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.

For the asset management of a water pipe network, it would be necessary to understand the extent of the maintenance cost required for the water pipe network for the future. This study would develop a method to draw the optimum cost required for the maintenance of the water pipe network in waterworks facilities to maintain the aim revenue water ratio and to achieve the target revenue water ratio, considering the water service providers’ waterworks condition and revenue water ratio comprehensively. This study conducted a survey with 96 water service providers as of the early 2015 and developed models to estimate the optimum maintenance cost of the water pipe network, considering the characteristics of the water service providers. Since the correlation coefficient of all the developed models was higher than 0.95, it turned out that it had significant reliability, which was statistically significant. As a result of applying the developed models to the actual water service providers, it was drawn that increasing revenue water ratio to more than a certain level can reduce the maintenance cost of the water pipe network by a great deal. In other words, it is judged that it would be the most efficient to secure the reliability of waterworks management by increasing the short-term revenue water ratio to more than a certain level and gradually increase the revenue water ratio from the long-term perspective. It is expected that the proposed methodology proposed in this study and the results of the study will be used as a basic research for planning the maintenance of water pipe network or establishing a plan for waterworks facilities asset management.