• Journal of Korean Society on Water Environment
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• v.31 no.5
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• pp.491-506
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• 2015

Distributed models represent watersheds using a network of numerous, uniform calculation units to provide spatially detailed and consistent evaluations across the watershed. However, these models have a disadvantage in general requiring a high computing cost. Semi-distributed models, on the other hand, delineate watersheds using a simplified network of non-uniform calculation units requiring a much lower computing cost than distributed models. Employing a simplified network of non-uniform units, however, semi-distributed models cannot but have limitations in spatially-consistent simulations of hydrogeochemical processes and are often not favoured for such a task as identifying critical source areas within a watershed. Aiming to overcome these shortcomings of both groups of models, a hybrid watershed model STREAM (Spatio-Temporal River-basin Ecohydrology Analysis Model) was developed in this study. Like a distributed model, STREAM divides a watershed into square grid cells of a same size each of which may have a different set of hydrogeochemical parameters reflecting the spatial heterogeneity. Like many semi-distributed models, STREAM groups individual cells of similar hydrogeochemical properties into representative cells for which real computations of the model are carried out. With this hybrid structure, STREAM requires a relatively small computational cost although it still keeps the critical advantage of distributed models.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.515-518
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• 2003

Mathematical models can be used to evaluate the effects of operational alternatives of dam on the downstream aquatic environment. An unsteady, one-dimensional water quality model, CE-QUAL-RIVI was calibrated and validated in Geum river as a sub model for the realtime water management system in the basin. The main usage of the model within the system is to predict the effects of flow regulation by Daecheong Dam on the downstream water quality. The validated model was then used to simulate dynamic water quality changes at several key stations responding to different scenarios of reservoir releases under a hypothetical spill condition. The model showed fairly good performance in the simulation of hydrodynamic and mass transport processes under highly unsteady conditions.

• Journal of Korean Society of Rural Planning
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• v.2 no.2
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• pp.91-102
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• 1996

Monitoring techniques for afro-ecological environments were studied, Hydrologic and ecological components in conjunction with water quality were monitored in the Balkan watershed. The hydrologic monitoring program consists of four water level gauging stations along creeks and stream at the watershed having 26.5 km2. Stage - storage relationship of reservoir, rainfall amount of the watershed, and rating curve of the stream gauging stations were established. Soil type, land use, hydrologic soil group, population and economic activities within the watershed were surveyed. Water quality data from the streams were sampled weekly and chemical analysis was conducted. Temporal variations of water quality were investigated and water quality map of each reach of stream was made to identify spatial variations. Seasonal and spatial variations of vegetation densities along stream in the watershed were investigated using grid, Density variations of insect species such as arthropod, flying insect, spider spices, rice insects were also monitored to determine seansonal surveying density. These monitored data will be used to develop monitoring techi%ues and afro - ecological environment models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1477-1485
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• 2018

There are two major issues for activated sludge process in sewage treatment plant. One is how to make sewage be more clean and the other is the energy saving in sewage treatment process. The major monitoring sewage qualities are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent. These are transmitted to the national TMS(Telemetry Monitoring System) at every hour. If these exceed the environmental standard, the environmental charges imposed. So, these water qualities are to be controlled below the environmental standard in operation of sewage treatment plant. And recently, the energy saving is also important in process operation. Over 50% energy is consumed in blowers and motors for injection oxygen into aeration tank. So, with the water qualities to be controlled below the environmental standard, the energy saving also is to be accomplished for efficient plant management. Almost researches are aimed to control water quality without considering energy saving. AI techniques have been used for control water quality. AI modeling simulator provided the optimal control inputs(blower speed, waste sludge, return sludge) for control water quality. Blower speed is the main control input for activated sludge process. To make sewage be more clean, the excessive blower speed is supplied, but water quality is not better than the previous. In results, non necessary energy is consumed. In this paper we propose a new method that the energy saving also is to be accomplished with the water qualities to be controlled below the environmental standard for efficient plant management. Water qualities in only aeration tank are used the inputs of fuzzy models. Outputs of these models are chemical oxygen demand, phosphorus, nitrogen, suspended solid in effluent and have the environmental standards. In test, we found this method could save 10% energy than the previous methods.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.121-129
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• 2008

Major factors affecting water quality in rivers are transportation, input of pollutant loads and kinetic transformation of pollutants. Government level decision makings on water quality management are based on steady state water quality modeling. However, it is more than often that such a steady state assumption is far from real situations in rivers. Therefore, it is unavoidable to have modeling errors in water quality modeling especially for steady state modeling for longer period of time. Authors attempted to identify sources of errors in results of steady state models and thus tried to find out ways to minimize those errors. Three water quality models, QUAL2E (Brown et al., 1983), QUAL2K (Chapra et al., 2006) and CAP (Seo and Lee, 2000) were applied to the lower stream of the Geum River. $BOD_5$ and COD tend to underestimate observed data while TN and TP showed relatively smaller errors. QUAL2E model provided best calibration results for BOD5 and TP and QUAL2K model showed best calibration results for TN. Since these errors are only relative values, it was difficult to conclude which model is better performing in certain situations. The most probable reasons for errors in water quality modeling are; 1) inappropriate consideration on flow characteristics, 2) lack of information on incoming pollutant load and 3) inappropriate location of sampling for water quality analysis.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.141-146
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• 2002

Chlorophyll-a concentration maps of Yongdam reservoir in September and October, 2001 were produced using Landsat ETM imagery and the in-situ water quality measurement data. In-situ water samples were collected on 16th September and 18th October during the satellite overpass. The correlations between the DN values of the imagery and the values of chlorophyll-a concentration were analyzed. The visible bands(band 1, 2, 3) and the near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed correlation coefficient values of about 0.7 due to the low variations of chlorophyll-a concentration. Regression models between the DN values of the Landsat ETM image and the chlorophyll-a concentration have been developed for each image. The developed regression models were then applied to each image, and finally the chlorophyll-a distribution maps of Yongdam reservoir were produced. The produced maps showed the spatial distribution of the chlorophyll-a in Yongdam reservoir in a synoptic way so that the tropic state could be easily monitored and analysed in the spatial domain.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.46-60
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• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.227-233
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• 2022

The objective of the study, to develop adsorbent based purifier for removal of radiological and nuclear contaminants from contaminated water. In this regard, 3-aminopropyl silica functionalized with ethylenediamine tetraacetic acid (APS-EDTA) adsorbent prepared and characterized by Fourier Transform Infrared Spectroscopy (FT-IR), Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD). Prepared APS-EDTA used for adsorptive studies of Cs(I), Co(II), Sr(II), Ni(II) and Cd(II) from contaminated water. The effect on adsorption of various parameters viz. contact time, initial concentration of metal ions and pH were also analyzed. The batch method has been employed using metal ions in solution from 1000-10000 ㎍/L, contact time 5-60 min., pH 4-10 and material quantities 50-200 mg at room temperature. The obtained adsorption data were used for drawing Freundlich and Langmuir isotherms model and both models were found suitable for explaining the metal ions adsorption on APS-EDTA. The adsorption data were followed pseudo second order reaction kinetics. The maximum adsorption capacity obtained 1.3037-1.4974 mg/g for above said metal ions. The results show that APS-EDTA have great potential to remove Cd(II), Co(II), Cs(I), Ni(II) and Sr(II) from aqueous solutions through chemisorption and physio-sorption.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.6
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• pp.657-664
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• 2008

This research compared several unsteady friction models for transient analysis of pipeline system. Unsteady friction is an important factor for accurate simulation of hydraulic transient. Steady friction, quasi-steady friction, Zielke's model and two versions of Brunone model were compared with measurement data of identical pipeline conditions. This study showed that the existing simple steady friction model can be useful for the safer design of pipeline system due to its overestimation of waterhammer, but introduction of more elaborate models are required for advanced analysis such as inverse transient analysis of friction or leakage and the preliminary analysis of water quality prediction of water distribution system.