Timescale dependence in river channel migration measurements. Issue 8 (5th March 2019) - Donovan, Mitchell; Belmont, Patrick
Abstract: Accurately measuring river meander migration over time is critical for sediment budgets and understanding how rivers respond to changes in hydrology or sediment supply. However, estimates of meander migration rates or streambank contributions to sediment budgets using repeat aerial imagery, maps, or topographic data will be underestimated without proper accounting for channel reversal. Furthermore, comparing channel planform adjustment measured over dissimilar timescales are biased because short‐ and long‐term measurements are disproportionately affected by temporary rate variability, long‐term hiatuses, and channel reversals. We evaluate the role of timescale dependence for the Root River, a single threaded meandering sand‐ and gravel‐bedded river in southeastern Minnesota, USA, with 76 years of aerial photographs spanning an era of landscape changes that have drastically altered flows. Empirical data and results from a statistical river migration model both confirm a temporal measurement‐scale dependence, illustrated by systematic underestimations (2–15% at 50 years) and convergence of migration rates measured over sufficiently long timescales (> 40 years). Frequency of channel reversals exerts primary control on measurement bias for longer time intervals by erasing the record of observable migration. We conclude that using long‐term measurements of channel migration for sediment remobilization projections, streambank contributions to sediment budgets, sediment flux estimates, and perceptions of fluvial change will necessarily underestimate such calculations. © 2019 John Wiley & Sons, Ltd. Abstract : Empirical observations and results from a novel statistical model illustrate a systematic convergence and underestimation in channel migration rates as temporal measurement scale increases, predominantly the result of reversals in migration direction. Our research demonstrates how timescale dependence inherently biases comparisons of migration measurements from disparate timescales in addition to providing an approach to guide future research aimed at quantifying how rivers respond to hydrologic changes.