• 상하수도학회지
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• 제38권1호
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

• 상하수도학회지
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• 제19권4호
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• pp.395-403
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• 2005

It is very important to forecast water supply for reasonal operation and management of water utilities. In this paper, water supply forecasting models using artificial intelligence are developed. Artificial intelligence models shows better results by using Temperature(t), water supply discharge (t-1) and water supply discharge (t-2), which are expressed by neural network(LMNNWS; Levenberg-Marquardt Neural Network for Water Supply, MDNNWS; MoDular Neural Network for Water Supply) and neuro fuzzy(ANASWS; Adaptive Neuro-Fuzzy Inference Systems for Water Supply). ANFISWS model which is applied for water supply forecasting shows stable application to the variable water supply data. As results, MDNNWS model shows the highest overall accuracy among proposed water supply forecasting models and the lowest estimation error with the order of ANFISWS, LMNNWS model.

• 상하수도학회지
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• 제34권6호
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• pp.503-512
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• 2020

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

• 상하수도학회지
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• 제21권5호
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• pp.601-607
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• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.472-472
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• 2023

본 연구에서는 낙동강 수계에서 발생한 수질오염사고에 대해 K-River와 K-DRUM 결합모형을 이용하여 오염물질의 이동을 분석하였다. 국내에서는 수질오염총량제 도입 이후 수질관리에서 물순환과정을 수용한 배분모델의 필요성과 비점오염원의 중요성이 강조되었다. 따라서 비점오염원의 유출특성을 반영하기 위해 유역의 오염도를 분석할 수 있는 K-DRUM 분포모형을 사용하였다. 그리고 낙동강 수계에서 운영되는 댐 운영규칙을 적용하여 모델의 재현성을 높였다. 또한 하천 내 오염물질의 이동을 분석하기 위해 대류-분산 방정식의 대류 부분만을 1차원 수리모델 K-River에 적용하여 오염물질 추적을 수행하였다. 수질오염 분석 결과 오염물질의 최고농도는 과소평가 되었으나 도착시간과 전체 오염물질 농도의 추이는 잘 재현되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.74-83
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• 2007

The goal of this study is to establish an integrated watershed hydrologic model for the whole Nakdong River basin whose area is an approximately 24,000 km2. Including a number of watershed elements such as rainfall, runoff, water use, and so on, the proposed model is based on SWAT model, and is used to improve the flow duration curve estimation of ungauged watersheds for Korean Total Maximum Daily Load (TMDL). The model is also used to recognize quantitatively the river flow variation due to water use elements and large dam effluents in the whole watershed. The established combined watershed hydrologic model, SWAT-Nakdong, is used to evaluate the quantified influences of artificial water balance elements, such as a dam and water use in the watershed. We apply two water balance scenarios in this study: the dam scenario considering effluent conditions of 4 large multi-purpose dams, Andong dam, Imha dam, Namgang dam, and Habcheon dam, and the water use scenario considering a water use for stream line and the effluent from a treatment plant. The two scenarios are used to investigate the impacts on TMDL design flow and flow duration of particular locations in Nakdong River main stream. The results from this study will provide the basic guideline for the natural flow restoration in Nakdong River.

• 한국농공학회지
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• 제34권1호
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• pp.87-99
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• 1992

A mathematical model, UNSATR which predicts the seepage flow through the body of dike especially under the tidal fluctuation has been developed. This model has been revised from UNSAT2 model which was developed on the basis of the saturated-unsaturated theory by Neuman. UNSATR has been verified and applied to the hydraulic model in order to estimated the seepage quantity, the formation of free water surface etc. The results lead to the following conclusions : 1. Seepage rates between the mathematical model and hydraulic model experiment are very similar to each other both in constant and transient water level conditions. 2. The lapsed time to be steady state of the free water surface becomes late as the tidal levels are relatively low mainly due to the seepage flow from the unsaturated zone of the body of dike. 3. Under the transient state of water levels, owing to the flow from the unsaturated domain, streamlines crossing to the free water surface are found and time lag during a falling tide may allow the free water surface inside the body of dike to stand at a high level than the outside water level. 4. The utility and validity of UNSATR model are convinced when the analyses on seepage problems through the porous embankment of the soil structures on the conditions of the steady and unsteady states are carried out.

• 한국환경농학회지
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• 제33권1호
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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.

• 한국농공학회지
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• 제35권2호
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• pp.23-32
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• 1993

This paper describes the background and the development of a hydrologic network flow model. The model was development to simulate daily water demand and supply for selected stream reaches within a watershed, and used as a tool for evaluating, simulating, and planning a water resources system. The proposed network flow model considers daily runoff from subareas, various water demands, and diversion structures within each subarea. Daily streamflow at a reach is simulated after balancing the water demands from subareas. The lateral inflow from subareas is simulated using a modified tank model. Total water demands consist of the daily demands for agricultural, domestic, industrial, livestock, fishery, and environmental uses within a rural district. The return flow, diversions from sources and storage components such as reservoirs were also incorporated into the mode l . The developed model is a generalized version that may be applied to different combinations of river reaches for a given system. This may help potential users identify areas where water supply does not suffice the demands for different time horizons.

• 한국수자원학회논문집
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• 제52권7호
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• pp.463-473
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• 2019

본 연구에서는 공급 우선순위에 따른 물수급 분석 결과의 비교를 위해 국내 수자원장기종합계획에서 활용한 K-WEAP (Korea-Water Evaluation And Planing System) 모형과 MODSIM (Modified SIMYLD) 모형을 이용하여 분석하였다. 기존의 수자원장기종합계획은 수요처의 공급 우선순위를 모두 동일하게 공급하는 것으로 가정하여 분석하였으며 K-WEAP은 최대충족률을 만족시키기 위한 비율 배분을 수행하는 반면 MODSIM은 물 공급 우선순위의 적용이 필수적인 것으로 분석되었다. 먼저 우선순위에 따른 한강 유역의 물수급 분석 결과, 평균 1,035 천 $m^3$의 물부족이 감소하였으며 이는 생 공용수의 배분량이 증가하면서 회귀수량이 증가하고, 수자원의 재이용이 많아지기 때문인 것으로 분석되었다. 우선순위를 적용한 K-WEAP과 MODSIM의 분석결과를 비교할 경우, 상대오차 최대 5.3%이내, 결정계수($R^2$)는 0.9999로 매우 유사한 물 부족이 발생하였다. 또한 두 모형 모두 합리적인 물 부족 분석 결과를 제공한다면, 모형의 구축과 데이터 처리에 해당하는 GUI 편의성은 K-WEAP이 더 우수한 것으로 나타났으나, 구동시간의 효율성은 MODSIM이 더 우수한 것으로 분석되었다. 향후 K-WEAP모형 뿐만 아니라 MODSIM 모형을 활용한 다양한 시나리오에 따른 분석을 수행할 수 있을 것으로 기대된다.