| Contents Notes |
1. Introduction -- 2. Standards, codes, and voluntary initiatives -- 3. Methods and approaches for integrating efficiency improvements into demand forecasts -- 4. Characterizing end uses of water through stock models and behavior -- 5. Available datasets in North America for informing stock models and end-use analysis -- 6. Collecting market penetration and ownership data -- 7. Incorporating data into stock models -- 8. Identifying and characterizing uncertainty in stock models -- 9. Case study on market saturation models with Tampa Bay Water -- 10. Case study on evolution of end-use modeling with Yarra Valley Water, Australia -- 11. Guidance and recommendations -- Appendix A. Interview questions and findings -- Appendix B. Demand forecasting and outdoor water use -- Appendix C. Market and sales reports and datasets for purchase -- References -- Appendix D. Water conservation and efficiency standards -- Appendix E. Device lifetimes and flow ratings -- Appendix F. Relevant water use studies reviewed. "Key findings: Per capita water demand is declining due, in part, to water conservation and efficiency improvements resulting from standards and codes. Long-range demand forecasts should account for the impacts of efficiency standards and codes to more accurately predict future water demand; To account for efficiency improvements, forecasters should consider the various end uses of water by examining the stock and efficiency of appliances as well as behavioral aspects of water use, such as shower duration and frequency; Stock models are a series of mathematical equations that can help predict the turnover of older, less efficient devices and the increasing market penetration of efficient devices. This research focuses on methods for incorporating stock models into long-range demand forecasts; Stock models should rely on local data whenever possible, but in the absence of those data, they can reasonably use data from previous North American end-use studies; Through end-use analysis, stock modeling, and scenario testing, forecasters can anticipate the future impacts of standards and codes, as well as new water efficient technologies. Incorporating factors that are likely to affect per-capita water demand into demand forecasts will improve the reliability of future demand management and planning efforts." |
