• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.93-103
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• 2018

The aim of this study is to apply the Water-Energy-Food-Land Nexus approach which can analyze the trade-offs among resources, and assess the holistic impacts of food security. First, we applied rice as a study crop and analyzed the trend of consumption of rice and the area of paddy fields. Second, the portfolios of water, energy, and land for rice production were constructed using data of footprints and productivity. Finally, the self-sufficiency ratio (SSR) of rice in target year was set as food security scenario and assessed the impacts of food security on water, energy, and land availability. In 2030, the SSR of rice decreased to 87 %, and water use for producing rice decreased from 4,728 to $3,350million\;m^3$, and the water availability index increased from 0.33 to 0.53. However, food security is essential issue and we set the 50 % and 100 % SSR of rice as high and low food security scenarios. For 100% SSR in 2030, about $3,508million\;m^3$ water was required and water availability index reached to 0.5. In other words, there is the trade-off between food security and water-energy-lands availability. Therefore, it is difficult to make a decision whether a high level of SSR is better or worse. However, this study showed the both positive and negative impacts by change of food security and it can be useful for setting the policy decision considering both food security and sustainable resource management at the same time.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Journal of Korean Society on Water Environment
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• v.37 no.6
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• pp.501-509
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• 2021

In 2018, total 263 micro and emerging contaminants were selected as target substances by the Ministry of Environment, and 80 of them were first-class substance including endocrine disruptors, residual Pharmaceuticals and Personal Care Products (PPCPs), residual organic pollutants, pesticides and heavy metals. In this study, in order to evaluate the Hazard Quotient (HQ) of the 80 types in the domestic water environment the concentration of discharged effluent and nearby water environment reported by Korean institutes since 2010 was investigated. There were 45 substances reported to be detected, and Measurement Environment Concentration (MEC) were obtained by collectively converting them into water environment concentration. For biotoxicity, half maximal Effective Dose (EC50) to Daphnia magna, a water fleas species widely adopted in Material Safety Data Sheet (MSDS) was applied. As for the biotoxicity level, the Predicted No-Effect Concentration (PNEC) was obtained by applying the Assessment Factor (AF) and the HQ was derived by dividing it from the MEC. As a result of calculating the HQ, more than 1 substances were Cabamazepine, Mefenamic acid, Acetaminophen, Ibuprofen, Nonylphenol, Nickel, Erythromycin, Acetylslic acid, etc. Meanwhile, perfluorinated compounds were identified as hazardous substances in the water env ironment, with 5 out of 14 species included in the 20 ranks of first-class substance.

• Journal of Environmental Science International
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• v.21 no.1
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• pp.57-67
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• 2012

The midge samples were undertaken at three streams, representing different surrounding environments, to investigate the contaminant exposure of midge. The content of heavy metals in midge collected in Singil stream were generally higher as a result of input to the industrial effluents with respect to other streams. Adsorption experiments were done to evaluate the possibility of removing contaminants from water with midge. Diazinon and heavy metals were contaminant target compounds in this study. The removal rate of diazinon in water by midge was 60-75%. In the case of Cu, the removal rate was reached around 90% at the lower initial concentration of 1.87 and 0.81 ppm rather than 4.25 ppm. The reduction of concentration of Cr and Cd according to the lapse of time was similar to the Cu, but their removal rates were shown 50% and 60-74%, respectively. The removal rate of Zn by midge represented relatively high level within the experimental condition. No change in concentration of Cr and As with time were occurred at all experimental conditions. It accounts for the fact that the reduction of Cr and As could not be achieved through the adsorption process, using midge.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2556-2563
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• 2021

Metaheuristic algorithms can work well in solving or optimizing problems, especially those that require approximation or do not have a good analytical solution. Particle swarm optimization (PSO) is one of these algorithms. The response quality of these algorithms depends on the objective function and its regulated parameters. The nonlinear nature of the pressurized light-water nuclear reactor (PWR) dynamics is a significant target for PSO. The two-point kinetics model of this type of reactor is used because of fission products properties. The proportional-integral-derivative (PID) controller is intended to control the power level of the PWR at a short-time transient. The absolute error (IAE), integral of square error (ISE), integral of time-absolute error (ITAE), and integral of time-square error (ITSE) objective functions have been used as performance indexes to tune the PID gains with PSO. The optimization results with each of them are evaluated with the number of function evaluations (NFE). All performance indexes achieve good results with differences in the rate of over/under-shoot or convergence rate of the cost function, in the desired time domain.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.249-249
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• 2023

Spring drought forecasting in South Korea is essential due to the sknewness of rainfall which could lead to water shortage especially in spring when managed without prediction. Therefore, drought forecasting over South Korea was performed in the current study by thoroughly searching appropriate predictors from the lagged global climate variable, mean sea level pressure(MSLP), specifically in winter season for forecasting time lag. The target predictand defined as accumulated spring precipitation(ASP) was driven by the median of 93 weather stations in South Korea. Then, it was found that a number of points of the MSLP data were significantly cross-correlated with the ASP, and the points with high correlation were regionally grouped. The grouped variables with three regions: the Arctic Ocean (R1), South Pacific (R2), and South Africa (R3) were determined. The generalized linear model(GLM) was further applied for skewed marginal distribution in drought prediction. It was shown that the applied GLM presents reasonable performance in forecasting ASP. The results concluded that the presented regionalization of the climate variable, MSLP can be a good alternative in forecasting spring drought.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.599-606
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• 1998

This study was carried out to develop the control system with PLC and its operating software and to investigate its control ability of greenhouse environments. Two experimental greenhouses were controlled by PLC and ON/OFF controller, respectively. In greenhouse controlled by PLC, target values of air temperature, relative humidity and $CO_2$ concentration were automatically changed. In warm-water heating, the variation of air temperature was reduced to $\pm$ $0.6^{\circ}C$ by the method of proportional-integration(PI) control with an inverter. In ventilation, the variation of air temperature was reduced, since windows open and close with multistage by mutual relation formula among the target, indoor, and outdoor temperature. Relative humidity at daytime was maintained with range of 35% to 55% by PLC controlled fogger. $CO_2$ concentration was automatically controlled from 300 to 800 $\mu$molㆍ$mol^{-1}$ according to amount of solar radiation. The suppling amount and frequency of nutrient solution were controlled by total integrated solar radiation. Difference in the yield of cucumber in the greenhouse controlled by PLC and by ON/OFF controller was not significant at the 5% level.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.579-588
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• 2016

Changes in precipitation due to climate change is made to induce the local and intensive rainfall, it is increasing damage caused by inland inundation. Therefore, it requires a technique for predicting damage caused by flooding. In this study, in order to determine whether this flood inundated by any route when the levee was destroyed, Which can simulate the path of the flood inundation model was developed for the SIMOD (Simplified Inundation MODel). Multi Direction Method (MDM) for differential distributing the adjacent cells by using the slope and Flat-Water Assumption (FWA)-If more than one level higher in the cell adjacent to the cell level is the lowest altitude that increases the water level is equal to the adjacent cells- were applied For the evaluation of the model by setting the flooding scenarios were estimated hourly range from the target area. SIMOD model can significantly reduce simulation time because they use a simple input data of topography (DEM) and inflow flood. Since it is possible to predict results within minutes, if you can only identify inflow flood through the runoff model or levee collapse model. Therefore, it could be used to establish an evacuation plan due to flooding, such as EAP (Emergency Action Plan).

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.614-621
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• 2010

A indigenous freshwater bivalve Unio douglasiae was introduced to compare the differences in the efficacy of algal bloom control and the appearances of mussel-mediated adverse effects between two different reservoirs such as mesotrophic (Shingu r.) and hypertrophic (Seokmun r.). We constructed the study mesocosm in the shore of each reservoir, stocked the mussel at density of $30indiv./m^3$ for 7 days, and measured daily the phytoplankton density and water quality. In mesotrophic reservoir, even though approximately 38% of suspended solids and chlorophyll-a was reduced by stocked bivalves for the first 3 days, algal density, ammonia and soluble reactive phosphorus gradually increased with increasing mussel death. In hypertrophic reservoir, mussels strongly inhibited suspended solids and chlorophyll-a by the termination of study with no increase of mussel death and nutrient, especially ammonia concentration. In both reservoirs, a strong selectivity showed mussels preferred to diatom rather than cyanobacteria and green algae without algal density and nutrient level. Our results indicate that an introduction of freshwater bivalve U. douglasiae is more strategic to improve water quality of hypertrophic than mesotrophic reservoir, but many preliminary studies on the treatment method and the selection of target water system are required.

• Environmental Engineering Research
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• v.16 no.3
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• pp.121-129
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• 2011

The completely mixed flow and plug flow (CAP) water quality model was developed for streams with discontinuous flows, a condition that often occurs in low base flow streams with in-stream hydraulic structures, especially during dry seasons. To consider the distinct physical properties of each reach effectively, the CAP model stream network can include both plug flow (PF) segments and completely mixed flow (CMF) segments. Many existing water quality models are capable of simulating various constituents and their interactions in surface water bodies. More complicated models do not necessarily produce more accurate results because of problems in data availability and uncertainties. Due to the complicated and even random nature of environmental forcing functions, it is not possible to construct an ideal model for every situation. Therefore, at present, many governmental level water quality standards and decisions are still based on lumped constituents, such as the carbonaceous biochemical oxygen demand (CBOD), the total nitrogen (TN) or the total phosphorus (TP). In these cases, a model dedicated to predicting the target concentration based on available data may provide as equally accurate results as a general purpose model. The CAP model assumes that its water quality constituents are independent of each other and thus can be applied for any constituent in waters that follow first order reaction kinetics. The CAP model was applied to the Geum River in Korea and tested for CBOD, TN, and TP concentrations. A trial and error method was used for parameter calibration using the field data. The results agreed well with QUAL2EU model predictions.