Data from: Reconstructing lateral migration rates in meandering systems - a novel Bayesian approach combining OSL dating and historical maps



Identifying lateral migration rates of meandering rivers is relevant both for fluvial geomorphology and to support river management. Lateral migration rates for contemporary meandering systems are often reconstructed based on sequential remote-sensing images or historical maps; however, the time frame for which these sources are available is limited and hence likely to represent fluvial systems subjected to human influence. Here, we propose to use scroll bar sequences as an archive to look further back in time using optically stimulated luminescence (OSL) dating of sand-sized quartz grains. We develop a modelling procedure for the joint Bayesian analysis of (OSL) dating results and historical map data. The procedure is applied to two meanders from the Overijsselse Vecht, a medium-sized sand-bed river in the Netherlands. We obtained nine samples for OSL dating from scroll bars and combined OSL dating results with historical map data for the period 1720–1901 CE (Common Era). The procedure we propose here incorporates the strengths of both data types for reconstructing fluvial morphodynamics over longer time frames. Using an iterative modelling approach, we translate spatial uncertainty of historical maps into temporal uncertainty of channel position required for Bayesian deposition modelling. Our results indicate that meander formation in the Overijsselse Vecht system started around 1400 CE, and lateral migration rates were on average 2.6 and 0.9 m yr-1 for the two investigated bends, until river channelization around 1900 CE.
Date made available13 Sep 2018
PublisherWageningen University & Research
Temporal coverage1800 - 1900
Geographical coverageJunner Koeland and Prathoek meander bends, Overijsselse Vecht


  • Bayesian chronological modelling
  • Fluvial geomorphology
  • historical maps
  • Holocene
  • lateral migration
  • optically stimulated luminescence
  • OxCal

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