Predicting River Floodplain and Lateral Channel Migration for Salmon Habitat Conservation¹

Abstract

In this article, we describe a method for predicting floodplain locations and potential lateral channel migration across 82,900 km (491 km2 by bankfull area) of streams in the Columbia River basin. Predictions are based on channel confinement, channel slope, bankfull width, and bankfull depth derived from digital elevation and precipitation data. Half of the 367 km2 (47,900 km by length) of low‐gradient channels (≤ 4% channel slope) were classified as floodplain channels with a high likelihood of lateral channel migration (182 km2, 50%). Classification agreement between modeled and field‐measured floodplain confinement was 85% (κ = 0.46, p < 0.001) with the largest source of error being the misclassification of unconfined channels as confined (55% omission error). Classification agreement between predicted channel migration and lateral migration determined from aerial photographs was 76% (κ = 0.53, p < 0.001) with the largest source of error being the misclassification of laterally migrating channels as non‐migrating (35% omission error). On average, more salmon populations were associated with laterally migrating channels and floodplains than with confined or nonmigrating channels. These data are useful for many river basin planning applications, including identification of land use impacts to floodplain habitats and locations with restoration potential for listed salmonids or other species of concern.

Spatial disaggregation and aggregation procedures for characterizing fluvial features at the network-scale: Application to the Rhône basin (France)

“…A large set of previous works generated resolution-driven spatial units (from several meters to several kilometers long) along the streamline to measure attributes and highlight longitudinal patterns (e.g., Piégay et al, 2000;Hall et al, 2007). This measuring process is generalized through the spatial disaggregation of the UGO into high resolution spatial units, called the 'DGO' (disaggregated geographical object).…”

“…A first method consists in isolating this relatively low and flat valley component from the landscape by a neighborhood analysis of cell elevation and/or slope (Gallant and Dowling, 2003). A second approach consists in considering the valley bottom as a submerged floodplain for a uniform waterflow height (Williams et al, 2000) or scaled with channel width or discharge (Nardi et al, 2006;Hall et al, 2007). We used this second approach with a uniform threshold of relative height independent from the channel size because the valley bottom coincides with the Holocene floodplains (Fig.…”

“…The data available at the national scale (e.g., digital elevation models (DEM), orthophotographs and land use databases) provide new possibilities for the spatially continuous characterization of stream networks (Hall et al, 2007;Amos et al, 2008;Orr et al, 2008). Nevertheless, few methodological efforts have been made to develop spatial frameworks that integrate the theoretical advances in our understanding of the longitudinal and hierarchical organization of the fluvial system (Frissell et al, 1986;Poole, 2002), i.e.…”

Assessment Approach for Identifying Compatibility of Restoration Projects with Geomorphic and Flooding Processes in Gravel Bed Rivers

“…We initially considered two alternative, relatively established approach frameworks, consisting of (1) identifying and siting projects based on classification and mimicry of channel morphology where it is assumed function follows form (e.g., Rosgen and Silvey 1996;Brierley et al 2002Brierley et al , 2011, and (2) evaluating landscape and watershed scale attributes to identify reach potential for restoration (e.g., Bartz et al 2006;Burnett et al 2007;Hall et al 2007;Beechie et al 2008). In the former case, we noted that while the approach can work at times, the results are susceptible to failure because they do not account explicitly for larger-scale processes such that the river simply ignored the specific imposed channel form (Kondolf 1998;Kondolf et al 2001;Parker 2004;Simon et al 2007), and the choice of which class a stream belongs to may be equivocal (Roper et al 2008).…”

Biophysical Characterisation of Fluvial Corridors at Reach to Network Scales

“…In addition, data from oblique aerial photos, field campaigns (e.g. grain size distribution, hydraulic parameters) or other GIS resources (floodplain or land-use polygons, stream power/flow records using regionalized hydrological models) (Williams et al, 2000;Dawson et al, 2002;Nardi et al, 2004;Hall et al, 2007) can be incorporated into the analysis.…”