Influence of cover on mean column hydraulic characteristics in small pool riffle morphology streams

Abstract

The field of ecohydraulics tries to link biological-and physical-based processes in order to describe better the distribution of plants and animals in rivers. We tested the hypothesis that the influence of cover in pools and riffles would not be detectable using average velocity, turbulent kinetic energy and turbulent intensity, and compared these measurements to locations distant from cover. We measured water velocity fluctuations using an acoustic Doppler velocimeter. We found that turbulent intensity in the downstream direction (u 0 ) and the transverse or cross-stream direction (v 0 ) were the most useful in detecting the presence of cover in pools and riffles. Differences were apparent between locations near cover in pools and riffles. Turbulent kinetic energy (k) and vertical turbulent intensity (w 0 ) detected cover in pools but not in riffles. Average downstream velocity (u) detected cover in riffles but not in pools. Average cross-stream (v) and vertical (w) velocities did not detect any differences at all. We rejected the null hypothesis and concluded that turbulence caused by habitat features such as large rocks, wood or other channel complexities results in a statistically meaningful difference in flow characteristics in locations near cover. This finding was tempered by the fact that knowledge about how fish respond to turbulence is limited in comparison to our understanding of average velocity values. Despite the potential benefits to habitat modelling of incorporating turbulence-based metrics, application of these findings will be challenging because turbulence modelling is difficult and current models may not be appropriate for application to rivers.

Interactive effects of cover and hydraulics on brown trout habitat selection patterns

“…This was illustrated in the fast waters, wherein the largest proportion of >1þ individuals occupied positions with water depths ranging 30-40 cm associated with undercut banks or a combination of overhanging vegetation and tree roots, avoiding the more exposed shallow pools. In water depths below 30 cm, adult trout were observed in fast-flowing riffles, selecting positions connected to velocity shelters such as large boulders and woody debris, which also act as visual shelters by creating surface turbulence (Smith and Brannon, 2007) and increasing habitat complexity and thus visual isolation (Dolinsek et al, 2007). These complex patterns were well described by the resource selection models developed in the present study through interaction terms between the FR and cover and substrate variables.…”

“…However, our multivariate RSFs highlight that distribution of fish cannot be only defined by hydraulic patterns, depicting a scenario where position choice is driven by biologically important interactions among microhabitat variables. Consequently, as Smith and Brannon (2007) pointed out, models that simulate complex flow patterns in streams resulting from the interaction of cover and flow (Leclerc et al, 1995;Ghanem et al, 1996;Diplas, 2000, 2002) may improve our ability to predict distribution and abundance of fish. Moreover, other important components of cover such as surface turbulence (Smith et al, 2005) should be also included in habitat models by using the FR (Bovee et al, 1998) which has been proved to be ecologically meaningful (Kemp et al, 2000;present study).…”

Use of Ecohydraulic-Based Mesohabitat Classification and Fish Species Traits for Stream Restoration Design

“…This hypothesis defines that during low-flow stages velocities in pools are slow and riffles are relatively fast, and near bankfull high-flows velocities transition where pools are fast and riffles are slow [76,[138][139][140][141][142][143]. A reversal in bed shear stress also occurs from low-to high-flow stages resulting in bed scour in pools and bedload deposition in riffles during high flows.…”

“…While pool spacing is regular in less complex stream reach morphologies where 3D helical flow patterns develop, spacing can be influenced by instream channel structures [128,143]. In streams with large roughness elements, velocity vectors and turbulence intensities scale to these elements, and appear to prevent development of reach-scale 3D helical patterns [91,160].…”

A high‐resolution hydrodynamic investigation of brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss) redds

“…To illustrate any depth-wise trends, a modification of turbulent kinetic energy was developed. An alternative to the Reynolds number as a measure of turbulence, mean turbulent kinetic energy per unit mass is used to assess the consistency of time-averaged velocity measurements (Moody and Smith, 2004;Stone et al, 2006;Smith and Brannon, 2007) The data collected are thirty-second time-averaged velocities. If the above form is modified where the variance is calculated from the collection of individual threedimensional velocities that constitute a single velocity profile, a water column with a reduced influence from secondary flows will be indicated by a reduced overall turbulent kinetic energy along the depth of the velocity profile.…”