Bayesian age modelling applied to palaeoflood geochronologies and the investigation of Holocene flood magnitude and frequency

A new methodology, based on Bayesian age modelling, is presented for the analysis of palaeoflood geochronologies and palaeodischarge data. Bayesian age models were developed, using the Oxcal radiocarbon calibration software, for the geochronologies of three palaeoflood sites in Spain, namely the Gaudalentín, Tagus and Llobregat rivers in SE, Central and NE Spain, respectively. The age–depth plots resulting from the applied Sequence models enabled the construction of flood magnitude-frequency plots through substitution of the original stratigraphic depth data with the associated minimum discharge quantified by hydraulic modelling. The age models presented demonstrate that a Bayesian approach for analyzing Holocene flood magnitude and frequency prevents the loss of geomorphic and hydrologic information inherent in radiocarbon frequency methods previously used in the analysis of palaeoflood data sets. Frequency approaches do not allow proper consideration of flood magnitude information and only incorporate those geomorphic units specifically dated. The Bayesian age models calculate modeled ages for undated units as well, so that all the individual flood events identified in the field can be incorporated and visualized in the data output. The palaeoflood age models therefore illustrate: (1) the age range for clusters of palaeoflood events; (2) the number of events within each flood cluster, with an age estimate and palaeodischarge value for each event; and (3) the potential impact of discharge censoring on the record, for example the role of accommodation space infilling on the quantification of palaeodischarge. The methodology and results are briefly discussed within the wider context of fluvial palaeohydrology, in particular: (1) the role of Bayesian modelling in future fluvial palaeohydrology research; and (2) the value of bedrock gorge sites for investigating past flood–climate relationships, given the problems of deciphering allogenic and autogenic drivers in alluvial sedimentary records.