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Population Projections March 15, 2011COMPREHENSIVE Monroe County 2010-2030 Population Projections March 15, 2011 Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates TABLE OF CONTENTS Section Title Page 1.0 Background Forecast Approach...............................................................................................2 2.0 ROGO Based Permanent Population Series............................................................................ 2 3.0 Analysis of Permanent Population Data.................................................................................. 2 4.0 Analysis of Seasonal Population Data....................................................................................... 3 5.0 Seasonality ...............................................................................................................................................4 6.0 Methodological Flaw in MCPD and FKAA Regarding Seasonal Shift ......................... 8 7.0 Seasonality in Retail Sales............................................................................................................10 8.0 Long term Trends in Retail Sales and Traffic.....................................................................12 9.0 Countywide Functional Population..........................................................................................14 10.0 Determination of Unincorporated Area Functional Population..............................18 11.0 Unincorporated Population in Upper/Middle/Lower Keys ......................................... 20 Appendix 1- Monroe County Planning Department Population Study Appendix 2 - FKAA Seasonal Methodology Appendix 3 - County Population with Seasonal Replacement Calculations Appendix 4 - Response to DCA Review Notes/Request for Additional Information Monroe County 2010-2030 1 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates ONROE COUNTY COMPREHENSIVE PLAN I. PRATE 1.0 Background -Forecast Approach The population forecast was prepared' for unincorporated Monroe County through year 2030 for the update of the County's Comprehensive Plan. Population is identified according to upper/middle/lower (UML) keys. It is based on the countywide functional population control total forecast through 2030; functional population is the sum of permanent plus seasonal population. The Keith and Schnars (K&S) team begins with a permanent population forecast and a seasonal population forecast at the county level. The seasonal population series is based on the Florida Keys Aqueduct Authority (FKAA) data series. This series includes estimates of seasonal residences, RV's, hotel/motel, camps, boat liveaboards, mobile home, and other. The Department of Community Affairs (DCA) has recommended using the FKAA series for the purposes of estimating the seasonal population component, with appropriate updates to the methodology. The permanent population series is the latest published by the University of Florida, Bureau of Economic and Business Research (BEBR). In as much as ROGO has been in place since 1993, BEBR population projections reflect a ROGO constrained growth trend. This means permanent population growth projections implicitly assume the continuation of the ROGO constraint and the effects of the ROGO constraint are implicitly embedded in the history. 2.0 ROGO Based Permanent Population Series The ROGO based permanent population series will be used in the Comp Plan update as one component of the functional population. At the county level, for control totals, DCA has recommended using the latest BEBR annual estimates and the BEBR Medium series population projections from PS 156, published March 2010 for permanent population estimates. 3.0 Analysis of Permanent Population Data University of Florida annual population estimates for municipalities and unincorporated areas indicates permanent population fell in the Keys from 2006- 2008, with some a return to growth evidenced in 2009. The effect of the short term decline is to drive the long term population projections down. Thus, both recent history and future projections from BEBR suggest a downward trend in permanent population. This is reflected in the resulting Functional Population series shown in Figure 1. This series represents the sum of the most recent BEBR permanent projection and the FKAA seasonal projection. 1 The population forecast was prepared by Fishkind and Associates with support from Keith and Schnars, P.A. Monroe County 2010-2030 2 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates MONROE COUNTY COMPREHENSIVE PLAN UPDATE I Figure 1- Preliminary Functional Population Projection 4.0 Analysis of Seasonal Population Data There is ongoing ROGO based residential growth and there is a substantial inventory of non -conforming, substandard, live -aboard and RV camp housing. Substandard, non- conforming units are being gradually removed from inventory, however, not at a rate fast enough to net out all residential growth. It is our view a portion of the permanent population losses have occurred as a result of the recession, a rise in foreclosures, depletion of affordable housing and increased unemployment. Nearly 3500 units have been foreclosed throughout the Keys since 2005. The rise in home prices and threat of hurricanes has also contributed in our view to some permanent population loss. Losses associated with some of these conditions may be temporary, resulting in renewed growth after the recession. The BEBR annual permanent population estimate for 2009 indicated, net positive permanent population growth in 2009 and small losses in 2010. On the other hand, of all the new single family housing growth in Monroe County since 1999, nearly 70% has been in non -homesteaded units. It is likely this is a function of both growth in seasonal population as well as permanent population loss, which may cause once permanently occupied existing units to become non -homesteaded. This latter aspect represents a shift from existing permanent population to seasonal population and is why the non -homesteaded mix is so high. Monroe County 2010-2030 3 Keith and Schnars, P.A. Population Projections 3-IS-11 Fishkind and Associates 5.0 Seasonality Seasonal population is one component of Functional population. K&S has researched three functional population series. The three functional series in this analysis include permanent populations based on Census, BEBR and FKAA. In each of these scenarios the same Seasonal series, from FKAA, is used. The FKAA seasonal series is the seasonal series developed by Monroe County Planning Department (MCPD). The detailed methodology for the Seasonal series is found in the MCPD report included as Appendix 1. The FKAA seasonal series methodology generated from the MCPD report is found in Appendix 2. As permanent population has fallen we must examine whether and the degree to which it is replaced by seasonal population. The American Communities Survey from 2005, 2008 and the Census 2000 data indicate a substantial increase in housing units held for seasonal use. These data indicate the number of seasonal units has risen from 12,628 in 2000 to 15,262 in 2005 to 19,195 in 2008 (Table 2). This is an increase of 6,567 seasonal units. This would represent a shift into seasonal population by as much as 16,418 persons. During the same period permanently occupied units have fallen from 35,086 to 29,084, some 6,002 units or a decline of 15,005 persons (Table 1). Based on the ACS and Census data, the loss in permanent population is approximately equivalent to the gain in seasonal population since year 2000. Monroe County 2010-2030 4 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COUNTY COMPREHENSWE PLAN UPDATE vwvw>oaelr C0k 'Pt.�►r .00M Table 1- H1- Vacant and Occupied Unit Counts Table H1. Housing Units by Vacancy Status and Tenure by Units in Structure. 2000 - Monroe monroe Lounty ()ccupted Units Vacant Total Vacant Units in Structure Owner I Renter I Total Units Units % 1, detached 13,866 3,496 17,362 6,850 24,212 28.29% 1, attached 1,045 1,503 2.548 1,655 4,203 39.38% 2 480 1,598 2,078 453 2,531 17.90% 3or4 306 1,875 2,181 589 2,770 21.26% 5to9 215 1,042 1,257 897 2,154 41.64% 10 to 19 403 425 828 899 1,727 52.06% 20 to 49 375 180 555 1,039 1,594 65.18% 50 or more 346 1,043 1,389 444 1,833 24.22% Mobile home 4,468 1,945 6,413 3,401 9,814 34.65% Boat, RV, van, etc 396 79 475 304 779 39.02% Total F-2i,9001 13,1861 35,0861 16,531 51,617 32.03% Table H1. Housing Units by Vacancy Status and Tenure by Units in Structure, 2005 - Monroe Coun Monroe County I Occupied Units Vacant Total Vacant Units in Structure Owner I Renter I Total Units Units % 1, detached 16,618 2,024 18,642 7,448 26,090 28.55% 1, attached 1,427 2,106 3,533 2,978 6,511 45.74% 2 621 973 1,594 636 2,230 28.52% 3 or 4 52 1,521 1,573 638 2,211 28.86% 5 to 9 458 482 940 1,440 2,380 60.50% 10 to 19 597 46 643 505 1,148 43.99% 20 to 49 132 1,125 1,257 1,198 2,455 48.80% 50 or more 435 532 967 203 1,170 17.35% Mobile home 2,876 1,485 4,361 3,904 8,265 47.24% Boat, RV, van, etc_ 405 46 451 0 451 0.00% Total 1 23,6211 0,340 33,9611 18,9501 52,9111 35.81% 1, detached 15,019 3,3" 18,363 10,351 28,714 36.05% 1, attached 490 11233 1,723 3,209 4,932 65.06% 2 371 803 1,174 764 1,938 39.42% 3 or 4 283 699 982 1,581 2,563 61.69% 5to9 272 845 1,117 2,158 3,275 65.89% 10 to 19 170 202 372 1,011 1,383 73.10% 20 to 49 161 56 217 828 1,045 79.23% 50 or more 463 504 967 816 1,783 45.77% Mobile home 2,739 1,121 3,860 4,011 7,871 50.96% Boat, RV, van, etc. 164 145 309 0 309 0.00% Total 7 20,1321 8,9521 29,0841 24,729 53,813 45.95% Monroe County 2010-2030 5 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates MONROE COUNTY COMPREHENSIVE Table 2-H3 Table H3. Number of Vacant Units by Vacancv Status, 2000 - Monroe Countv Monroe County Vacant I Vacancy Status Units % For rent 1,bbJ 1U_Ub'7u For sale only 759 4.59% Rented or sold, not occupied 304 1.84% For seasonal, recreational, or occasional use 12,628 76.39% For migrant workers 48 029% Other vacant 1,129 6.83% Total 1 16,531 1 DD.00% Table H3_ Number of Vacant Units by Vacancv Status_ 2005 - Monroe Countv Monroe County Vacant I Vacancy Status Units % For rent 943 4.98% Rented, not occupied 458 2.42% For sale only 448 2.36% Sold, not occupied 123 0.65% For seasonal, recreational, or occasional use 15,738 83.05% For migrant workers 0 0.00% Other vacant 1,240 6.54% Total 1 18,950 1 D0.01i% Tahte H3_ Number of Vacant llnits by Vacancv Status_ 2008 - Mnnrne (-nunty Monroe County Vacant Vacancy Status Units For rent 1,581 6.43% Rented, not occupied 53 0.22% For sale only 1,545 6.28% Sold, not occupied "1 1.79% For seasonal, recreational, or occasional use 19,195 78.03% For migrant workers 0 0.00% Other vacant 1,914 7.78% Total 1 24,7291 100.53% Source: US Census and American Communities Survey; Prepared by the South Florida Regional Planning Council UPDATE Contributing to the support of the seasonal increase phenomenon is the rate of foreclosures and the Monroe County Property Appraiser data regarding homestead exemptions. It is generally believed non -homesteaded properties represent seasonal vacant, second homes, or for -rent units. Population in these should be distinguished from Monroe County 2010-2030 6 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COUNTY COMPREHENSWE PLAN UPDATE short-term tourist visitors. However, in times of high foreclosure rates, a shift to non - homestead may represent a temporary loss in permanent population. During the housing bubble from 2003-2008 in fact non -homesteaded units did rise. This coincided with a rise in foreclosures, as well as speculative investing and reported permanent population losses. There were 3,431 foreclosures in Monroe County from 2005-2009. During the 2000-2009 period, total homesteaded units increased from 16,005 to 16,698 units, a net increase of 693 units. Non -homesteaded units moved from 20,784 to 22,197, a net increase of 1,413 units. This compares with the 3,431 foreclosures from 2005-2009, recognizing it is likely as much as half of the foreclosed units may have been resold since the initial foreclosures which began in 2005, and some tendency to for those units to return to a homesteaded status. By 2009, after speculative investing ceased, the share of non - homesteaded properties went back down, falling to 2003 levels. This is consistent with the expectation of resold foreclosures regaining homesteads (Figure 2). Also, as noted, permanent population increased during 2009 according to BEBR, supporting an increase in permanent population. The non -homestead rate for all units is now 57.1%. This is essentially the same rate both pre and post bubble. dingle family non -homestead rates began to move up more closely in concert with rising foreclosures (Figure 2). This supports our belief a considerable portion of permanent population losses may be attributable to foreclosures arising from the speculative housing bubble, and thus temporary. The expectation is some permanent population may return to these units over the course of the planning horizon — thus permanent population may increase over this period in substantially greater numbers than the growth in new housing units. To the degree this condition occurs, the BEBR medium series permanent population projection will be in error and will under -project permanent population growth. Planning for this contingency in the face of an unknown resolution to thousands of foreclosures is necessary. Thus, reflecting the population associated with portions of these foreclosed units as non -homestead and seasonal population will also correct and compensate for this potential longer term problem with the BEBR projection. monroe county ZUIU-2030 7 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COMPREHENSWE PLAN UPDATE A Figure 2- Monroe County - Foreclosures and The Percent of Non -Homestead Residential Units There has been an increase in vacant units from 2005-2009. During this period both the Census and BEBR indicated permanent population loss. From 2005 to 2008 the ACS indicated an increase in seasonal vacancy of 3,457 units. During the 2005-2009 period, foreclosure data indicated there were 3,431 foreclosures, as noted earlier. Thus, the ACS data indicates, on net, the permanent population losses and associated housing vacancy is being shifted into seasonal units. Further, it is believed there is associated seasonal (non- permanent population) associated with these vacant units. With a reported permanent population growth in 2009 and increasing homestead exemptions in 2009 on one hand and coinciding numbers of foreclosures and seasonal increase through ACS, it is equally possible in our view, the permanent population loss is temporary and due as much to the end of the housing bubble, foreclosures and rising unemployment as it is due to a shift from permanent to seasonal residency. It is likely both conditions exist and are occurring. 6.0 Methodological Flaw in MCPD and FKAA Regarding Seasonal Shift The MCPD seasonal population methodology and the FKAA seasonal population methodology did not contemplate or recognize the shift of the existing population base from permanent to seasonal. The MCPD methodology considered residential unit growth only and the depletion of available buildable lots, when contemplating the future level of either permanent or seasonal populations. This is partly due to the MCPD methodology not having the benefit of the data beyond year 2000 which shows a more pronounced shift among existing units from permanent/homesteaded units to non -homesteaded units, and the American Communities Survey data, which supports the seasonal shift Monroe County 2010-2030 8 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates MONROE COUNTY CJMPREHENSNE PLAN UPDATE The failure to consider or incorporate the shift in the existing population base is the reason for the change that has been made to the previously approved FKAA population methodology in this update. The methodological change employed here is to both shift some of the projected dwelling unit growth into seasonal residences and account for the loss of existing permanent residents through an offsetting shift to seasonal residents. Further, in the MCPD analysis, rather than showing seasonal population increasing as it has been, on pages 32 and 33 of the MCPD report it states an assumption was employed causing the seasonal population to decline in a similar fashion to anticipated permanent population decline. The MCPD methodology employed an assumption called the "drag factor" of .1% per year to reduce the growth of seasonal populations over time. The "drag factor" is used to illustrate the assumption of seasonal population declines from the historic actual. However there is no analysis or data which is presented to support the use of the "drag factor", nor the .1% level of the "drag factor" with respect to seasonal populations. Further there is no mention or discussion in the MCPD analysis which recognizes that the loss in the existing permanent population base may be offset by an increase in the seasonal population. The current population projections in this report correct this methodological flaw. The discussion of the "drag factor" assumption is found in the MCPD permanent population methodology on page 30 and is excerpted below: A "drag" factor was applied to each year's percent increase figures by PAED. This drag factor increases by .1% each year over the ten year period, so that by 2015, the rate of increase in permaneru resident population by PAED will have declined by 1.1 %. This drag factor was employed as an assumption that the availability of building permits will decline as the carrying capacity of the Keys is reached, It is also likely thot the availability of building sites will also decline in the early years of the twenty-first century. Analysis has shown that a 1.1% decline in mean percentage increases in population over a ten year period would not significantly affect the validity of the population forecasts. It is important to mote this methodology reveals the beginnings of a decline in the total number of permanent residents in unincorporated Monroe County by 2014. YN=«u,n •, 11urv, rg au , e: uiscussion or permanent population The Remainder of This Page Intentionally Blank Monroe County 2010-2030 9 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates MONRCOE COUNTY COMPREHENSIVE PLAN UPDATE The use of the "drag factor" assumption as applied to growth in seasonal population is found in the methodology on page 33 is excerpted below: A similar methodology was employed to determine the seasonal resident and vacation rental visitor population by PAED from 2005 to 201 S. Essentially, the average percent increase figure was applied to the previous year's population figures. The product of this equation was then added to the previous years population to estimate the following year's total seasonal resident and vacation rental visitor population. A "drag" factor was applied to each year's percent increase figures by PAED (similar to the one applied to the permanent resident population figures). This drag factor increases by .1%each year over the ten year period, so that by 2015, lire percent increase in seasonal resident and vacation rental visitor population by PAED will have declined by 1.1%/ II is important to note this methodology reveals the beginnings of a decline in the total number of seasonal residents and visitors in vacation rentals in unincorporated Monroe County by 2013. one year prior to similar declines expected for the permanent resident population forecasts. Source: Appendix 1, MI;YI); Pg 33 re: discussion of seasonal population In this analysis the attempt has been made to analyze and determine whether and to what degree the existing permanent base has shifted to seasonal population, and to correct the population projections to reflect this phenomenon. 7.0 Seasonality in Retail Sales In a further test of seasonal conditions K&S examined historic monthly retail sales from 1998-2009 to determine if seasonal trends were becoming more pronounced. In this investigation we conducted a regression analysis using inflation adjusted monthly gross retail sales for Monroe County as the dependent variable. The econometric model developed tests both the effects of cyclical economic conditions and seasonal variations as predictors of retail sales. We further tested this model to determine if, over time, the seasonal pattern became more pronounced. The model's initial results indicate seasonal patterns are the strongest and most significant predictor of monthly retail sales. Cyclical factors including Gross Domestic Product, gasoline prices, unemployment and housing starts are also all significant predictors of retail sales. It is these cyclical factors which led to the 2006-2009 overall decline in sales. Thus these declines are not permanent as would be the case with a loss in permanent and seasonal population. Despite population losses in Monroe County estimated by BEBR for year 2010, retail sales did not decline, further validating the cyclical nature of sales. The second part of the test indicates that the seasonal pattern did not increase over time compared with the average seasonality. The econometric model results are shown below in Table 3. These results indicate the overall predictive ability of the model is very high (R2=.963). Further, the seasonal dummy variable (SeasDuml), which tests seasonality over the historic test period, is highly significant (t=11.2) and finally, a second set of seasonal dummy variables to test for additional seasonality after 2005 and also for Monroe County 2010-2030 1 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates additional peak season seasonality after 2005 (SeasDum2 and SeasDum3) both resulted in a lack of significance (t=.27 and t=.16 respectively). Thus, we conclude seasonal sales patterns are not changing nor were they becoming more pronounced from 2005-2009 compared with the 1998-2004 period. We believe this supports the theory that permanent population losses has been offset and replaced by a new type of seasonal population which spends, travels and behaves similarly to permanent population.' This could be' the case if a) homeowners lose a home to foreclosure and are forced to rent causing a shift to non - homesteaded (seasonal) units but still remain present in the market or b) newly built seasonal units are rented out for increasing periods and durations throughout the year, mimicking a "permanent" household. Anecdotal evidence supports both these conditions are presently occurring. Other significant variables in the model include Gross Domestic Product, national gasoline prices, national housing starts and national unemployment rates. Interestingly, the change in Monroe County permanent population growth was not a significant predictor of retails sales, despite permanent population losses and a decline in of sales in 2007, 2008 and 2009. In such a case one would expect negative population growth would cause retail sales declines. Because this was not evident in the statistical analysis, our belief that the decline in retail sales was cyclical garners greater support. Thus we conclude economic recession and seasonal activity determine sales volumes but declining permanent population, which is not statistically significant, does not. Again, the retail model analysis supports the view as permanent population is lost; it has been replaced by longer duration seasonal population or renters with no change in retail spending patterns. This would explain that while permanent population falls, there may be limited change in functional population due to seasonal replacement, as evidenced by retail sales. Table 3 - Econometric Test Results for Increasing Seasonality SUMMARY OUTPUT Regression Statistics Multiple R 0.981816 R Square 0.9639626 Adjusted R S 0.9447427 Standard Err 9209659 Observations 24 ANOVA df SS MS Regression 8 3.40318E+16 4.25E+15 Residual 15 1.27227E+15 8.48E+13 Total 23 3.53041E+16 Coefficients Standard Error t Slat Intercept 14947330 70400081.75 0.21232 GDPOO X Variable 1 28577.724 8869.439916 3.222044 WGAS X Variable 2 -136177.6 110696.9446 -1.23018 HUSTQ X Variable 3 27846.359 6935.672302 4.014947 RUQ X Variable 4 -8224690 2684043.539 -3.06429 SeasDuml X Variable 5 60680019 5395979.787 11.24541 SeasDum2 X Variable 6 2884055.9 10598795.93 0.272112 SeasDum3 X Variable 7 1368525.4 8297684.899 0.164929 Pop Ch X Variable 8 1473.2782 2520.714671 0.584468 Monroe County 2010-2030 Population Projections 3-15-11 11 Keith and Schnars, P.A. Fishkind and Associates Table 4 - Florida Keys Visitors Florida Keys Visitor Person -Trip Estimates 2003 2004 2005 2006 2007 2008 2009 Key West Overnight Visitors 1,309,559 1,303,633 11046,111 1,063,752 1,094,647 1,112,978 1,165,327 Key West Day Trippers 242,268 241,172 237,460 196,794 202,510 205,901 206,263 Cruise Ship Passengers 1,067,222 934.070 925,795 888,183 816,919 739,218 859,409 Total Key West Visitors 2,619,049 2,478,875 2,209,366 2,148729 2,114,076 2,058,097 2,230,999 All Keys Overnight Visitors 2,425,110 2,414,135 1,937,244 2,030,062 2.089,021 2.169,565 2,092,732 All Keys Day Trippers 448,645 446,615 439,742 375,561 386,469 401,369 370,414 Cruise Ship Passengers (Key west otuy) 1,067,222 934,070 925,795 888,183 816,919 739,218 859,409 Total All Keys Visitors 3,940,977 3,794,820 3,302,781 3,293,806 3,292,409 3,310.152 3,322,555 Monroe County Lodging Occupancy %: 72-2% 711% 70.0% 66.5% 68.1% 67.5% 70.3 % Sources: Monroe Counpr Tourist Derelapnwa Conner!: Smith Zrm•el Research Further, the seasonal stability and long term growth trend in retail sales is not attributed to additional retail spending by tourists or cruise ship passengers. Cruise ship and other tourists have declined over the past six years (Table 4) indicating the underlying retail sales growth pattern does not appear to be tourist related. 8.0 Long term Trends in Retail Sales and Traffic Retail sales have been trending up on an inflation adjusted basis over time (Figure 3). Total trend based growth is about 4% from 1998-2009. The declines in sales in 2007, 2008 and 2009 are as a result of rising gasoline prices in 2008 which reduced trips and travel and the cyclical effects of recession. As the recession ended retail sales stabilized and sales through November 2010 indicated no further loss in year over year retail sales countywide, despite a decline in permanent population in 2010 as reported by BEBR annual population estimates. 4.20 4.00 3.80 c 3.60 0 GO 3.40 �.70 3.00 — - , - - 10$ 19�� y��O 1`�� ti�� 'yp�a '1QPII 1COO LQPI Figure 3 - Monroe County Annual Retail Sales (inflation adjusted) Monroe County 2010-2030 12 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COUNTY COMPREHENSIVE PLAN UPDATE Similarly, in average daily traffic flows, the long term trend has been gradually increasing. Total trend based growth is about 6% (see Figure 4). This is generally consistent with and of similar magnitude to the trend in retail sales data. Based on sales and traffic it appears that the permanent population losses are being replaced by seasonal residents and there is no permanent net decline in economic activity (sales and traffic), as would be suggested by sustained permanent population losses without replacement. 27,000 26,000 25,000 24,000 23,000 22,000 21,000 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Figure 4 - Annual Average Daily Traffic Counts (Average of Selected Count Stations) The trend analysis of traffic data was examined in a variety of ways. These included selection of data stations to reflect only single locations per Key and data for which the entire history was available in a consistent fashion. This prevented overweighting by location or the effects of changing data collection methodologies. The trend analysis was conducted looking at 1999-2009, as well as 1999-2007 (eliminating the most recent highly volatile recession years and the period of highly volatile gasoline prices). A third approach was taken comparing the average of traffic counts from 1999-2002 with 2006-2009. The average of these three methods results in a 6% growth rate over time. The overall statistical significance of the trend line from 1999-2007 improved substantially over the 1999-2009 trend line through removal of the volatile outlying data points, however the magnitude of the trend line increase did not substantially change. After careful review of the traffic data we conclude the increasing trend in traffic counts is both valid and significant. This means traffic activity is not declining despite a decline in permanent population. We conclude then the growth in traffic is supported by a shift from permanent to seasonal population. Monroe County 2010-2030 13 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COMPREHENSIVE PLAN UPDATE 9.0 Countywide Functional Population The best available data in our view indicates a loss in permanent population with likely replacement through an increase in seasonal residents. Further, both sales and traffic are trending up by similar magnitude suggesting there is limited growth, and no sustained decline in economic activity. This volume of limited growth is consistent with growth which occurs under the ROGO cap. American Communities Survey data and homestead exemption data support the growth of seasonal population. Total non -homesteaded units are 57% today compared with 55% in 1998. Among single family units only, the non -homestead share has risen from 45% in 1998 to 49% in 2009. For single family units, 70% of the growth since 1998 has been in non -homestead units, and the American Communities Survey indicates a substantial rise in seasonal households during the 2000-2008 time period. This supports an increase in non- permanent/seasonal occupancy, which offsets the permanent population losses. As a decline in permanent population has occurred, there is a real increase in non- permanent/seasonal replacement as evidenced by an increase in the trend in auto -traffic volume, an increase in the trend in inflation adjusted retail sales, an increase in non - homesteaded residential properties, and an increase in seasonal population shown in the American Communities Survey. A complicating aspect is the 2008 permanent population figures from both the annual Census population and American Communities Survey population data which indicate permanent population in the Keys is now between 70,000 and 72,000; this is well below the BEBR 2009 estimate of 78,000. There is some probability the April 2010 Census count may indicate a sharply reduced permanent population level. With the understanding that permanent losses do appear to be replaced by seasonal population, and some losses in permanent population may be temporary and cyclical due to recession and foreclosures, if all of the recent Census or ACS based permanent losses were shifted into the seasonal population, the resulting 2030 functional population would still likely demonstrate small levels of growth consistent with the ROGO allocations. Based on this analysis, K&S prepared a county level functional population series to reflect these conditions. This series begins with the medium series population projection from the BEBR medium series projection, PS156, published in 2010. Next, the FKAA seasonal series through 2025 was used and to this was applied the 2000-2025 CAGR growth rate of the FKAA seasonal series to extend the series from 2025 to 2030. In addition, from 2006-2030 K&S has added 70% of the permanent population loss as forecast by BEER to the seas population to " � �" seasonal � ., population. Further, we have added the egniva�nt of 70% of the ROGO growth to $easorkal p©Ie5. series, reflecting the seasonal shi component not evidenced in FKAA's original data. The resulting functional population is seen in Figure 5 and Table 7. Monroe County 2010-2030 14 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates K&S believes this data series is the most reflective of actual economic and market conditions and is most representative of the long term functional population outlook. Our findings are based on extensive analysis of multiple data series. K&S recommends the use of this functional population data series for use in the 2010 EAR comp plan update. It is also noted, for units shifting to seasonal status and for seasonal population associated with ROGO growth, a persons -per -household figure of 2.7 was used. On pages 34 and 36 of the MCPD population report in Appendix 1, it is noted the measures of seasonal persons per household were greater than 2.7. Further supporting the use of 2.7 persons per household for seasonal population, Property Appraiser data (Table 5) suggests a steady increase in persons per household through year 2008, as described by an increase in the number of bedrooms per unit. This increase in bedrooms also suggests an increase in overall unit size; however, the Monroe County Property Appraiser data for unit size is unavailable. K&S believes seasonally occupied homes and rentals have a greater number of bedrooms and higher person per household occupancy due to the increasing size of newly built units. Newly built units today are primarily non -homesteaded and likely to have a higher proportion of seasonal residents. For these reasons, as well as the data analysis presented in the original MCPD population study, 2.7 persons per household was used for seasonal household size. Table 5 - Average Number of Bedrooms per Single Family Unit by Year Built - —^ 2.1 Pre-1970 2.4 1970-1989 2.5 1990-1999 2.8 2000-2008 Source: Monroe�o._Fr6P_e_0 p raiser, iFishkind &Associates, Inc. The preliminary population series shown in Figure 5 represents the BEBR medium series projection plus the FKAA seasonal series. The Final Revised series is recommended for use. This series represents this same data as the preliminary with the addition of the seasonal replacement population, which offsets the permanent population loss. The Final series is the recommended series and corrects the FKAA methodological flaw. This flaw finds the original MCPD study looked only at growth and did not contemplate the shift of the existing population from permanent to seasonal. Monroe County 2010-2030 15 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates 165,000 160.000 155,000 150.000 MONROE COUNTY COMPREHENSIVE PLAN UPDATE Comparative Population Series Monroe County oq0 �p`L oQa o��' oQ4' 0`30 oy�, oy°` o'y`" o^y4' o,.yo oti�, o,Looy�o otiQ, o,�o ti ti ti� ti ti ti ti ti� ti ti ti ti ti ti --EP—Preliminory —0 -Final Revised Figure 5 - Recommended Functional Population The Remainder of This Page Intentionally Left Blank monroe county 2010-2030 16 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates MONROE COUNTY Table Source: Fishkind & Asso i- Kecommenaea runcuonai ronuiation Monroe County Population Projection Seasonal Replacement Series YEAR Permanent Seasonal Functional 2000 79,589 73,491 153,080 2001 80,011 73,540 153,551 2002 80,434 73,589 154,023 2003 80,856 73,639 154,495 2004 81,236 73,688 154,924 2005 82,413 73,737 156,150 2006 80,510 75,228 155,738 2007 78,987 76,453 155,440 2008 76,081 78,647 154,728 2009 77,925 77,516 155,441 2010 76,887 78,401 155,288 2011 78,080 77,974 156,054 2012 77,960 78,431 156,391 2013 77,840 78,887 156,727 2014 77,720 79,343 157,063 2015 77,600 79,800 157,400 2016 77,460 80,270 157,730 2017 77,320 80,740 158,060 2018 77,180 81,211 158,391 2019 77,040 81,681 158,721 2020 76,900 82,151 159,051 2021 76,760 82,622 159,382 2022 76,620 83,092 159,712 2023 76,480 83,562 160,042 2024 76,340 84,033 160,373 2025 76,200 84,503 160,703 2026 76,060 84,973 161,033 2027 75,920 85,444 161,364 2028 75,780 85,914 161,694 2029 75,640 86,384 162,024 2030 75,500 86,855 162,355 fates, Inc.; Fl Keys Aqueduct Authoritv: Univ. FL BEBR. PS ] Wand ar FLAN UPDATE series nual estimates Monroe County 2010-2030 17 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates M►ONROE COUNTY COMPREHENSIVE PLAN UPDATE 10.0 Determination of Unincorporated Area Functional Population Permanent Population The unincorporated population as a share of countywide population has increased from 45.3 percent in 2002 to 46.5 percent in 2009. Figure 6 shows the 10 year trend in the unincorporated share, based on the University of Florida annual population estimates. Source: University of Florida, Annual Population Estimates Figure 6 - Unincorporated Population Share of Countywide Population The unincorporated permanent share has increased in the past three years likely due to foreclosures and conversions from permanent to seasonal in incorporated areas. As foreclosures abate, the change in unincorporated permanent population as a share of countywide totals will stabilize. Further, the permanent population share in the unincorporated area is likely to fall as unoccupied homes in municipal areas once again become occupied and come under ownership. Based on this discussion, for the future estimates of permanent population as a share of countywide totals we have used 46 percent as the stabilized figure representing the unincorporated share of permanent population over time. Seasonal Population The unincorporated areas contain 46 percent of all non -homesteaded residential units in Monroe County, based on 2009 Monroe County Property Appraiser Tax Roll data. This represents some 11,664 units. Using seasonal persons per household size of 2.7 the seasonal population in residential housing units is 29,160. monroe county Z010-Z030 18 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates SIVE PLAN UPDATE 1 In addition, the unincorporated areas contain 27 percent of all hotel motel space in Monroe County. This converts to an estimated 2,197 hotel/motel rooms within the unincorporated area. With average annual hotel occupancy of 69.8% (based on Smith Travel Hotel Trends Reports 2003-2010) and average persons per room of 2.73, the hotel based seasonal population in the unincorporated areas is 5,558. Further, the original MCPD/FKAA population methodology did not include the functional population associated with Keys Tourist Day Trips. This is a daily number which increases the functional population. Based on the average share of annual unincorporated day trips divided by 365, the number of unincorporated day trippers represents an addition of 325 persons to the functional population, as described in Table 8. Table 8 - Day Trippers As A Component of Unincorporated Seasonal Population 2003 2004 2005 2006 2007 2008 2009 All Keys Day Trippers 448,645 446,615 439,742 375,561 386,469 401,369 370,414 Key West Day Trippers 242,268 241,172 237,460 196,794 202,510 205,901 206,263 All Else Keys Day Trippers 206,377 205,443 202,282 178,767 183,959 195,468 164,151 other Municipal Day Trip 69,659 69,344 68,277 60,340 62,093 65,977 55,407 Uninc Keys Day Tripers 136,718 136,099 134,005 118,427 121,866 129,491 108,744 Functional Day Trippers 375 373 367 324 334 355 298 Source: Monroe County Tourist Development Council, Fishkind & Associates, Inc. Combining the household based seasonal populations, hotel based seasonal population, day trippers, and adjusting for non-standard dwelling units populations including those in camps, liveaboards and other, it is estimated there are 35,053 seasonal residents throughout unincorporated Monroe County, in 2009. This represents 45 percent of the 2009 countywide seasonal population as shown in Table 4. Applying this percentage to the countywide seasonal population projection yields a seasonal population in the unincorporated areas of 39,226 by year 2030. Table 9 provides the permanent, seasonal and functional population for unincorporated Monroe County, through year 2030. Total unincorporated functional population is expected to increase from 71,311 in year 2009 to 73,956 by year 2030. This represents an increase of 2,645 persons over the entire planning horizon. Table 9 provides the determination of unincorporated permanent and seasonal population. Monroe County 2010-2030 19 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates T� COMPREHENSIVE PLAN UPDATE ime 9- unincorporated Functional Populatic Unincorporated Population Projection Seasonal Replacement Series Permanent Seasonal Functional 2000 36,036 33,241 69,277 2001 36,250 33,263 69,512 2002 36,452 33,285 69,737 2003 36,543 33,307 69,850 2004 36,606 33,329 69,935 2005 37,164 33,351 70,515 2006 36,466 34,019 70,485 2007 35,749 34,568 70,317 2008 34,788 35,550 70,338 2009 36,268 35,043 71,311 2010 35,368 35,440 70,808 2011 35,917 35,249 71,166 2012 35,862 35,453 71,315 2013 35,806 35,658 71,464 2014 35,751 35,862 71,613 2015 35,696 36,067 71,763 2016 35,632 36,277 71,909 2017 35,567 36,488 72,055 2018 35,503 36,698 72,201 2019 35,438 36,909 72,348 2020 35,374 37,120 72,494 2021 35,310 37,330 72,640 2022 35,245 37,541 72,786 2023 35,181 37,752 72,933 2024 35,116 37,962 73,079 2025 35,052 38,173 73,225 2026 34,988 38,384 73,371 2027 34,923 38,594 73,518 2028 34,859 38,805 73,664 2029 34,794 39,016 73,810 2030 34,730 39,226 73,956 Source: Fishkind & Associates, Inc. 11.0 Unincorporated Population in Upper/Middle/Lower Keys Permanent Population - Upper/Middle/Lower Series With the functional unincorporated population determined, the distribution between upper, middle and lower regions is based on the permanent population, ratio of seasonal to permanent population plus the distribution of hotel/motels by sub -area. Monroe County 2010-2030 20 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates IM ONROE COUNTY COMPREHENSIVE PLAN UPDATE W W W.IMYSCOM"LW.COM 18W) 488-12SS Permanent population is based on the on-line service I -Site which provides updated block group information based on US Census data (Table 10). The distribution of permanent population based on these data is shown in Table 11. 44% 3% 52% 100% 42% 3% 55% 100% 41% 3% 56% 100% 40% 3% 57% 100% Source: Fishkind & Associates, Inc.; I -Site online demographic database The Remainder of This Page Left Intentionally Left Blank Monroe County 2010-2030 21 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates AO ROE COUNTY COMPREHENSIVE PLAN UPDATE Table 11- Permanent Population Distribution by Sub -Area Unincorporated Permanent Population Projection Seasonal Replacement Series Upper Middle Lower 2000 15,135 1,081 19,820 2001 15,185 1,087 19,978 2002 15,229 1,094 20,130 2003 15,226 1,096 20,221 2004 15,212 1,098 20,296 2005 15,402 1,115 20,647 2006 15,073 1,094 20,299 2007 14,737 1,072 19,940 2008 14,263 1,044 19,481 2009 14,797 1,088 20,383 2010 14,430 1,061 19,877 2011 14,654 1,078 20,185 2012 14,632 1,076 20,154 2013 14,609 1,074 20,123 2014 14,586 1,073 20,092 2015 14,564 1,071 20,061 2016 14,538 1,069 20,025 2017 14,511 1,067 19,989 2018 14,485 1,065 19,953 2019 14,459 1,063 19,916 2020 14,433 1,061 19,880 2021 14,406 1,059 19,844 2022 14,380 1,057 19,808 2023 14,354 1,055 19,772 2024 14,327 1,053 19,735 2025 14,301 1,052 19,699 2026 14,275 1,050 19,663 2027 14,249 1,048 19,627 2028 14,222 1,046 19,591 2029 14,196 1,044 19,554 2030 14,170 1,042 19,518 Source: Fishkind & Associates, Inc. Monroe County 2010-2030 1 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COMPREHENSIVE PLAN UPDATE Population - Upper/Middle/Lower Seasonal population within the upper/middle/lower unincorporated areas is estimated based on the ratio of unincorporated seasonal population to unincorporated permanent population, multiplied by the permanent population distributions by sub -area (Table 12). Table 12- Seasonal Population Distribution by Sub -Area Unincorporated Seasonal Population Projection Seasonal Replacement Series Upper Middle Lower 2000 14,048 1,056 18,137 2001 14,020 1,057 18,185 2002 13,993 1,058 18,234 2003 13,966 1,058 18,283 2004 13,938 1,059 18,332 2005 13,910 1,060 18,381 2006 14,150 1,080 18,789 2007 14,339 1,096 19,133 2008 14,665 1,126 19,759 2009 14,388 1,111 19,545 2010 14,550 1,122 19,768 2011 14,472 1,117 19,660 2012 14,555 1,123 19,775 2013 14,639 1,129 19890 2014 14,722 1,135 20,005 2015 14,806 1,141 20,120 2016 14,891 1,148 20,238 2017 14,977 1,154 20,357 2018 15,063 1,160 20,475 2019 15,149 1,167 20,593 2020 15,235 1,173 20,712 2021 15,321 1,179 20,830 2022 15,407 1,185 20,948 2023 15,493 1,192 21,067 2024 15,579 1,198 21,185 2025 15,665 1,204 21,304 2026 15,751 1,211 21,422 2027 15,837 1,217 21,540 2028 15,923 1,223 21,659 2029 16,009 1,230 21,777 2030 16,095 1,236 21,896 Source: Fishkind & Associates, Inc. Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COUNTY COMPREHENSIVE 1255 Based on these data we are able to determine the functional population for unincorporated Keys according to the upper/middle/lower sub -areas of the unincorporated portion of Monroe County. Table 13 presents the functional population for unincorporated Monroe and the sub -areas. Table 13 - Unincorporated Functional Population Distribution by Sub -Area Unincorporated Functional Population Projection Seasonal Replacement Series Upper Middle Lower TOTAL 2000 29,183 2,138 37,957 69,277 2001 29,205 2,145 38,163 69,512 2002 29,222 2,151 38,364 69,737 2003 29,192 2,155 38,504 69,850 2004 29,150 2,157 38,628 69,935 2005 29,313 2,175 39,027 70,515 2006 29,222 2,174 39,089 70,485 2007 29,075 2,169 39,073 70,317 2008 28,928 2,169 39,240 70,338 2009 29,185 2,199 39,927 71,311 2010 28,980 2,183 39,645 70,808 2011 29,126 2,194 39,846 71,166 2012 29,187 2,199 39,929 71,315 2013 29,248 2,203 40,013 71,464 2014 29,309 2,208 40,097 71,613 2015 29,370 2,212 40,181 71,763 2016 29,429 2,217 40,263 71,909 2017 29,489 2,221 40,345 72,055 2018 29,549 2,225 40,427 72,201 2019 29,608 2,230 40,510 72,348 2020 29,668 2,234 40,592 72,494 2021 29,728 2,238 40,674 72,640 2022 29,787 2,243 40,756 72,786 2023 29,847 2,247 40,838 72,933 2024 29,907 2,252 40,921 73,079 2025 29,966 2,256 41,003 73,225 2026 30,026 2,260 41,085 73,371 2027 30,086 2,265 41,167 73,518 2028 30,145 2,269 41,249 73,664 2029 30,205 2,274 41,332 73,810 2030 30,265 2,278 41,414 73,956 Source: Fishkind & Associates, inc. Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COMPREHENSIVE PLAN UPDATE APPENDIX 1 Monroe County 2010-2030 Population Projections 3-15-11 Keith and Schnars, P.A. 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G i-y a c4 U a) N c a° m �w w w a� sM 91 4&:' 4J1 Table 2.29 SeasonalPopulation Projections Unicorporated Monroe County 1990-2010 By Planning Area/Enumeration (PAED) Districts PAED 1990 1995 2000 2005 2010 LOWER KEYS 1 1,734 1,903 2,072 2,257 2,464 2 717 787 856 933 1,014 3 944 1,035 1,127 1,228 1,335 4 2,117 2,323 2,529 2,755 2,996 5 2,154 2,364 2,573 2,803 3,048 6 981 1,076 1,172 1,277 1,388 Sub -Total 8,647 9,488 10,329 11,253 12,236 MIDDLE KEYS 7 5,099 5,593 6,092 6,633 7,215 8 371 407 443 482 524 9 455 500 544 593 644 10 1,917 2,104 2,291 2,495 2,713 11 1,401 1,537 1,673 1,823 1,982 12 1,650 1,811 1,971 2,148 2,335 13 2,049 2,249 2,448 2,687 2,900 Sub -Total 12,942 14,201 15,462 16,841 18,313 UPPER KEYS 14 4,745 5,204 5,669 6,173 6,714 15 1,500 1,646 1,792 1,953 2,123 16 2,940 3,225 3,512 3,826 4,160 17 2,703 2,966 3,229 3,518 3,825 18 2,948 3,235 3,522 3,837 4,172 19 418 459 499 544 591 20 2,236 2,453 2,671 2,909 3,163 21 3,862 4,237 4,613 5,025 5,464 22 169 186 202 221 240 Sub -Total 21,521 23,611 25,709 28,006 30,452 PAED TOTAL 43,110 47,30 551,500 56,100 61,000 Note: The City of Key West, Key Colony beach, and layton are not included. Cape Sable is included in PAED 21; Windiey Key is included in PAED 12 Source: U.S. Census 19W, Price Waterhouse. Table 2.30 Functional Population Projections Unicorporated Monroe County 1990-2010 By Planning ArealEnumeration (PAED) Districts PAED 1990 19961 20001 2005 2010 LOWER KEYS 1 6,275 6,480 6,667 6,894 7,132 2 3,823 3,946 4,057 4,181 4,323 3 4 2,730 6,100 2,915 6,895 3,079 7,561 3,262 8,302 3,475 9,212 5 6,362 7,265 8,015 8,852 9,884 6 1,422 1,517 1,614 1,718 1,829 Sub -Total 26,712 29,018 31,003 33,209 35,855 MIDDLE KEYS 7 8 13,960 1,068 14,938 1,363 15,815 1,559 16,779 1,598 17,909 1,641 9 10 11 12 13 Sub -Total 1,541 2,546 1,757 2,746 3,269 26,887 1,698 2,813 1,893 3,106 3,469 29,280 1,829 3,062 2,029 3,421 3,668 31,383 1,976 3,336 2,179 3,772 3,887 33,527 2,155 3,645 2,338 4,019 4,120 35,827 UPPER KEYS 14 9,150 10,155 11,048 12,031 13,192 15 16 3,933 5,227 4,303 5,912 4,623 6,510 4,980 6,894 5,404 7,228 17 5,168 5,679 6,135 6,641 7,230 18 7,075 8,167 9,081 9,966 10,300 19 1,326 1,462 1,576 1,704 1,859 20 3,785 4,002 4,220 4,458 4,712 21 5,649 6,447 7,154 7,936 8,580 22 230 270 303 342 387 Sub -Total 41,543 46,387 1 50,650 54,952 58,892 PAED TOTAL . 95,142 104,695 113,036 121,688 130,574 Note' 'rho City of Key West, Key Colony beach, and layton an, not included. 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Population Projections 3-15-11 Fishkind and Associates SECTION 2 Population and Water Demand Forecast Summary 2.1 Introduction The development of accurate population projections and water use demands for the Florida Keys is challenging because of the high number of seasonal residents (those residing in the Keys for 6 months or less), and day visitors (from cruise ships docking in Key West or visitors from the mainland). The population projections developed by the Monroe County Planning Department (MCPD) and used in the U.S. Army Corps of Engineers (USACE) Florida Keys Carrying Capacity Study (USACE, 2003) are used as the basis for the majority of population projections developed by other agencies, and were also used for this analysis. The MCPD permanent and seasonal population projections were used to develop a functional population (permanent plus seasonal) for FKAA's service area through 2025. The projected population was then multiplied by FKAA's projected per capita demand to project customer demand in the service area. The per capita demand is projected to in- crease as the changing demographics of the Keys result in higher indivi- dual water use (for example, redevelopment of existing property usual- ly involves some level of irrigation or other water -consuming amenities where none previously existed). 2.2 Projected Population 2.2.1 Permanent Population The MCPD permanent population projections include the most appro- priate and applicable information and are viewed as the basis of future projections in this Plan. From 1990 through 1995, the permanent popula- tion of Monroe County increased from 78,856 to 79,200 (0.4 percent); from 1995 through 2000, it increased from 79,200 to 79,589 (0.5 percent); and from 2000 through 2005, it increased from 79,589 to 81,701 (2.7 percent). GNV31013363600.DOC/061640008 2-1 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY The 1N4CPD data in the USACE Carrying Capacity Study (USAGE, 2003) project a permanent population of 79,589 for 2000; 81,701 in 2005; 83,400 in 2010; 83,799 in 2015; 84,200 in 2020; and 84,603 in 2025. Exhibit 2-1 summarizes the MCPD permanent population projections. The permanent population is projected to grow at an overall average rate of 1.2 percent for each 5-year period from 2005 through 2025, with a higher rate (2.1 percent from 2005 to 2010) and a lower rate (0.5 percent) thereafter as Monroe County nears build -out. 2.2.2 Seasonal Population The MCPD seasonal population projections in the USACE Carrying Capacity Study (USACE, 2003) also were used to project the seasonal population for Monroe County. Although there are no exact counts of the seasonal population, the MCPD developed historical seasonal population projections for 1990,1995, and 2000. The MCPD projected that the 1990 seasonal population of 70,493 increased by 1.1 percent to a 1995 population of 71,266, and further in- creased by 3.1 percent to a 2000 seasonal population of 73,491.The MCPD continues these seasonal population projections in 5-year increments starting with a seasonal population of 73,737 in 2005; 74,533 in 2010; 74,712 in 2015; 74,891 in 2020; and 75,071 in 2025. The seasonal population is projected to increase at an overall average rate of 0.4 percent for each 5-year period from 2005 through 2025, with a 1.1 percent increase between 2005 and 2010 and a 0.24 percent increase from 2010 through 2025. 2.2.3 Functional Population The germ "functional population" is a concept that incorporates three elements of popula- tion: permanent residents, seasonal visitors, and day visitors. Because of the unique nature of the Keys, which has an economy based on seasonal tourism, it is appropriate to use one "population" number that incorporates these three separate population components. In 2004 and 2005, CH2M HILL developed population projections for the FKAA service area. The population projections were based on those developed by the Monroe County Planning Department, and combined the permanent population with the seasonal population to form a "functional population" that was used to estimate water demand. As part of this effort, CH2M HILL contacted the agencies or municipalities listed in Exhibit 2-1 to determine if they could provide data that could be used to develop population projections for the FKAA service area. Ultimately, it was decided to use the functional population projections developed by Monroe County. Exhibit 2-2 presents the MCPD permanent, seasonal, and functional populations between 1990 and 2025. For this Plan, the functional population value is used in all per capita calcula- tions and estimates. There are approximately 3.6 people per customer account within FKAA's service area using functional population as the basis. Exhibit 2-3 summarizes the percent change in the functional population in 5-year intervals, starting in 1990. GNV31013363600.DOC1061640006 2-2 WB122005005DFB EXHIBIT 2-1 Sources of Population Projection Data SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY Agency or Municipality Type of Data Contact Person Data Source Comments University of Florida Permanent Population N/A 2003 Annual Report Projections for the entire state Bureau of Economic Projections of Florida by county from and Business 2000 through 2025. Research (BEBR) Monroe County Permanent and N/A 2004 Seasonal and permanent Planning Department Seasonal Population Comprehensive population projections were Projections Plan and Facilities based off 1990 US Census Capacity and updated with the 2000 Assessment US Census numbers for the entire county. Monroe County Tourist Hotel, Cruise Ship, and Jessica Three Penny The most detailed seasonal Development Council Airline Data Mazzola, Revenue Report, data, but did not account for (TDC) Director of Call Counts, Trend the "day trip" visitor. Market Report and Airline Research Passenger Data Report FY 2004 Islamorada Permanent Population Patrick Small, 2003 Developed based on the US Projections Principal Comprehensive Census. Planner Plan Key Colony Beach Permanent and Clyde Burnett, 1992 Developed based on the US Seasonal Population Mayor Comprehensive Census. Projections Plan Key West Permanent and Ty Symrowski, 1994 Developed based on the US Seasonal Population City Planner Comprehensive Census. Projections Plan Layton Permanent and Norm Anderson, N/A Developed based on the US Seasonal Population City Council Census. Projections Marathon Permanent and Katie Parker, 2003 Developed based on the US Seasonal Population Planner Comprehensive Census. Projections Plan U.S. Census Permanent Population N/A 2000 Census Permanent population Estimates Estimates estimates for 2000 by county. South Florida Water Population and Water N/A Lower East Coast Draft data from November Management District Demand Projections Regional Water 2003. (SFWMD) Supply Plan (LEC RWSP) (2003) U.S. Army Corps of Permanent and N/A Carrying Capacity Included constraints on Engineers (USACE) Seasonal Population Study (2003) growth and environmental Projections factors. Note: N/A = not applicable GNV31013363600.DOC/061640006 2-3 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY EXHIBIT 2-2 Monroe: County Historic and Projected Population Projections Functional Population (Permanent + Year Permanent Population Seasonal Population Seasonal + Day Visitors) 1990 78,856 70,493 149,349 1991 78,925 70,648 149,572 1992 78,994 70,802 149,796 1993 79,062 70,957 150,019 1994 79,131 71,111 150,243 1995 79,200 71,266 150,466 1996 79,278 71,421 150,698 1997 79,356 71,575 150,931 1998 79,433 71,730 151,163 1999 79,511 71,884 151,396 2000 79,589 73,491 153,080 2001 80,011 73,540 153,552 2002 80,434 73,589 154,023 2003 80,856 73,639 154,495 2004 81,279 73,688 154,966 2005 81,701 73,737 155,438 2006 82,041 73,896 155,937 2007 82,381 74,055 156,436 2008 82,720 74,215 156,935 2009 83,060 74,374 157,434 2010 83,400 74,533 157,933 2011 83,480 74,569 158,049 2012 83,560 74,605 158,164 2013 83,639 74,640 158,280 2014 83,719 74,676 158,395 2015 83,799 74,712 158,511 2016 83,879 74,748 158,627 2017 83,959 74,784 158,743 2018 84,040 74,819 158,859 2019 84,120 74,855 158,975 2020 84,200 74,891 159,091 2021 84,281 74,927 159,208 2022 84,361 74,963 159,324 2023 84,442 74,999 159,441 2024 84,522 75,035 159,557 2025 84,603 75,071 159,674 GNV31013363600.DOC/061640008 2-4 WB1220C5005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY EXHIBIT 2.3 5-Year Historic and Projected Percent Changes in Functional Population Percent Change in 5-Year Period Functional Population 1990-1995 0.75 1995-2000 1.74 2000-2005 1.54 2005-2010 1.61 2010-2015 0.37 2015-2020 0.37% 2020-2025 0.37% 2.3 Historic Water Production CH2M HILL reviewed the raw water pumpage records from the FKAA's Florida City well - field from 1990 through 2005. These data, obtained from the FKAA's previous water use permit (WUP) applications, Monthly Operating Reports (MORs), and Monthly Production Reports (MPRs), are summarized in Exhibit 2-4. Exhibit 2-5 summarizes the same data for finished water; however, because of limited continuous annual historic data, a summary from 2000 to 2005 is presented. Unlike population growth, which increased less than 2 percent for each 5-year period from 1990 through 2005 (Exhibit 2-3), the average -day raw water demand for the FKAA service area increased much more rapidly. From 1990 to 1995, the average -day raw water demand for the service area increased from 12.06 mgd to 14.07 mgd, an increase of 16.7 percent. From 1995 to 2000, the average -day demand increased by 21.2 percent, from 14.07 mgd to 17.06 mgd. From 2000 to 2005, average -day demand increased by only 4.0 percent, from 17.06 mgd to 17.73 mgd. As seen in Exhibits 2-4 and 2-5, the 2000 drought with water restrictions resulted in significantly lower demands in 2001 (the year in which water restrictions were fully implemented). It is also possible that reduction in travel following the September 11, 2001, terrorist attacks resulted in less tourism. GNV310'13363600.DOC1061640008 2-5 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY EXHIBIT 2.4 Historic Raw Water Production Per Capita Annual Average Daily Max Day Demand Average Monthly Demand Year Demand (MG) Demand (mgd) (mgd) Demand (MG) (gpcd) 1990 4,404 12.06 14.89 367.01 80.74 1991 4,290 11.75 14.87 357.53 78.53 1992 4,742 12.98 15.9 395.16 86.67 1993 5,163 14.14 16.76 430.29 94.23 19,94 5,076 13.90 16.88 423.01 92.50 19,95 5,140 14.07 16.49 428.37 93.53 1996 5,273 14.44 17.82 439.40 95.80 1997 5,357 14.67 18.36 446.38 97.17 1998 5,622 15.39 18.29 468.49 101.82 1999 5,953 16.30 20.24 496.06 107.65 2000 6,230 17.06 20.79 519.15 111.42 2001 5,627 15.41 19.15 468.89 100.32 2002 6,191 16.95 20.46 515.93 110.05 2003 6,288 17.22 22.20 524.01 111.43 2004 6,383 17.48 22.00 531.92 112.77 2005 6,477 17.73 22.39 539.75 114.10 Notes: MG=million gallons mgd=million gallons per day gpcdl=gallons per capita per day per capita=functional population EXHIBIT 2.5 Historic Finished Water Production Average Annual Average Daily Max Day Monthly Per Capita Demand Year Demand (MG) Demand (mgd) Demand (mgd) Demand (MG) (gpcd) 2000 6,116 16.76 20.46 510 109.46 2001a 5,558 15.23 19.24 463 99.17 2002 6,031 16.52 19.95 503 107.28 2003 6,248 17.12 20.43 521 110.80 2004 6,347 17.39 20.43 529 112.22 2005 6,338 17.36 22.30 528 111.71 Notes: a2001 maximum day for historic finished water was higher than maximum day for raw water (Exhibit 2-3) because of higher pumpage from storage tanks at Florida City during peak hours. MG million gallons mgd=million gallons per day gpcdl=gallons per capita per day per capita=functional population GNV310'13363600.DOC/061640008 2-6 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY Exhibit 2-6 compares the changes in population, raw water demand, and per capita use for the 5-year periods from 1990 through 2005. EXHIBIT 2-6 5-Year Historic Percent Changes in Functional Population Raw Water Demand and Per Capita Water Demand Percent Change in Percent Change in Average Day Percent Change in per 5-Year Period Functional Population Raw Water Demand Capita Water Demand 1990-1995 0.75 16.72 15.85 1995-2000 1.74 21.19 19.12 2000-2005 1.54 3.97 2.39 The high rate of growth in raw water demand, along with an increasing per capita demand over time, as seen in Exhibit 2-4, is primarily the result of a strong shift in demographics seen in the FKAA service area. The Keys as a whole are seeing an increasing number of affluent customers moving into the area who are then displacing the lower -income demo- graphic group. These new customers are either improving existing homes or tearing them down and building larger, more expensive homes that use more water. Thus, new cus- tomers are consuming more water on a per capita basis and resulting in a higher per capita and average -day demand for the FKAA service area. This hypothesis was explored by investigating two issues believed to possibly contribute to this trend: • Swimming pool construction permits, and • Differences in water use following a home sale. 2.3.1 Swimming Pool Construction Permits Homes constructed or redeveloped by higher -income residents typically have swimming pools, which further increase the water demand for that residence. CH2M HILL obtained the annual number of swimming pool construction permits issued by Monroe County from 1995 through 2004, as shown in Exhibit 2-7. EXHIBIT 2.7 Annual Swimming Pool Construction Permits Issued by Monroe County Number of New Swimming Pool Year Construction Permits Issued Percent Annual Increase 1995 65 N/A 1996 82 26 1997 88 7 1998 98 11 1999 88 -10 2000 96 9 2001 88 -8 2002 111 26 2003 195 76 2004 153 -22 Annual Average 106 13 GNV31013363600.DOC/061640008 2-7 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY The rate of swimming pool permit issuance increased, on average, by 13 percent annually from 1995 through 2004, which included both the drought year and recovery of 2001 as well as 2004, which had multiple hurricanes. In the past 3 years (2002 through 2004), pool permit issuance increased by an average of 27 percent annually (except 2004). Since 1995, the number of permits issued annually has increased by more than 250 percent. 2.3.2 Current Homeowner Versus Former Homeowner Water Use In a trend that has become commonplace across Florida, higher -income residents are dis- placing lower -income residents and substantially improving their "new" homes. Many of these improvements involve upgrading the landscaping with lush foliage that typically requires substantially more irrigation than the previous landscaping. In addition, many times smaller homes are replaced with larger homes with more bathrooms. As a result of these changes, many of these residences show large increases in water use without a cor- responding increase in population. Additionally, higher -income residents are typically less sensitive to increases in their water bill and are less likely to decrease their water use in response to the increased cost. Combined, these factors can result in an increased per capita water use by new residents. CH2N4 HILL analyzed residential home sales prices to determine if the increase in home sales prices could be correlated with increasing per capita water demand. Individual account data were only available from 2000 through 2004, and to compare a full year of usage for each customer, only home sales occurring between 2002 and 2003 were used, which allowed for at least one full year of usage data before and after the sale. Water use in 2001 was excluded because of the impact of the water restrictions in effect at this time. The FKAA service area is made up of several municipalities that are going through re- development and changes in demographics at different paces. To substantiate the correla- tion between increased home values and water use, CH2M HILL examined the home sale data for each separate municipality and for Monroe County as a whole. 1. CH2M HILL analyzed 2002 and 2003 home sale data provided by the Monroe County Property Appraiser to identify transactions in which the previous sale price was $150,000 or less. In 2002, 163 sales met this criterion; 268 purchases met this criterion in 2003. 2. The annual water use for each group of residential accounts was summed for 2000 through 2004. 3. For homes sold in 2002, their 2003 and 2004 water use was compared to their water use in 2000. Data from 2001 were excluded because of the drought, and data from 2002 (the sale year) were not included because of homes being sold at different times during the year and the lack of a full year's worth of water use under either the old or new home- owners. 4. The water use in homes sold in 2004 was compared against their 2002 water use. Data from 2001 and 2003 were excluded as noted above. For the 2002 home sales in Monroe County, water use increased by 13.4 percent in 2003 and 21.1 percent in 2004 when compared to water use in 2000. For the 2003 home sales, water use increased by 11.4 percent in 2004 when compared to 2002 water use. GNV31013363600.DOC/061640008 2-8 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY A technical memorandum documenting the projected change in per capita use, prepared for the South Florida Water Management District as part of the FKAA's water use permitting process is included as Appendix A. 2.4 Projected Finished Water Demand The projected finished water demands for the FKAA service area from 2005 through 2025 are shown in tabular form in Exhibit 2-8 and in graphical form in Exhibit 2-9. EXHIBrr 2.8 FKAA Service Area Vation and Finished Wate Population Finished Water Demands Avg. Max. Avg. Max. per capita Day Day Annual Mo. Mo. Year Permanent Seasonal Functional (gpcd) (mgd) (mgd) (MG) (MG) (MG) 2005 (Actual) 81,701 73,737 155,438 114.08 17.73 22.39 6477 539.74 597.15 2006 82,041 73,896 155,937 119.15 18.58 23.23 6786 565.53 625.69 2007 82,381 74,055 156,436 119.99 18.77 23.46 6856 571.31 632.08 2008 82,720 74,215 156,935 122.34 19.2 24.00 7013 584.40 646.56 2009 83,060 74,374 157,434 124.75 19.64 24.55 7174 597.79 661.38 2010 83,400 74,533 157,933 127.08 20.07 25.09 7331 610.88 675.86 2011 83,480 74,569 158,049 129.58 20.48 25.60 7480 623.36 689.67 2012 83,560 74,605 158,164 132.01 20.88 26.10 7626 635.54 703.14 2013 83,639 74,640 158,280 134.45 21.28 26.60 7773 647.71 716.61 2014 83,719 74,676 158,395 136.87 21.68 27.10 7919 659.89 730.08 2015 83,799 74,712 158,511 139.30 22.08 27.60 8065 672.06 743.55 2016 83,879 74,748 158,627 140.90 22.35 27.94 8163 680.28 752.64 2017 83,959 74,784 158,743 142.43 22.61 28.26 8258 688.19 761.40 2018 84,040 74,819 158,859 144.03 22.88 28.60 8357 696.41 770.49 2019 84,120 74,855 158,975 145.56 23.14 28.93 8452 704.32 779.24 2020 84,200 74,891 159,091 147.15 23.41 29.26 8551 712.54 788.34 2021 84,281 74,927 159,208 147.61 23.5 29.38 8583 715.28 791.37 2022 84,361 74,963 159,324 148.13 23.6 29.50 8620 718.33 794.73 2023 84,442 74,999 159,441 148.64 23.7 29.63 8656 721.37 798.10 2024 84,522 75,035 159,557 149.04 23.78 29.73 8686 723.80 800.80 2025 84,603 75,071 159,674 149.55 23.88 29.85 8722 726.85 804.16 Notes: Population data based on Monroe County Planning Department data in the USACE Carrying Capacity Study (2003) Maximum -day demand based on maximum -day to average -day ratio of 1.25 (2002-2005 average). Maximum -month demand based on maximum -month to average -month ratio of 1.11 (2002-2005 average). The projections include the U.S. Navy's historic use of 1.05 mgd out of their contract for 2.4 mgd. GNV310'13363600.DOCI061640008 2-9 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY 35 _ 250,000 30 . 225,000 a 2.51 a 200,000 E 2-o p N R 0 *AII,-1 `r a d o ' 15 jaa�a 175,000 IL t -110 A* �smass 150,000 U. 0 I i 1_ ; 125,000 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 Year a- Historic Average Day Demand Projected Average Day Demand --AHistoric Maximum Day Demand Projected Mabmum Day Demand a Historic Functional Population (Estimated) Projected Functional Population EXHIBIT 2-9 Graphic Representation of FKAA Service Area Projected 2005-2025 Population and Finished Water Demands Including the existing U.S. Navy's historic demand of 1.05 mgd, the projected average -day finished water demand for the FKAA service area is expected to be 20.07 mgd in 2010, 22.08 mgd in 2015, 23.41 mgd in 2020, and 23.88 mgd in 2025. Maximum -day demands to be used to determine treatment plant capacity needs are expected to be 25.09 mgd in 2010, 27.60 mgd in 2015, 29.26 mgd in 2020, and 29.85 mgd in 2025 (see Exhibit 2-8). In comparing FKAA's finished water demands and per capita water use to other large utilities across South Florida, as listed in the SFWMD Lower East Coast (LEC) Water Supply Plan (Chapter 5 - Table 59), both FKAA's existing (2005) per capita water use (114.08 gpcd) and projected (2025) per capita water use (149.55 gpcd) are well below the LEC Water Supply Plan's calculated average of 172 gpcd. 2.4.1 Peak Hour Demands FKAA provided daily log sheets from the J. Robert Dean Water Treatment Plant (WTP) for selected periods in 2004 and 2005 with above -normal demand, such as Spring Break, Memorial Day, and July 4th. The highest hourly flow rate (23.9 mgd) occurred on March 25, 2005. The 2005 average daily flow rate was 17.73 mgd; therefore, the peak hour demand peaking factor is the peak hour GNV310'13363600.DOC/061640008 2-10 W8122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY (23.9 mgd) divided by the average daily flow for the year (17.73 mgd), or 1.35. This is significantly lower than the typical utility's 3.0 to 6.0 average -day to peak -hour demand ratio reported by Haestad Methods (2003). This discrepancy is attributed to the buffering capacity of the nearly 45 MG of storage in FKAA's distribution and transmission system. This peaking factor was used in conjunction with the average -day demands in Exhibit 2-8 to develop peak hour demands for the FKAA service area. Exhibit 2-10 presents the projected peak hour demand for the FKAA service area through 2025. EXHIBIT 2.10 Projected Peak Hour Demands Year Average Day Demand (mgd) Peak Hour Demand (mgd) 2006 18.58 25.08 2007 18.77 25.34 2008 19.2 25.92 2009 19.64 26.51 2010 20.07 27.09 2011 20.48 27.65 2012 20.88 28.19 2013 21.28 28.73 2014 21.68 29.27 2015 22.08 29.81 2016 22.35 30.17 2017 22.61 30.52 2018 22.88 30.89 2019 23.14 31.24 2020 23.41 31.60 2021 23.5 31.73 2022 23.6 31.86 2023 23.7 32.00 2024 23.78 32.10 2025 23.88 32.24 Notes: Peak hour demand based on the 2005 peak hour to average hour ratio of 1.35. 2.5 Demand by Service Type 2.5.11 Demand by Service Type FKAA records water usage in the following general categories: residential, commercial, government, Navy, and Key West municipal government use. FKAA provided water use GNV31013363600.DOG061640008 2-11 WB122006005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY information for each of these service categories from October 2003 through September 2005. Exhibits 2-11 and 2-12 present tabular and graphical summaries, respectively, of the average monthly water use for each service category. Nearly half (56 percent) of the water produced by the FKAA is used by residential customers. Commercial customers are the next -largest category, with an average use of 32 percent. No large commercial customers (that is, those using 40 percent or more of the water sold in the commercial category) have been identified. The U.S. Navy is FKAA's largest single customer, accounting for 7 percent of its monthly production. Government, senior citizen, and Key West municipal use makes up another 5 percent. EXHIBIT 2-11 Average Monthly Water Use by Category, million gallons, October 2003-September 2005 Month Residential Commercial Navy Government Key West Municipal Senior Citizen Total Jan 273 153 29 16 3 2 476 Feb 236 136 29 15 3 2 421 Mar 241 141 27 14 3 2 428 Apr 291 167 28 17 4 2 509 May 262 152 30 16 4 2 466 Jun 268 149 31 18 4 2 472 JUI 273 158 28 17 4 2 482 Aug 248 143 30 14 3 2 440 Sep 242 136 24 16 3 2 423 Oct 194 113 30 15 3 2 357 Nov 229 136 29 15 3 2 414 DE!C 223 129 29 15 4 2 402 Average 248 143 29 15 3 2 441 Percent 56% 32% 7% 3 % 1 % 1 % GNV31013363600.DOC/061640008 2-12 WB1220f15005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY 1% Demand By Service Type 1% 356% % 7% ■ Residential ■ Commercial o Navy (DOD) 32% o Government ■ Key West Municipal ■ Senior Citizen EXHIBIT 2-12 Graphic Summary of Average Monthly Water Use by Category, million gallons, October 2003—September 2005 FKA.A's contract with the DoD calls for supplying the U.S. Navy with up to 2.4 mgd of water. Fromm 2000 to 2004, deliveries to the U.S. Navy have averaged 1.05 mgd (see Exhibit 2-13). 1.20 1.00 0.80 V E 0.60 0.40 0.20 0.00 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Year EXHIBIT 2-13 U.S. Navy Water Usage from 1996 to 2005 GNV31013363600.DOC/061640008 2-13 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY 2.5.2 Unmetered Water FKAA provided master tap readings for its distribution system (excluding Key West and the Navy) for the period December 2002 through December 2005. The data included the month- ly total for each master tap, the total customer sales for each master tap, and the difference unaccounted -for -water (UAW). FKAA's transmission and distribution system has certain specified maintenance require- ments and activities that result in water being un-metered. These include regular flushing activities to maintain water quality, extensive flushing required during change of chlorine residuals twice per year, water loss resulting from transmission and distribution main break:, and draining of potable water storage tanks for maintenance. Exhibit 2-11 does not include UAW, which has historically averaged 10 to 12 percent. The Amei.ican Water Works Association (AWWA) recommends that UAW should not exceed 5 percent, and that a goal of less than 10 percent is desirable. A total of 4 months with UAW (March, May, October, and December) contribute to the high overall average UAW. FKAA is not: aware of any particular events (maintenance, line breaks, etc.) that may have contributed to the high UAW in those months. If UAW in those months could be reduced, FKAA's UAW would be significantly less. To summarize data from the annual UAW reports that are provided to the SFWMD, the following percentages were recorded: Percentage Year UAW 2003 10.5 2004 9.71 2005 14.93 2006 (Year To Date June 2006) 11.45 FKA-A should set a goal of 10 percent or less UAW in their system based on the uniqueness and operating pressures that FKAA experiences in their system. FKAA should continue to correlate transmission and distribution meter reads so that the data are correlated accurately and so that the actual losses in the transmission mains and the distribution system can be assessed. After this task is complete, identifying and locating potential losses throughout the system may be needed. 2.6 Conclusions Population projections developed by the MCPD were used to develop water demand pro- jections for the FKAA service area through 2025. FKAA's average daily raw water demand is expected to increase from 17.73 mgd in 2005 to 20.07 mgd in 2010, 22.08 mgd in 2015, 23.41 mgd in 2020, and 23.88 mgd in 2025. Maximum -day and peak hour demand were calculated using peaking factors of 1.25 and 1.35, respectively. GNV310'13363600.DOC1061640008 2-14 WB122005005DFB SECTION 2 - POPULATION AND WATER DEMAND FORECAST SUMMARY Residential (nearly half) and commercial (more than one -quarter) account for nearly three- quarters of the FKAA's water demand. UAW comprises approximately 12 percent of FKAA's total production; the remaining water is used primarily by the U.S. Navy and state and local governments. UAW in the FKAA service area is higher than other water systems, and may be the result of FKAA's metering and accounting system, along with system leaks. Additionally, UAW is not distributed evenly throughout the service area, but varies considerably from key to key. Converting the 160 or so master meters along the transmission mains to automatic meter reading may help in identifying the largest areas of UAW. Additional tasks that FKAA could implement include a formal water audit and more specific investigations of water leaks in areas suspected of having UAW. GNV31013363600.DOC1061640008 2-15 W8122005005DFB MONROE COUNTY APPENDIX 3 PLAN Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates COMPREHENSWE PLAN UPDATE County Population with Seasonal Replacement Calculations Monroe County Population Projection Seasonal Replacement Series Perm Change @70%rocs ROGO Growth YEAR Permanent Seasonal Functional 2000 79,589 73,491 153,080 2001 80,011 73,540 153,551 422 2002 80,434 73,589 154,023 423 2003 80,856 73,639 154,495 422 2004 81,236 73,688 154,924 380 2005 82,413 73,737 156,150 1,177 2006 80,510 75,228 155,738 (1,903) -1332.1 1332.1 2007 78,987 76,453 155,440 (1,523) -1066.1 2398.2 2008 76,081 78,647 154,728 (2,906) -2034.2 4432.4 2009 77,925 77,516 155,441 1,844 1290.8 3141.6 ROGO Ou ROGO pop •.7 @2.7pph 2010 76,887 78,401 155,288 (1,038) -726.6 3868.2 2011 78,080 77,974 156,054 1,193 835.1 3033.1 197 372.33 :2012 77,960 78,431 156,391 (120) 84 197 372.33 2013 77,840 78,887 156,727 (120) 84 197 372.33 2014 77,720 79,343 157,063 (120) 84 197 372.33 .2015 77,600 79,800 157,400 (120) 84 197 372.33 2016 77,460 80,270 157,730 (140) 98 197 372.33 2017 77,320 80,740 158,060 (140) 98 197 372.33 .2018 77,180 81,211 158,391 (140) 98 197 372.33 2019 77,040 81,681 158,721 (140) 98 197 372.33 Z020 76,900 82,151 159,051 (140) 98 197 372.33 2021 76,760 82,622 159,382 (140) 98 197 372.33 2022 76,620 83,092 159,712 (140) 98 197 372.33 2023 76,480 83,562 160,042 (140) 98 197 372.33 2024 76,340 84,033 160,373 (140) 98 197 372.33 2025 76,200 84,503 160,703 (140) 98 197 372.33 2026 76,060 84,973 161,033 (140) 98 197 372.33 2027 75,920 85,444 161,364 (140) 98 197 372.33 2028 75,780 85,914 161,694 (140) 98 197 372.33 2029 75,640 86,384 162,024 (140) 98 197 372.33 2030 75,500 86,855 162,355 (140) 98 197 372.33 Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-1S-11 Fishkind and Associates APPENDIX 4 Monroe County 2010-2030 Keith and Schnars, P.A. Population Projections 3-15-11 Fishkind and Associates FISHKIND & ASSOCIATES bbbib bbb Memorandum TO: Debbie Love, AICP, Senior Planner, Keith and Schnars, P.A. FROM: Stanley P. Geberer, Associate Fishkind & Associates, Inc. SUBJECT: DCA Finding Regarding Population Methodology DATE: November 16, 2010 1.0 Background Fishkind has prepared the population projections for unincorporated Monroe County. We have reviewed extensively with County Staff, and provided an update to the final report on August 30 which addressed a series of non -formal questions DCA posed and finally had a conference call with DCA to review their questions and our responses. After a 60 day review DCA has found the methodology unacceptable as shown below. Department has completed its review of the methodology utilized for the seasonal population and identified its concerns below. Due to these concerns, the Department does not find the projection methodologies to be professionally acceptable. This memo will review the items of DCA concern. 2.0 Discussion of Concerns 1-10 Concern 1 1. For Water Supply planning, the Department has previously accepted the methodologies employed by the Florida Keys Aqueduct Authority (FKAA) and recommended that the County utilize the FKAA methodology. The data submitted to date to the Department does not provide the base data utilized by FKAA and how the County applied the FKAA methodology for calculating the seasonal population. The most recent FKAA projections to year 2025 were used as the baseline seasonal projections. These data are attached as Appendix 1. These data were applied directly to the seasonal forecast series and modified as described in Concern 3. Concern 2 12051 Corporate Blvd., Orlando, Florida 32817 • (407) 382-3256 • FAX (407) 382-3254 • email Homeoffice@fishkind.com 2. Please provide a justification for the use of the Compound Annual Growth Rate (CAGR) to extend the FKAA series from 2025 to 2030 for the functional population. This is a geometric extrapolation and should be used with caution. The computed CAGR has not been provided. The new planning horizon must be extended from 2025 to 2030. Compound annual growth rate is an appropriate mechanism whereby baseline growth may be extrapolated. Over the time horizon from 15 to 20 years, the error level of employing other methodologies cannot be said to be superior given these are the final out years of the planning horizon and are subject to the greatest degree of error. The comment from DCA suggesting "caution" should be used is gratuitous to the extent it implies caution was not used, and adds no meaningful dialogue. Further, the Department has not rejected the use of CAGR and fails to suggest a more appropriately method herein. The computed CAGR from year 2000-2025 is as follows: (FKAA seas pop 2025/FKAA seas pop 2000)^(1/26)-1=.082% Concern 3 3. The County indicates there will be a decline in the permanent population as forecast by BEBR. The County has indicated that there will be an increase in seasonal growth equivalent to 70% of the decline in permanent population. For example, the County has submitted information that indicates that retail sales have decreased since 2006. Information submitted regarding changes in annual average daily traffic counts may be attributable to other causes that were not evaluated. Please provide an explanation as to how this addition to the FKAA projections makes sense within the context of the FKAA projection methodology. This addition as well as the addition in the next comment number 4, effectively changes the methodology. The FKAA Seasonal Population methodology as described by FKAA is shown below: FKAA Seasonal Population Methodol 2.2.2 Seasonal Population The MCPD seasonal population projections in the USACE Girnjit[g Capacity St uh,t (USAGE, 2003) also were used to project the seasonal population for Monroe County. Although there are no exact counts of the seasonal population, the MCPD developed historical seasonal population projections for 1990,1995, and 2000. The MCPD projected that the 1990 seasonal population of 70,493 increased by 1.1 percent to a 1995 population of 71,266, and further in- creased b}- 3.1 percent to a 2000 seasonal population of 73,491.The MCPD continues these seasonal population projections in 5-year increments starting with a seasonal population of 73,737 in 2005; 74,533 in 2010; 74,712 in 2015; 74,891 in 2020; and 75,071 in 2025. The seasonal population is projected to increase at an overall average rate of 0.4 percent for each 5-year period from 2005 through 2025, with a 1.1 percent increase between 2005 and 2010 and a 0.24 percent increase from 2010 through 2025. The historic data on seasonal populations presented by FKAA above indicate seasonal population is increasing at an increasing rate. The FKAA methodology failed to incorporate this into its seasonal projections. FKAA projected seasonal population increases at 1/3 the level of the most recent available data initially and then provided a decreased rate of growth through 2025. This rate is far slower than recent trend data FKAA observed. There is no explanation or justification in the FKAA methodology for the failure to recognize and include the robust levels of seasonal growth identified. Table 1 compares the FKAA seasonal growth rates with County seasonal growth rates. Table 1. Seasonal Population Growth Kates Monroe Net FKAA Series Count Difference 1990-1995 1.10 % 1995-2000 3.12% 2000-2005 0.33% 0.33% 2005-2010 1.08% 7.73% 4,904 2010-2015 0.24% 2.70% 1,965 2015-2020 0.24% 2.71% 2,035 2020-2025 0.24% 2.64% 2,034 2025-2030 0.41% 2.57% 1,906 Total Difference 2005-2030 12,843 The approach taken in the preparation of the County seasonal projections is to correct for this problem in the original FKAA methodology in recognizing the more dramatic seasonal population expansion. Concern 4 4. The County included the following sentence which is not clear: "Further, we have added the equivalent of 70% of the ROGO growth to seasonal population to the FKAA seasonal series, reflecting the seasonal shift component not evidenced in FKAA's original data." This appears to add additional population. This has not been adequately explained or justified. The source data, calculations, and results have not been provided. Please see response to Concern 3. Concern 5 5. Please provide justification for the use of the persons -per -household (PPH) figure of 2.5. No data or analysis has been provided for the average size of seasonal households. Please include data or analysis regarding "seasonality." For example, there was no analysis of the maximum occupancy of seasonal units and the amount of time that these seasonal units are occupied at this maximum rate. For the purposes of this analysis seasonal and permanent household sizes used are the same. The preponderance of data provided supports the use of 2.5 persons per household. The Population Report is cited below. from Auqust 30 Population Keport — page I 1 It is also noted, for units shifting to seasonal status and for population associated with ROGO growth, a persons -per -household figure of 2.5 was used. Intercensal data (see Tables 5 and 6) suggests an increase in persons per household by year 2009. Fishkind believes seasonally occupied homes and rentals have a higher person per household occupancy due to the increasing size of newly built units. For these reasons 2.5 was used for seasonal households. Table 5. Persons Per Household Census/Isite Total Unincorp 1990 2.33 2.38 2000 2.27 2.29 2009 3.12 2.89 2014 5.29 4.94 source: I -Site online data Table 6. - Average Number of Bedrooms and Bathrooms per Single Family Unit by Year Built Average Bed/Bath 2.65 Pre-1970 3.33 1970-1989 3.63 1990-1999 3.77 2000-2008 Source: Monroe Co. Property Appraiser, Fishkind & Associates, Inc. Because seasonal population is derived from the seasonal population as presented by FKAA, seasonal occupancy rates are implicit in the analysis, for the original seasonal series. Concern 6 6. Based on Table 7, the seasonal population is roughly equivalent to the residential population. However, the number of seasonal units is much less than the number of occupied (resident) units. Does the FKAA data include population other than those living in housing and if so, how is that accounted for in the data and in the projection? The percentage of non -homesteaded units is higher than homesteaded units in Monroe County, suggesting seasonal population could be at least equivalent to permanent. The FKAA methodology includes cruise ship visitors, visitors from the mainland and those residing in the keys for 6 months or less. They are accounted for in the FKAA calculation of seasonal residents. Concern 7 7. Please provide additional citation for The "I -Site" source. If the data is Census data, then that should be made clear. Projection data from a private sector, third party source cannot be evaluated without a complete explanation of how the projections were made, e.g. the full methodology with all support data must be provided. The I -site data was not used in any methodological calculation in the Monroe County population projections. I -site data was used as a reference source only in referring to support for use of the 2.5 persons per household figure. Concern 8 8. Section 8.0, third paragraph on page 10 discusses "an increase in seasonal population shown in the American Community Survey (ACS)." The ACS does not estimate seasonal population. The ACS provides estimates of seasonal units as shown in Table 2-H3, page 5 of the population report. The change in seasonal population is based in part on the increase in seasonal units identified in the ACS data. Concern 9 9, Section 5.0 and Tables I and 2 provide Census data. There were 51,617 housing units (occupied and vacant) in 2000. Census data indicates there were 21,900 owner occupied units. However, the second paragraph on page 6 indicates that there were 16,005 homestead units and 20,784 non -homestead units in 2000, which add to a total of 36,789 housing units. The housing units for homesteaded/non-homesteaded units should be reconciled with the Census housing units or data provided to explain the difference. The difference cannot be reconciled without imposing egregious costs on the government and citizens of Monroe County in order to do so. The Property Appraiser is the source of homestead and non -homestead status. The property Appraiser data is not reconcilable with Census unit counts. This is a vexing problem addressed by the Regional Planning Council in the hurricane evacuation modeling effort as well. It is believed the difference lies in substandard housing, non -permitted housing, maritime live-aboards and other housing. It is for this reason the analysis and projections were made on a population basis not a housing unit basis. The data on housing units is used as a guide to help estimate changes in the mix and character of resident and seasonal population. Concern 10 10. The final paragraph in Section 1.0 states that a "reconciliation of the Fishkind and Hurricane model data will take place subsequent to the Hurricane data publication." Is this a preliminary report? Will the final population projection be submitted with your Evaluation and Appraisal Report? The Regional Planning Council has reviewed and affirmed the County's population projection methodology. A final review by RPC will be requested and submitted with the EAR.