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Research Articles

Impacts of an extreme flood on large wood recruitment and transport processes

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon &
Pages 55-83
Received 25 Jan 2021
Accepted 11 Sep 2021
Published online: 29 Nov 2021
 

ABSTRACT

This research investigates impacts of an extreme flood on recruitment and transport of large wood (LW) in sub-basins of the North Fork River, Missouri. Data collection took place two months after a >500 year flood to characterize LW conditions before natural recovery processes could obscure impacts. We used sites from previous LW studies in the region as reference to help identify flood impacts. Results showed 1) LW load volumes were no different than reference sites, but individual LW pieces comprised a greater percentage of the total load, 2) a high proportion of pieces at flood-impacted sites contained root wads, 3) transport capacity of the flood-impacted sites was high compared to reference sites, and 4) LW recruitment increased exponentially with flood magnitude. These results suggest that extreme floods have a significant impact on the composition of the LW load, and that geomorphic impacts of such floods may result in enhanced transport capacities. Based on these findings, we present two possible post-flood LW response/recovery scenarios; one in which elevated transport capacity serves to speed system recovery to the pre-flood LW regime, and one in which the enhanced LW piece composition results in a new post-flood LW regime with an enhanced load.

Acknowledgements

The authors would like to thank the funding source for this research: National Science Foundation RAPID Response Grant SBE GSS-1748816. We would also like to thank the Missouri State University summer 2017 Geography Field Methods class for helping with field data collection. Finally, we would like to thank the four anonymous reviewers that helped improve the quality of this manuscript.

Data availability statement

The data that support the findings of this study can be made available, upon reasonable request from the corresponding author at martindj1@appstate.edu

Additional information

Funding

This work was supported by the National Science Foundation [SBE GSS- 1748816].

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