FORECASTING URBAN WATER USE: THE IWR‐MAIN MODEL¹

Abstract

In the current forecasting practice, future water requirements of a growing urban area are often represented as the product of the number of people to be served by the water system and an assumed quantity of gross per capita water use. This paper describes a forecasting approach that differs from the per capita method in two important aspects. First, it disaggregates urban water use into a large number of categories, each consisting of a relatively homogeneous group of water users. Second, it links water use in each category to factors that determine both the need for water as well as the intensity of water use. This approach is incorporated into a computerized forecasting system referred to as IWR‐MAIN. The advantages of the IWR.MAIN model over the traditional per capita method are illustrated in a case study of Anaheim, California.

REPLY TO DISCUSSION by Lee Wilson and Ron Luke1

“…This version, released in 1988, is substantially different from the earlier release, with many new capabilities including more flexible projection routines and internal calculation of water conservation savings. Our work in Anaheim (Dziegielewski and Boland, 1989) made use of Version 5.1.…”

Water Footprint of 65 Mid‐ to Large‐Sized U.S. Cities and Their Metropolitan Areas

“…The classes are based on the Standard Industry Classification (SIC) system (Davis et al ., ) or the North American Industry Classification System (NAICS) (CDM‐Smith, ; NAICS, ). The coefficients were derived using employment data and water billing information for various MSAs across the U.S. (Davis et al ., ; Dziegielewski and Boland, ). The coefficients represent average national conditions as they were obtained by averaging the individual coefficients from the different MSAs.…”

Predicting Future Demands for Water

“…These were followed by the development of computer software programs for disaggregate water-use forecasting, for the analysis of demand reduction alternatives, for optimization of long-term water management plans, and for the monitoring of water demands over time (Dziegielewski and Boland, 1989;Dziegielewski, 1993;Baumann et al, 1998). These were followed by the development of computer software programs for disaggregate water-use forecasting, for the analysis of demand reduction alternatives, for optimization of long-term water management plans, and for the monitoring of water demands over time (Dziegielewski and Boland, 1989;Dziegielewski, 1993;Baumann et al, 1998).…”

“…The model was based on the residential and commercial water-use research projects carried on at the Johns Hopkins University Wolff et al, 1966;Howe and Linaweaver, 1967). The product of this effort was a public-domain software package called IWR-MAIN version 5.1 (Dziegielewski and Boland, 1989) and the IWR-MAIN Water Demand Analysis Software, version 6.0 (Dziegielewski, 1993;Dziegielewski et al, 1996). The product of this effort was a public-domain software package called IWR-MAIN version 5.1 (Dziegielewski and Boland, 1989) and the IWR-MAIN Water Demand Analysis Software, version 6.0 (Dziegielewski, 1993;Dziegielewski et al, 1996).…”