• Journal of Environmental Science International
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• v.8 no.3
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• pp.331-336
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• 1999

The monthly water quality data measured at 14 stations located in the Geum-River watershed were clustered into 2 to 7 clusters. Furthermore, factor analyses were conducted on Gabcheon and Yugucheon to characterize the water qualtiy, based on the information obtained from the results of culster analysis. The results of cluster analysis show that the water quality charactersitic of main stream of the Geum-River is somewhat different from that of substream of the Geum-River. Furthermore, the water quality characteristic of Gabcheon which is expected to have the most serious water quality problems in the Geum-River watershed shows the most different water quality characteristic from Yugucheon. Based ont he factor loadings in each factor, Gabcheon and Yugucheon have their own water quality characteristics. This is mainly because of composite factors such as different population density, industrial activities, and land use conditions in Gabcheon and Yugucheon subwatersheds.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.700-714
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• 2015

The characteristic of the water quality and pollutant discharge was analyzed at the units watershed of the total amount management in Han-river basin, and after classified in a similar area by multivariate statistical analysis, the main trend such as the water quality trend and pollutant discharge characteristic were analyzed. As a result of this study, the density of the pollutant at the unit watershed is not necessarily identified as discharge density, and the primary management watershed and targeted substances were analyzed depending on the operating status of the environmental infrastructure in watershed and the main pollution factor and discharge path per pollutants. As a result of cluster analysis, watersheds were classified into four groups according to discharge characteristics. It will be used when selecting target area of primary management that is appropriate to the characteristics of each river and establishing efficient water quality improvement plans.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.6
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• pp.503-512
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• 2020

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.695-703
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• 2013

Soil erosion and sediment delivery ratio(SDR) were estimated by using HSPF model in 3 tributaries of upper stream of Geum river-basin. Meteorological data and other input data were constructed from 2006 to 2011 year by the HSPF model. Flow and suspended solid results were relatively matched with the measurement data through the calibration and validation of the model. Soil erosion was proportional to the amount of rainfall and the area of watershed based on the results of model calibration and validation. SDR in Moojunamdea stream was the highest and one in Cho stream was the lowest. This was effected by the geographical characteristic. SDR was 17.6% Moojunamdea stream, 9.1% Cho stream and 13.2 % Bocheong stream. As the SDR was effected by watershed area and shape factor in this study area.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.351-360
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• 2014

The allocation of margin of safety (MOS) at a uniform rate to all areas of the unit watershed makes it very difficult to keep the load allotment stable in the area for lack of reduction measures like forest land. This study developed an equation to calculate margin of safety differentially according to the regional characteristics. The equation was formulated on the basis of the regional characteristic factors such as a load contribution factor for land use type and a site conversion factor for the unit watershed. The load contribution factor represents a contribution of loads from a particular land use. The site conversion factor was derived from the site conversion ratio of a unit watershed. Margin of safety for the non-point pollution load in the land use sector decreased by 20~25% in three river basins. The margin of safety in the unit watersheds with low site occupation ratios decreased in high rate, while in the unit watersheds with large urban area decreased in low rate. With the application of the differential margin of safety considering regional characteristics, not only the reduction of pollution loads can become lighter but also it can be easier to develop plans for Total Maximum Daily Loads (TMDLs) even where the reduction measures are not available.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.89-99
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• 2015

In this research, 1,032 data of precise safety inspection from 2004 to 2013 are gathered and constructed for finding effective safety inspection systems. Items are extracted from constructed data and factors for typology are decided with statistical method such as principle component analysis and cluster analysis. For factor decision, we extruded independent characteristics such as morphological and geographical characteristic, and deleted items which can be expressed by combination of independent characteristics. Four factors such as total storage, watershed ratio, levee length ratio, and spillway length ratio are extracted in this process. In cluster analysis, levee length ratio is excluded because it is not separated as cluster. Finally nine types of agricultural reservoir are extruded by total storage, watershed ratio, and spillway length ratio with frequency analysis.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.371-381
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• 2022

Since tributaries have greater water quality variability than main streams, a comprehensive evaluation method that considers the effects of various parameters rather than one water quality parameter has been introduced for effective water quality management of tributaries, but the characteristic of the watershed is not considered. In this study, the urbanization rate, livestock excreta generation, and industrial wastewater discharge in the Hantan River middle-watershed classify urban and non-urban watersheds, and evaluate the suitability of water quality indexes by watershed characteristics by analyzing water quality characteristics and calculating CCME WQI, RTWQI, and NSFWQI. Factor analysis was used to understand the effect of water quality parameters used to calculate the water quality index on the water quality index results. As a result of the factor analysis, the relationship between CCME WQI, TC, and FC was derived, and the relationship between RTWQI and DO, SS in urban watersheds and NSFWQI and FC in non-urban watersheds was revealed. As a result of evaluating suitability through comparison with BOD and T-P grades, it was interpreted that the suitability of the water quality index was low in urban watersheds and that comprehensive water quality evaluation using RTWQI was possible in non-urban watersheds.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.91-106
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• 2014

This study tries to cluster the 795 standard watersheds of Korea Water Resources Unit Map using multivariate statistical analysis technique. The 30 factors of watershed characteristics related to topography, stream, meteorology, soil, land cover and hydrology were selected for comprehensive analysis. From the factor analysis, 16 representative factors were selected. The significant factors in order were the pedological feature, scale and geological location and meteorological and hydrological features of the watershed. As a next step, the 73 gauged watersheds were selected for cluster analysis. They are scattered properly to the whole country and the discharge data were within a confidential level. Based on the 73 watersheds, the other ungaged watersheds were clustered by applying the 16 factors and calculating Euclidian distances. The clustering results showed that the similarity between standard watersheds within the same river basin were 87%, 69%, 41%, 52%, and 27% for Han, Nakdong, Geum, Seomjin, and Yeongsan river basins respectively.

• Journal of Korean Society on Water Environment
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• v.34 no.4
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• pp.409-422
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• 2018

The purpose of this study is to find the characteristics of organic matters based on the distribution and oxidation rates, as noted according to the spatial and temporal variations from 2008 to 2016. Generally speaking, the Han River system is separated into one lower course and two upper courses which are the Namhan River and Bukhan River. The seasonal factor is one of the most important causes of water quality changing in both of the upper courses as a result of a few pollution sources. The concentration of organic matter was measured as higher in the lower course into which great streams with point and non-point sources were identified. According to seasonal variations, however, the change of the organic matter in the lower course is comparatively slighter than that of organic matters in the upper courses. The oxidation rates related to the BOD were 15 %, 17 % and 26 % in the Bukhan River, Namhan River and the lower course, respectively. These results could be explained that more biodegradable organic matter were seen to have existed in the lower courses comparing to the activity in the upper course. The oxidation rates of the BOD were noted as relatively higher in the eutrophicated places with phytoplankton. Therefore the BOD is one of the good index models to find the characteristic of the eutrophicated water. On the other hand BOD would not be enough to estimate concentration of refractory organic matters in the Bukhan and Namhan river. Consequently, both of the TOC and BOD are necessary indices to understand the identified refractory and/or biodegradable characteristics of organic matter.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.