• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.64-71
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• 2007

In this study daily flow data is constructed from 8-day intervals flow data which has been measured by Nakdong River Water Environmental Laboratory. TANK model is used to expand 8-day intervals flow data into daily flow data. Using the Sequential quadratic programing, TANK model is auto-calibrated with daily precipitation and 8-day interval flow data. Generated and measured daily surface flow, ground water flow data and ground water recharge are shown to be in a good agreement. From this result, it is thought that this method has the potential to provide daily flow data for calibrating an watershed model such as SWAT.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.224-231
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• 2012

It is necessary to develop flow duration curve (FDC) on each unit watershed in order to analyze flow conditions in the stream for the management of Total Maximum Daily Loads (TMDLs). This study investigated a simple method to develop FDC for the general use of the curve. A simple equation for daily flow estimation was derived from the regression analysis between the 8-day interval flow data of a unit watershed and the daily flow monitoring data of an adjacent upstream region. FDC can be prepared with the calculation of daily flow by the equation for each unit watershed. An annual and a full-period FDC were drawn for each unit watershed in Guem river basin. Standard flow such as low and ordinary flow can be obtained from the annual FDC. Major percentile of flow such as 10, 25, 50, 75 or 90% can be obtained from the full-period FDC. It is considered that this simple method of developing FDC can be utilized more widely for the calculation of standard flow and the assessment of water quality in the process of TMDLs.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.111-119
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• 2012

Applicability of 8 day interval flow data for the calibration of hydrologic model was evaluated using Hydrological Simulation Program-Fortran (HSPF) at Kyungan watershed. The 8 day interval flow monitored by Ministry of Environment located at upstream was calibrated and periodically validated during 2004-2008. And continuous daily flow monitored by Ministry of Construction & Transportation (MOCT) and located at the mouth was compared with daily simulated data during 2004-2007 as spatial validation. Automatic calibration tool which is Model-Independent Parameter Estimation & Uncertainty Analysis (PEST) was applied for HSPF calibration procedure. The model efficiencies for calibration and periodic validation were 0.63 and 0.88, and model performances were fair and very good, respectively, based on criteria of calibration tolerances. Continuous daily stream flow at the mouth of Kyungan watershed were good agreement with observed continuous daily stream flow with showing 0.63 NS value. The PEST program is very useful tool for HSPF hydrologic calibration using non-continuous daily stream flow as well as continuous daily stream flow. The 8 day interval flow data monitored by MOE could be used to calibrate hydrologic model if the continuous daily stream flow is unavailable.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.55-65
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• 2013

It is very difficult to apply stream flow data directly to the management of Total Maximum Daily Loads because there are some differences between the unit watershed and the stream flow monitoring network in their characteristics such as monitoring locations and its intervals. Flow duration curve can be developed by linking the daily flow data of stream monitoring network to 8 day interval flow data of the unit watershed. This study investigated the current operating conditions of the stream flow monitoring network and the flow relationships between the unit watershed and the stream flow monitoring network. Criteria such as missing and zero value data, and correlation coefficients were applied to select the stream flow reference sites. The reference sites were selected in 112 areas out of 142 unit watersheds in 4 river basins, where the stream flow observations were carried out in relatively normal operating conditions. These reference sites could be utilized in various ways such as flow variation analysis, flow duration curve development and so on for the management of Total Maximum Daily Loads.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.6
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• pp.877-884
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• 2011

Although peak loading coefficient is one of critical design factors for sewer works, its detailed affecting factors were not analyzed because of limited data availability. This study analyzed the affecting factors on peak loading coefficient with plenty data obtained from several newly constructed sewer works. Simple and multiple regression analysis methods were adopted to analyze the relationships of each variable with or without data filtering. Drainage population, drainage area, population density, and daily sewage flow per person showed very weak relationships under diverse characteristics of cities. However, daily sewage flow per person showed stronger relationships with peak loading when daily sewage flow per person was splitted into two ranges. Population density (i.e., drainage population divided by drainage area) and daily sewage flow per person considerably were related with peak loading coefficient when daily sewage flow per person is less than about 400 Lpcd.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.595-600
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• 2012

This study is to assess the application of SWAT-CUP(Soil and Water Assessment Tool-Calibration Uncertainty Programs) and to extend daily flow data from 8-day interval flow data which has been measured by Korean Ministry of Environment(MOE). Model sensitivity analysis and calibration were performed with sequential uncertainty fitting(SUIF-2), which is one of the programs interfaced with SWAT, in the package SWAT-CUP. The most sensitive parameters were SOL_K.sol, CH_N2.rte, CN2.mgt, SOL_BD.sol, ALPHA_BF.gw, ALPHA_BNK.rte, SOL_AWC.sol, CH_K2.rte, SFTMP.bsn, GW_DELAY.gw. Following the sensitivity analysis, SWAT-CUP calibration was carried out using 8-day interval flow data from January 2008 to December 2010. The results were then assessed based on the visual agreement and simulated flow plots and the performance statistics generated $R^2$ and NSE which are 0.71 and 0.61 respectively. Results of these statistics indicated that there was a good agreement between the observed and simulated flow. To extend daily flow data from 8-day interval flow data, parameters, which were estimated by SWAT-CUP, re-entered for SWAT model. As a result, the observed flow data were found to reflect the trend of simulated flow data. From these results, it is thought that this method could be used to provide daily flow data using 8-day interval flow data.

• Journal of Environmental Science International
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• v.26 no.8
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• pp.939-953
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• 2017

For the development of flow duration curves for the management of 41 Total Maximum Daily Load (TMDL) units of the Nakdong River basin, first, an equation for estimating daily flow rates as well as the level of correlation (correlation and determination coefficients) was extrapolated through regression analysis of discrete (Ministry of Environment) and continuous (Ministry of Land, Infrastructure and Transportation) measurement data. The equation derived from the analysis was used to estimate daily flow rates in order to develop flow duration curves for each TMDL unit. By using the equation, the annual flow duration curves and flow curves, for the entire period and for each TMDL unit of the basin, were developed to be demonstrated in this research. Standard flow rates (abundant-, ordinary-, low- and drought flows) for major flow duration periods were calculated based on the annual flow duration curves. Then, the flow rates, based on percentile ranks of exceedance probabilities (5, 25, 50, 75, and 95%), were calculated according to the flow duration curves for the entire period and are suggested in this research. These results can be used for feasibility assessment of the set values of primary and secondary standard flow rates for each river system, which are derived from complicated models. In addition, they will also be useful for the process of implementing TMDL management, including evaluation of the target level of water purity based on load duration curves.

• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.343-353
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• 2013

Flow duration curve (FDC) can be developed by linking the daily flow data of stream flow monitoring network to 8-day interval flow data of the unit watersheds for the management of Total Maximum Daily Loads. This study investigated the applicable method for the development of long term FDC with the selection of the stream flow reference sites, and suggested the development of the FDC in 4 river basins. Out of 142 unit watersheds in 4 river basins, 107 unit watersheds were shown to estimate daily flow data for the unit watersheds from 2006 to 2010. Short term FDC could be developed in 64 unit watersheds (45%) and long term FDC in 43 unit watersheds (30%), while other 35 unit watersheds (25%) were revealed to have difficulties in the development of FDC itself. Limits in the development of the long term FDC includes no stream monitoring sites in certain unit watersheds, short duration of stream flow data set and missing data by abnormal water level measurements on the stream flow monitoring sites. To improve these limits, it is necessary to install new monitoring sites in the required areas, to keep up continuous monitoring and make normal water level observations on the stream flow monitoring sites, and to build up a special management system to enhance data reliability. The development of long term FDC for the unit watersheds can be established appropriately with the normal and durable measurement on the selected reference sites in the stream flow monitoring network.

• Journal of Korean Society on Water Environment
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• v.33 no.4
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• pp.394-402
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• 2017

In korea, TMDL is being implemented to manage nonpoint pollution sources as well as point pollution sources. LDC is being used for the planning of TMDL. In order to analyze the water quality using LDC, it is necessary to prepare FDC using the daily flow data. However, only the daily flow data is measured at the WAMIS branch, and 8days flow data and water quality data are measured at the monitoring Networks. So, in many researches, the water quality is being grasped by deriving the LDC using the 8days flow or the daily flow obtained by various methods. These fluctuations may lead to differences in determining whether the target load is achieved. In this study, each LDC was prepared using the 8day flow and the related daily flow. Then, the effect using different flow data on the achievement of target load was compared according to flow conditions. As a result, the difference ratio in the number of overloads under flow condition was showed 19% in high flows, 42% in moist conditions, 49% in mid-range flows, 41% in dry conditions, and 104% in low flows. In the top ten watershed with the highest difference ratio, the flow became lower the difference ration increases. These differences can cause uncertainty in assessing the achievement of target load using LDC. Therefore, in order to evaluate the water quality accurately and reliably using LDC, accurate daily flow data and water quality data should be secured through the installation of national nonpoint measurement network.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.417-425
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• 2018

The purpose of this study was to analyzed the correlation between upper extremity function, activities of daily living, quality of life and therapeutic flow in stroke clients and identify the factors influencing therapeutic flow. Total 249 stroke patients from 13 hospitals were measure at therapist and researcher for upper extremity function, activities of daily living, therapeutic flow and quality of life. Factors that affect the quality of life correlation as s result of positively correlated with upper extremity function(r=.312, p<.001), activities of daily living(r=.605, p<.001), therapeutic flow(r=.525, p<.001). And the effect on quality of life in stroke clients variables affecting therapeutic flow(${\beta}=.344$, p<.001), activities of daily living(${\beta}=.293$, p<.05) and Time since of onset(${\beta}=.145$, p<.05) were the order of analysis. The regression model explained 35.9% of variances(F=35.736, p<.001). Therefore, it was found that therapeutic flow in stroke clients is an important factor for quality of life, future therapeutic flow study will continue to be needed.