• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.359-365
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• 1998

A global optimization method known as the Shuffled Complex Evolution method from the University of Arizona(SCE-UA) was used for calibrating a Tank model. The model was calibrated with error-free synthetic data, and the SCE-UA method was found to effectively search optimal parameters. Historical data from an agricultural watershed was used to calibrate and validate the model parameters. The simulated results were in good agreement with the observed.

• Journal of the Korean earth science society
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• v.35 no.2
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• pp.97-103
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• 2014

An isotopic hydrograph separation technique has been able to determine the contribution of new water (event water such as rain or snowmelt) and old water (pre-event water like groundwater) to a stream hydrograph for last several decades using stable water isotopes. It is based on the assumption that the isotopic compositions of both new water and old water at a given instant in time are known and the stream water is a mixture of the two waters. In this study, we show that there is a systematic error (standard error in the new water fraction) in the isotopic hydrograph separation if the average isotopic compositions of new water were used ignoring the temporal variations of those of new water. The standard error in the new water fraction is caused by: (1) the isotopic difference between the average value and temporal variations of new water; (2) the new water fraction as runoff contributing to the stream during rainfall or spring melt; and (3) the isotopic differences between new and old water (inversely). The standard error is large, in particular, when new water dominates the stream flow, such as runoff during intense rainfall and in areas of low infiltration during spring melt. To reduce the error in the isotopic hydrograph separation, incorporation of fractionation in the isotopic composition of new water observed at a point should be considered with simultaneous sampling of new water, old water and stream water.

• International Journal of Contents
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• v.12 no.1
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• pp.49-53
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• 2016

"Hahoe Village" in Andong region is an UNESCO World Heritage Site. It should be protected against various disasters such as fire, flooding, earthquake, etc. Among these disasters, flooding has drastic impact on the lives and properties in a wide area. Since "Hahoe Village" is adjacent to Nakdong River, it is important to monitor the water level near the village. In this paper, we developed a hydrological modelling using multi-layer perceptron (MLP) to predict the water level of Nakdong River near "Hahoe Village". To develop the prediction model, error back-propagation (EBP) algorithm was used to train the MLP with water level data near the village and rainfall data at the upper reaches of the village. After training with data in 2012 and 2013, we verified the prediction performance of MLP with untrained data in 2014.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.378-383
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• 2000

The daily streamflow in the Yalu watershed located in the north-estern part of China was simulated by the DAWAST model. The parameters of model were calibrated by optimization technique with the input data of daily rainfall and pan evaporation occurred from 1997 to 1998, and they were Umax of 404mm, Lmax of 39mm, FC of 104mm, CP of 0.018, and CE of 0.003, respectively. Model verification tests were carried out with a data of 1996, and the results were generally satisfactory. Root mean square error was 0.3mm and Percent error in volume was 9.7%, and Correlation coefficient was 0.941.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• Water for future
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• v.13 no.2
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• pp.35-47
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• 1980

An algorithm is developed to derive a representative I hr-unit hydrograph through an analysis of rainfall-runoff relations of a watershed as a closed system. For the base flow seperation of a flood hydrograph the multi-deflection method is proposed herein, which gace better results compared with those by the existing empirical methods. A modified $\Phi$index method is also proposed in this stidy to determine the time distribution rainfall excess of a rainstorm, which is essetially a modification of the commonly used $\Phi$index method of rainfall seperation. With the so-obtained rainfall excess hyetograph and the direct runoff hydrograph a trial and error computation of the ordinates of 1 hr-unit hydrograph was executed in such a manner that the synthesized flood hydrograph closely approximates the observed one, thus resulting a unit hydrograph of a piecewise exponential function type. To verify the validity of this study the 1 hr-unit hydrographs for the Imha and Dongchon in Nagdong River basin, and Yongdam in Geum River basin were derived by this algorithm, and the results were compared with those by the conventional synthetic unit hydrograph method and the Nakayasu method. Besides, the validity of this stiudy was also tested by comparing the observed hydrograph with the one computed by applying the unit hydrograph to a specific rainfall event. To generalize the result of this study a computer program, consisited of a main and three subprograns (for rainfall excess estimation, convolution summation, and sorting), is developed as a package, which is believed to be applicable to other watersheds for the similar purpose as those in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.849-858
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• 2014

The mount of antecedent 5-day rainfall (P5) is usually used to determine the antecedent soil moisture condition for estimating effective rainfall using the NRCS-CN method. In order to re-establish the threshold of P5 considering basin characteristics, this study investigated the sensitivity of the threshold of P5 to effective rainfall by comparing the corresponding observed direct runoff. The overall results indicate that the direct runoff estimated using the re-establihed threshold of P5 has smaller mean error (RMSE of 27.3 mm) than those using the conventional threshold (RMSE of 35.2 mm). In addition, after evaluating the effectiveness of threshold of P5 using the improvement index, the threshold re-established in this study improved the ability to estimate the direct runoff by 30% on average. This study also suggested to employ regression models using topographic indices to re-establish the threshold for ungauged basins. When using the re-established threshold from the regression model, the RMSE decreased ranging from 0.4 mm to 15.1 mm and the efficiency index of Nash and Sutcliffe increased up to 0.33.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.13-25
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• 1998

It is necessary to develop methodologies for the application of artificial neural network into hydrologic rainfall-runoff process, although there is so much applicability by using the functions of associative memory based on recognition for the relationships between causes and effects and the excellent fitting capacity for the nonlinear phenomenon. In this study, some problems are presented in the application procedures of artificial neural networks and the simulation of runoff hydrograph experiences are reviewed with nonlinear functional approximator by artificial neural network for rainfall-runoff relationships in a watershed. which is regarded as hydrdologic black box model. The neural network models are constructed by organizing input and output patterns with the deserved rainfall and runoff data in Pyoungchang river basin under the assumption that the rainfall data is the input pattern and runoff hydrograph is the output patterns. Analyzed with the results. it is possible to simulate the runoff hydrograph with processing element of artificial neural network with any hydrologic concepts and the weight among processing elements are well-adapted as model parameters with the assumed model structure during learning process. Based upon these results. it is expected that neural network theory can be utilized as an efficient approach to simulate runoff hydrograph and identify the relationship between rainfall and runoff as hydrosystems which is necessary to develop and manage water resources.

• The Journal of Engineering Geology
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• v.29 no.3
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• pp.303-314
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• 2019

Surface permeability and shallow geological structures play significant roles in shaping the groundwater recharge of shallow aquifers. Surface permeability can be characterized by two concepts, intrinsic permeability and hydraulic conductivity, with the latter obtained from previous near-surface geological investigations. Here we propose a hydraulic equation via the cross-correlation analysis of the rainfall-groundwater levels using a regression equation that is based on the cross-correlation between the grain size distribution curve for unconsolidated sediments and the rainfall-groundwater levels measured in the Gyeongju area, Korea, and discuss its application by comparing these results to field-based aquifer test results. The maximum cross-correlation equation between the hydraulic conductivity derived from Zunker's observation equation in a sandy alluvial aquifer and the rainfall-groundwater levels increases as a natural logarithmic function with high correlation coefficients (0.95). A 2.83% difference between the field-based aquifer test and root mean square error is observed when this regression equation is applied to the other observation wells. Therefore, rainfall-groundwater level monitoring data as well as aquifer test are very useful in estimating hydraulic conductivity.

• Journal of the Korean Geotechnical Society
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• v.35 no.10
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• pp.17-31
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• 2019

This study describes a prediction method for rainfall-induced landslides and subsequently debris flows in a regional scale areas. Special attention is given to the calculation of the propagation of debris flows by considering rainfall infiltration into soil slopes and soil entrainments by debris flows. The proposed method was verified by comparing the analytical results and the measured ones reported by the previous research. As a result, predictions and observations were quite similar in terms of the front position, the velocity, volume and momentum of debris flows. Even when applied to natural mountain slope with complicated terrain, numerical results and observations were similar. At last, the combined analysis of landslides and debris flows were conducted. The landslides prediction showed a predictive rate of about 83%, and the result of the final volume of debris flow showed an error rate of 3%. As a result, the proposed combined method for landslides and debris flows overcomes the problem of separating the landslides analysis and the debris flows simulation. Especially, the proposed method can analyze the effects of rainfall on entrainments by debris flows as well as rainfall-induced landslides and the behavior of debris flows.