• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.365-376
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• 2013

The purpose of this study was to evaluate effects of spatio-temporal changes in land uses and rainfall magnitude using the Soil and Water Assessment Tool (SWAT). Prior of application of the model to real-world problem, the model should be calibrated and validated properly. In most modeling approaches, the validation process is done assuming no significant changes occurring at the study watershed between calibration and validation periods, which is not proper assumption for agricultural watersheds. If simulated results obtained with calibrated parameters match observed data with higher accuracy for validation period, this does not always mean the simulated result represents rainfall-runoff, pollutant generation and transport mechanism for validation period because temporal and spatial variables and rainfall magnitude are often not the same. In this study SWAT was applied to Mandae study watershed in Korea to evaluate effects of spatio-temporal changes in landuses using 2009 and 2010 crop data for each field at the watershed. The Nash-Sutcliffe model efficiency (NSE) values for calibration and validation with either 2009 or 2010 was evaluated and the NSE value for calibration with 2009 and calibration with 2010 were compared. It was found that if there is substantial change in land use and rainfall, model calibration period should be determined to reflect those changes. Through these approaches, inherent limitation of the SWAT, which does not consider changes in land uses over the simulation period, was investigated. Also, Effects of changes in rainfall magnitude during calibration process were analyzed.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.264-274
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• 2009

Concentration of Air Quality Models (CMAQ) has a deep connection with emissions and wind fields. In particular the wind field is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. The purpose of this study is to examine the impact of interpolation on Air quality model. This study was designed to evaluate enhancement of MM5 and CMAQ predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station and the MODerate resolution Imaging Spectroradiometer (MODIS). The alternative meteorological fields predicted with and without MODIS data were used to simulate spatial and temporal variations of ozone in combined with CMAQ on June 2006. The result of this study indicated that data assimilation using MODIS data provided an attractive method for generating realistic meteorological fields and dispersion fields of ozone in the Korea peninsular, because MODIS data in 10 km domain are grid horizontally and vertically. In order to ensure the success of Air quality model, it is necessary to FDDA using MODIS data.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.04a
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• pp.63-66
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• 2003

This study applied a hydrogeological field survey and isotope investigation to identify source locations and delineate pathways of groundwater contamination by nitrogen compounds. The infiltration and recharge processes were analyzed with groundwater-level fluctuation data and oxygen-hydrogen stable isotope data. The groundwater flow pattern was investigated through groundwater flow modeling and spatial and temporal variation of oxygen isotope data. Based on the flow analysis and nitrogen isotope data, source types of nitrate contamination in groundwater are identified. Groundwater recharge largely occurs in spring and summer due to precipitation or irrigation water in rice fields. Based on oxygen isotope data and cross-correlation between precipitation and groundwater level changes, groundwater recharge was found to be mainly caused by irrigation in spring and by precipitation at other times. The groundwater flow velocity calculated by a time series of spatial correlations, 231 m/yr, is in good accordance with the linear velocity estimated from hydrogeologic data. Nitrate contamination sources are natural and fertilized soils as non-point sources, and septic and animal wastes as point sources. Seasonal loading and spatial distribution of nitrate sources are estimated by using oxygen and nitrogen isotopic data.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.61-72
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• 2000

The purpose of this study is to improve the method of evaluating groundwater recharge by using grid-based soil moisture routing technique. A model which predicts temporal variation and spatial distribution of soil moisture on a daily time step was developed. The model uses ASCII-formatted map data supported by the irregular gridded map of the GRASS(Geographic Resources Analysis Support System)-GIS and can generate daily and monthly spatial distribution map of surface runoff, soil moisture content, evapotranspiration within the watershed. The model was applied to Ipyunggyo watershed($75.6\;\textrm{km}^2$) located in the upstream of Bocheongchun watershed. Seven maps; DEM(Digital Elevation Mode]), stream, flow path, soil, land use, Thiessen network and free groundwater level, were used for input data. Predicted streamflows resulting from two years (l995, 1996) daily data were compared with the observed values at the watershed outlet. The results of temporal variations and spatial distributions of soil moisture are presented by using GRASS GIS. As a final result, the monthly predicted groundwater recharge was presented.sented.

• Journal of Korea Water Resources Association
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• v.38 no.5 s.154
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• pp.345-354
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• 2005

Time Domain Reflectometry (TDR) with multiplex system has been installed to configure the spatial and temporal characteristics of soil moisture at the Bumreunsa hillslope of Sulmachun Watershed. An intensive surveying was performed to build a refined digital elevation model (DEM) and flow determination algorithms with inverse surveying have been applied to establish an efficient soil moisture monitoring system. Soil moisture data were collected through intensive monitoring during 380 hrs in November of 2003. Soil moisture data shows corresponding variation characteristics of soil moisture on the upper, middle and lower parts of the hillslope which were classified from terrain analysis. Measured soil moisture data have been discussed on the context of physical process of hydrological modeling.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1189-1192
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• 2005

Due to their slow degradation properties, hydrophobic organic contaminants in estuarine sediment have been a concern for risks to human health and aquatic organisms. Studies of fate and transport of these contaminants in estuaries are further complicated by the fact that hydrodynamics and sediment transport processes in these regions are complex, involving processes with various temporal and spatial scales. In order to simulate and quantify long-term attenuation of Polycyclic Aromatic Hydrocarbons (PAH) in the Elizabeth River, VA, we develop a modeling approach, which employs the U.S. Environmental Protection Agency's water quality model, WASP, and encompasses key physical and chemical processes that govern long-term fate and transport of PAHs in the river. In this box-model configuration, freshwater inflows mix with ocean saline water and tidally averaged dispersion coefficients are obtained by calibration using measured salinity data. Sediment core field data is used to estimate the net deposition/erosion rate, treating only either the gross resuspension or deposition rate as the calibration parameter. Once calibrated, the model simulates fate and transport PAHs following the loading input to the river in 1967, nearly 4 decades ago. Sediment PAH concentrations are simulated over 1967-2022 and model results for Year 2002 are compared with field data measured at various locations of the river during that year. Sediment concentrations for Year 2012 and 2022 are also projected for various remedial actions. Since all the model parameters are based on empirical field data, model predictions should reflect responses based on the assumptions that have been governing the fate and sediment transport for the past decades.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.445-460
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• 2011

The objective of this study was to construct and assess the applicability of the EFDC model for Saemangeum Reservoir as a 3D hydrodynamic and water quality modeling tool that is necessary for the effective management of water quality and establishment of conservation measures. The model grids for both reservoir system only and reservoir-ocean system were created using the most recent survey data to compare the effects of different downstream boundary conditions. The model was applied for the simulations of temperature, salinity, water quality variables including chemical oxygen demand (COD), chlorophyll-a (Chl-a), phosphorus and nitrogen species and algal biomass, and validated using the field data obtained in 2008. Although the model reasonably represented the temporal and spatial variations of the state variables in the reservoir with limited boundary forcing data, the salinity level was underestimated in the middle and upstream of the reservoir when the flow data were used at downstream boundaries; Sinsi and Garyuk Gates. In turn, the error caused to increase the bias of water quality simulations, and inaccurate simulation of density flow regime of river inflow during flood events. It is likely because of the loss of momentum of sea water intrusion at downstream boundaries. In contrast to flow boundary conditions, the mixing between sea water and freshwater was well reproduced when open water boundary condition was applied. Thus, it is required to improve the downstream boundary conditions that can accommodate the real operations of the sluice gates.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.377-397
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• 2005

A new box model is proposed to describe the dynamic trend of the spatially averaged concentrations of pollutants over a large urban area such as metropolitan Seoul. Being averaged temporally and spatially over a thresh-hold scales, the dynamics of the pollutant concentration becomes simple enough that the governing equation can be expressed in an explicit algebraic form as a function of several meteorological factors and the pollutant emission rate. The single most important meteorological factor is the wind speed dominating the daily variations of the pollutant concentrations. Given the meteorological data from the surface station in the metropolitan Seoul, the model concentration shows excellent agreement with observations from January 1, 1990 to December 31, 2000: the modeling uncertainty, for example, of $NO_2$ concentrations, defined as mean differences between the model concentrations and observations is $16\%$ of the model concentrations. Even for $PM_{10}$ of which secondary sources are considered to be very important and simple box model is irrelevant to, the model performance turns out good, modeling uncertainty being about $32\%$.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.194-204
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• 2012

Measuring task complexity of movement skill is an important factor to evaluate a difficulty of learning and/or imitating a task for autonomous robots. Although many complexity-measures are proposed in research areas such as neuroscience, physics, computer science, and biology, there have been little attention on the robotic tasks. To cope with measuring complexity of robotic task, we propose an information-theoretic measure for task complexity of movement skills. By modeling proprioceptive as well as exteroceptive sensor data as multivariate Gaussian distribution, movements of a task can be modeled as probabilistic model. Additionally, complexity of temporal variations is modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on the real robotic movement tasks.