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Charles A. Dolloff

Researcher at United States Forest Service

Publications -  8
Citations -  699

Charles A. Dolloff is an academic researcher from United States Forest Service. The author has contributed to research in topics: Riparian zone & Stream restoration. The author has an hindex of 8, co-authored 8 publications receiving 631 citations. Previous affiliations of Charles A. Dolloff include United States Fish and Wildlife Service.

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Regional frameworks applied to hydrology: can landscape-based frameworks capture the hydrologic variability?

TL;DR: In this paper, a study was conducted to determine whether landscape-based regional frameworks could explain variation in streamflow classifications and in the hydrologic variables used in their creation.
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Application of the ELOHA framework to regulated rivers in the Upper Tennessee River Basin: a case study

TL;DR: Although ELOHA provided a robust template to construct hydrologic information and predict hydrology for ungaged locations, the results do not suggest that univariate relationships between flow and ecology can produce results sufficient to guide flow restoration in regulated rivers.
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Revisiting the homogenization of dammed rivers in the southeastern US

TL;DR: In this paper, the authors used a regional flow classification as the foundation for evaluating patterns of hydrologic alteration due to dams and to determine if the response of rivers to regulation was specific to different flow classes.
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Gravel Addition as a Habitat Restoration Technique for Tailwaters

TL;DR: In this paper, the authors assessed the efficacy of passive gravel addition at forming catostomid spawning habitat under various flow regimes in the Cheoah River, a high-gradient tailwater river in North Carolina.
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A regional classification of unregulated stream flows: spatial resolution and hierarchical frameworks

TL;DR: In this article, the authors classify unregulated streams within an eight-state region into groups in order to provide environmental flow standards for managers and to relate that dataset to frameworks created at larger scales.