Abstract River‐floodplain exchange occurs when high flows inundate the floodplain and exchange water bi‐directionally between substrates and communities. While well‐understood locally, the full spatial heterogeneity of exchange event duration (the residence time) and magnitude (the exchange flux, or discharge) remains poorly constrained, limiting our understanding of the role that underlying structural connectivity and hydrologic regime plays in basin‐scale mixing. Here, we use machine learning to predict river‐floodplain exchange duration and magnitude for over 1.8M rivers in the contiguous United States. We find residence time is on average 3.4 times longer in the floodplain than the river, with that difference decreasing as both event and river size increase. Further, more than 31% of basin water may exchange with the floodplain during large floods. We confirm that the cumulative effect of reach‐scale exchange influences basin‐scale mixing and subsequent biogeochemical processing, though the nature of that influence will be region, river, and constituent specific.
Brinkerhoff et al. (Sat,) studied this question.