Examination of High Resolution Channel Topography to Determine Suitable Metrics to Characterize Morphological Complexity

Abstract:

Complex bed morphology is deemed necessary to restore salmonid habitats, yet quantifiable metrics that capture channel complexity have remained elusive. This work utilizes high resolution topographic data from the 40 miles of the Trinity River of northern California to determine a suitable metric for characterizing morphological complexity at the reach scale. The study area is segregated into reaches defined by individual riffle pool units or aggregates of several consecutive units. Potential measures of complexity include rugosity and depth statistics such as standard deviation and interquartile range, yet previous research has shown these metrics are scale dependent and subject to sampling density-based bias. The effect of sampling density on the present analysis has been reduced by underrepresenting the high resolution topographic data as a 3’x 3’ raster so that all areas are equally sampled. Standard rugosity, defined as the three-dimensional surface area divided by projected area, has been shown to be dependent on average depth. We therefore define R*, a empirically depth-corrected rugosity metric in which rugosity is corrected using an empirical relationship based on linear regression between the standard rugosity metric and average depth. By removing the dependence on depth using a regression based on the study reach, R* provides a measure reach scale complexity relative to the entire study area. The interquartile range of depths is also depth-dependent, so we defined a non-dimensional metric (IQR*) as the interquartile range dividing by median depth. These are calculated to develop rankings of channel complexity which, are found to closely agree with perceived channel complexity observed in the field. Current efforts combine these measures of morphological complexity with salmonid habitat suitability to evaluate the effects of channel complexity on the various life stages of salmonids. Future work will investigate the downstream sequencing of channel complexity as it relates to high value ecological functioning for salmonid production.