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3 occasions in 1996 and twice during 1997. Discharges during mapping ranged from 2,100 to 27,000 ft3/s. Flow patterns were divided into areas of downstream flow, and eddies which have zones of flow recirculation. Eddies were demarcated as the area of channel enclosed by the shoreline and the Von Karmen vortex street, generally known as an eddy fence. Areal extent of eddies was determined by obtaining a vantage reasonably high above the river from which the eddies were easily identified and mapped. Flow chazacteristics within the eddies were determined from observations of flotsam from shore, or by direct inspection from an inflatable kayak. Shorelines in each of the reaches were delineated into 6 general categories; fine-grained alluvium, densely-vegetated fine-grained alluvium, cobble and gravel, debris flow deposits, talus, and bedrock. Because of the significance to neaz-shore habitat, densely-vegetated fine-grained alluvium, where vegetation was inundated or overhanging the river, was mapped as a shoreline class separate from haze fines. Vegetation occurring on coazse substrates was also mapped, but because it occurred infrequently was not considered independently. The effect discharge has on the relative abundance of any given shoreline habitat type was analyzed both by individual. study reach and as the summation of the 4 reaches. Lengths of each shoreline class were measured in each reach at 5 or 6 discharges ranging from 2,100 to 27,000 ft3/s. Total lengths of each shoreline category were totaled for each reach, and divided by channel length. The resultant unit lengths of each shoreline type were plotted against discharge for each reach. GPS Each individual air photo was geo-referenced in the field in order to transform field maps into a continuous reach rnap. The coordinate position of control points on the Earth's surface was obtained using ahand-held Global Positioning System (GPS). A minimum of 4 control points were established on the first air photo of each reach, and each subsequent photo contained enough controls to overlap with previous and subsequent photos. Control points were objects that could be positively identified on the ground and photo, and were not likely to have changed since the time of the photograph. Control points were typically prominent boulders and man- made structures. GPS relies on the availability of navigation satellites within the visible sky. In narrow canyons, narrow windows of sky may contain too few satellites to calculate positions. Pathfinder software was used before mapping field trips to calculate times and locations within the canyons where abundant satellites would be visible. GPS accuracy is also influenced by a pre-installed error in the satellite signal which limits the accuracy tot 100 m. To eliminate this error, GPS data collected in the field were compared with data collected simultaneously at a base-station of known geographic location. The direction and magnitude of the pre-installed error was calculated and subtracted from the field data resulting in positions accurate to f 2 m. GIS Database Creation Individual segments of field maps were digitized separately and entered into a GIS database using Arc/Info software. Once digitized, control points in each map segment were assigned coordinate values in Universal Transverse Mercator (LTTM) units. The softwaze was used to organize the map segments into their correct positions in space according to the coordinate values of the control points. Segments were then stitched together into one A-5