• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.508-520
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• 2020

Dam reservoirs have been reported to contribute significantly to global carbon emissions, but unlike natural lakes, there is considerable uncertainty in calculating carbon emissions due to the complex of emission pathways. In particular, the method of calculating carbon dioxide (CO2) net atmospheric flux (NAF) based on a simple gas exchange theory from sporadic data has limitations in explaining the spatiotemporal variations in the CO2 flux in stratified reservoirs. This study was aimed to analyze the spatial and temporal CO2 distribution and mass balance in Daecheong Reservoir, located in the mid-latitude monsoon climate zone, by applying a two-dimensional hydrodynamic and water quality model (CE-QUAL-W2). Simulation results showed that the Daecheong Reservoir is a heterotrophic system in which CO2 is supersaturated as a whole and releases CO2 to the atmosphere. Spatially, CO2 emissions were greater in the lacustrine zone than in the riverine and transition zones. In terms of time, CO2 emissions changed dynamically according to the temporal stratification structure of the reservoir and temporal variations of algae biomass. CO2 emissions were greater at night than during the day and were seasonally greatest in winter. The CO2 NAF calculated by the CE-QUAL-W2 model and the gas exchange theory showed a similar range, but there was a difference in the point of occurrence of the peak value. The findings provide useful information to improve the quantification of CO2 emissions from reservoirs. In order to reduce the uncertainty in the estimation of reservoir carbon emissions, more precise monitoring in time and space is required.

• Journal of IKEEE
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• v.28 no.2
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• pp.199-203
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• 2024

In this paper, we propose variations in the kernel size of 1D convolutional layers for single-frame supervised temporal action localization. Building upon the existing method, which utilizes two 1D convolutional layers with kernel sizes of 3 and 1, we introduce an approach that adjusts the kernel sizes of each 1D convolutional layer. To validate the efficiency of our proposed approach, we conducted comparative experiments using the THUMOS'14 dataset. Additionally, we use overall video classification accuracy, mAP (mean Average Precision), and Average mAP as performance metrics for evaluation. According to the experimental results, our proposed approach demonstrates higher accuracy in terms of mAP and Average mAP compared to the existing method. The method with variations in kernel size of 7 and 1 further demonstrates an 8.0% improvement in overall video classification accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.213-216
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• 2003

Efforts for better understanding of the interaction between groundwater recharge and thermal regime of the subsurface medium is gaining momentum for its diverse applications in water resources. A numerical model is developed to simulate temperature variations of the subsurface under time varying groundwater recharge. The model utilizes MacCormack scheme for finite difference approximation of the partial differential equation describing the conductive and advective heat transport. For the estimation of recharge rate, optimization of the model is realized by searching for the unknown parameters which minimize the root-mean-square error between simulated and measured temperatures. Simulation results for 22-year time series data of temperature measurements reveal that the proposed model can accurately simulate subsurface temperature variations resulting from the redistribution of the heat due to the movement of water and it can also estimate temporal variations of recharge. Seasonal variations of recharge and a linear relationship between precipitation and recharge are clearly reflected in the simulated results.

• Journal of Korean Society of Rural Planning
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• v.2 no.2
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• pp.91-102
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• 1996

Monitoring techniques for afro-ecological environments were studied, Hydrologic and ecological components in conjunction with water quality were monitored in the Balkan watershed. The hydrologic monitoring program consists of four water level gauging stations along creeks and stream at the watershed having 26.5 km2. Stage - storage relationship of reservoir, rainfall amount of the watershed, and rating curve of the stream gauging stations were established. Soil type, land use, hydrologic soil group, population and economic activities within the watershed were surveyed. Water quality data from the streams were sampled weekly and chemical analysis was conducted. Temporal variations of water quality were investigated and water quality map of each reach of stream was made to identify spatial variations. Seasonal and spatial variations of vegetation densities along stream in the watershed were investigated using grid, Density variations of insect species such as arthropod, flying insect, spider spices, rice insects were also monitored to determine seansonal surveying density. These monitored data will be used to develop monitoring techi%ues and afro - ecological environment models.

• Advances in environmental research
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• v.6 no.1
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• pp.53-65
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• 2017

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of river pollution due to natural or anthropogenic inputs of point and non-point sources. In this study, surface water quality data for 15 physico-chemical parameters collected from 7 monitoring stations in a river during the years from 2014 to 2016 were analyzed. The principal component analysis technique was employed to evaluate the seasonal correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing seasonal variations of river water quality. Analysis shows that a parameter that is most important in contributing to water quality variation for one season may not be important for another season except alkalinity, which is always the most important parameters in contributing to water quality variations for all three seasons.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.305-312
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• 2011

Because groundwater recharge shows spatial-temporal variability due to climatic conditions, it is necessary to investigate land use and hydrogeological heterogeneity, and estimate the spatial variability in the daily recharge rate based on an integrated surface-groundwater model. The integrated SWAT-MODFLOW model was applied to compute physically based daily groundwater recharge in the Jincheon region. The temporal variations in estimated recharge were calibrated using the observed groundwater head at several National Groundwater Monitoring Stations and at automatic groundwater-monitoring sites constructed during the Basic Groundwater Investigation Project (2009-2010). For the whole Mihocheon watershed, including the Jincheon region, the average groundwater recharge rate is estimated to be 20.8% of the total rainfall amount, which is in good agreement with the analytically estimated recharge rate. The proposed methodology will be a useful tool in the management of groundwater in Korea.

• Journal of Environmental Science International
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• v.13 no.1
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• pp.27-36
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• 2004

Present study analyzed the temporal and spatial characteristics of PM10 pollution in Metropolitan Daegu area based on air pollution monitoring station data and measurements of PM10 concentrations in background area in order to provide essential data for efficient PM10 pollution management. The significant variation of spatial and temporal PM10 concentrations in Daegu area was observed during the study years. The highest maximum PM10 concentration(332 $\mu\textrm{g}$/㎥), average concentration(88 $\mu\textrm{g}$/㎥) and frequency exceeding PM10 daily standard(150 $\mu\textrm{g}$/㎥) were all observed in Namsandong located near a major roadway. The hourly and weekly variations of PM10 concentrations had different pattern for the measurement sites. The monthly and seasonal concentrations exhibited a notable characteristic： the maximum concentration was obtained in spring season, most likely due to Yellow sand effects. Furthermore, this temporal variation of PM10 pollution varied with study site. Meanwhile, the PM10 values measured at the monitoring site, Manchondong, were comparable with those of a control site. The average PM10 concentration ranged from 23 $\mu\textrm{g}$/㎥ to 115 $\mu\textrm{g}$/㎥ with a mean value of 53 $\mu\textrm{g}$/㎥ in the former site and from 22 $\mu\textrm{g}$/㎥ to 91 $\mu\textrm{g}$/㎥ with a mean value of 45 $\mu\textrm{g}$/㎥ in the latter site.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.5-13
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• 1995

In order to estimate the variability of the wave propagation loss (PL) du e to hourly variations of the sound speed profiles (SSPs), we conducted oceanographic measurements every hour for 39 hours in October 1993 in the Korea Strait. Currents and meteorological data were measured simultaneously to examine the causes of the temporal variations of temperatures. During the experiment, the temporal variations of temperatures in the surface layer highly depend on the water mass transport from adjacent seas. The PL for low frequency (75-300 Hz) is calculated using the parabolic equation scheme and averaged over the whole water depth. The hourly variation of the SSP may cause a PL difference of up to 10 dB over a 30-50 km range. The variability of PL, represented by standard deviation for the 39 SSPs, is as large as 3 dB over a 50 km range.

• Fisheries and Aquatic Sciences
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• v.12 no.2
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• pp.130-137
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• 2009

Temporal variations of seaweed biomass and coverage were seasonally examined at Ongdo in the Yellow Sea, Korea from August 2006 to April 2008. Average seaweed biomass was 245.79 g/$m^2$ in wet weight and coverage was 16.49% with seasonal variations from 13.97% in spring to 18.55% in autumn. Seaweeds were distributed across the shore gradient from the high intertidal to 10m depth in the subtidal zone. Biomass was always higher in the subtidal zone (310.24 g/$m^2$) than in the intertidal zone (181.35 g/$m^2$). Of total seaweed biomass, 76.52% (first year) and 80.32% (second year) occurred from the low intertidal zone, down to depth of 1 to 5m. Gelidium amansii had the highest importance value and biomass, and sub dominant species were Chondrus ocellatus and Chondria crassicaulis. Coarsely-branched seaweeds comprised the highest proportion of biomass (214.84 g/$m^2$, or 87.41% of the total biomss). Seasonal variations in algal biomass were largely explained by fluctuations in the biomass of coarsely-branched and thick-leathery forms. In conclusion, seaweed biomass of Ongdo shore was very low because of perennial G. amansii showing low biomass as compared to kelp or Sargassum spp. However, these results indicate Ongdo is good place to grow seaweeds because coarsely-branched form seaweeds including G. amansii are dominant at unpolluted and clean environment.