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<br />tv <br />00 <br />~ <br />~ <br /> <br />form. Trage-offs exist among alternative salinity control <br />measures and some are prerequisite on the implementation of <br />others. It is therefore difficult, if not impossible, to <br />identify the best program to implement without incorporating <br />an optimizational analysis. A case study of the Grand Valley ,~t, <br />of western Colorado uSlng these tools demonstrated a 20-30% cos~~" <br />savings over the existing salinity control plan. On a larger ,~ <br />scale such as the Upper Colorado River Basin, the benefits of <br />optimization basin planning could amount to many millions of <br />dollars annually. <br /> <br />Unfortunately, there is not enough data in most irrigated <br />areas for a Grand Valley type investigation and one may be <br />inclined to wonder at the value of this study. The problem <br />in other areas will be delineating the best management practices <br />at the firSt levels of salinity control planning. It should be <br />possible to identify the relative emphasis on desalting on- <br />farm improvements, conveyance system linings, and drainage, <br />but not the individual characteristics of these alternatives. <br />consequently, the value of the optimizational techniques in <br />the planning process will occur in two stages. The first <br />analysis can identify the priority among the primary control <br />measures to serve as a guide to more detailed studies. Then <br />as is the case in the Grand Valley, the process can be repeated <br />with the agded data to determine the policies for implementation, <br />on a more detailed level. <br /> <br />5 <br /> <br />i. <br /> <br />