• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.853-865
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• 2014

Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship need to be established to quantify various uncertainties associated modeling process and inputs. However, the systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, two major innovations are introduced to address this situation. The first is the use of a Hierarchical Bayesian model based regional frequency analysis to better convey uncertainties associated with the parameters of probability density function to the dam risk analysis. The second is the use of Bayesian model coupled HEC-1 rainfall-runoff model to estimate posterior distributions of the model parameters. A reservoir routing analysis with the existing operation rule was performed to convert the inflow scenarios into water surface level scenarios. Performance functions for dam risk model was finally employed to estimate hydrologic dam risk analysis. An application to the Dam in South Korea illustrates how the proposed approach can lead to potentially reliable estimates of dam safety, and an assessment of their sensitivity to the initial water surface level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1227-1240
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• 2014

Abandoned mines often cause environmental problems, such as alteration of landscape, metal contamination, and landslides due to a heavy rainfall. Geotechnical and rheological tests were performed on waste materials corrected from Imgi waste rock dump, located in Busan Metropolitan City. Debris flow mobility was examined with the help of 1-D BING model which was often simulated in both subaerial and subaqueous environments. To determine flow curve, we used a vane-penetrated rheometer. The shear stress (${\tau}$)-shear rate (${\dot{\gamma}}$) and viscosity(${\eta}$)-shear rate (${\dot{\gamma}}$) relationships were plotted using a shear stress control mode. Well-known rheological models, such as Bingham, bilinear, Herschel-Bulkley, Power-law, and Papanastasiou concepts, were compared to the rheological data. From the test results, we found that the tested waste materials exhibited a typical shear shinning behavior in ${\tau}$-${\dot{\gamma}}$ and and ${\eta}$-${\dot{\gamma}}$ plots, but the Bingham behavior is often observed when the water contents increased. The test results show that experimental data are in good agreement with rheological models in the post-failure stage during shearing. Based on the rheological properties (i.e., Bingham yield stress and viscosity as a function of the volumetric concentration of sediment) of waste materials, initial flowing shape (5 m, 10 m, and 15 m) and yield stress (100 Pa, 200 Pa, 300 Pa, and 500 Pa) were input to simulate the debris flow motion. As a result, the runout distance and front velocity of debris flow are in inverse propositional to yield stress. In particular, when the yield stress is less than 500 Pa, most of failed masses can flow into the stream, resulting in a water contamination.

• Journal of the Korean Geotechnical Society
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• v.30 no.4
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• pp.35-45
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• 2014

Limit equilibrium methods of slope stability analysis have been widely adopted mainly due to their simplicity and applicability. However, the conventional methods may not give reliable and convincing results for various geological conditions such as nonhomogeneous and anisotropic soils. Also, they do not take into account soil slope history nor the initial state of stress, for example excavation or fill placement. In contrast to the limit equilibrium analysis, the analysis of deformation and stress distribution by finite element method can deal with the complex loading sequence and the growth of inelastic zone with time. This paper proposes a technique to determine the critical slip surface as well as to calculate the factor of safety for shallow failure on partially saturated soil slope. Based on the effective stress field in finite element analysis, all stresses are estimated at each Gaussian point of elements. The search strategy for a noncircular critical slip surface along weak points is appropriate for rainfall-induced shallow slope failure. The change of unit weight by seepage force has an effect on the horizontal and vertical displacements on the soil slope. The Drucker-Prager failure criterion was adopted for stress-strain relation to calculate coupling hydraulic and mechanical behavior of the partially saturated soil slope.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.221-232
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• 2011

Applicability of three soil erosion models for burnt hillslopes was evaluated. The models were estimated with the data from plots established after tremendous wildfire occurred in the east coastal region. Soil erosion and surface runoff were simulated by the Water Erosion Prediction Project (WEPP) and the Revised Universal Soil Loss Equation (RUSLE) of application mode for disturbed forest areas and the Soil Erosion Model for Mountain Areas (SEMMA) developed for burnt hillslopes. Simulated sediment yield and surface runoff were compared with the measured those. In maximum value of sediment yield, three models was under-predicted and RUSLE and WEPP had difference of over two times. SEMMA showed the best model response coefficient, determination coefficient and the model efficiency. In application of models to the soil erosion according to the elapsed year after wildfire, all models were underestimated in initial stage disturbed by wildfire. Evaluation of models in this burnt hillslopes was shown the tends to under-predict soil erosion for larger measured values. Although a lot of sediment can be generated in small rainfall event as fine-grained soil of the high water repellency was exposed excessively right after wildfire, this under-prediction was shown that those models have a limit to estimate the weighted factors by wildfire.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.315-315
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• 2017

In Japan, more than 80 % of soybean growing area is converted fields and excess water is one of the major problems in soybean production. For example, recent study (Yoshifuji et al., 2016) suggested that in the fields of shallow groundwater level (GWL) (< 1m depth), rising GWL even in a short period (e.g. 1 day) causes inhibition of soybean growth. Thus it becomes more and more important to predict GWL and soil moisture in detail. In addition to conventional surface drainage and underdrain, FOEAS (Farm Oriented Enhancing Aquatic System), which is expected to control GWL in fields adequately, has been developed recently. In this study we attempted to predict GWL and soil moisture condition at the converted field with FOEAS in Biwa lake reclamation area, Shiga prefecture, near the center of the main island of Japan. Two dimensional HYDRUS model (Simuinek et al., 1999) based on common Richards' equation, was used for the calculation of soil water movement. The calculation domain was considered to be 10 and 5 meter in horizontal and vertical direction, respectively, with two layers, i.e. 20cm-thick of plowed layer and underlying subsoil layer. The center of main underdrain (10 cm in diameter) was assumed to be 5 meter from the both ends of the domain and 10-60cm depth from the surface in accordance with the field experiment. The hydraulic parameters of the soil was estimated with the digital soil map in "Soil information web viewer" and Agricultural soil-profile physical properties database, Japan (SolphyJ) (Kato and Nishimura, 2016). Hourly rainfall depth and daily potential evapo-transpiration rate data were given as the upper boundary condition (B.C.). For the bottom B.C., constant upward flux, which meant the inflow flux to the field from outside, was given. Seepage face condition was employed for the surrounding of the underdrain. Initial condition was employed as GWL=60cm. Then we compared the simulated and observed results of volumetric water content at depth of 15cm and GWL. While the model described the variation of GWL well, it tended to overestimate the soil moisture through the growing period. Judging from the field condition, and observed data of soil moisture and GWL, consideration of soil structure (e.g. cracks and clods) in determination of soil hydraulic parameters at the plowed layer may improve the simulation results of soil moisture.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.214-226
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• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.373-380
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• 2016

The NRCS-CN (Natural Resources Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. However, there are no criteria which reflect the geographic characteristics of Korea having more than 70% of mountainous and rice paddy areas, leading to significant errors in runoff calculation. Thus, it is required to estimate the runoff curve number considered Korea land use classification, however there are practical difficulties to conduct the accurate research and experimentation. In this study, after selecting target areas (urban, agriculture, forest), we performed the runoff analysis to redetermine CN values for the selected basins. To do this, curve numbers for soil type A were estimated using genetic algorithm, and then curve numbers for soil type (B, C, D) were estimated using CN aligner equation. Comparing the initial curve numbers with the estimated curve numbers, it was observed that the slightly differences at Chunwang(0), Choonyang(-1), Janggi(-3). Through the above process, this study proposed new curve numbers to reflect observed rainfall-runoff.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.60-69
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• 2020

Purpose: Cavity growth process monitoring is to periodically monitor changes in common size and topography for general and observational grades to predict the rate of common growth. The purpose of this study is to establish a systematic cavity management plan by evaluating the general and observational class community in a non-destructive method. Method: Using GPR exploration equipment, the acquired surface image and the surrounding status image are analyzed in the GPR probe radargram in depth, profile, and cross section of the location. The exact location is selected using the distance and surrounding markings shown on the road surface of the initial detection cavity, and the test cavity is analyzed by calling the radar at the corresponding location. Result: As a result of monitoring tests conducted at a cavity 30 sites of general and observation grade, nine sites have been recovered. Changes in scale were seen in 21 cavity locations, and changes in size and grade occurred in 13 locations. Conclusion: The under road cavity is caused by various causes such as damage to the burial site, poor construction, soil leakage caused by groundwater leakage, waste and ground vibration. Among them, indirect factors could infer the effects of groundwater and localized rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1261-1271
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• 2018

This study evaluates the applicability of the classification rule of hydrological soil group proposed by Lee et al. (2018) with its application to three river basins (Jungmuncheon, Cheonmicheon, and Hancheon) in Jeju Island. The CN values are estimated as results of this application to these three basins, which is then compared with those estimated by applying the conventional three methods. Additionally, previous studies related with the classification of soil groups of Jesu Island, such as the infiltration and rainfall-runoff analysis, are reviewed to evaluate how the resulting hydrological soil groups vary depending on the adopted classification method.. Summarizing the results is as follows. (1) Comparison result of the hydrological soil groups of Jeju Island with respect to the classification method shows that the soil group B is dominant in the application of Lee et al. (2018). However, it is hydrological soil groups C and D in the application of Hu and Jung (1987), hydrological soil groups A and C in the application of Jung et al. (1995), and hydrological soil group D in the application of RDA (2007). (2) In all the applications of Lee et al. (2018) to three selected river basins in Jeju Island, the CN valuse are found to be smaller than those by other conventional three methods.. Lastly, (3) The evaluation results of previous studies related with the classification of hydrological soil groups analysis in Jeju Island shows that the CN value in the Jeju Island may be smaller than those estimated by conventional three methods, also the initial loss higher than 0.2S.