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TABLE 3. NET CONSUMPTIVE USE VALUES 1984-1985: CRDSS VS. XCONS2 <br />19841985 <br />HYDRO- XCONS 2 XCONS2 CRDSS XCONS 2 XCONS2 CRDSS <br />LOGIC BOOK PROGRAM PROGRAM BOOK PROGRAM PROGRAM <br />UNITCOUNTYACRES (AC-FT ) (AC-FT) (AC-FT)ACRES (AC-FT ) (AC-FT) (AC-FT) <br />14020002 Delta 9490 15619 15619 15620 10280 17373 17373 17350 <br />14020004 Delta 26280 37318 37318 37980 26400 41888 41888 42250 <br />14020005 Delta 41370 81568 85912 88290 41540 87199 90176 91490 <br />14020006 Delta 7630 13823 13823 14130 7940 15807 15807 15930 <br />14020001 Gunnison 9370 3693 3693 3720 9510 4818 4818 4820 <br />14020002 Gunnison 24840 28897 24881 27390 25210 29244 31786 31770 <br />14020003 Gunnison 11720 11388 11388 12570 11890 14278 14278 14280 <br />14020004 Gunnison 940 363 363 360 950 469 469 470 <br />14020002 Hinsdale 610 320 320 360 670 490 490 490 <br />14020005 Mesa 5210 11141 13941 13950 5180 11064 13606 13610 <br />14020002 Montrose 9230 12007 12007 12630 9200 13746 13746 13850 <br />14020005 Montrose 5380 10639 10639 10660 5360 11394 11394 11400 <br />14020006 Montrose 48140 80273 93111 92990 48020 92198 102683 102610 <br />14020006 Ouray 16720 15466 15466 15460 16720 13543 13543 13510 <br />14020003 Saguache 10600 8401 8401 9490 13680 11719 11719 11720 <br />Totals 227530 330916 346882 355600 232550 365230 383776 385550 <br />Finally, the biggest difference comes from Tables 1 and 3 from the computation of Delta5 which is 3,692 <br />acre-feet. The total difference between the two programs for all the hydrologic units is 10,492 acre-feet. <br />Therefore, Delta5 is considered the worst case. <br />Summary of Computations for Delta5 - Vegetables <br />Table 4 summarizes computations of Crop Evapotranspiration of vegetables for Delta5 (the worst case). <br />Vegetables and alfalfa were selected in order to have a representation analysis of perennial and annual <br />crops. <br />In order to understand how the differences were distributed, the different values of crop <br />evapotranspiration were evaluated at the beginning, during, and at the end of the season (Table 5). It was <br />determined from the data in Table 5 that the end of the season values caused a large portion of the <br />differences in the results between the two programs. <br />The data was further analyzed to determine if the differences at the end of the season were related to the <br />percentage of days in the month corresponding to the ending period. The output from a regression <br />analysis showed that the percentage of error was strongly correlated with the percentage of days in the <br />month (coefficient of regression of 0.99), and the greater the percentage of days in the month, the greater <br />the percentage of error. <br />3 <br />A275 01.09.95 1.14-21 CSU-IDS <br />