• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.733-744
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• 2000

Due to the randomness of reservoir inflow and supply demand it is not easy to establish an optimal reservoir operation rule. However, the operation rule can be derived by the implicit stochastic optimization approach using synthetic inflow data with some demand satisfied. In this study the optimal reservoir operation which was reasonably formulated as Linear Tracking model for maximizing the hydro-energy of seven reservoirs system in the Han river was performed by use of the optimal control theory. Here the operation model made to satisfy the 2001st year demand in the capital area inputted the synthetic inflow data generated by multi-site Markov model. Based on the regressions and statistic analyses of the optimal operation results, monthly reservoir operation rules were developed with the seasonal probabilities of the reservoir stages. The comparatively larger dams which would have more controllability such as Hwacheon, Soyanggang, and Chungju had better regressions between the storages and outflows. The effectiveness of the rules was verified by the simulation during actually operating period.period.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.3
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• pp.305-317
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• 2015

The function failure of present major facilities is likely to lead to failure of related systems and/or whole facilities, increasing the necessity for protection of infrastructures, main structures, and major industrial facilities. In addition, safe and efficient management for urban infrastructure (waterworks and sewerage facilities, electricity, telecommunications, roads, etc) installed in the basement or on large cities grounds at various public areas is required. Recently in response to this demand, efforts for vitalizing asset management are being made such as enacting related laws and developing asset management system in the U.S., Australia, Europe and other advanced countries with the concept for a new maintenance. In our county, identifying maintenance system problems such as aging and rapid increasing of existing infrastructures and decision-making about updating maintenance is required for systematic and organizational maintenance. In this study, by comparing and observing the LOS(Level of Service) of each countries' waterworks and risk-based LOS, we suggest the direction of future urban water infrastructure management systems for more effective management.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.870-876
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• 2005

The multiple regression models which have two factors(population and commercial area) have been used to forecast the water demand in the future. But, the coefficient of population had a negative value because proper regional classification wasn't performed, and it is not reasonable because the population must be a positive factor. So, the regional classification was performed by principal component and cluster analysis to solve the problem. 6 regional characters were transformed into 4 principal components, and the areas were divided into two groups according to cluster analysis which had 4 principal components. The new regression models were made by each group, and the problem was solved. And, the future water demands were estimated by three scenarios(Active, moderate, and passive one). The increase of water demand ore $89.034\;m^3/day$ in active plat $49,077\;m^3/day$ in moderate plan, and $19,996\;m^3/day$ in passive plan. The water supply ability as scenarios is enough in water treatment plant, however, 2 reservoirs among 4 reservoirs don't have enough retention time in all scenarios.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.953-963
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.211-211
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• 2020

The concept of virtual water has been largely applied in the study of regional, national, and global water flows with particular emphasis on water scarcity. Despite water traditionally being managed locally, certain global forces influence the local water resource scarcity/availability and hence virtual water exchanges worldwide. It is therefore of necessity that the significant forces be examined to understand the relationship between available water in a region and the variability and trends in environmental, social, and economic factors that are of utmost importance in the formulation of water resources management policies. This study therefore reviewed recent literature from 2003 - 2019 to determine the significant indicators of virtual water trade at different spatiotemporal levels. The study examined and compared the major approaches to virtual water trade flows accounting, and also identified and discussed policy implications and future research options concerning the analysis of virtual water trade. Available information has shown that virtual water trade is significantly influenced by economic (GDP, Demand-Supply of goods and services), geographical (Distance), institutional (population) and environmental (water availability, arable land, precipitation) factors. Reports further show that the selection of a given approach for virtual water trade flows accounting will depend on the scope of the study, the available datasets, and other research preferences. Accordingly, this study suggests that the adoption of multidisciplinary approaches to virtual water trade, taking into consideration the spatial and temporal variations in water resources availability and the complexity of environmental and socioeconomic factors will be pivotal for establishing the basis for the conservation of water resources worldwide.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.493-499
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• 2022

The standards pertaining to the quality of discharged water in sewage treatment plants are strengthening, and accordingly, facilities in sewage treatment plants are being upgraded. In addition, the discharge water quality of sewage treatment plants must be maintained at a high level, and efficient sewage treatment plant operations have thus emerged as a very important issue. For the efficient operation of sewage treatment plants, this study applied a basic blowing amount calculation method based on sewage facilities to evaluate the required oxygen amount and blowing amount according to inflow water quality by logicizing various influencing factors. As a result of calculating the amount of air blown by applying actual April water quality data from sewage treatment plant A to the blower demand calculation developed through this study, it was found that the average amount of air blown was reduced by about 12%. When the blower demand calculation developed here is applied to an actual sewage treatment plant, the amount of air blown can be controlled based on the inflow water quality. This can facilitate the realization of an autonomous control of sewage treatment plants, in contrast to the existing sewage treatment operation method that relies on operational experience of operator. In addition, it is expected that efficient sewage treatment plants can be operated by reducing blowing amounts and power costs, which will contribute to both energy and carbon savings.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.628-632
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• 2012

우리나라의 최근 30년(1981-2010년)간 연 강수량은 1307.7mm로 세계 평균보다 크지만 좁은 국토면적과 높은 인구밀도로 1인당 수자원 강수량은 세계평균의 1/8에 지나지 않아 물 부족국가로 분류되고 있다. 기후 및 지형적 영향으로 매년 홍수와 가뭄이 반복되고 기상이변으로 더욱 심화되고 있는 실정이다. 최근 기후변화에 따른 저수지의 이 치수 능력을 강화하는 저수지 둑높이기 사업이 시행되고 있다. 이에 따라서 용수량이 증가함으로 치수 대책이 반드시 필요하다. 이를 위해서 반드시 체계적인 계측이 필요하고 수요 공급의 시스템적인 관리 체계가 필요하다. 본 연구에서는 저수지 유입량 및 공급량에 대한 정량적인 해석을 위해서 현재 용덕저수지에서 계측되고 있는 자료의 신뢰성 분석, 계측자료를 통해 유입량 및 공급량 분석, 이론에 의한 유입량 및 공급량 분석, 계측과 이론에 의한 무효 방류량 분석을 실시하였고, 저수지 계측 시스템의 방향을 제시하기 위해서 모의 및 계측결과의 비교를 통한 저수지 운영의 효율성 분석, 계측자료의 부족함과 이론식의 비현실성 파악, 무효방류량의 계측 필요성을 파악하였다. 이 결과를 바탕으로 Smart Water Grid의 개념을 도입하여 저수지 유역의 Proto Type을 제시하고 수자원의 효율적 운영을 위해 추가적인 계측 지점을 제안하였다. 또한 기존 시스템의 관측 및 분석 모듈을 분석하여 계측을 통한 통합적인 수자원 관리 시스템을 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.457-457
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• 2015

최근, 우리나라에서는 효과적인 수자원 관리와 추가적인 수원 확보 차원에서 빗물 재이용에 관한 관심이 크게 증대되고 있다. 하지만 국내의 관련된 제도와 기술 지침은 단지 규제 측면에서 빗물이용시설을 설치하도록 제시하고 있어 빗물이용시설의 실제 사용을 고려한 계획이 배제되어 있다. 본 연구의 목적은 실용적인 빗물이용시설의 계획을 위해 SWMM을 이용하여 빗물 재이용의 수요(빗물 재이용 목표량)와 공급(연간 강우량과 패턴)을 반영한 설계 방법을 제시하는 것이다. 이를 위해 SWMM 내에 구현되어 있는 빗물통 모의에 관한 수식을 이용하되, 수식을 목적에 맞도록 일부 변형하여 활용하였다. 그리고 빗물이용시설의 규모는 설정한 목표량을 만족할 수 있는 최소의 크기로 결정하는 것이 적절하고, 장기간의 강우자료를 이용한 물수지 석이 요구되므로 이를 고려하였다. 본 연구에서 제시한 빗물이용시설의 설계 방법은 송산 그린시티 동측지구에 계획된 빗물이용시설의 규모 결정에 활용되었다. 빗물 재이용의 목표량이 일정한 경우, 빗물이용시설의 크기가 커질수록 빗물 재이용 가능량은 로그함수의 형태로 증가하여, 빗물이용시설이 특정 규모 이상으로 커지더라도 빗물 재이용 가능량은 더 이상 증가하지 않는 임계점이 나타난다(그림 1). 따라서 빗물이용시설은 이러한 임계점이 나타나는 규모 정도로 설계하는 것이 합리적이다. 본 연구에서 제시한 빗물 재이용을 고려한 빗물이용시설의 계획은 빗물이용시설을 보다 합리적으로 계획하는데 도움을 줄 수 있을 것으로 판단된다.

• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.126-133
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• 2011

The current world wide interest in environmental issues has moved from energy conservation to $CO_2$emission reduction. Recently, according to the increase in demand for water resources, insufficient potable water circumstance is supposed, unless there are corresponding in crease in water conservation and water recycling. This study has attempted to analyze $CO_2$emission reduction by water saving strategies like installation water saving devices, rain water harvesting and grey water system. To do this, this research investigates applicable water conservative strategies by literature review and calculated total water saving. The results show that (1) firstly, the water usage and $CO_2$ emission could be reduced up to 44%, (2) $CO_2$ emission reduction by water saving devices and rainwater harvesting system is about 47.7%, and (3) water usage and $CO_2$ emission reduction by grey water system is about 66%. In the future, this paper will be utilized for water management from the early design stage to maintenance stage of water glutton building.