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.. The Government Bridge study site was modeled with a single IFG4 data deck by combining 3 sets of stage-discharge measurements and one set of velocity measurements. Results of the calibration are presented in Table 12. Only sixty-seven percent of the velocity adjustment factors fell within the II good II category. While the predictive water surface elevations were good (Table 11), the velocity adjustment factors were poor. Overall, this data deck is rated marginal to fair. WA Predictions The calibrated data deck was run through HABTAT4 for adult Colorado squawfish (Size 5, 400+mm). The resulting habitat versus discharge relationship (Table 13) suggests that adult Colorado squawfish habitat is maximized at 400 cfs with a 90 percent habitat retention level at approximately 150 and 800 cfs. Compared to the historic flow of record at the Government Bridge site (Attachment 3), 400 cfs is exceeded 100, 87.7, 35.4 and 13.8 percent of the time in June, July, August and September respectively. As with the previous study sites, the model's predicted optimal habitat versus discharge represents a rare historic event in June and July. Discussion Bovee (1982) suggested that in most cases the Instream Flow Incremental Methodology (IFIM) should be used as a decision making tool to compare alternative water management scenarios associated with a particular project proposal. He further advised that IFIM should not be considered an ecosystem model intended to generate a single solution but rather a predictive technique best used to analyze relative impacts of different flow regimes. PHABSIM is but one component of IFIM and predicts the availability of suitable physical micro-habitats as a function of discharge. In this case, PHABSIM was applied in an attempt to develop stream flow recommendations to optimize habitat conditions for endangered fishes. Its relative usefulness, particularly on large rivers, is problematic. The combination of hydraulic data collected along stream cross-sectional transects, and 51 curves assumes that suitable habitat for fish species can be accurately described by three microhabitat variables (depth, velocity and substrate), when macrohabitat variables, such as channel stability, temperature and water quality, are assumed suitable throughout a given range of flows. These assumptions, however, may not be valid if other physical, chemical or biological variables are influencing species distribution and abundance. Kaeding and Osmundson (1989), as well as others, have pointed out that variables other than depth, velocity and substrate may be of equal or greater influence on the actual microhabitat use of the fish. In this analysis, the potential influence of other variables was not included nor modeled. Bovee (1986) stated that the development of a valid utilization function requires the unbiased measurement of microhabitat variables at specific fish locations. Development of SI curves which accurately reflect the actual microhabitat used by target fishes in large, turbid rivers is currently constrained by state-of-the-art measuring techniques and sampling gear limitations. Determining the exact location of fish in turbid rivers is virtually impossible. Thus, microhabitat information collected from radio- telemetered fishes employing customary USGS measuring techniques may not 15