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Resource managers, scientists, government regulators, and stakeholders are considering sophisticated numerical models for managing complex environmental problems. In this study, observations from a river-rehabilitation experiment involving gravel augmentation and spawning habitat enhancement were used to assess sources and magnitudes of error in depth, velocity, and shear velocity predictions made at the 1-m scale with a commercial two-dimensional (depth-averaged) model. Error in 2D model depth prediction averaged 21%. This error was attributable to topographic survey resolution, which at 1 pt per 1.14 m2, was inadequate to resolve small humps and depressions influencing point measurements. Error in 2D model velocity prediction averaged 29%. More than half of this error was attributable to depth prediction error. Despite depth and velocity error, 56% of tested 2D model predictions of shear velocity were within the 95% confidence limit of the best field-based estimation method. Ninety percent of the error in shear velocity prediction was explained by velocity prediction error. Multiple field-based estimates of shear velocity differed by up to 160%, so the lower error for the 2D model's predictions suggests such models are at least as accurate as field measurement. 2D models enable detailed, spatially distributed estimates compared to the small number measurable in a field campaign of comparable cost. They also can be used for design evaluation. Although such numerical models are limited to channel types adhering to model assumptions and yield predictions only accurate to ∼20-30%, they can provide a useful tool for river-rehabilitation design and assessment, including spatially diverse habitat heterogeneity as well as for pre- and post-project appraisal. © 2006 Elsevier B.V. All rights reserved.

Substantial research effort has been devoted to understanding stream-dwelling salmonids' use of summer rearing and growth habitat, with a subset of studies focusing on foraging position selection and the energetic trade-offs of differential habitat use. To date, however, cost-benefit analyses for most foraging model studies have focused on small sampling areas such as individual habitat units. To address this knowledge gap, we applied a mechanistic foraging model to 22 stream reaches (100-400 m) from two watersheds within the Columbia River Basin. We found a strong, positive correlation ([R.sup.2] = 0.61, p < 0.001) between predicted carrying capacities and observed fish densities. Predicted proportion of suitable habitat was weakly correlated with observed fish density ([R.sup.2] = 0.18, p = 0.051), but the mean net rate of energy intake prediction in sampling reaches was not a significant predictor of observed fish biomass. Our results suggest spatial configuration of habitat, in addition to quantity and quality, is an important determinant of habitat use. Further, carrying capacity predicted by the model shows promise as a habitat metric. We also evaluated the feasibility of applying this data- intensive modeling approach in a large-scale monitoring program to examine habitat quality and quantity. Though the approach can be computationally expensive, we feel the model's ability to integrate physical habitat metrics (e.g., depth, velocity) with important biological considerations like food availability and temperature is a benefit that far outweighs associated costs. We feel this modeling approach has great potential as a tool to help understand habitat use in drift-feeding fishes. D'importants efforts de recherche ont ete voues a la comprehension de l'utilisation d'habitats estivaux d'alevinage et de croissance par les salmonides de cours d'eau, dont un sous-ensemble d'etudes s'etant axe sur la selection de la position d'approvisionnement et les compromis energetiques associes a l'utilisation differentielle d'habitats. Les analyses coutsavantages realisees a ce jour pour la plupart des etudes de modeles d'approvisionnement se sont toutefois attardees a de petites zones d'echantillonnage comme des unites d'habitat individuelles. Pour combler ce manque de connaissances, nous avons applique un modele d'approvisionnement mecaniste a 22 troncons de cours d'eau longs de 100 a 400 m dans deux bassins versants du bassin du fleuve Columbia. Nous avons constate une forte correlation positive ([R.sup.2] = 0,61, p < 0,001) entre les capacites de charge predites et les densites de poissons observees. La proportion predite d'habitats convenables etait faiblement correlee a la densite de poissons observee ([R.sup.2] = 0,18, p = 0,051), mais le taux net moyen d'apport energetique predit dans les troncons echantillonnes n'etait pas une variable explicative significative de la biomasse de poissons observee. Nos resultats donnent a penser que la configuration spatiale de l'habitat, combinee a sa quantite et sa qualite, est un important determinant de l'utilisation de cet habitat. En outre, la capacite de charge predite par le modele s'avere prometteuse comme parametre de l'habitat. Nous avons egalement evalue la faisabilite d'appliquer cette approche de modelisation riche en donnees dans le cadre d'un programme de surveillance a grande echelle visant a examiner la qualite et la quantite des habitats. Bien que cette approche puisse etre couteuse sur le plan computationnel, nous estimons que la capacite du modele a integrer des parametres physiques de l'habitat (p. ex. profondeur, velocite) et des considerations biologiques importantes comme la disponibilite de nourriture et la temperature constitue un avantage qui compense amplement les couts associes. Nous croyons que cette approche de modelisation a beaucoup de potentiel comme outil pour aider a comprendre l'utilisation de l'habitat chez les poissons qui se nourrissent a la derive. [Traduit par la Redaction], Introduction Conservation and recovery of many lotic fishes depend on successful management and restoration of their habitat. In the Columbia River Basin (CRB), for example, recovery efforts for listed salmon [...]