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1 1 '~ t C 1 needs of targeted fish species. Tazgeted fish species locations were marked while snorkeling, and physical parameters for microhabitat use--depth, velocity, cover, substrate, and distance to cover--determined for each location. Suitability weighting factors were developed for each pazameter and the weighted usable area (WUA) calculated. The stream and the accompanying physical parameters were then modeled for a variety of discharges, and azeas of optimal, useable, and unsuitable habitat were calculated for a range of low flows. Riparian and Valley Flows Hill et al. [1991] used HEC-2 modeling to determine dischazges for bankfull, riparian, and floodplain flows. These modeled dischazges were combined with historic exceedance probabilities for peak flows and flow duration curves to determine the magnitude, duration, and hydrograph shape of different flow regimes (for example riparian vs. valley flows). Hill et al. [1991] assumed that the restoration of a "natural" hydrograph would guarantee ecological integrity, but they ignored many of the other consequences of stream alteration such as changes in temperature, sediment load, sediment availability and size distribution, and water quality. Complexity Indices Complexity indices based on physical habitat parameters such as depth, water velocity, and substrate size have been related to habitat complexity in cold water streams [Bovee, 1982]. In that light, some river ecologists have used a "bank coefficient" [Gosse, 1963, as cited in Bedell, 1989] to measure river heterogeneity and hence, habitat heterogeneity or complexity [Bedell, 1989]. The "bank coefficient" is the ratio of shoreline length to channel centerline length, and quantifies the relative amount of shoreline per unit length of river [Gosse, 1963, cited in Bedell, 1989]. High values of the bank coefficient indicate the presence of islands and/or bank irregularities. Consequently, a complexity index such as the bank coefficient reflects within- channel morphology. In the context of nursery habitat, the convoluted nature of the shoreline maybe indicative of the azea of low or no velocity areas within the channel. The Green River neaz Ouray includes midchannel bars and some very large vegetated islands. As is shown below, these features greatly increase the length of shoreline, but do not necessarily contribute to nursery habitat azea, and the "bank coefficient" of Gosse [1963] maybe only weakly correlated to habitat availability in this reach. Consequently, a complexity index that, to some degree, minimizes the effects of midchannel bars and lazge islands maybe more desirable for reaches such as Ouray NWR. Previous Green River Instream Flow Studies Although sand-bedded rivers and the response of these rivers to flow regulation have been the focus of much study over the past three decades, many questions remain unanswered. The response of channels to disturbance was studied by Andrews [1986], Lyons et al. [1992], and Yu and Wohnan [1987]. The first two studies addressed the long-term downstream effects of Flaming Gorge Dam and the latter study modeled the response of channels to flood passage, but all of these studies used channel width, not within-channel distribution of bars, to measure channel response. Colorado pikeminnow use habitats formed in the lee ofwithin-channel bed- and barforms. Consequently, the long-term measurements used to assesses the effects of dams (i.e., changes in channel width) measure neither changes to within-channel geomorphic features nor the impact of channel changes on habitat availability. A-11