• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.91-102
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• 2007

To anticipate and respond to harmful algae produced in a big artificial lake like Daecheong reservoir, development of a regional analysis computer system using GIS or RS technique is needed in addition to biological and chemical research. The purpose of this study is to develop a cyanobacterial blooming prediction model to prevent harmful algae produced in Daecheong reservoir and construct an early forecasting system based on GIS. For this purpose this paper examines previous studies related to the relationship between cyanobacteria and environmental factors in Daecheong reservoir and selects precipitation and air temperature as two important environmental factors for the development of cyanobacterial blooming prediction model. Data used in this study are water quality and weather data for three water regions in Daecheong reservoir between 2000 and 2004. Based on qualitative correlation analysis between cyanobacteria and environmental factors, this paper presents a Rump model which enables us to predict cyanobacteria in water regions of Daecheong reservoir. Under this model the prediction of initial occurrence time and growth period of cyanobacteria are possible. The model is also applied to the GIS-based early forecasting system for cyanobacteria, and finally a GIS which can predict cyanobacteria produced in Daecheong reservoir and can manage the related data is developed.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.134-145
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• 2023

Currently, the floodplains of major rivers are transforming into various types of waterfront spaces according to the increase in leisure activities and improved accessibility. In general, waterfront activities in river channels tend to be concentrated in summer, and the waterfront activities during this period directly affect water quality. Accordingly, it is necessary to accurately compare and evaluate the characteristics and water quality of waterfront activities during the period when waterfront activities are concentrated. In this study, the following research was conducted to compare and analyze the current status of waterfront activities of users of waterfront areas and the water quality of waterfront areas. First, three waterfront areas were selected for investigation using the information from the Ministry of Environment's water quality measurement network. Second, a survey was conducted on the satisfaction and types of waterfront activities targeting users of waterfront areas. Third, water quality grades were calculated based on monthly water quality measurement factors and compared. Fourth, statistical analysis (one-way analysis of variance) was conducted to see if there was a significant difference in water quality characteristics between periods of high waterfront activity and periods of low waterfront activity using water quality measurement data for the last 5 years. As a result of this analysis, the following conclusions were drawn in this study. First, the use of waterfront activities was investigated in the order of camping, water skiing, fishing, swimming, and rafting. Second, satisfaction factors for waterfront activities were investigated in the order of activity convenience, water quality, waterlandscape, transportation access convenience, and temperature. Third, it was found that satisfaction with water quality in waterfront areas was generally unsatisfactory regardless of the water quality grade presented by the competent authority. Fourth, as a result of comparing the water quality measurement network data of the Ministry of Environment by water quality grade, generally good grades were found, and in particular, there was a difference in grade frequency by season in the BOD category. Fifth, as a result of statistical analysis (one-way ANOVA) of water quality monitoring network data by season, there were statistically significant differences in COD, BOD, TP, and TOC except for DO. Considering the results of these studies, it is judged that it is necessary to prepare a comprehensive management system for water quality improvement in the waterfront zone and to improve water quality during periods of high waterfront activity, and to prepare a water quality forecasting system for waterfront areas in the future.

• Environmental Engineering Research
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• v.15 no.2
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• pp.123-126
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• 2010

Modeling non-point pollution across multiple scales has become an important environmental issue. As a more representative and practical approach in quantifying and qualifying surface water, a modular neural network (MNN) was implemented in this study. Two different site-scales ($1.5\;{\times}\;10^5$ and $1.62\;{\times}\;10^6\;m^2$) with the same plants, soils, and paddy field management practices, were selected. Hydrologic data (rainfall, irrigation and surface discharge) and water quality data (time-series nutrient loadings) were continuously monitored and then used for the verification of MNN performance. Correlation coefficients (R) for the results predicted from the networks versus measured values were within the range of 0.41 to 0.95. The small block could be extrapolated to the large field for the rainfall-surface drainage process. Nutrient prediction produced less favorable results due to the complex phenomena of nutrients in the drainage water. However, the feasibility of using MNN to generate improved prediction accuracy was demonstrated if more hydrologic and environmental data are provided. The study findings confirmed the estimation accuracy of the upscaling from a small-segment block to large-scale paddy field, thereby contributing to the establishment of water quality management for sustainable agriculture.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1248-1252
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• 1999

To provide electricity power of good quality, it is essential to establish generation of electricity plan in electric power system based on accurate power-demand prediction and cope with changes of power-need fluctuating constantly. The role of hydraulic-power generation of electricity in electric power system is of importance because responding to electric power-demand counts or reservoir-type hydraulic-power generation of electricity which is designed for additional load in electric power system. So hydraulic-power generation of electricity must have fast start reserve. But the amount of water, resources of reservoir-type hydraulic-power generation of electricity is restricted and multi-used, so the scheduling of management by exact forecasting the amount of water is critical. That is why efficient hydraulic-power generation of electricity makes a main role on pumping up the utility of energy and water resource. This thesis introduced the example of optimal generation of electricity plan establishment which is used in managing reservoir-type hydraulic-power generation of electricity.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.287-287
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• 2023

Surface water-groundwater interaction (SWGI) is an important hydrological process that influences both the quantity and quality of water resources. However, regional scale SWGI model calibration and uncertainty analysis have been a challenge because integrated models inherently carry a vast number of parameters, modeling assumptions, and inputs, potentially leaving little time and budget to explore questions related to model performance and forecasting. In this study, we have proposed the application of iterative ensemble smoother (IES) for uncertainty analysis and calibration of the widely used integrated surface-subsurface model, SWAT-MODFLOW. SWAT-MODFLOW integrates Soil and Water Assessment Tool (SWAT) and a three-dimensional finite difference model (MODFLOW). The model was calibrated using a parameter estimation tool (PEST). The major advantage of the employed IES is that the number of model runs required for the calibration of an ensemble is independent of the number of adjustable parameters. The pilot point approach was followed to calibrate the aquifer parameters, namely hydraulic conductivity, specific storage, and specific yield. The parameter estimation process for the SWAT model focused primarily on surface-related parameters. The uncertainties both in the streamflow and groundwater level were assessed. The work presented provides valuable insights for future endeavors in coupled surface-subsurface modeling, data collection, model development, and informed decision-making.

• Journal of Environmental Science International
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• v.17 no.4
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• pp.451-459
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• 2008

This study was carried out forecasting of pollution inflow of the Small Mountainous Catchment, namely; Seolma-cheon experimental catchment. Pollutographs of DO, BOD, T-N, Conductivity, T-p, pH. COD, SS from this catchment were obtained from in-situ data of total ten events using QUAL2E-PULS model. From the analysis results, between up stream(Sabang-bridge) and down stream (Memorial-bridge, outlet) obtained relation formula of water quality component. Determination coefficient of relation formula, Conductivity, COD, BOD, DO, pH, T-N, T-P, and SS showed high relation of $0.87{\sim}0.99$. The increases of DO, BOD, COD, and pH concentration of Memorial-bridge were associated with pollution inflow by road building far 2.25km from Sabang-bridge to down stream. The analysis results of QUAL2E-PULS simulation and up/down stream relation formula, pollution amounts of DO, BOD, COD and pH increased at Memorial-bridge and pollution source site. Therefore, pollution inflow can be forecasted exactly by up/down stream relation formula at pollution source site.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1075-1086
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• 2019

Recently, as the incidence of climate warming and abnormal climate increases, the forecasting of hydrological factors such as precipitation and river flow is getting more complicated, and the risk of water shortage is also increasing. Therefore, this study aims to develop a model for predicting the amount of water intake in mid-term. To this end, the correlation between water intake and meteorological factors, including temperature and precipitation, was used to select input factors. In addition, the amount of water intake increased with time series and seasonal characteristics were clearly shown. Thus, the preprocessing process was performed using the time series decomposition method, and the support vector machine (SVM) was applied to the residual to develop the river intake prediction model. This model has an error of 4.1% on average, which is higher accuracy than the SVM model without preprocessing. In particular, this model has an advantage in mid-term prediction for one to two months. It is expected that the water intake forecasting model developed in this study is useful to be applied for water allocation computation in the permission of river water use, water quality management, and drought measurement for sustainable and efficient management of water resources.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.310-310
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• 2018

Generally, precipitation measurement were conducted with various authrities. Among these, the MOLIT conduct the hydrological survey for the water resource management such as flood and low-flow forecasting, drought countermeasure, streamflow management. There is totally 424 observatory were existed and each precipitation measurement were obtained and quality assuranced with 10-min interval. It could be arranged or estimated with nearby observatory and radar reflectivity when the total amount of precipitation are existed. The objective of the study is therefore to suggest the method to estimate missing data with rain radar reflectivity. To validate suggested method, 50 observartory were obtained, and the efficiency were analyzed with estimated and observed precipitation. As the result of the study, the suggested method has reliability, and can be used as a method for quality assurance.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1047-1058
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• 2003

Seasonal occurrence of high ammonia nitrogen(NH3-N) concentrations has hampered chemical treatment processes of a water plant that intakes water at Buyeo site of Geum river. Thus it is often needed to quantify the effect of Daecheong Dam ouflow on the mitigation of $NH_3$-N contamination. In this study, multiple regression models were developed for forecasting daily $NH_3$-N concentrations using 8 years of water quality and dam outflow data, and verified with another 2 years of data set. During model development, the coefficients of determination($R^2$) and model efficiency($E_{m}$) were greater than 0.95. The verification results were also satisfactory although those statistical indices were slightly reduced to 0.84∼0.94 and 0.77∼0.93, respectively. The validated model was applied to assess the effect of different amounts of dam outflow on the reduction of $NH_3$-N concentrations in 2002. The NH3-N concentrations dropped by 0.332∼0.583 mg/L on average during January∼March as outflow increases from 5 to 50cms, and was most significant on February. The results of this research show that the multiple regression approach has potential for efficient cause and effect analysis between dam outflow and downstream water quality.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.853-862
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• 2018

An adaptive cut-cell grid based 2D inundation analysis model, K-Flood, is developed in this study. Cut cell grid method divides a grid into a flow area and a non-flow area depending the characteristics of the flows. With adaptive mesh refinement technique cut cell method can represent complex flow area using relatively small number of cells. In recent years, the urban inundation modeling using high resolution and fine quality data is increasing to achieve more accurate flood analysis or flood forecasting. K-Flood has potential to simulate such complex urban inundation using efficient grid generation technique. A finite volume numerical scheme of second order accuracy for space and time was applied. For verification of K-Flood, 1) shockwave reflex simulation by circular cylinder, 2) urban flood experiment simulation, 3) Malpasset dam collapse simulation are performed and the results are compared with observed data and previous simulation results.