• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.755-758
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• 2008

Currently, the increased run-off and the shortened arrival time are one of the causes of the city environmental disasters in urbanization. Therefore, it is necessary to properly design the hydrologic structures, but it is very difficult to forecast the values necessary to design from the planning stage. Moreover, as the parameter is changed due to the urban development, it is difficult not only to analyze the run-off influences but also to find the related studies and literatures. The purpose of this study is to utilize the results as the important basic data of the hydrologic structures, its proper design and run-off influences through the sensibility analysis of the model parameter variables. In this study, the absolute and relative sensibility analysis method were used to find out the correlation through the sensibility analysis of the topology and hydrology parameters. Especially, in this study, the changes in the run-off amount and volume were calculated according to increase/decrease in CN, the coefficient of discharge, and the empirical formula is prepared and proposed through the regressive analysis among the parameters. In the meantime, the parameter sensibility analysis was performed through the simulation HEC-HMS that is used and available in Korea. From the results of this study, it was found that the run-off amount is increased about by 10% when the CN value is increased by 5% before and after the development through the HEC-HMS simulation and data analysis. As long as there will be additional data collection analysis and result verification, and continuous further studies to find out the parameters proper to the domestic circumstances, it is expected to considerably contribute to the proper design of the hydrologic structures with respect to the ungauged basin.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.4
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• pp.27-43
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• 1990

This study aimed at developing a generalized model on the estimation of the long - term run - off volume for practical purpose. During the research period of last 3 years( 1986-1988), 3 types of estimation model on the long - term run - off volume(Effective rainfall model, unit hydrograph model and barne's model for dry season) had been developed by the author. In this study, through regressional analysis between determinant factors (bi of effective rainfall model, ai of unit hydrograph model and Wi of barne's model) and catchment characteris- tics(catchment area, distance round the catchment area, massing degree coefficient, river - exte- nsion, river - slope, river - density, infiltration of Watershed) of 11 test case areas by multiple regressional method, a new methodology on the derivation of determinant factors from catchment characteristics in the watershed areas having no hydrological station was developed. Therefore, in the resulting step, estimation equations on run - off volume for practical purpose of which input facor is only rainfall were developed. In the next stage, the derived equations were applied on the Kang - and Namgye - river catchment areas for checking of their goodness. The test results were as follows ; 1. In Kang - river area, average relative estimation errors of 72 hydrographs and of continuous daily run - off volume for 245 days( 1/5/1982 - 31/12) were calculated as 6.09%, 9.58% respectively. 2. In Namgye - river area, average relative estimation errors of 65 hydrographs and of conti- nuous daily run - off volume for 2fl days(5/4/1980-31/12) were 5.68%, 10.5% respectively. In both cases, relative estimation error was averaged as 7.96%, and so, the methodology in this study might be hetter organized than Kaziyama's formula when comparing with the relative error of the latter, 24~54%. However, two case studies cannot be the base materials enough for the full generalization of the model. So, in the future studies, many test case studies of this model should he carries out in the various catchment areas for making its generalization.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.555-562
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• 2013

Jeju Island, the heaviest raining area in Korea, is a volcanic Island located at the southernmost of Korea, but most streams are of the dry due to its hydrological/geological characteristics different from those of inland areas. Therefore, there are limitations in applying the results from the mainland to the studies on stream run-off characteristics analysis and water resource analysis of Jeju Island. In this study, the SWAT(soil & water assessment tool) model is used for the Hwabuk stream watershed located east of the downtown to calculate the long-term stream run-off rate, and WMS(watershed modeling system) and HEC-HMS(hydrologic modeling system) models are used to figure out the stream run-off characteristics due to short-term heavy rainfall. As the result of SWAT modelling for the long-term rainfall-runoff model for Hwabuk stream watershed in 2008, 5.66% of the average precipitation of the entire basin was run off, with 3.47% in 2009, 8.12% in 2010, and root mean square error(RMSE) and determination coefficient($R^2$) was 496.9 and 0.87, respectively, with model efficient(ME) of 0.72. From the results of WMS and HEC-HMS models which are short-term rainfall-runoff models, unless there was a preceding rainfall, the runoff occurred only for rainfall of 40mm or greater, and the run-off duration averaged 10~14 hours.

• Journal of Korean Society of Forest Science
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• v.77 no.3
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• pp.269-275
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• 1988

To investigate the cause of overflow in the torrential stream, the estimated peak flow of run-off and the maximum tarring capacity of the stream were measured at the upstream of Samsung-cheon located in Kwanak Aboretum during July, 1987. The results obtained from this study could be summarized as follows : 1. The surveyed catchment area was 477ha, which was 116 of the designed area (410ha) by the plan. 2. The maximum rainfall intensity measured was 99.5mm/hr and was almost same as the designed intensity(100mm/hr). 3. The surveyed run-off coefficient was 0.672 that was about twice as much as designed one(0.35). 4. The surveyed peak flow of run-off was $88.59m^3/sec$, 222% as large the designed one($39.9m^3/sec$). 5. The designed cross-sectional area of the stream was $17.25m^2$, which was 68% of the designed one$25.43m^2$. 6. The surveyed hydraulic mean radius was 0.94m, which was shorter than the designed one(1.28m). 7. The surveyed mean stream-bed gradient(0.998%) was almost the same as the designed one(1.00%). 8 The surveyed maximum velocity of flow passing through the stream was 2.87m/sec, 78.0 of the designed one(3.68m/sec). 9 The surveyed run-off capacity of the stream was $49.51m^3/sec$, 53% of the designed one ($93.5m^3/sec$).

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.123-146
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• 1995

Several quality control schemes have been extensively compared using multivariate normal data sets simulated with various correlation structures. They include multiple univariate CUSUM charts, multivariate EWMA charts, multivariate CUSUM charts and Shewhart T$^{3}$ chart. This paper considers a new approach of the multivariate EWMA chart, in which the smoothing matrix has full elements instead of only diagonal elements. Performance of the schemes is measured by avaerage run length (ARL), coefficient of variation of run length (CVRL) and rank in order of signaling of off-target shifts in the process mean vector. The schemes are also compared by noncentrality parameter. The multiple univariate CUSUM charts are generally affected by the correlation structure. The multivariate EWMA charts provide better ARL performance. Especially, the new EWMA chart shows remarkable results in small shifts.

• Clean Technology
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• v.17 no.4
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• pp.353-362
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• 2011

In our nature, the utilization of rainwater is essential for healthy water recirculation. This is one of the solutions of the increment of impermeability surface according to the development of new cities; this study of the improvement of rainwater quality has been carried on through the improvement of collecting and restoring system of rainwater. The southwestern region of Daejeon City, the rainwater coefficient of run off was 0.40 and this number had computed to 0.59 after the development. After filtration of rainwater, the heavy metal (Cu, As, Cr, Fe, Mn) contents level were lower than underground water. Moreover, collected rainwater showed better quality than underground water in following criteria; hardness, permanganate consumption quality, chloride, evaporation residue, sulfates and nitrate nitrogen. This water quality met the gray water quality standards. The rainwater quality was still suitable to use as bathroom flushing and gardening after 100 days of storage. This study proved that modification (installation of cover with gutter to existing rainwater collection system, proper filtering, and installation of underground storage tank) of collection system could improve quality of water and maintain this approximately 100 days.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.3
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• pp.407-417
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• 2011

Nowadays, the high land use, mainly used for urbanization, is affecting runoff loads of non-point pollutants to increase. According to this fact, increasing runoff loads seems like to appear that it contributes to high ratio of pollution loads in the whole the pollution loads and that this non-point source is the main cause of water becoming worse quality. Especially, concentrated pollutants on the impermeable roads run off to the public water bodies. Also the coefficient of runoff from roads is high with a fast velocity of runoff, which ends up with consequence that a lot of pollutants runoff happens when it is raining. Therefore it is very important project to evaluate the quantity of pollutant loads. In this study, I computed the pollutant loadings depending on time and rainfall to analyze characteristics of runoff while first flush storm water and evaluated the runoff time while first flush storm water and rainfall based on the change in curves on the graph. I also computed contribution ratio to identify its impact on water quality of stream. I realized that the management and treatment of first flush storm water effluents is very important for the management of road's non-point source pollutants because runoff loads of non-point source pollution are over the 80% of whole loads of stream. Also according to the evaluation of runoff loads of first flush storm water for SS, run off time was shown under the 30 minute and rainfall was shown under the 5mm which is less than 20% of whole rainfall. These are under 5mm which is regarded amount of first flush storm water by the Ministry of Environment and it is judged to be because run off by rainfall is very fast on impermeable roads. Also, run off time and rainfall of BOD is higher than SS. Therefore I realized that the management of non-point source should be managed and done differently depending on each material. Finally, the contribution ratio of pollutants loads by rainfall-runoff was shown SS 12.7%, BOD 12.7%, COD 15.9%, T-N 4.9%, T-P 8.9%, however, the pollutants loads flowing into the steam was shown 4.4%. This represents that the concentration of non-point pollutants is relatively higher and we should find the methodical management and should be concerned about non-point source for improvement on water quality of streams.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.500-507
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• 1998

The measures for water quality improvement have been planned to introduce for several reservoirs which were badly polluted among the sites included in the Network of Agricultural Water Quality Survey (NAWQS). Considering conditions of circumstances around reservoirs, self-purification systems such as natural ecosystem, oxidation ponds with plants, grassed waterways, weirs, and manmade plant-islands are taking into account enhancing to trap nutrients in waters running off from agricultural lands. The Pollutant Run off Ratios were analysed to predict the effects of water quality improvement for self-purification systems. The cost of water quality improvement was evaluated. The correlation equation between cost and irrigation area showing high correlation coefficient was derived.

• Journal of Environmental Impact Assessment
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• v.16 no.1
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• pp.79-87
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• 2007

The performance of a stream water quality analysis model depends upon many factors attributed to the geological characteristics of a watershed as well as the distribution behaviors of pollutant itself on a surface of watershed. Because the model run has to import the pollution load from the watershed as a boundary condition along an interface between a stream water body and a watershed, it has been used to introduce a pollution delivery coefficient to behalf of the boundary condition of load importation. Although a nonlinear regression model (NRM) was developed to cope with the limitation of a conventional empirical way, this an up-to-date study has also a limitation that it can't be applied where the pollution load washed off (assumed at a source) is less than that delivered (observed) in a stream. The objective of this study is to identify what causes the limitation of NRM and to suggest how we can purify the process to evaluate a pollution delivery coefficient using many field observed cases. As a major result, it was found what causes the pollution load delivered to becomes bigger than that assumed at the source. In addition, the pollution load discharged to a stream water body from a specific watershed was calculated more accurately.