The Importance of a Null Model for Identifying Change in Alluvial River Channels
Abstract
Predicting a single rivers response to climate change remains a challenging endeavor due to limited observations, the absence of a dynamic model for rivers, and the inherent variability within a river corridor. Despite this challenge, predicting river response to hydroclimatic change remains a research priority due to the close coupling between society and alluvial rivers. Progress requires distinguishing between variation attributable to changing hydroclimate or land use and the variability inherent within a dynamic river system. Unlike changes in climate or river discharge where historic data records may be readily available, a baseline for river geomorphic behavior is limited to a few locales. Absent a baseline, we posit an expectation of the first order channel geometry as a reasonable starting point from which to document and compare change. It is not altogether obvious that rivers should have a consistent expected geometry given widely varying hydroclimates, sediment supply, regional lithologic constraints and varying vegetation. However, natural rivers follow remarkably consistent hydraulic-geometry scaling relations. Starting with the constraint that channel formation requires that fluid stress exceeds the threshold for sediment entrainment, we review the explanatory power of the near-threshold channel model as an empirically and experimentally verified explanation for the hydraulic geometry of alluvial rivers. We demonstrate the utility of a first order model for channel geometry for understanding channel patterns, responses to variations in changing boundary conditions, and framing dynamic channel behavior. While we continue to lack a dynamic model for channel response to perturbations, the near-threshold model provides a robust prediction of the first order geometry and we propose that this expectation can serve as a reliable null hypothesis when parsing variability from change within alluvial rivers.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMEP55C1129P