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Table 1:. Summaf'/l of yield lo..e. in the Pacific Coast area due to increasing salinity of irrigation water from the (::.:) Colorado River and irrigation method as compared with present water quaUty and best irrigation ) practice - thousand tons. !\) ...::r Total Dissolved Solids in Irrigation Water, rug/1 t- Crop Irrigations ~ Per Year 900 1000 1100 1200 1300 1400 Avocados Surface 0.6 1.7 2.8 13,256 Ac. Sprinkler 0.6 Trickler Grapefruit Surface 0.55 0.80 1.06 1.36 1.55 4.50 655 Ac. Sprinkler 0.16 0.40 0.69 0.93 1.24 1.60 Trickler Lemons Surface 3.5 5.1 6.8 8.6 9.8 21.1 3.158 Ac. Sprinkler 1.0 2.5 4.4 5.9 7.9 10.2 Trickler Naval Oranges Surface 0.55 0.82 1.08 1.39 1.58 3.39 1,145 Ac. Sprinkler 0.15 0.40 0.70 0.94 1.26 1.63 TrickIer Valencia Oranges Surface 4.48 6.52 8.64 11.09 12.64 27.14 9,465 Ac. Sprinkler 1.30 3.26 5.63 7.58 10.11 13.05 TrickIer Potatoes Surface 0.06 0.27 625 Ac. Sprinkler Trickler Strawberry Surface 0.29 0.64 0.99 635 Ac. Sprinkler Trickier Tangerine Surface 0.78 Ll3 1.49 1.92 2.19 4.70 1,070 Ac. Sprinkler 0.22 0.56 0.97 1.31 1.75 2.26 Trickler Summer Tomatoes Surface 0.11 0.29 0.49 0.64 0.80 0.97 330 Ac. Sprinkler 0.21 0.42 0.59 0.77 Trickler Fall Tomatoes Surface 0.74 1.88 3.28 3.75 5.16 6.56 3,135 Ac. Sprinkler 1.41 2.81 3.98 5.16 Trickier Spring Tomatoes Surface 0.2 0.8 1.4 1.6 2.2 14.3 1,019 Ac. Sprinkler 0.6 1.2 1.7 2.2 Trickler Limes Surface 0.22 0.32 0.42 0.54 0.61 1.31 325 Ac. Sprinkler 0.06 0.16 0.27 0.37 0.49 0.63 Trickle! then used as inputs to a linear programming profit maximization model, wherein the optimal farmer response to salinity change was delineated. From this optimization for salinity levels from 900 to 1,400 mg/l, a damage function was defined for each impact area. This linear programming work was carried out by personnel of the Bureau of Reclamation. The Linear Programming Model The linear programming routine (APEX.I), utilized for analysis, was a program supplied by Control Data Corporation and run on the CDC Cyber 74/28 system of the Bureau of Reclamation in Denver. This LP package has sufficient capacity and flexibility to allow modeling of all sizes of irrigation districts. The model was designed to maximize net returns to aU farmers in a district above variable production costs and 'new capital investments subject to resource and production constraints. Detailed enterprise budgets for the crops representative of conditions in each irrigated area were used to develop the input for the linear programming model. The crops used were alfalfa hay, cotton, sugar beets, sorghum, wheat, barley, lettuce, tomatoes. asparagus, onions, watermelon, carrots, and canta- loupe which account for about 90 percent of the acreages. Each of these crop activities was defined on four soil drainage conditions: very poorly drained, poorly drained, moderately well drained, and well drained. Tbe combination of each crop under each soil 13