Reconstructing ancient river dynamics from the stratigraphic record: can lessons from the past inform our future?

Abstract:

The richness of the deep-time record and its potential for revealing important characteristics of ancient fluvial landscapes has been demonstrated time and again, including compelling examples of rivers altering their behavior in response to changes in vegetation patterns or abrupt shifts in water and sediment discharge. At present, reconstructions of ancient river and floodplain dynamics are commonly qualitative, and when quantitative metrics are used, it is often for comparison among ancient deposits. Without being able to reconstruct, more comprehensively, important aspects of ancient river and floodplains dynamics, this information has only anecdotal relevance for evaluating and managing present-day landscapes. While methods for reconstructing hydrodynamic and morphodynamic aspects of ancient rivers and floodplains are useful, uncertainties associated with these snapshots complicate the ability to translate observations from geologic to engineering scales, thereby limiting the utility of insight from Earth’s past in decision-making and development of sustainable landscape-management practices for modern fluvial landscapes. Here, we explore the degree to which paleomorphodynamic reconstructions from ancient channel and floodplain deposits can be used to make specific, quantitative inferences about ancient river dynamics. We compare a suite of paleoenvironmental measurements from a variety of ancient fluvial deposits (including reconstructions of paleoflow depth, paleoslope, paleo-channel mobility, the caliber of paleo-sediment load, and paleo-floodplain heterogeneity) in an effort to evaluate sampling and empirical uncertainties associated with these methods and identify promising avenues for developing more detailed landscape reconstructions. This work is aimed at helping to develop strategies for extracting practicable information from the stratigraphic record that is relevant for sustainably managing and predicting changes in today’s environments.