2002 Denver Annual Meeting (October 27-30, 2002)

Paper No. 8
Presentation Time: 8:00 AM-12:00 PM


JOHNSON III, Harold E.1, JACOBSON, Robert B.2, REUTER, Joanna M.2 and PANFIL, Maria S.2, (1)USGS Columbia Environmental Rsch Ctr, 4200 New Haven Road, Columbia, MO 65203, (2)USGS Columbia Environmental Research Center, 4200 New Haven Road, Columbia, MO 65203, hejohnson@usgs.gov

Land-use changes have the potential to disturb streams by altering hydrologic or sediment-yield characteristics of drainage basins. Geomorphic responses, however, may be difficult to detect because of inherent spatial variability of the landscape, because disturbances may be subject to thresholds and time lags, and because disturbances may diminish or grow as they travel downstream. We surveyed 70 reaches of streams in the Ozarks of southern Missouri and northern Arkansas using a consistent fluvial geomorphology and aquatic habitat assessment protocol. Reach-scale geomorphic and sediment data are tested for association with numerous geologic, physiographic, and land-use measures for the contributing drainage basins. Previous analysis of part of this dataset concluded that drainage-basin size and physiography dominate land-use disturbance signals; statistically significant variation with land-use intensity could only be detected when looking at subsets of physiographically similar drainage basins (Panfil and Jacobson, 2001, U.S. Geological Survey, BSR-2001-0005). Among a new set of drainage basins with less variation in size (11 – 67 km2) and more variation in land-use practices (100% forested to 60% pasture/range) more trend is apparent. For example, residual pool depth, variation among streams in residual pool depth, median particle size, and variation among streams in median particle size appear to decrease with increasing agricultural land use. Bankfull widths show a slight decrease with increasing agricultural land use. Although these trends are what would be expected from land-use disturbance, large variation in dependent variables and co-variation among explanatory variables confound cause and effect linkages.