WET input data. WET was calibrated and validated for water temperature, dissolved oxygen, and water quality concentration (T-N, T-P) of Andong lake. The WET calibrated results was analyzed that PBIAS was +19%, -13%, +4%, and +26.5% respectively and showed that it was simulated to a significant level compared with the observation data. The observed dry weight (gDW/m²) of zoobenthos was less than 0.5, but the average value of simulation was analyzed to be 0.8, which is because the WET model considers zoobenthos with a broader concept. Although accurate calibration is difficult due to the lack of observed data, SWAT-WET can analyze the effects of environmental change in the upstream watershed on the lake based on long-term simulation based on watershed model. Therefore, the results of this study can be used as basic data for managing the aquatic environment of Andong lake.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.2
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• pp.102-109
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• 2021

In this study, the effect of forage sources in the total mixed ration (TMR) on in vitro goat rumen fermentation was investigated. Rice straw (RS), Italian ryegrass (IRG), timothy (TIM), and alfalfa (ALF) were used as forage sources. Each forage source was mixed with a commercial goat concentrate diet in the ratio of 1:1. Total 4 TMR were prepared. Rumen simulated in vitro fermentation using goat rumen fluid collected from the slaughterhouse was conducted until 72^th. For fermentation parameters, gas production (GP), volatile fatty acids (VFAs), and ammonia nitrogen (NH₃-N) were examined. All assays were performed at 24^th, 48^th, and 72^th h of incubation individually. Contents of crude protein and non-fibrous carbohydrate were greater in the order of RS < IRG < TIM < ALF. Significant treatment effects were found in valerate and NH₃-N at 24^th h of incubation (p<0.05). ALF showed the greatest contents of them and RS was the lowest. At 48^th incubation, a significant effect was detected at GP (p<0.05) and RS was greater than others. However, GP of RS was lower than others at 72^th. Significant effects on Total VFA, butyrate, and valerate productions were found at 72^th h of incubation (p<0.05). ALF showed the greatest production. Methane production from all treatments was not significantly different for each incubation time (p>0.05). The present study provided primary information on how goat rumen fermentation responds to different nutrient contents and forage sources of TMR. And the information could be used for the design or optimizing economical diet formulation for goats.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.47-60
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• 2021

Recently, as the occurrence frequency of sudden floods due to climate variability increased, the damage of aging chuteway slabs of spillway are on the rise. Accordingly, a wide array of field survey, hydraulic experiment and numerical simulation have been conducted to find the cause of damage on chuteway slabs. However, these studies generally reviewed the flow characteristics and distribution of pressure on chuteway slabs. Therefore the derivation of damage on chuteway slabs was relatively insufficient in the literature. In this study, the cavitation erosion and hydraulic jacking were assumed to be the causes of damage on chuteway slabs, and the phenomena were reproduced using 3D numerical models, FLOW-3D and COMSOL Multiphysics. In addition, the cavitation index was calculated and the von Mises stress by uplift pressure distribution was compared with tensile and bending strength of concrete to evaluate the possibility of cavitation erosion and hydraulic jacking. As a result of numerical simulation on cavitation erosion and hydraulic jacking under various flow conditions with complete opening gate, the cavitation index in the downstream of spillway was less than 0.3, and the von Mises stress on concrete was 4.6 to 5.0 MPa. When von Mises stress was compared with tensile and bending strength of concrete, the fatigue failure caused by continuous pressure fluctuation occurred on chuteway slabs. Therefore, the cavitation erosion and hydraulic jacking caused by high speed flow were one of the main causes of damage to the chuteway slabs in spillway. However, this study has limitations in that the various shape conditions of damage(cavity and crack) and flow conditions were not considered and Fluid-Structure Interaction (FSI) was not simulated. If these limitations are supplemented and reviewed, it is expected to derive more efficient utilization of the maintenance plan on spillway in the future.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.993-1003
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• 2023

Due to the increasing greenhouse gas emissions, the global mean temperature has risen by 1.1℃ compared to pre-industrial levels, and significant changes are expected in functioning of water supply systems. In this study, we assessed impacts of climate change and instreamflow management on water supply reliability in the Geum River basin, Korea. We proposed univariate climate response functions, where mean precipitation and potential evaporation were coupled as an explanatory variable, to assess impacts of climate stress on multiple water supply reliabilities. To this end, natural streamflows were generated in the 19 sub-basins with the conceptual GR6J model. Then, the simulated streamflows were input into the Water Evaluation And Planning (WEAP) model. The dynamic optimization by WEAP allowed us to assess water supply reliability against the 2020 water demand projections. Results showed that when minimizing the water shortage of the entire river basin under the 1991-2020 climate, water supply reliability was lowest in the Bocheongcheon among the sub-basins. In a scenario where the priority of instreamflow maintenance is adjusted to be the same as municipal and industrial water use, water supply reliability in the Bocheongcheon, Chogang, and Nonsancheon sub-basins significantly decreased. The stress tests with 325 sets of climate perturbations showed that water supply reliability in the three sub-basins considerably decreased under all the climate stresses, while the sub-basins connected to large infrastructures did not change significantly. When using the 2021-2050 climate projections with the stress test results, water supply reliability in the Geum River basin was expected to generally improve, but if the priority of instreamflow maintenance is increased, water shortage is expected to worsen in geographically isolated sub-basins. Here, we suggest that the climate response function can be established by a single explanatory variable to assess climate change impacts of many sub-basin's performance simultaneously.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• Maritime Security
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• v.7 no.1
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• pp.31-60
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• 2023

This study proposes a new convergence weapon system that combines the covert placement and detection abilities of a self-propelled mobile mine with the rapid tracking and attack abilities of supercavitating rocket torpedoes. This innovative system has been designed to counter North Korea's new underwater weapon, 'Haeil'. The concept behind this convergence weapon system is to maximize the strengths and minimize the weaknesses of each weapon type. Self-propelled mobile mines, typically placed discreetly on the seabed or in the water, are designed to explode when a vessel or submarine passes near them. They are generally used to defend or control specific areas, like traditional sea mines, and can effectively limit enemy movement and guide them in a desired direction. The advantage that self-propelled mines have over traditional sea mines is their ability to move independently, ensuring the survivability of the platform responsible for placing the sea mines. This allows the mines to be discreetly placed even deeper into enemy lines, significantly reducing the time and cost of mine placement while ensuring the safety of the deployed platforms. However, to cause substantial damage to a target, the mine needs to detonate when the target is very close - typically within a few yards. This makes the timing of the explosion crucial. On the other hand, supercavitating rocket torpedoes are capable of traveling at groundbreaking speeds, many times faster than conventional torpedoes. This rapid movement leaves little room for the target to evade, a significant advantage. However, this comes with notable drawbacks - short range, high noise levels, and guidance issues. The high noise levels and short range is a serious disadvantage that can expose the platform that launched the torpedo. This research proposes the use of a convergence weapon system that leverages the strengths of both weapons while compensating for their weaknesses. This strategy can overcome the limitations of traditional underwater kill-chains, offering swift and precise responses. By adapting the weapon acquisition criteria from the Defense force development Service Order, the effectiveness of the proposed system was independently analyzed and proven in terms of underwater defense sustainability, survivability, and cost-efficiency. Furthermore, the utility of this system was demonstrated through simulated scenarios, revealing its potential to play a critical role in future underwater kill-chain scenarios. However, realizing this system presents significant technical challenges and requires further research.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.400-412
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• 2023

In this study, the biogeochemistry management (BGC-MAN) model was applied to North and South Korea pine and oak forest stands to evaluate the Net Primary Productivity (NPP), an indicator of forest ecosystem productivity. For meteorological information, historical records and East Asian climate scenario data of Shared Socioeconomic Pathways (SSPs) were used. For vegetation information, pine (Pinus densiflora) and oak(Quercus spp.) forest stands were selected at the Gwangneung and Seolmacheon in South Korea and Sariwon, Sohung, Haeju, Jongju, and Wonsan, which are known to have tree nurseries in North Korea. Among the biophysical information, we used the elevation model for topographic data such as longitude, altitude, and slope direction, and the global soil database for soil data. For management factors, we considered the destruction of forests in North and South Korea due to the Korean War in 1950 and the subsequent reforestation process. The overall mean value of simulated NPP from 1991 to 2100 was 5.17 Mg C ha^-1, with a range of 3.30-8.19 Mg C ha^-1. In addition, increased variability in climate scenarios resulted in variations in forest productivity, with a notable decline in the growth of pine forests. The applicability of the BGC-MAN model to the Korean Peninsula was examined at a time when the ecosystem process-based models were becoming increasingly important due to climate change. In this study, the data on the effects of climate change disturbances on forest ecosystems that was analyzed was limited; therefore, future modeling methods should be improved to simulate more precise ecosystem changes across the Korean Peninsula through process-based models.