• Spatial Information Research
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• v.4 no.2
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• pp.147-157
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• 1996

A rural water quality management information system(RWQMIS) by integrating Geo¬graphic Information System(GIS) with the existing models (pollutants transport and river water quality) is described. A simple pollutant load model to calculate delivered pollutants to stream, Tank model to generate daily runoff and QUAL2E model to predict river water quality, were incorporated into GIS. The system was applied to $80km^2$ watershed in Icheon Gun and Yongin Gun, Kyonggi Do. The spatial distributions of produced pollutant load, discharged pollutant load, delivered ratio to the stream, and the river water quality status for given sites were successfully generated.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.783-788
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• 1999

In this study, a decision support system (DSS) was developed to calculate optimal wastetreatment cost, treatment level and treatment quantity of various pollutants for applying for in rural basin. The DSS includes a gegraphic informatino system (GIS), relational database system (RDBS), water quality models(Loading function , WASP5), watershed pollution load calculation module(SPLC), optimal water quality management plan to satisfy the water quality regulations. The system can be modified by user to trace the optimal condition for decision. The effort was conducted to apply the developed DSS to select the for optimal water quality management plan small rural basin called Kwanri Stream.

• Journal of Environmental Impact Assessment
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• v.9 no.1
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• pp.25-37
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• 2000

This paper presents a study of hydrological and hydraulic model applications in environmental impact statements which were submitted during recent years in Korea. In many cases (almost 70 %), the hydrological and hydraulic changes were neglected from the impact identification processes, even if the proposed actions would cause significant impacts on those environmental items. In most cases where the hydrological and hydraulic impacts were predicted, simple equations were used as an impact prediction tool. Computer models were used in very few cases(5%). Even in these few cases, models were improperly applied and thus the predicted impacts would not be reliable. The improper applications and the impact neglections are attributed to the fact that there are no available model application guidelines as well as no requirements by the review agency. The effects of mitigation measures were not analyzed in most cases. Again, these can be attributed to no formal guidelines available for impact predictions until now. A brief guideline is presented in this paper. This study suggested that the model application should be required and guided in detail by the review agency. It is also suggested that the hydrological and hydraulic items shoud be integrated with the water quality predictions in future, since the non-point source pollution runoff is based on the hydrologic phenomena and the water quality reactions on the hydraulic nature.

• Journal of Environmental Impact Assessment
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• v.20 no.1
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• pp.25-36
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• 2011

In this study, the accurate water quality analysis in rivers, including the non-point source is performed. First of all, watershed model, SWAT(Soil and Water Assessment Tool) was applied to analyze the impact of the non-point source in study area. And then, water quality analysis integrating the point source and the non-point source is implemented using QUALKO model. For more exact simulation, it should be the calibration and verification of variables and parameters which are needed for simulation. In addition, the importance of considering the non-point source was confirmed in river water quality simulation. BOD, TN, TP were analysed, and the results shows that BOD, TN and TP concentration was increased to 16.8%, 8.2% and 25.8% respectively. The more accurate estimate will be carried if use of reliable measurements and watershed simulation be done in models linking process. The suggested technique will improve the accuracy of the water quality analysis. The methodologies presented in this study will contribute to basin-wide water quantity and quality management.

• Environmental Engineering Research
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• v.24 no.4
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• pp.582-590
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• 2019

Currently, the waterfront facility was constructed in New Songdo City, South Korea. It has the various water leisure areas and especially an artificial urban canal with filtered seawater by re-circulating flow system. However, due to excessive amount of nutrients from seawater combined with complicated geometry, it is highly vulnerable to deterioration of water quality. In this study, flow characteristics and pollutant transport were analyzed with comprehensive numerical models, MIKE 3 FM and ECO-lab. Based on these numerical results, notable sampling points were selected for field measurements and comparison between modeling and measured results were conducted. In addition, the integrated water quality evaluation index, Water Quality Index was applied to analyze various water quality issues. We also set up scenarios to control the two kinds of water quality factors, dissolved oxygen (DO), and total phosphorus (TP). As a result, the effect of 20% reduction of TP was less than 10% and it was almost ineffective for a year but it was reduced by up to 40% in case of scenario which DO is increased by 20%. Therefore, it was recommended to control the DO concentration, usually by applying re-aeration facility, rather than TP in artificial urban canal with seawater.

• Coupled systems mechanics
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• v.8 no.6
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• pp.489-500
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• 2019

With drinking water standards becoming more rigorous and increasing demands for additional water quantities, while water resources are becoming more polluted, mathematical models became an important tool to improve water treatment processes performance in the water supply system. Water treatment processes models reflect the knowledge of the processes and they are useful tools for water treatment process optimization, design, operator training for decision making and fundamental research. Unfortunately, in the current practice of drinking-water production and distribution, water treatment processes modeling is not successfully applied. This article presents a review of some existing water treatment processes simulators and the experience of their application and indicating the main weak points of each process. Also, new approaches in the modeling of water treatment are presented and recommendations are given for the work in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.1-12
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• 2022

Estuary reservoirs were artificial reservoir with seawalls built at the exit points of rivers. Although many water resources can be saved, it is difficult to manage due to the large influx of pollutants. To manage this, it is necessary to analyze watersheds and reservoirs through accurate modeling. Therefore, in this study, we linked the Hydrological Simulation Program-FORTRAN (HSPF), Environmental Fluid Dynamics Code (EFDC), and Water quality Analysis Simulation Program (WASP) models to simulate the hydrology and water quality of the watershed and the water level and quality of estuary lakes. As a result of applying the linked model in stream, R² 0.7 or more was satisfied for the watershed runoff except for one point. In addition, the water quality satisfies all within 15% of PBIAS. In reservoir, R² 0.72 was satisfied for water level and the water quality was within 15% of T-N and T-P. Through the modeling system, We applied upstream pollutant management scenarios to analyze changes in water quality in estuary reservoirs. Three pollution source management were applied as scenarios, the improvement of effluent water quality from the sewage treatment plant and the livestock waste treatment plant was effective in improving the quality of the reservoir water, while the artificial wetland had little effect. Water quality improvement was confirmed as a measure against upstream pollutants, but it was insufficient to achieve agricultural water quality, so additional reservoir management is required.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.413-424
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• 2011

The study was aimed to evaluate the applicability of a three-dimensional (3D) hydrodynamic and water quality model, ELCOM-CAEDYM for Yongdam Reservoir, Korea. The model was applied for the simulations of hydrodynamics, thermal stratification processes, stream density flow propagation, and water quality parameters including dissolved oxygen, nutrients, organic materials, and algal biomass (chl-a) for the period of June to December, 2006. The field data observed at four monitoring stations (ST1~ST4) within the reservoir were used to validate the models performance. The model showed reasonable performance nevertheless low frequency boundary forcing data were provided, and well replicated the physical, chemical, and biological processes of the system. Simulated spatial and temporal variations of water temperature, nutrients, and chl-a concentrations were moderately consistent with the field observations. In particular, the model rationally reproduced the succession of different algal species; i.e., diatom dominant during spring and early summer, after then cyanobacteria dominant under warm and stratified conditions. ELCOM-CAEDYM is recommendable as a suitable coupled 3D hydrodynamic and water quality model that can be effectively used for the advanced water quality management of large stratified reservoirs in Korea.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• 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.