• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.1
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• pp.99-108
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• 1990

A Synthetic Unit Hydrograph Method was investigated for representation of the effective rainfall-direct runoff hydrograph by using a Geomorphologic Instantaneous Unit Hydrograpb(GIUH) proposed by Gupta et al(1980). The response function of the basin was assumed to be the two-parameter gamma probability density function. The physical parameters of the response function(Nash Model) was determined by using the regression eqs. were parameterized in terms of Horton order ratios and the relations between the basin lag time and time-scale parameter. The capability of the Synthetic Unit Hydrograph to the real basin was tested for the Pyungchang river basin and Wi Stream basin, and its capability to reproduce the hydrologic response was investigate and compared with the Moment Method and the Least Square Method used incomplete gamma function. The representation of the peak flow, the time to peak and the hydrographs the derived Synthetic Unit Hydrograph were tested on some obseved flood data and showed promising, and it was approved to be used for prediction of the ungaged basins.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4B
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• pp.353-360
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• 2011

The objectives of this study were to analyzes temporal variation of local scour depth in the downstream of weir with shapes. Prediction of maximum or equilibrium scour depth was the main focus of engineers and researchers in the downstream of weir. However, it is necessary to analyzes temporal variation of local scour depth in the downstream of weir to predict real time scour depth. Experiment were performed with various weir shapes like sharp crest and inclined stepped with time variation and non-dimensional scourhole shapes, scour depths were proposed. A formula for predicting scour depths with temporal variation for weir were proposed through non-linear regression analysis. Temporal variation of scour depths could be estimated with suggested formula and 4 input data (Equilibrium scour depth, weir height, overflow depths, and water depth downstream). Suggested formula could make it possible to design a apron and bed protection economically in the downstream of a weir by considering flood duration time.

• Coupled systems mechanics
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• v.4 no.1
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• pp.37-65
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• 2015

Modeling and simulation of mechanical response of infrastructure object, solids and structures, relies on the use of computational models to foretell the state of a physical system under conditions for which such computational model has not been validated. Verification and Validation (V&V) procedures are the primary means of assessing accuracy, building confidence and credibility in modeling and computational simulations of behavior of those infrastructure objects. Validation is the process of determining a degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. It is mainly a physics issue and provides evidence that the correct model is solved (Oberkampf et al. 2002). Our primary interest is in modeling and simulating behavior of porous particulate media that is fully saturated with pore fluid, including cyclic mobility and liquefaction. Fully saturated soils undergoing dynamic shaking fall in this category. Verification modeling and simulation of fully saturated porous soils is addressed in more detail by (Tasiopoulou et al. 2014), and in this paper we address validation. A set of centrifuge experiments is used for this purpose. Discussion is provided assessing the effects of scaling laws on centrifuge experiments and their influence on the validation. Available validation test are reviewed in view of first and second order phenomena and their importance to validation. For example, dynamics behavior of the system, following the dynamic time, and dissipation of the pore fluid pressures, following diffusion time, are not happening in the same time scale and those discrepancies are discussed. Laboratory tests, performed on soil that is used in centrifuge experiments, were used to calibrate material models that are then used in a validation process. Number of physical and numerical examples are used for validation and to illustrate presented discussion. In particular, it is shown that for the most part, numerical prediction of behavior, using laboratory test data to calibrate soil material model, prior to centrifuge experiments, can be validated using scaled tests. There are, of course, discrepancies, sources of which are analyzed and discussed.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Atmosphere
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• v.21 no.4
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• pp.391-404
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• 2011

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• Journal of Korean Society on Water Environment
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• v.23 no.2
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• pp.236-243
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• 2007

Fluorescence measurements of dissolved organic matter (DOM) have the superior advantages over other analysis tools for the applications to water quality management due to their rapid analysis. It is known that protein-like fluorescence characteristics are well corelated with microbial activities and biodegradable organic matter. In this study, potential biochemical oxygen demand (BOD) predictor were explored using the fluorescence peak intensities and/or the integrated fluorescence intensities derived from synchronous fluorescence spectra and the first derivative spectra of river samples. A preliminary study was conducted using a mixture of a river and a treated sewage to test the feasibility of the approach. It was demonstrated that the better BOD predictor can be derived from synchronous fluorescence spectra and the derivatives when the difference between the emission and the excitation wavelengths (${\Delta}{\gamma}$) was large. The efficacy of several selected fluorescence parameters was rivers in Seoul. The fluorescence parameters exhibited relatively good correlation coefficients with the BOD values, ranging from 0.59 to 0.90. Two parameters were suggested to be the optimum BOD predictors, which were a fluorescence peak at a wavelength of 283 nm from the synchronous spectrum at the ${\Delta}{\gamma}$ value of 75 nm, and the integrated fluorescence intensity of the first derivatives of the spectra at the wavelength range between 245 nm and 280 nm. Each BOD predictor showed the correlation coefficients of 0.89 and 0.90, respectively. It is expected that the results of this study will provide important information to develop a real-time efficient sensor for river BOD in the future.

• Journal of the Korean GEO-environmental Society
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• v.12 no.5
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• pp.29-36
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• 2011

In this study, settling experiment was performed about cohesive and sandy soils among representative sample expected to dredge and dump for analysis of settling and consolidation characteristic. The analysis showed the definite difference between cohesive soils and sandy soils of relationships with settling and consolidation coefficient, a water content, interfacial heights. But directly after a dredged reclamation, prediction results about a initial volume change showed that cohesive soil of a water content change was decreased rapidly as time goes by, but sandy soils made no difference in a water content change. Results were compared and analyzed with the settling and consolidation coefficient and a initial settling velocity by real soil amounts for a feasibility check about test conditions applied to these experiment: we judge that test conditions are appropriate, each material by such these analyses suggests the scope of settling and consolidation coefficient, average and the representative relational formula.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.61-73
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• 2009

To efficiently carry out the flood management of a multipurpose dam, two flood forecasting models are developed, each of which has the capabilities of forecasting upstream inflows and flood discharges downstream of a dam, respectively. The models are calibrated, validated, and evaluated by comparison of the observed and the runoff forecasts upstream and downstream of Namgang Dam. The upstream inflow forecasting model is based on the Grey system theory and employs the sixth order differential equation. By comparing the inflows forecasted by the models calibrated using different data sets with the observed in validation, the most appropriate model is determined. To forecast flood discharges downstream of a dam, a Grey model is integrated with a modified Muskingum flow routing model. A comparison of the observed and the forecasted values in validation reveals that the model can provide good forecasts for the dam's flood management. The applications of the two models to forecasting floods in real situations show that they provide reasonable results. In addition, it is revealed that to enhance the prediction accuracy, the models are necessary to be calibrated and applied considering runoff stages; the rising, peak, and falling stages.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.