Investigating the contribution of first-order streams to floods in downstream water bodies on the central Appalachian plateau.

Flash floods are the costliest natural disaster in Appalachia. The goal of this study is to better understand flood response in headwater streams and the role of these systems in the generation of downstream floods. We applied a process-based hydrologic model using data from the Robinson Forest environmental monitoring network to estimate the contribution of headwaters to downstream floods. We then used the model to understand the effects of landscape disturbance in headwaters on downstream floods. Finally, we developed empirical hydrologic models to identify useful data for predicting downstream peak flood discharge. Results indicate that headwaters in our study catchment contribute 73% of volume to downstream floods on average, and landscape disturbances in headwaters can increase downstream flood volume and peak discharge, especially during high intensity storms. We find headwater discharge data is useful for prediction of downstream flash floods, thus we encourage researchers to increase monitoring in such systems.

Publication Details

Journal
ThinkIR: The University of Louisville's Institutional Repository (University of Louisville)
Published
2024-12-01
Primary Topic
Study of Mite Species
Type
article
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article

Investigating the contribution of first-order streams to floods in downstream water bodies on the central Appalachian plateau.

ThinkIR: The University of Louisville's Institutional Repository (University of Louisville)
Study of Mite Species
article

Investigating the contribution of first-order streams to floods in downstream water bodies on the central Appalachian plateau.

article en

Abstract

Flash floods are the costliest natural disaster in Appalachia. The goal of this study is to better understand flood response in headwater streams and the role of these systems in the generation of downstream floods. We applied a process-based hydrologic model using data from the Robinson Forest environmental monitoring network to estimate the contribution of headwaters to downstream floods. We then used the model to understand the effects of landscape disturbance in headwaters on downstream floods. Finally, we developed empirical hydrologic models to identify useful data for predicting downstream peak flood discharge. Results indicate that headwaters in our study catchment contribute 73% of volume to downstream floods on average, and landscape disturbances in headwaters can increase downstream flood volume and peak discharge, especially during high intensity storms. We find headwater discharge data is useful for prediction of downstream flash floods, thus we encourage researchers to increase monitoring in such systems.

ThinkIR: The University of Louisville's Institutional Repository (University of Louisville)
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Openalex Percentile: Top 25%
Study of Mite Species
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