Concepciones de la enseñanza de la escritura en la universidad

Note: The average work year, which excludes holidays and weekends, is 225 days/year.

2 Although the CDWR survey data were from 1994, we included them in our 1995 estimate because much of the other data were from this year. In doing this, we assumed that no drastic changes in industrial water use occurred between 1994 and 1995.

3 GED is a typical coefficient used to calculate water use in the CII sectors because of data availability, not because it is the most accurate coefficient.

4 The SIC system was recently replaced by the North American Industrial Classification System (NAICS). We use the SIC code system herein because the CDWR’s industrial survey data (our largest data set) are classified by SIC code

5 For more information on detailed corrections performed on these surveys, see Appendix F.

6 The CDWR sample was skewed towards high water users so that using the arithmetic mean of the GED within a two-digit SIC code would yield a biased estimate. To correct for the skewed sampling problem we calculated the mean GEDs at the three-digit SIC code level, and weighted them by the statewide employment for the three-digit SIC code. This gave us a “weighted average” GED for each two-digit SIC code.

7 To test whether it was appropriate to use the same GED for all regions in the state, we also calculated GEDs at the regional level and compared them to each other. For the most part, the GEDs by region for each industry were comparable, although there were a few exceptions. In cases where regional differences were explicable, we used the region- specific GEDs. In cases where the differences could not be explained, the statewide GED was applied to all regions. See Appendix F for statewide GEDs, by SIC code, for the industrial sector.

8 The employment data were reported by county (California Employment Development Department, 1994). These data were distributed into hydrologic regions based on the proportion of a county’s population in each hydrologic region.

To calculate water use in the commercial sector with Method A, we eval- uated GEDs from various studies9_{and then chose a best estimate.}10_We

used more than one report because none of the reports covered the entire commercial sector and the findings of the reports were often inconsistent. Moreover, while Dziegielewski et al. (1990) and Davis et al. (1988) classi- fied findings by three-digit SIC code, Dziegielewski et al. (2000) reported findings by establishment type (i.e., restaurant, school, etc.). In most cases we used the GED estimates reported by Dziegielewski et al. (1990), because the data were based on only California-based surveys and the sample sizes were sufficiently large. We compared the two estimates by mapping SIC codes to establishment types. The comparison of the different estimates and the GEDs finally selected for Method A are shown in the online Appendix E and F at http://www.pacinst.org/reports/urban_usage/. Corrections were made to two industries:

• SIC code 82 included only private schools, while public schools were categorized separately under “local education.” We aggregated employ- ment in public and private schools under SIC code 82.

• SIC code 79 included golf courses (SIC code 7992) in addition to other recreational facilities such as amusement parks and theaters. Water-use patterns at these establishments vary tremendously, and little data about water use in this industry exists. While these constraints pre- vented us from calculating water use for SIC code 79 as a whole, suffi- cient amounts of data enabled us to calculate water use at golf courses (SIC code 7992), one of the largest water users in SIC code 79.

Method B

The second approach to estimating 1995 water use in the CII sectors involved using public water-supply delivery data reported to the CDWR by 147 water agencies across the state (CDWR 1995b).11_{After elimi-}

nating agencies that reported incomplete or inaccurate delivery informa- tion, the remaining agencies’ water delivery numbers, by sector and popu- lation served, were categorized and subtotaled by region. Each region’s sample population was divided by its actual population to obtain the per- centage of the population sampled. The CII deliveries in each region were then divided by this percentage to produce regional estimates of deliveries from the public water suppliers.

Once publicly supplied water use was calculated from agency data, we had to estimate self-supplied water use not captured by the agencies. For the industrial sector, we applied our findings of the percentage of indus- trial water that was self-supplied in Method A (38 percent) to our regional industrial estimates in Method B. And for the commercial sector, we used a USGS estimate of self-supplied commercial water use (20 per- cent of total use) (Solley et al. 1998).

Best Estimate

The total CII water-use estimates calculated in Methods A and B were within ten percent of each other (Table 4-2). Published estimates for spe- cific hydrologic regions, known sources of errors inherent in the data,

9 See Davis et al. 1988, Dziegielewski et al. 1990, and Dziegielewski et al. 2000.

10The GEDs often varied from one study to the next. In some cases, we chose a GED that was close to the GED calculated in more that one study, while in other cases we chose the GED that was based on the largest sample population.

11Over 470 agencies were listed in the CDWR file, but most of these agencies did not differentiate between commercial, institutional, and industrial uses and, therefore, could not be included in this analysis.

86 Commercial, Institutional, and Industrial (CII) Water Use and Conservation Potential

and sample sizes were used to guide our decision on which estimate to choose for each region.12

The next step involved updating the 1995 water-use estimates for 2000. Again, the two approaches, Methods A and B, were used.

Method A

Because no new survey of firms was available for the year 2000, we applied the 1995 GED estimates to the year 2000. In taking this approach, we encountered two challenges: how to account for efficiency improvements that took place between 1995 and 2000 and how to modify county-level SIC code employment estimates, since new data were not available for 2000. To address the efficiency omission, we assumed that Method A overestimated water use in 2000 when choosing our best estimate of water use.

We used several sources to overcome the SIC code employment data chal- lenge. For the 1995 estimate we used County Business Patterns (CBP) SIC code employment data published by the U.S. Census Bureau. By 2000, however, CBP data had been updated to the North American Industrial Classification System (NAICS). While the California Employment Development Department (EDD) data did provide 2000 employment fig- ures at the state level by two-digit SIC code, county information was often suppressed to maintain confidentiality. Eventually, county-level SIC code employment data for the year 2000 were extrapolated from 1995 data, county employment totals, and statewide SIC code employment totals. Although the SIC and NAICS systems do not match perfectly, we were able to use the 2000 CBP data as a crosscheck for our employment estimates. Once the employment data were in order, the total water use was calculated in the same way for 2000 as it was for 1995.

Method B

DWR supplied us with the updated public supply data for the year 2000, and we repeated the Method B approach with the new data. No new information on self-supplied water use was available for the year 2000, so the 1995 percentages of self-supplied water were used.

Central Coast 97 56 76 25 96 25 Colorado River 33 50 35 8 4 8 North Coast 35 30 33 12 16 14 South Coast 1,065 1,289 1,065 319 293 306 San Francisco 421 261 341 149 76 120 Central Valley 309 452 381 144 202 144 Lahontan 42 65 54 18 75 18 Total (000 AF/year) 2,002 2,203 1,985 675 763 635

Hydrologic Region Commercial Water Use Industrial Water Use

Method A Method B Best Est. Method A Method B Best Est.

Table 4-2

Estimates of CII Water Use 1995 (TAF)

12For comparisons of our estimates to other published sources and for additional information about uncertainties inherent in the data, see Appendix F.

Best Estimate

In choosing our best estimate of water use in 2000, we generally took the best regional estimates or an average of Methods A and B based on what we know about published estimates for specific hydrologic regions, known sources of errors inherent in the data, and sample sizes (see Table 4-3). In a few cases, regional information indicated that an overall average was not accurate and permitted adjustments in the best estimate.

Interpretation of 1995 and 2000 Estimates

Comparing the two methods’ estimates for 1995 and 2000 provided us with some valuable insights. Using Method A, water use in the CII sec- tors was estimated to increase slightly between 1995 and 2000 because it failed to account for efficiency improvements over this period. The Method B estimate, which is based on actual public deliveries, showed a decrease in CII water deliveries from 1995 to 2000. Some of this differ- ence can be attributed to errors in sampling, employment, etc., but at least part of it must be from actual conservation efforts.

For both years the Method A estimate tended to be higher for the coastal regions, while the Method B estimate was higher for the inland regions. An examination of regional conservation efforts (below) shows that the coastal regions have made greater efforts to improve CII efficiency than the inland areas. This finding supports our expectation that applying average GEDs to all regions biases the regional Method A estimates – the estimate will be too high if the region has a higher-than-average conserva- tion track record and too low if the region has a below-average conserva- tion record.

We needed industry-level water use data in order to estimate the overall conservation potential. The only comprehensive estimate we had was the Method A estimate, which we considered somewhat high, as described above. For 2000, we modified the Method A GED estimates to account for efficiency improvements put in place in the late 1990s.

Central Coast 115 61 88 28 19 24 Colorado River 39 30 34 13 15 14 North Coast 41 34 37 16 7 12 South Coast 1,232 828 828 323 294 309 San Francisco 489 355 422 153 75 114 Central Valley 362 410 386 155 166 161 Lahontan 50 63 56 21 45 33 Total (000 AF/yr) 2,337 1,781 1,852 709 621 665

Hydrologic Region Commercial Water Use Industrial Water Use

Method A Method B Best Est. Method A Method B Best Est.

Table 4-3

88 Commercial, Institutional, and Industrial (CII) Water Use and Conservation Potential