• Water Engineering Research
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• v.4 no.3
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• pp.155-173
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• 2003

Parameters and quantiles of the 2-parameter generalized Pareto distribution were estimated using the methods of regular moments, modified moments, probability weighted moments, linear moments, maximum likelihood, and entropy for Monte Carlo-generated samples. The performance of these seven estimators was statistically compared, with the objective of identifying the most robust estimator. It was found that in general the methods of probability-weighted moments and L-moments performed better than the methods of maximum likelihood estimation, moments and entropy, especially for smaller values of the coefficient of variation and probability of exceedance.

• Proceedings of the Korea Water Resources Association Conference
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• 1987.07a
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• pp.151-158
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• 1987

The purpose of thes study is to estimate the parameters of linear reservoir models in order to derive the instantaneous unit hydrograph from a given small experimental watershed. The linear reservoir model is a conceptual model, consisting of cascade or parallel equal linear reservoirs, preceded by a linear channel which involved NASH, SLR(single linear reservoir)and 2-PLR(two-parallel linear reservoir)model. The NASH model have two parameters N and K, single linear reservoir has one parameter K1 and two-parallel linear reservoirs have two parameters K1, K2;where N denote the number of reservoirs and K is the storage coefficient of each reservoirs.

• Journal of Environmental Science International
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• v.26 no.10
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• pp.1125-1133
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• 2017

In this study a method for filling in missing data of river water temperature using a pre-constructed mathematical relationship between air and water temperatures is presented. A regression between water temperatures at individual stations and ambient air temperatures at nearby weather stations can provide a practical method for representing missing water temperature data for an entire region. Air and water temperature data that were collected from two test sites (one coastal and, one inland) were individually fitted to a nonlinear regression model. To consider seasonal hysteresis effects, separate functions were fitted to the data in the rising and falling limbs. A single-criterion, multi-parameter optimization technique was used to determine the optimal parameter sets. This method minimizes the differences between the time series of the measured and estimated data. The constructed air-water temperature relationship was subsequently applied to represent missing water temperature data. It was found that the RMSEs(MBEs) were in the range of $1.843-1.976^{\circ}C(-0.329-0.201^{\circ}C)$ and the coefficient of determination were in the range of 0.92-0.96. The results demonstrate that the predicted water temperatures using the regression equations were reasonably accurate.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.292-299
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• 2012

The objective of this study is to develop a novel method for evaluating forward osmosis (FO) membrane performances using a non-pressurized FO system. Basic membrane performance parameters including water (A) and solute (B) permeability coefficients and unique parameter for FO membrane such as the support layer structural parameter (S) were determined in two FO modes (i.e., active layer faces feed solution (AL-FS) and active layer faces draw solution (AL-DS)). Futhermore, these parameters were compared with those determined in a pressurized reverse osmosis (RO) system. Theoretical water flux was calculated by employing these parameters to a model that accounts for the effects of both internal and external concentration polarization. Water flux from FO experiment was compared to theoretical water fluxes for assessing the reliability of those parameters determined in three different operation modes (i.e., AL-FS FO, AL-DS FO, and RO modes). It is demonstrated that FO membrane performance parameters can be accurately measured in non-pressurized FO mode. Specifically, membrane performance parameters determined in AL-DS FO mode most accurately predict FO water flux. This implies that the evaluation of FO membrane performances should be performed in non-pressurized FO mode, which can prevent membrane compaction and/or defect and more precisely reflect FO operation conditions.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.2
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• pp.86-96
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• 1997

In order to investigate the formation of a shallow water front and its relation to water quality distributions, oceanographic measurements were made, and the numerical computations of the Simpson-Hunter stratification parameter log(H/U$^3$) were performed. It is shown from satellite image and hydrographic data that the shallow water front is formed near the northern Kaduk channel, and the stratification parameter log(H/U$^3$) near the front is in a range of 2.0-2.5. Measured COD (Chemical Oxygen Demand) concentrations in offshore region of the front and in the western part of the bay are below 2.0 mg/1. whereas the concentrations in Masan Bay located in the northern inside of the frontal zone are high as 3.0-5.5 mg/1. COD concentrations decrease gradually from Masan Bay toward the offshore due to the dilution by strong water mixing. Anoxic and hypoxic water masses at the bottom layer in summcr occur in the western part of Chinhae Bay and in Masan Bay, and DO (Dissolved Oxygen) concentrations become low with increasing the stratification parameter. DO concentrations outside the front are more than about 4.0 mg/1, whereas the concentrations inside the front are low. The shallow water front plays a significant role for material transport from coastal area to oceanic area, and the frontal region seems to be important physical and chemical boundaries.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Journal of Korea Water Resources Association
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• v.35 no.2
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• pp.161-171
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• 2002

It has been known that the accurate estimates of 2-dimensional water quality model parameters are difficult for non-experts due to the complexity of theoretical background and input requirement and complicated inter-relationship between model Parameters. The main goal of this study is to Provide expert system for the optimal estimation of water quality model parameters, which is based on the development of chaining mechanism according to the sensitivity analysis of model parameter interactions and GUI interface system on ArcView Avenue. The selected study area is the 35.3- km main Han river starting from Paldang Dam site to the Point of Indo bridge and the tributary inflows including pollutant data are used for the system application and validation. The estimated main model parameters are 0.367 for transverse dispersion coefficient, 0.074 for and 0.162 for. It also shows that the simulated water quality constituents such as DO and BOD based on the estimated model parameters are well agreed with the observed ones. It can be concluded that the developed GIS-based expert system for water quality model parameter estimation and graphical representation of water quality analysis is useful for the scientific water quality management.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.1
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• pp.28-33
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• 2013

Multidirectional random waves that obliquely approach the shore were found to become directionally asymmetric due to refraction. The directional asymmetry was expressed in terms of the asymmetry parameter which is related to the maximum spreading parameter ($s_{max}$). In this study, we calculate variation of both the asymmetry and maximum spreading parameters at different water depths for various cases of incident wave angles and maximum spreading parameters in deep water. These values are different from Goda and Suzuki (1975) who neglected directional asymmetry of waves. In calculating directional asymmetry and maximum spreading parameters, we use the JONSWAP spectrum (Hasselmann et al., 1973) and Lee et al.'s (2010) directional distribution function. The processes and results are nondimensionalized with significant wave height, peak frequency and peak wave length in deep water.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1900-1908
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• 2014

This paper establishes a compact and practical model for a water-wall system comprising supercritical once-through boilers, which can be used for automatic control or simple analysis of the entire boiler-turbine system. Input and output variables of the water-wall system are defined, and balance equations are applied using a lumped parameter method. For practical purposes, the dynamic equations are developed with respect to pressure and temperature instead of density and internal energy. A comparison with results obtained using APESS, a practical thermal power plant simulator developed by Doosan Heavy Industries and Construction, is presented with respect to steady state and transient responses.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.57-62
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• 2003

It is difficult to determine the feeding rate of coagulant in the water treatment plant, due to nonlinearity, multivariables and slow response characteristics etc. To deal with this difficulty, the genetic-fuzzy system genetic-equation system and the neural network system were used in determining the feeding rate of the coagulant. Fuzzy system and neural network system are excellently robust in multivariables and nonlinear problems. but fuzzy system is difficult to construct the fuzzy parameter such as the rule table and the membership function. Therefore we made the genetic-fuzzy system by the fusion of genetic algorithms and fuzzy system, and also made the feeding rate equation by genetic algorithms. To train fuzzy system, equation parameter and neural network system, the actual operation data of the water treatment plant was used. We determined optimized feeding rates of coagulant by the fuzzy system, the equation and the neural network and also compared them with the feeding rates of the actual operation data.