Prediction of mountain stream morphology

Abstract

[1] We use a large and diverse data set from mountain streams around the world to explore relationships between reach-scale channel morphology and control variables. The data set includes 177 step-pool reaches, 44 plane-bed reaches, and 114 pool-riffle reaches from the western United States, Panama, and New Zealand. We performed several iterations of stepwise discriminant analysis on these data. A three-variable discriminant function using slope (S), D 84 , and channel width (w) produced an error rate of 24% for the entire data set. Seventy percent of plane-bed reaches were correctly classified (16% incorrectly classified as pool-riffle and 14% incorrectly classified as step-pool). Sixtyseven percent of pool-riffle channels were correctly classified (31% incorrectly classified as plane-bed and 2% as step-pool). Eighty-nine percent of step-pool reaches were correctly classified (9% incorrectly classified as plane-bed and 2% as pool-riffle). The partial R 2 values and F tests indicate that S is by far the most significant single explanatory variable. Comparison of the eight discriminant functions developed using different data sets indicates that no single variable is present in all functions, suggesting that the discriminant functions are sensitive to the specific stream reaches being analyzed. However, the three-variable discriminant function developed from the entire data set correctly classified 69% of the 159 channels included in an independent validation data set. The ability to accurately classify channel type in other regions using the three-variable discriminant function developed from the entire data set has important implications for water resources management, such as facilitating prediction of channel morphology using regional S-w-D 84 relations calibrated with minimal field work.

Occurrence of cluster microforms in mountain rivers

“…It should also be noted that the inclusion of slope lessened the statistical significance of the predictive models. This was not expected since slope has been found to be a good predictor for reach average conditions (Wohl et al, 2004;Wohl and Merritt, 2005;Thompson et al, 2006). While the bivariate model of ln(S) did out perform other predictor variables, it did not perform as well as w* or the remaining variables in Equation (4) ( Table II).…”

“…Individual variables that were found to be most descriptive in predicting a dominant clustered topography on the three rivers examined were w, d 84 and Q. Wohl and Merritt (2005) also found w and d 84 to be useful in predicting reach morphology, but they found that S rather than Q was also important. Non-dimensional forms of these variables, e.g.…”

A catchment-scale model of mountain stream channel morphologies in southeast Australia

“…In previous catchment-scale analyses, the importance of correctly determining channel slope from available data sources has been recognised as a key factor in model performance Wohl and Merritt, 2005). For this study, modelled slopes compare well to surveyed reach slopes and show a significant correlation (R 2 = 0.66; p b 0.001; Fig.…”

“…Recent evaluations of mountain stream channel morphology suggest channel slope is the dominant discriminating variable (Montgomery and Buffington, 1997;Wohl and Merritt, 2005;Thompson et al, 2006). For Southeast Australian mountain streams Thompson et al (2006) indicated that catchment lithology and contributing catchment area are also required to discriminate between some reach morphologies.…”

A roughness-corrected index of relative bed stability for regional stream surveys

“…Kaufmann (1987a), however, showed that hydraulic resistance was inversely related to the relative submergence of bedforms and other large-scale roughness elements (riffles, pools, steps), and these could be quantified by the ratio of mean thalweg depth (d th ) to mean thalweg residual depth (d res ). He interpreted d th /d res as an expression of relative submergence of bedforms (e.g., riffles and pools), analogous in concept to Wohl and Merritt's (2005) definition of "relative form roughness," the ratio of hydraulic radius to bedform height (which is actually a relative submergence index). The inverse hydraulic resistance measure, (8/f t ) 0.5 = U/U⁎ = (U 2 /gRS) 0.5 , back-calculated from mean advective dye transport velocity, was log-linearly related to relative submergence of residual depth [(8/f) 0.5 = 0.62 Ln(d th / d res ), R 2 = 0.57, n = 40].…”