Prediction of mountain stream morphology

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). Sixty‐seven 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.