• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.37-43
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• 2014

BACKGROUND: Water quality data are collected less frequently than flow data because of the cost to collect and analyze, while water quality data corresponding to flow data are required to compute pollutant loads or to calibrate other hydrology models. Regression models are applicable to interpolate water quality data corresponding to flow data. METHODS AND RESULTS: A regression model was suggested which is capable to consider flow and time variance, and the regression model coefficients were calibrated using various measured water quality data with genetic-algorithm. Both LOADEST and the regression using genetic-algorithm were evaluated by 19 water quality data sets through calibration and validation. The regression model using genetic-algorithm displayed the similar model behaviors to LOADEST. The load estimates by both LOADEST and the regression model using genetic-algorithm indicated that use of a large proportion of water quality data does not necessarily lead to the load estimates with smaller error to measured load. CONCLUSION: Regression models need to be calibrated and validated before they are used to interpolate pollutant loads, as separating water quality data into two data sets for calibration and validation.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.272-285
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• 2015

Accurate assessment of chlorophyll-a (Chl-a) concentrations in inland waters using remote sensing is challenging due to the optical complexity of case 2 waters. and the inherent optical properties (IOPs) of natural waters are the most significant factors affecting light propagation within water columns, and thus play indispensable roles on estimation of Chl-a concentrations. Despite its importance, no IOPs retrieval model was specifically developed for inland water bodies, although significant efforts were made on oceanic inversion models. So we have applied and validated a recently developed Red-NIR three-band model and an IOPs Inversion Model for estimating Chl-a concentration and deriving inland water IOPs in Lake Uiam. Three band and IOPs based Chl-a estimation model accuracy was assessed with samples collected in different seasons. The results indicate that this models can be used to accurately retrieve Chl-a concentration and absorption coefficients. For all datasets the determination coefficients of the 3-band models versus Chl-a concentration ranged 0.65 and 0.88 and IOPs based model versus Chl-a concentration varied from 0.73 to 0.83 respectively. and Comparison between 3-band and IOPs based models showed significant performance with decrease of root mean square error from 18% to 33.6%. The results of this study provides the potential of effective methods for remote monitoring and water quality management in turbid inland water bodies using hyper-spectral remote sensing.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.907-915
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• 2010

Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was $R^2=0.85$.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.1
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• pp.58-66
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• 2014

Water pollution problems of urban rivers due to the urbanization and industrialization have been the subject of public attention. In particular, considering the fact that the characteristics of water cycle of each basin change dramatically through the development of new towns, a large number of concerns about future water quality have been raised. However, reasonable measures to predict future water quality quantitatively have not been presented by this moment. In this study, by the linkage of annual unit load generation based on long-term monitoring results of the ministry of environment (MOE) to a semi-distributed rainfall runoff model, SWMM (Storm Water Management Model), we proposed a new methodology to estimate future water quality macroscopically and testified it to verify its applicability for the estimation of future water quality of a small watershed at G new town. As a result of the estimation using Y-EMC (Yearly based Event Mean Concentration), future water quality were simulated as BOD 18.7, T-N 16.1 and T-P 0.85 mg/L respectively which could not achieve the grade III of domestic river life guidance and these criteria could be satisfied by the reduction of domestic wastewater discharge load by over 80%. The results of this study are shown to be utilized for one of basic tools to estimate and manage water quality of urban rivers in the course of new town developments.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.4
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• pp.348-354
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• 2001

This study was conducted to estimation of change characteristics for water quality by the dyke gate operation in the Keum River estuary. The estimation data made use of surveyed data in Keum River estuary by NERDI (National Fisheries Research and Development Institute) during $1990\~1999$. Shown to compare water quality changes at st. A and st. D in Figure 1, the concentrations of TSS, COD and nutrients at st. A were as high as about $2\~4$ times than those at st. D due to affection of fresh water discharge in the Keum River. The percentages of water quality change at surface water by dyke gate operation in the Keum River estuary were shown that TSS (Total Suspended Solid) was decrease to $56\%,\;47\%$ at st. A and D, and COD (Chemical Oxygen Demand) was increase to $68\%,\;71\%$ at st. A and D, respectively. The changes percentage of DIN (Dissolved Inorganic Nitrogen) by dyke gate operation in the Keum River estuary were increase high to $95\%$ at surface water and $7\sim30\%$ at bottom water, but those of DIP (Dissolved Inorganic Phosphorus) were increase to $2.8\sim8.6\%$ at surface water and $28\%$ at bottom water. The range of fluctuation for water quality at each station by dyke gate operation has shown that salinity and TSS are little better than before dyke gate operation, but COD show highly fluctuation. Also we studied estimation of characteristics of water quality change by the season, COD was increased except the summer, TSS was decreased to all season. DIN was increased to about $61\sim172.1\%$ for all season, but DIP was increased to the spring and decreased to the autumn, DIN enrichment in the estuary by dyke gate operation are interpreted to improvement of organic matter decomposition and nitrification by increasing the residence time and to increase nutrient flux in sediments due to decreasing dissolved oxygen and increasing a deposit matter.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.641-655
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• 1998

The methods of development and application of an expert system are suggested to solve more efficiently the problems of water resources and quality induced by the rapid urbanization. Major parameters of the water quantity and quality of urban areas are selected their characteristics are presented by the sensitivity analysis. The rules to decide the parameters effectively are proposed based on these characteristics. the ESPE(Expert System for Parameter Estimation), an expert system based on the 'facts' and 'rules', is developed using the CLIPS 6.0 and applied to the basin of the An-Yang stream. The results of estimating t도 parameters of water quantity show a high applicability, but those of water quality imply the necessity of improving the present methods due to both the complexity of estimation processes and the lack of decision rules.

• Ecology and Resilient Infrastructure
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• v.5 no.2
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• pp.88-93
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• 2018

In-situ water quality sampling is used for accurate water quality assessment. However, in-situ water quality sampling offers limited samples and requires much time and intensive labors. Remote sensing approach has recently applied for water quality assessment. It has shown the advantage of offering a synoptic view but also more efficient and economical. In this study, we utilized Landsat Imagery to estimate the water quality of the Tamsui River basin, considered as one of the most important rivers located in the north of Taiwan. In order to monitor water quality of Tamsui River basin, a linear regression relation between the value of spectral radiance and four water quality parameters are investigated with 38 water sampling stations. Through the regression model, we could estimate river pollution index (RPI) from the predicted value of four water quality parameters. By using RPI, we can examine the pollution level of Tamsui River. The accuracy of RPI conversion of this study ranged from 32.2% to 68.2%.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.591-596
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• 2002

• Journal of Korean Society of Water and Wastewater
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• v.22 no.5
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• pp.541-550
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• 2008

In this investigative study, the unit mass discharge for the major water quality parameters such as flowrate, SS, BOD, CODmn, CODcr, TN, TP from textile spinning/weaving industry nearby Nakdong river basin was estimated. To represent the respective industries, three companies from hundreds of textile spinning/weaving industries located in Nakdong river basin was carefully selected based on its manufacturing goods, flowrate and location for the estimation of unit mass discharge based on unit operation and process. There was a drastic decrease of unit mass discharge estimation between influents and effluents of water quality parameters, which represents the removal capacity of wastewater treatment plant. With the advent of new regulation on the imposed payment proportional to the total amount of pollutants discharge into the water body, the concept of cleaner production technology should be employed in the unit operation/process in wastewater treatment plant as well as textile manufacturing procedure to minimize the levy on the pollutants discharge. Unit mass discharge estimations of unit process (estimated in this study) in major water quality parameters (SS, BOD, COD, TN and TP) based on land were similar to those of composite process (estimated by National Institute of Environmental Research). But the unit mass discharge estimations of unit process in BOD and CODmn based on total sale were much higher than those of composite one while in SS, TN and TP similar to each other. For the detailed estimation of the imposed payment, unit mass estimation based on unit process should be further emphasized.

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.575-583
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• 2005

In this study the flow curve estimation is discussed using TANK model which is one of hydrologic models. The main interest is the accuracy of TANK model parameter estimation with respect to the sampling frequency of input data. For doing this, input data with various sampling frequencies is used to estimate model parameters. As a result, in order to generate relatively accurate flow curve, it is recommendable to measure stream flow at least every 8 days.