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<br />6 <br /> <br />26. Another form of comparison, which involves only flow records ta]wn from <br />the target area, results when the decision to seed an area is made periodically at <br />random before the nature of the flow for an ensuing water year has been influenced <br />by observed events. All storms exhibiting pre',-iously specified temperature, moistuTe, <br />and .dnd characteristics could be seeded in the years desienated for seedine, and <br />left untreated in the years designated for no seeding. Comparison of target area <br />flow during years selected for seeding at random with the flows observed in the <br />intervening years i"hen no seeding occurred will at 1east be free of the complication <br />of fortuitous runs of several i'let or dry years in a row, but care must be taken that <br />the assumptions of normal distribution that underlie some tests of significance are <br />adequately met before they are applied (Thorn, 1957). It is important that successive <br />year flows do not exhibit large carryover effects. <br /> <br />27. The second, general type of hydrological evaluation involves comparison of <br />each period of seeded target flow with an estimate of what the flow i'lould have been <br />in the absence of seeding. These estimates have usually been made by employing <br />prediction equations developed by regression analysis inVOlving the past records of <br />the target basin and one or more neighbouring basins. The name "target-control" <br />has usually been applied to this approach. <br /> <br />28. The evaluation of <br />is an example of the use of <br />ring basins as predictors. <br /> <br />the seeding of the Kines River Basin (Henderson, 1975) <br />a prediction equation employing the fIoH of two neighbou- <br />The equation: <br /> <br />Ke <br /> <br />1.85 CI + 1.72 O2 - 124.4, <br /> <br />where X is the predicted floi'! (in acre-feet) of the Kings River and 01 ancl C2 <br />represegt the flow of the Merced and Kern Rivers respectively, has be~n used to <br />assess the seeding effectiveness during the period 1954 to 1974. In the 20 years <br />evaluated, 14 shovred evidence of positive effect. A significance level of 0.01 is <br />reported to apply. <br /> <br />29. Where good records of streamflow and precipitation are ava:Llable" the <br />estimates of target area flo.r can be based on controls that employ both precipit>ction <br />and streamflow values as precUctors. An outstanding example of this app:J:oach is the <br />evaluation applied to the Skagit River in the Cascade Hountains of the State of <br />"'ashington (Hastay and Gladvlell, 1968). The data bank: available for use in develop- <br />ing the prediction equations of target area streamflow consisted of 34 years of <br />record for 26 precipitation stations, 21 river gauginG stations and 13 temperature <br />stations. Eliminat,ion of 15 r;i.ver gauging stat:i.ons because of distance from the <br />target area, and elimination of certain precipitation records in which inhomogeniety <br />of observing circumstances seemed to be a problem, reduced the number of possible <br />control values to 29. In making the regression analysis, some very high correlations <br />were computed betiVeen the streamflows from the Skagit River target areas and neigh- <br />bourine basins. For example, the correlation coefficient between the records for <br />the Cascade River, gauged, at l1,-'],rblemount (d.I'ainage area 470 km2) and the Skagit <br />River, gauged at Concrete (drainage area 7000 km2) ivaS 0.98637. <br /> <br />30. Applica tion of prinCipal component analysis, .li th a requirement that a <br />variable be significant at the 0.10 level, produced prediction equations of the fO:l.'"JlI <br /> <br />Yt Bo + BIKit + ,......" + BkXkt + Ut <br /> <br />i.here Yt is the preclicted tax'get streamfl01,v, the Bs arc real constants, the Ks are <br />the explanatory variables and Ut is a nornnlly independently d.istributed. random e~Tor <br />with a mean of zero. <br />