• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1009-1019
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• 2009

In this research, various characteristics of South Korea's design flood have been examined by deriving appropriate design flood, using data obtained from careful observation of actual floods occurring in selected main watersheds of the nation. 19 watersheds were selected for research in Korea. The various characteristics of annual rainfall were analyzed by using a moving average method. The frequency analysis was decided to be performed on the annual maximum flood of succeeding one year as a reference year. For the 19 watersheds, tests of basic statistics, independent, homogeneity, and outlier were calculated per period of annual maximum flood series. By performing a test using the LH-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test, among applied distributions of Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distribution was found to be adequate compared with other probability distributions. Parameters of GEV distribution were estimated by L, L1, L2, L3 and L4-moment method based on the change in the order of probability weighted moments. Design floods per watershed and the periods of annual maximum flood series were derived by GEV distribution. According to the result of the analysis performed by using variation rate used in this research, it has been concluded that the time for changing the design conditions to ensure the proper hydraulic structure that considers recent climate changes of the nation brought about by global warming should be around the year 2002.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.515-522
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• 2017

This study investigated the runoff characteristics containing NPS pollutants in urban areas and estimated the optimal number of storm events to be monitored. 13 residential areas, 8 commercial areas, 9 transportation areas and 11 industrial areas were selected to be monitored located in urban areas. Monitoring was performed from 2008 to 2016 with a total of 632 rainfall events. As a result, it was found that commercial area needs priority NPS management compared to other landuses because the commercial area has high runoff coefficient and NPS pollutant EMC compared with other landuses. The annual monitoring frequency for each landuse was estimated to be 11 to 14 times for industrial area, 12 to 14 times for transportation area, 11 to 13 times for commercial area and 22 to 25 times for residential area. Even with the use of accumulated monitoring data for several years, there is still high probability of uncertainty due to high error in some pollutant items, and it is necessary to establish monitoring know-how and data accumulation to reduce errors by continuous monitoring.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.107-118
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• 2003

The purpose of this study is to assess the hydrological impact on a watershed from long-term land cover changes. Gyeongan-cheon watershed($558.2km^2$) was selected and WMS(watershed modeling system) HEC-1 model was adopted as an evaluation tool. To identify land cover changes, five Landsat images(1980/2/15, 1986/4/15, 1990/4/26, 1996/4/26, 2000/5/17) were selected and analyzed using maximum likelihood method. As a result, urban areas have increased by 5.6% and forest areas have decreased by 6.1% between 1980 and 2000. SCS curve number increased by 9.8. To determine model parameters and evaluate HEC-1 model, five storm events(1998/5/2, 1998/8/23, 1998/9/30, 1999/5/3, 2000/7/29) were used. The simulated stream flow agreed well with the observed one with relative errors ranging from 9% to 36%. For 254 mm daily rainfall of 30 years frequency, due to the increase of urban areas peak flow increased by $455m^3/sec$ and the time of peak flow reduced about four hours for 20 years land cover changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.64-79
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• 2016

The purpose of this study is to find the relationship between precipitation deficit, SPI(standardized precipitation index)-12 month, agricultural reservoir water storage deficit and agricultural drought-related big data, and to evaluate the usefulness of agricultural risk management through big data. For the long term drought (from January 2014 to September 2015), each data was collected and analysed with monthly and Provincial base. The minimum SPI-12 and maximum reservoir water storage deficit compared to normal year were occurred at the same time of July 2014, and August and September 2015. The maximum frequency of big data was occurred at June and July of 2014, and March and June to September of 2015. The maximum big data was occurred 1 month advanced in 2014 and 2 months advanced in 2015 than the maximum reservoir water storage deficit. The occurrence of big data was sensitive to spring drought from March, late Jangma of June, dry Jangma of July and the rainfall deficit of September 2015. The big data was closely related with the meteorological drought and agricultural drought. Because the big data is the in situ feeling drought, it is proved as a useful indicator for agricultural risk management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.439-447
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• 2011

It is a main concern for sustainable development in water resources management to evaluate adaptation capability of water resources structures under the future climate conditions. This study introduced the Fuzzy Inference System (FIS) to represent the change of release and storage of reservoirs in the Han River basin corresponding to various inflows. Defining the adaptation capability of reservoirs as the change of maximum and/or minimum of storage corresponding to the change of inflow, the study showed that Gangdong Dam has the worst adaptation capability on the variation of inflow, while Soyanggang Dam has the best capability. This study also constructed an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the more accurate and efficient simulation of the adaptation capability of the Soyanggang Dam. Nine Inflow scenarios were generated using historical data from frequency analysis and synthetic data from two general circulation models with different climate change scenarios. The ANFIS showed significantly different consequences of the release and reservoir storage upon inflow scenarios of Soyanggang Dam, whilst it provides stable reservoir operations despite the variability of rainfall pattern.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.997-1005
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• 2013

Since the cross-sectional shape of the Nakdong river is compound type, the water stage rises up to the top of the flood plane, as the flow discharge increases during the extreme rain storm in summer. The recent increase of rainfall intensity and flood frequency results in the immersions of parks and hydrophilic facilities located in the flood plain. Therefore it is necessary to analyze the hydraulic characteristics evolved by the extreme rain storm in the flood plain. The study reach ranging from the Gangjeong Goryeong Weir and the Dalseong Weir, where several hydraulic facilities are located along the channel, was selected and numerical simulations were conducted for 42 hours including the peak flood of the typhoon Sanba. The 2-D transient model, FaSTMECH was employed and the accuracy of the model was assessed by comparing the water level between the simulation results and the measured ones at a gauging station. It showed a high correlation with $R^2$ of 0.990, AME of 0.195, and RMSE of 0.252. In addition, the inundation time, the inundation depth, the inundation velocity, and the shear stress variation in the flood plain facilities were analyzed.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.365-374
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• 2009

Probability plotting positions are used for the graphical display of annual maximum rainfall or flood series and the estimation of exceedance probability of those values. In addition, plotting positions allow a visual examination of the fitness of probability distribution provided by frequency analysis for a given data. Therefore, the graphical approach using plotting position has been applied to many fields of hydrology and water resources planning. In this study, the plotting position formula for the Gumbel distribution is derived by using the order statistics and the probability weight moment of the Gumbel distribution for various sample sizes. And then, the parameters of plotting position formula for the Gumbel distribution are estimated by using genetic algorithm. The appropriate plotting position formulas for the Gumbel distribution are examined by the comparison of root mean square errors and biases between theoretical reduced Gumbel variates and those calculated from derived and existing plotting position formulas. As the results, Gringorten's plotting position formula has the smaller root mean square errors and biases than any other formulas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.712-721
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• 2017

Recently, the intensity and frequency of floods has increasing worldwide, and flood disasters have become a big problem. Flood disasters, which account for the largest portion of disasters, are floods accompanied by typhoons and localized heavy rainfall. As a result, they cause damage of levee overtopping, in which the water level of a river rises to the levee crown. Therefore, countermeasures are essential and necessary because of the damage to the facility itself as well as to life and other property. The damage magnitude depends on the collapse of the levee. A levee that is difficult to collapse will reduce the discharge inland significantly. Accordingly, the protection of the inland slope, where the collapse of the levee is initiated, is one of the most important countermeasures In this study, revetments with various porosity and forms were suggested and hydraulic experiments were carried out for each type. The hydraulic experiments showed that the stability of a revetment in an inland slope is strongly correlated with the weight per unit area of the revetment. The relationship between the critical velocity, which is the velocity at the moment of leaving the revetment, and the weight per unit area was derived. Through this study, by applying the nature friendly revetment, which has not yet been applied to Korea, it is expected that life and property damage caused by levee overtopping during flooding can be reduced, and a nature friendly river space can be constructed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.579-588
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• 2015

Recent climage changes have resulted in increases in rainfall intensity and flood frequency as well as the risk of flood damage due to typhoons during the summer season. Water-friendly facilities such as ecological parks and sports facilities have been established on floodplains of rivers since the river improvement project was implemented and increases in the flood levels of rivers due to typhoons can lead to direct flood damage to such facilities. To analyze the hydraulic influence of these water-friendly facilities on floodplains or to evaluate their stability, numerical analysis should be performed in advance. In addition, it is crucial to address the drying and wetting processes generated by water level fluctuations. This study uses a Nays2D model, which analyzes drying and wetting, to examine its applicability to simple terrain in which such fluctuations occur and to natural rivers in which drying occurs. The results of applying this model to sites of actual typhoon events are compared with values measured at water level observatories. Through this comparison, it is determined that values of coefficient of determination ($R^2$), mean absolute error (MAE), and root-mean-square error (RMSE) are 0.988, 0.208, and 0.239, respectively, thus showing a statistically high correlation. In addition, the results are used to calculate flood risk indices for evaluation of such risk for water-friendly facilities constructed on floodplains.

• 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.