• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.4
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• pp.45-61
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• 1988

The purpose of this study is to develop regression equations between annual specific sedi- ment of reservoirs and physiographic factors of watersheds. 122 irrigation reservoirs, which have irrigation areas equal to or larger than 200 ha, located in Korea except Cheju province are used in the analysis. Simple regression analyses between the specific annual sediment and each of the physical characteristic factors of the reservoirs are carried out at first. Then, multiple regression analyses between the annual specific sediment and the physical characteristic factors with high correlation coefficients in the simple regression analyses are made. The results obtained from this study are as follows : 1. The results of the sirnple regression analyses show that in each province the watershed area, the length of mainstream, the circumferential length of watershed have high cor- relation coefficients (R=0.814-0.986), and that drainage density, reservoir capacity per watershed area, drainage frequency, basin relief have low correlation coefficients (R=0. 387-0.955). 2. The purposed multiple regression equations between the annual specific sediment of reservoirs and three major characteritic factors of watersheds, namely, the watershed area, the circumferential length of watershed, and the length of mainstream, are proposed as given in Table 2. 3. The result of the simple regression analyses with respect to the reservoir elevation except Jeonnam province, which has very different characteristics comparing to other provinces, shows that watershed area, main stream length and circumferential length have high correlation coefficients (R=0.806-0.884) in low-elevation reservoirs and intermediate- elevation reservoirs, but low correlation coefficients (R=0.639-0.739) in high-elevation reservoirs. 4. With respect to the reservoir elevation, the proposed multiple regression equations bet- ween the annual specific sediment of reservoirs and the three major characteristic factors of watershed which have high correlation coefficients are proposed as given in Table 5.

• 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 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 The Korean Society of Agricultural Engineers
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• v.51 no.5
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• pp.107-113
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• 2009

The purpose of this study is to estimate the design flood runoff for ungaged forest watershed to reduce the flood damage in national park. Daewonsa watershed in Jirisan National Park was selected as study watershed, of which characteristic factors were obtained from GIS data. Flood runoff was simulated using SCS unit hydrograph module in HEC-HMS model. SCS Curve Number (CN) was calculated from forest type area weighted average method. Huff's time distribution of second-quartile storm of the Sancheong weather station, which is nearest from study watershed, was used for design flood runoff estimation. Critical storm duration for the study watershed was 3 hrs. Based on the critical duration, the peak runoff for each sub-watershed were simulated. It is recommended to monitor the long-term flow data for major stream stations in National Park for a better reliable peak runoff simulation results.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.1
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• pp.135-144
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• 2009

The objective of this study is to examine the effect of hydrological factors on critical durations, and to analyze the relationship between the watershed characteristics and the critical duration of design rainfall in the medium sized catchments. Hydrological factors are used to return period, probable intensity formula, hydrograph method, effective rainfall and temporal pattern of design rainfall. Hydrologic analysis has done over the 44 medium sized catchments with $50{\sim}5,000{\beta}{\yen}$. Watershed characteristics such as catchment area, channel length, channel slope, catchment slope, time to peak, concentration of time and curve number were used to simulate correlation analysis. All of hydrological factors except return period influence to the critical duration of design rainfall. Also, it is revealed that critical duration is influenced by the watershed characteristics such as area, channel length, channel slope and catchment slope. Multiple regression analysis using watershed characteristics is carried out for the estimation of relationship among these. And the 7 type equations are proposed by the multiple regression using watershed characteristics and critical duration of design rainfall. The determination coefficient of multiple regression equations shows $0.96{\sim}0.97$.

• Current Research on Agriculture and Life Sciences
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• v.10
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• pp.35-40
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• 1992

The purpose of this study is to develop regression equations between peak flow and physical characteristic factors of watersheds. 112 irrigation reservoirs located in South Korea which are equal or larger than 200 has. in the irrigation area, are used in the analysis of this study. The results obtained from this study are as follows. 1. The results of correlation analysis of the relationships among the characteristic factors of the watersheds have been derived high significances. 2. Relationship between the peak flow and the simple correlation analysis of physical characteristic factors of the watersheds has been derived low significance. 3. The result of the multiple regression analysis between the peak flow and four physical characteristic factors of watershed such as watershed area, main stream length, average slope of main stream and elevation of reservoir are shown as the equation ; $Q_{100}=66.43A^{0.869}L^{-0.536}S^{0.456}Hs^{-0.122}$.(r=0.838)

• 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.54 no.11
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• pp.955-968
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• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.169-173
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• 2008

A field monitoring was conducted in order to find out the discharge characteristics of non-point source pollutants in the agricultural area. Event Mean Concentration (EMC) of TSS, $BOD_5$, $COD_{Mn}$, TP, TN was calculated based on the monitoring data of 10 rainfall events at agricultural watersheds. A significant relationship was observed from the correlation between EMCs and rainfall characteristics. The result shows that EMC ranges of 95% confidence intervals were 50.5~203 mg/L for TSS, 0.8~14.2 mg/L for $BOD_5$, 4.2~20.7 mg/L for $COD_{Mn}$, 2.4~4.5 mg/L for TN and 0.2~0.5 mg/L for TP, respectively. The correlation coefficients between TSS and TP and between $BOD_5$ and $COD_{Mn}$ were found to be 0.912 and 0.961. But TN was lower correlated with other EMC factors. It was also found that rainfall characteristics was not correlated with EMCs.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.49-60
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• 2021

BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.