• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.44-54
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• 2010

In this study, a comprehensive exploration and evaluation of washland candidate locations by means of field monitoring as well as spatial analysis in six major river system (Han, Nakdong, Nam, Geum, Youngsan, and Seomjin Rivers). Washland(in other words, river detention basin) is an artificial wetland system which is connected to streams or rivers likely to riverine wetlands. Major purpose of washland creation is to control floodings, water supply and purification, providence of eco-cultural space to human and natural populations. Characteristics and functions of riverine wetlands can be expected as well, thus it is believed to be an efficient multi-purpose water body that is artificially created, in terms of hydrology and ecology. Geographical information and field monitoring results for the washland candidate locations were evaluated in 2009, with respect to optimal location exploration, ecosystem connectivity and educational-cultural circumstances. A total of $269\;km^2$ washland candidate locations were found from spatial analysis (main channel of Rivers South Han, 71.5; Nakdong 54.1; Nam, 2.3; Geum, 79.0; Youngsan 46.4; Seomjin 15.7), and they tended to be distributed in mid- to lower part of the rivers to which tributaries are confluent. Field monitoring at 106 sites revealed that some sites located in the Rivers Nam and Geum is appropriate for restoration or artificial creation as riverine wetlands. Several sites in the Nakdong and Seomjin Rivers were close to riverine wetlands (e.g., Upo), habitats of endangered species (e.g., otters), or adjacent to educational facility (e.g., museums) or cultural heritages (e.g., temples). Those sites can be utilized in hydrological, ecological, educational, and cultural ways when evidence of detailed hydrological evaluation is provided. In conclusion, determination of washland locations in the major river basins has to consider habitat expansion as well as hydrological function (i.e. flood control) basically, and further utility (e.g. educational function) will increase the values of washland establishment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.1
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• pp.121-129
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• 1987

The object of this study is the analysis of the factors which have significant effects in the floodplain and distribution pattern of carrying capacity in stream cross-section, which play important roles in the floodplain management. The conclusion are as follows, It has been found that the return period of bankfull discharge is about 1 to 2.5 years in Geum river system and the factors which have most important effects in the floodplain are the $Q_{100}$, the drainage area and the stream length. In Gong ju gauging station which has a recreation area, the carrying capacity is smaller than those of the other self-recording gauging station in Geum river basin. This shows that the complex cross-section of stream plays an important role in the distribution pattern of carrying capacity in floodplain.

• Journal of Environmental Impact Assessment
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• v.18 no.3
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• pp.171-183
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• 2009

This study aims to analyze the sedimentary environment change in mid-channel bar of the lower Geum river basin after the construction of the estuary barrage using multi-temporal satellite data and GIS. The sedimentary environment changes were observed in mid-channel bar areas. The mid-channel bar F was found to have been newly formed for 10 years(1996-2006), whereas the mid-channel bar B located between mid-channel bar A and C has disappeared by erosion during the same periods. When examined by section, the areas of the mid-channel bar in the upper stream section from the Yipo's reference point generally increased due to the prevailing sedimentary environments, and those of the downstream section decreased where corrosive environments are dominant. In ternms of the centroid movement, the mid-channel bars grew up toward the downstream by switching erosion and accumulation, as sedimentation was prevailing in the downstream area of mid-channel bars and corrosion was dominant in the upper stream. Through grain size analysis, the study areas are divided into three sections according to the average grain size. In Section I, the mid-channel bars were formed as a result of sedimentary process of tides in the past. In Section II, the mid-channel bars were formed partly through the sedimentary process of rivers although the sedimentary process of tides is prevailing. In Section III, the mid-channel bars were formed mainly through the sedimentary process of rivers, even if it showed the sedimentary process of tides in the past.

• Parasites, Hosts and Diseases
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• v.52 no.4
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• pp.391-397
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• 2014

We evaluated the status of Clonorchis sinensis infection and potential risk factors among residents of riverside areas (Geumgang) in Muju-gun, Jeollabuk-do (Province), Korea. From January to February 2010, a total of 349 (171 males, 178 females) stool samples were collected and examined by the formalin-ether concentration technique. Also, village residents were interviewed using questionnaires to obtain information about C. sinensis infection-related risk factors. Overall egg-positive rate of C. sinensis was 13.2%. Egg-positive rates were significantly higher in males, farmers, and residents who had lived there more than 20 years, and in residents who had eaten raw freshwater fish than in opposite groups, respectively. However, there was no significant difference between age groups, education levels, cigarette smoking, alcohol drinking, health status, past history of infection, and experience of clonorchiasis medication and examination. Logistic regression analysis was performed to determine risk factors for clonorchiasis. On univariate analysis, the odds ratios for males, farmers, those who had lived there more than 20 years, and who had eaten raw freshwater fish were 2.41, 4.44, 3.16, and 4.88 times higher than those of the opposites, respectively. On multivariate analysis, the odds ratio of residents who had eaten raw freshwater fish was 3.2-fold higher than that of those who had not. These results indicate that residents living in Muju-gun, along the Geum River, Korea, have relatively high C. sinensis egg-positive rates, and the habit of eating raw freshwater fish was the major factor for the maintenance of clonorchiasis.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.84-94
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• 2009

Moisture Index time series derived from NOAA/AVHRR data have showed to be useful for humid and arid states. The humid/arid states of the Geum river basin are classified by means of the moisture index estimated from the climatic water budget model. Validations showed that the moisture index has excellent ability to detect humid/arid conditions and to measure time of its onset, intensity and duration. In this study, a simple method to classify the moisture index is proposed by statistical distribution condition. Also, the moisture index is compared with the regional actual state to detect drought area.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Journal of Korean Society on Water Environment
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• v.20 no.3
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• pp.223-230
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• 2004

The QUAL2E and Box-Jenkins time series model were applied to the Miho river, a main tributary of the Geum river, to predict water quality. The models are widely used to predict water quality in rivers and watersheds because of its accuracy. As results of the study, we concluded as follows: Pollutant loadings in upper stream of Miho river were determined to 57,811 kgBOD/d, 19,350 kgTN/d, and 5,013 kgTP/d. The loading of TN in Mushim river was 19,450 kgTN/d, respectively. As the mass loadings were compared with pollutant sources, it concluded that the farming livestock contributed highly to mass emissions of BOD and TP and the population contributed to TN mass loading. The observed water quality values were applied to the models to verify and the models were used to predict the water quality. The QUAL2E Model predicted the concentrations of DO, BOD, TN and TP with high accuracy, but not for E-Coli. The Box-Jenkins time series model also showed high prediction for DO, BOD and TN. However, the concentrations of TP and E-Coli were poorly predicted. The result shows that the QUAL2E model is more applicable in Miho basin for prediction of water quality compared to Box-Jenkins time series model.

• IE interfaces
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• v.21 no.1
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• pp.75-84
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• 2008

It is a difficult task for decision makers(DMs) to choose an appropriate release plan which balances the conflicts between water storage and hydro-electric energy generation in a multi-reservoir operation problem. In this study, we proposed a DEA-based ranking procedure by which the DM can rank the potential alternatives and select the best solution among the Pareto-optimal solutions. The proposed procedure can resolve the problem of mix inefficiency that may cause errors in measuring the efficiency of alternatives. We applied the proposed procedure to the multi-reservoir operation problem for the Geum-River basin and could choose the best efficient solution from the Pareto-set which were generated by the Coordinated Multi-Reservoir Operating Model.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Water for future
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• v.13 no.1
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• pp.39-48
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• 1980

The purpose of this study was to set up the accurate way of estimating the frequency of the max. daily rainfall of the Korean rivers. The area selected for study were Han.Naktong, Geum, Yeongsan, and Seomjin River. The following five methods of the rainfallfrequency analysis were applied to twenty four subgrouped regions in the basins; 2 parameter lognormal, 3 parameter lognormal, Type I extremal(Gumbel method), Pearson Type III, and log-Pearson Type III. The regression equations were established between the depth of max. daily rainfall given 6 reccirrence interval(100, 50, 20, 10, 5, 2) and the basin area.