The Conserve Florida Water Clearinghouse has developed Internet‐based software called EZ Guide to assist Florida water utilities in evaluating water use efficiency. This modeling approach estimates single‐family outdoor water use for every parcel using a uniform statewide property appraisers' database to estimate irrigated area for each parcel. Billing data are needed to estimate the irrigation application rates for each parcel, although few utilities have used the available data for this purpose. Analyses using these unique databases for a benchmark utility in Florida provide new insights into the overall impact of single‐family outdoor water use and cost‐effective management options. A key result is that only a small percentage of homes are large irrigators, which makes them candidates for irrigation best management practices. However, this study also shows a dramatic rise in the prevalence of inground sprinkler systems over the past few decades, which has led to increased irrigation application rates.
The commercial, industrial, and institutional (CII) sectors are significant contributors to public water demand. To estimate CII water use, utilities historically have relied on water use coefficients that use the number of employees as the measure of size. However, it is difficult to obtain this information at a resolution fine enough to differentiate among individual water users and adequately evaluate water conservation options. To overcome these challenges, a methodology was developed to estimate CII water use through spatial, physical, and economic property-based information publicly available from the Florida Department of Revenue (FDOR) for each of the 8.8 million parcels in the state.Water use data for 3,172 CII parcels were linked with FDOR data to develop average and peak water use coefficients normalized by heated building area. By estimating water use at the parcel level, the methodology provides baseline water use estimates essential to evaluating water conservation options. C ommercial, industrial, and institutional (CII) users account for a significant portion of the the total water withdrawn and delivered by public or private suppliers to end water users. The US Geological Survey (USGS) estimated water use from public supplies across the United States in 1995 as 17% commercial, 12% industrial, and 15% public use and losses (Solley et al, 1998). CII water use comparisons across agencies and water utilities are complicated by dissimilar approaches to classifying customers. For example, the USGS generally groups institutional establishments within commercial water use and defines public water use as water from the public water supply used for such purposes as firefighting, street washing, and municipal parks; water losses are usually dealt with separately from public use. According to a survey of water agency reporting practices for water losses (Beecher, 2002), regulatory agencies in nearly all states have set upper limits on water losses ranging from 7.5 to 25%, with 15% being the most common value. Thus, the USGS estimate of CII water use in 1995 can be expressed as at least 29% of the total water delivered. The USGS did not include commercial water use in its 2005 update of the 1995 national water use assessment (Kenny et al, 2009), but other researchers (Dziegielewski et al, 2000) have estimated that CII water use accounts for approximately 15-25% of municipal water use. On the basis of metered data, the commercial/industrial sector of public water supply systems in the Southwest Florida Water Management District
In contrast to traditional supply augmentation options, demand management options include specifying and/or replacing many small end uses that individually have a minimal effect on overall water use but that collectively can constitute significant aggregate reductions in demand. This article outlines a systematic procedure to quantify savings potential of single-family residential indoor end-use devices of a given utility and then select the optimal blend of retrofits to achieve a specified goal. Three steps are used to quantify savings potential of all end-use devices. First, a utility's current end-use fixture inventory and associated water use is estimated from parcel-level data for each singlefamily residence. Second, customers are clustered into relatively homogeneous water use categories based on the age of the dwelling unit and the number of bathrooms. Third, water savings are calculated directly as the difference between current and proposed use after implementation of a management option for each group. This information is used to develop performance functions that estimate total water savings as a function of the number of fixture retrofits for each group. W ater demand management can be a viable alternative to augmenting a supply system to meet future water needs. Demand management should be compared with traditional supply augmentation methods to decide whether it is a viable option. Methods of analysis are well-established for choosing among supply augmentation options such as well field development, reservoir and pipeline construction, and desalination. Demand management is an emerging alternative in which several case studies have illustrated significant demand reduction from various strategies, including technological improvements, behavioral marketing campaigns, and adjustments of water pricing. The major difference between traditional supply augmentation and demand management is that traditional supply options are capital-intensive with long service lives; as a result, capacity expansion is done in discrete, relatively large, increments. Demand management options include many small changes that reduce water use for individual customers by a few gallons per day but that collectively can bring about significant aggregate reductions in demand if applied to a significant portion of the utility's customers.Advances in database availability, including an associated geographic information system (GIS), make it possible to do a bottom-up evaluation of water demand patterns across the utility and systematically determine the potential savings for all single-family indoor retrofit options within a given utility. An optimal mix of demand management strategies can then be selected by comparing each demand management control with a few large supply augmentation options. Existing
FIGURE 1Levels of FDOR land use disaggregation into nine residential and 55 CII sectors with associated parcel counts FDOR 41-49, 91-92 FDOR 71-79, 81-85, 90, 97 CII-commercial, industrial, and institutional; FDOR-Florida Department of Revenue, n-number of parcels Urban water use Residential n = 7,134,971 CII n = 515,916 Single family n = 6,916,180 Multifamily n = 218,791 Commercial n = 230,881 Industrial n = 93,264 Institutional n = 107,853 FDOR 01, 02, 04-05 FDOR 03, 06-08, 28 FDOR 11-27, 29-39 Morales et al | http://dx.
An effective urban water demand management program can greatly influence both peak and average demand and therefore long-term water supply and infrastructure planning. Although a theoretical framework for evaluating residential indoor demand management has been well established, little has been done to evaluate other water use sectors such as residential irrigation in a compatible manner for integrating these results into an overall solution. This paper presents a systematic procedure to evaluate the optimal blend of single family residential irrigation demand management strategies to achieve a specified goal based on performance functions derived from parcel level tax assessor's data linked to customer level monthly water billing data. This framework is then generalized to apply to any urban water sector, as exponential functions can be fit to all resulting cumulative water savings functions. Two alternative formulations are presented: maximize net benefits, or minimize total costs subject to satisfying a target water savings. Explicit analytical solutions are presented for both formulations based on appropriate exponential best fits of performance functions. A direct result of this solution is the dual variable which represents the marginal cost of water saved at a specified target water savings goal. A case study of 16,303 single family irrigators in Gainesville Regional Utilities utilizing high quality tax assessor and monthly billing data along with parcel level GIS data provide an illustrative example of these techniques. Spatial clustering of targeted homes can be easily performed in GIS to identify priority demand management areas.
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