논문 상세보기
pp.363-373
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.
2. 연구방법
2.1 대상지역의 SGIS 데이터 수집 및 소블록 단위 정리
2.2 상수도 GIS 관망도 및 물 사용량 데이터 수집
2.3 사회인구 특성 및 상수도 시설을 고려한 소블록그룹화
2.4 주성분 회귀를 이용한 물 수요예측 모델 생성
3. 결 과
3.1 중장기 물 수요예측을 위한 소블록 그룹화 결과
3.2 주성분 회귀를 이용한 물 수요예측 결과
4. 결 론
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