• 상하수도학회지
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• 제20권2호
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• pp.187-196
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• 2006

Forecasting the long-term water demand is important in the plan of water supply system because the location and capacity of water facilities are decided according to it. To forecast the long-term water demand, the existing method based on lpcd and population has been usually used. But, these days the trend among the variation of water demand has been disappeared, so expressing other variation of it is needed to forecast correct water demand. To accomplish it, we introduced the System Dynamics method to consider total connections of water demand factor. Firstly, the factors connected with water demand were divided into three sectors(water demand, industry, and population sectors), and the connections of factors were set with multiple regression model. And it was compared to existing method. The results are as followings. The correlation efficients are 0.330 in existing model and 0.960 in SD model and MAE are 3.96% in existing model and 1.68% in SD model. So, it is proved that SD model is superior to the existing model. To forecast the long-term water demand, scenarios were made with variations of employment condition, economic condition and consumer price indexes and forecasted water demands in 2012. After all scenarios were performed, the results showed that it was not needed to increase the water supply ability in Seoul.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.709-712
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• 2004

The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. h short-term water demand forecasting technology will be developed fatting into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

• 상하수도학회지
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• 제37권6호
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• pp.363-373
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• 2023

Numerous studies have established a correlation between sociodemographic characteristics and water usage, identifying population as a primary independent variable in mid- to long-term demand forecasting. Recent dramatic sociodemographic changes, including urban concentration-rural depopulation, low birth rates-aging population, and the rise in single-person households, are expected to impact water demand and supply patterns. This underscores the necessity for operational and managerial changes in existing water supply systems. While sociodemographic characteristics are regularly surveyed, the conducted surveys use aggregate units that do not align with the actual system. Consequently, many water demand forecasts have been conducted at the administrative district level without adequately considering the water supply system. This study presents an upward water demand forecasting model that accurately reflects real water facilities and consumers. The model comprises three key steps. Firstly, Statistics Korea's SGIS (Statistical Geological Information System) data was reorganized at the DMA level. Secondly, DMAs were classified using the SOM (Self-Organizing Map) algorithm to consider differences in water facilities and consumer characteristics. Lastly, water demand forecasting employed the PCR (Principal Component Regression) method to address multicollinearity and overfitting issues. The performance evaluation of this model was conducted for DMAs classified as rural areas due to the insufficient number of DMAs. The estimation results indicate that the correlation coefficients exceeded 0.9, and the MAPE remained within approximately 10% for the test dataset. This method is expected to be useful for reorganization plans, such as the expansion and contraction of existing facilities.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.507-510
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• 2003

The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. A short-term water demand forecasting technology will be developed taking into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

• 한국환경과학회지
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• 제22권8호
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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.

• 한국환경과학회지
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• 제22권8호
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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.

• 한국컴퓨터정보학회논문지
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• 제28권5호
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• pp.155-161
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• 2023

우리나라 수출의 97.5%, 수입의 87.2%가 해상운송으로 이뤄지며 항만이 한국 경제의 중요한 구성요소이다. 이러한 항만의 효율적인 운영을 위해서는 항만 물동량의 단기 예측을 통해 개선시킬 수가 있으며 과학적인 연구방법이 필요하다. 이전 연구는 주로 장기예측을 기반으로 대규모 인프라투자를 위한 연구에 중점을 두었으며 컨테이너 항만물동량에만 집중한 측면이 크다. 본 연구는 국내 대표적인 석유항만인 울산항의 석유 및 가스화물 물동량에 대한 단기 예측을 수행하였으며 딥러닝 모델인 LSTM(Long Short Term Memory) 모델을 사용하여 RMSE기준으로 예측성능을 확인하였다. 본 연구의 결과는 석유 및 가스화물 물동량 수요 예측의 정확도를 높여 항만 운영의 효율성을 개선하는 근거가 될 수 있을 것으로 기대된다. 또한 기존 연구의 한계로 컨테이너 항만 물동량뿐만 아니라 석유 및 가스화물 물동량 예측에도 LSTM의 활용할 수 있다는 가능성을 확인할 수 있으며 향후 추가 연구를 통해 일반화가 가능할 것으로 기대된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2001년도 학술발표회 논문집(I)
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• pp.15-24
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• 2001

This study introduces an integrated decision support system (DSS) for the water supply system in Fukuoka City, Japan. The objective is to conceive a comprehensive tool that may aid decision-makers to derive the best water supply alternatives from a multi-reservoir system in order to minimize the long-term drought damages and threat of water shortage. The present DSS consists of graphical user interface (GUI), a database manager, and mathematical models for runoff analysis, water demand forecasting, and reservoir operation. The methodology applied explicitly integrates the drought risk assessment based on the concept of reliability, resiliency, and vulnerability, as constraints to derive the management operation. The application of the DSS to the existing water supply system in Fukuoka City was found to be an efficient tool to facilitate the examination of a sequence of water supply scenarios toward an improved performance of the actual water supply system during periods of drought.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.322-323
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• 2022

정수장의 최적화 운영을 위하여 가장 필요한 것은 수용가에서 사용되는 수돗물의 패턴과 양을 정확하게 예측하여 필요한 만큼의 수돗물을 펌프를 이용하여 배수지로 전달하여 저장하고, 필요한 유량이 최소의 전기에너지를 이용하여 적기에 공급되어야 한다. 정수장의 수량 예측 중 에너지 최적화 운영의 관점에서 필요한 단기 수요예측은 시계열 분석, 회귀분석 및 신경망 알고리즘을 이용하여 계절별, 주요 기간별, 지역 특성별 등을 고려하여 이루어져 왔으며, 본 논문에서는 순환적 신경회로망의 일종인 LSTM(Long Short-Term Memory), GRU(Gated Recurrent Units) 등의 AI 기반 복합센서 적용성 분석을 통한 에너지 관리 방안에 대하여 분석하였다.

• Water Engineering Research
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• 제5권3호
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• pp.111-121
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• 2004

For the long-term strategic water resources planning, forecasting the future streamflow change is important to meet the demand of a growing society. The streamflow variation to the decade-long precipitation was investigated for the two major stage gauging stations in Korea. Precipitation and runoff characteristics have been analyzed at Yongwol stream stage in the Han River as well as Sutong stream stage in the Kum River for the future water resources management strategies. Monte Carlo method has been applied to estimate the future precipitation and runoff. Based on the trend line of 10-year moving average of runoff depth for the historical runoff records, the relation between runoff and the time variation was examined in more detail using regression analysis. This study showed that the surface flows have been significantly decreased while precipitation has been stable in these basins. Decreasing in runoff reflects the regional watershed characteristics such as forest cover changes. The findings of this study could contribute to the planning and development for the efficient water resources utilization.