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<br />Memorandum To: File <br />Page 5 <br />Table 3 <br />Daily Demand for NewDemand <br />Dates Demand (cfs) <br />A ril 15 - Ma 14 600 <br />Ma 15 -June 14 750 <br />June 15 -June 19 800 <br />June 20 -June 21 900 <br />June 22 -June 26 1000 <br />June 27 -Jul 14 800 <br />Jul 15 - Au ust 9 500 <br />Au ust 10 - Au ust 19 300 <br />August 20 - Au ust 29 250 <br />Au st 30 - Se tember 14 80 <br />Se tember 15 - Se tember 24 65 <br />These values were provided to the model in the daily diversion demand (*.ddd) file. <br />September 28, 2001 <br />Monthly baseflows developed in the E1kRvr model were used directly, so there was no baseflow run. <br />Base name for this model was Dlyelkl. <br />Daily Pattern Model (Dlyelk2) <br />The Daily Pattern model was like the Daily Average model except with respect to disaggregation of <br />monthly baseflow. Instead of setting daily baseflows to the monthly average baseflow throughout the <br />month, Statemod calculated each day's baseflow by scaling daily historical gage flow by the factor <br />QMbf~QMgage~ where QMbfis the monthly baseflow and QMgage is the monthly historical gage flow. This <br />was accomplished by 1) setting the daily flag in the river station (*. ris) file to "09241000", the station <br />ID of the Clark gage, and 2) providing the daily historical gage data in the daily streamflow (*.rid) file. <br />Diversion demand, instream flow demand, and reservoir targets were disaggregated in the same manner <br />as in the dlyelkl model, by setting them to an average daily value. Daily return flow fractions generated <br />in Task 1 were used, and because daily baseflows were created from monthly, there was no baseflow <br />run. <br />Base name for this model was Dlyelk2. <br />Daily Input Model (Dlyelk3) <br />In the last daily model, Statemod generated daily baseflows from daily gage records and historical <br />diversion records as available from the database. Daily historical reservoir content was created outside <br />Statemod by straight-line interpolation between end-of-month content data. Daily return flow fractions <br />generated in Task 1 were used as in the other two daily models. <br />TaskMem2Final.doc f30YLE' <br />