2025 Orange County Water Demand Projection Model
Where X i,m,t is an observed weather value for agency i in month m for year t and X i,m is the historical normal value for agency i in month m. A positive departure indicates above-normal conditions, and a negative value indicates below-normal conditions.
2.1.7
Water Price
Agencies provided historical water prices (in dollars per volumetric unit), which Hazen used to measure the effects of pricing on water usage. Three types of price structures were present across the agencies: • Uniform volumetric prices which are constant across demand sectors or equivalent for all demand sectors, which do not vary by amount of water purchased; • Volumetric tier prices, which vary by amount of water purchased by demand sector or are equivalent for all demand sectors; or • Water-balance based (also called budget-based) prices in which prices for single and multifamily demand sectors are based on specific indoor use thresholds and outdoor irrigation characteristics. Several agencies changed price structures over time; however, volumetric prices used in modeling reflect the marginal (or incremental) portion of the water rate that can be avoided by reducing consumption, consistent with economic theory. Any changes to price structure are incorporated in the marginal rate. The marginal price of water used in the demand model is defined as the cost of the 10th hundred cubic foot (CCF) for the single-family residential sector, and the cost of the 20th CCF for the multifamily residential, irrigation, and CII sectors. Prior to modeling, all marginal prices were converted into real, inflation-adjusted, 2022 dollars using the Bureau of Labor Statistics, Consumer Price Index – All Urban Consumers for the Urban West (Series ID: CUUR0400SA0, CUUS0400SA0). -
2.1.8
Economic Indices
Water demand is positively correlated with economic fluctuations of the business cycle. Periods of economic growth generally see increased water use. Annual Real Gross Domestic Product (GDP) is used to reflect general economic trends. GDP for all industries in Orange County, CA, was downloaded from the Federal Reserve Bank of St. Louis Economic Research Division (FRED Economic Data). The trend in the time series of the GDP index was removed during model development to better identify short-term fluctuations in economic activity. Departure from the trend (Figure 2-4 ) was calculated by running a regression on the natural log of GDP on a linear time counter (each subsequent year means the time counter is increased by 1) and the residual is used as the explanatory variable. This is standard econometric practice for addressing common statistical problems with trending variables and allows for a more flexible interpretation of forecast scenarios.
2-11
Appendix G - 30
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