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<br />"'j <br />r-.. <br />1.."" <br /> <br />'.:::..) <br /> <br />-~) <br />..:.: I. <br /> <br />. <br /> <br />. <br /> <br />Purpose - To more accurately estimate the salt loading at a given <br /> <br />station. Due to the spotty nature of the data (especially for <br /> <br />drains) in addition to many different methods of calculating salt <br /> <br />loading, the estimates can vary significantly. The program was <br /> <br />designed to handle any data availability situation and apply the <br /> <br />"best" method for that particular situation rather than simply using <br /> <br />one method for the entire record. <br /> <br />II. Description of Program - The program operates on a d..ily basis <br /> <br />defining a "data availability case" for each day then applying the <br /> <br />"best" method to calculate that day's flow, TDS, and salt loading. <br /> <br />The user must input one linear regression TDSzf(EC) function for the <br /> <br />irrigation season and one for the non-irrigation season. In <br /> <br />addition, a power regression of TDS=f(flow) for the entire year is <br /> <br />required. These equations can be derived using the grab sample <br /> <br />data. Figure 12 illustrates the data availability cases and the <br /> <br />parameters controlling which methods are used. <br /> <br />GSI = grab sample interval in days (lapse time between <br /> <br />the bordering samples) MAXILO = User supplied <br /> <br />parameter representing the maximum i.nterval (low) <br /> <br />between grab samples in days. If the grab sample <br /> <br />interval is less than MAXILO, then the program will <br /> <br />use a time specific TDS-EC relationE,hip instead of <br /> <br />the long-term regression equation. <br /> <br />A-l <br />