2021 CSDMS meeting-034

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Alex Lipp  choose to not submit an abstract for this conference.

The geochemistry of river sediments is used to interrogate numerous tectonic, climatic and geomorphic problems. Despite this importance, a quantitative understanding of how sedimentary geochemistry varies across drainage basins is lacking. We present a methodology to predict elemental compositions of river sediments using geochemical maps, digital elevation data and models of physical landscape evolution. Our predictions are evaluated using new sedimentary geochemical data gathered from sample sites in rivers draining the Cairngorms mountain range, UK. The geochemical and topographic input are derived from publicly accessible datasets (G-BASE, SRTM). The results indicated that topography and source region geochemistry provide the data necessary to predict the sedimentary compositions for most major and trace elements investigated (e.g. Mg, K, Be, Co, V, U) . Model predictions are insensitive to the different erosional model parameterisations we tested (e.g. linear and non-linear versions of the stream power model). A simplification of the river geochemical data using principal component analysis shows that the composition of river sediments, in our study region, can be mostly explained assuming simple conservative mixing of mafic and felsic source regions. The predictive framework we develop can be inverted to allow source region geochemistry to be determined from downstream samples. We discuss the non-uniqueness of this problem and how it can be solved using numerical methods. The inversion approach is a first step towards using higher-order fluvial geochemistry as a quantitative tool to interrogate source region geochemistry for environmental monitoring and exploration purposes. Our forward and inverse schemes represent progress towards a fully quantitative understanding of fluvial sedimentary geochemistry.