Enhancing NYC’s Demand Forecasting to Account for Efficiency, Climate, and Residual Variability

Authors:

  • Vlada Kenniff - New York City Department of Environmental Protection
  • Jack C. Kiefer - Hazen and Sawyer

The New York City Department of Environmental Protection (DEP) provides 1.2 billion gallons a day (BGD) of water to about 9.3 million people in the five boroughs of New York City and to many Upstate Communities. Anticipating future demands on the water supply system is central for DEP planning efforts aimed at ensuring water supply reliability and meeting wastewater capacity needs. In addition, expectations of water demand drive other important decisions regarding implementation of water efficiency programs, development of rates, and management of acute water shortages if they occur.

The importance of water demand forecasting to these planning objectives and operating functions has led DEP to make enhancements to its water demand forecasting procedures. These enhancements comprise the beginning elements of a longer-term strategy for improving DEP’s water demand modeling, analysis, and forecasting capabilities.

This paper will present a description of DEP’s water demand forecasting methodology. The discussion will highlight DEP’s initial forecast approach—which may be described as a geographically distributed application of the fixed per capita water use forecasting method—and identify primary reasons for making recent enhancements to this method including but not limited to:

• Historical evolution in demand trends, from long periods of increases in demand, to long periods of declines, and to more recent periods of demand stability
• The lack of strict correlation between population trends and demand trends
• The need to understand and account for the influence of natural water efficiency and active conservation efforts
• The need to capture the influence of weather variability as a source of inter-annual demand variability

The paper will present technical details on the analytical methods that were used to make DEP’s forecasting model more flexible for accommodating these needs including:

• De-trending procedures to account for long-term effects of water efficiency and socioeconomic phenomena
• De-seasonalization procedures to account for systematic and repeating effects of climate
• Weather-normalization procedures to account for the effects of weather variability
• Analysis and estimation fixture replacement rates to account for future efficiency trends
• Analysis of residual variance to develop projection intervals around the long-term forecast

Finally, the paper will preview future enhancements to DEP’s demand forecasting approaches, which focus on additional capabilities afforded by a growing body of available water use data.

For more information, please contact the author at jkiefer@hazenandsawyer.com.

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