Preprints
https://doi.org/10.5194/egusphere-2026-3786
https://doi.org/10.5194/egusphere-2026-3786
10 Jul 2026
 | 10 Jul 2026
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Soil-to-stream export of dissolved organic carbon and its functional composition can be predicted using only widely available data

Katarzyna Sawicka, Edwin C. Rowe, Donald T. Monteith, Amy Pickard, Brian M. Spears, Jennifer Williamson, Annette Burden, Alan Radbourne, Zak Mitchell, Dan J. Lapworth, Christopher A. Yates, Penny J. Johnes, and Christopher D. Evans

Abstract. Dissolved organic carbon (DOC) exports from soil to aquatic systems are significant components of the global carbon cycle and are of concern to the water industry owing to the role of DOC in the formation of disinfection byproducts. Modelling the processing of DOC as it flows from soil to the ocean requires distinction between compounds that are relatively more aromatic, coloured, ultraviolet-sorbent and photolabile, but resistant to microbial breakdown (T1), from less photo-reactive but more microbially labile compounds (T2). We assessed whether mean annual DOC concentration and its T1 fraction (pT1) can be predicted from data that are widely available, without in-situ measurements, to enable applications within Earth System Models. Using only spatially resolved data that are available at global scale, we estimated DOC concentration and pT1 for a range of headwater catchments in the United Kingdom. The best fitted models predicted DOC concentration (Nash-Sutcliffe efficiency, NSE = 0.71) and pT1 (NSE = 0.57) from land use (arable and wetland), soil type (peat or mineral), precipitation chemistry (ionic strength) and areal runoff. Application at national scale demonstrated expected spatial patterns in the distribution of DOC concentration and pT1, with high concentrations in peatlands in the north of the country, and highest pT1 in northern and western areas with high peat cover and surface runoff generation. The approach described here could be applied to other regions, transferring understanding of land-to-water DOC export from data-rich to data-poor areas.

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Katarzyna Sawicka, Edwin C. Rowe, Donald T. Monteith, Amy Pickard, Brian M. Spears, Jennifer Williamson, Annette Burden, Alan Radbourne, Zak Mitchell, Dan J. Lapworth, Christopher A. Yates, Penny J. Johnes, and Christopher D. Evans

Status: open (until 21 Aug 2026)

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Katarzyna Sawicka, Edwin C. Rowe, Donald T. Monteith, Amy Pickard, Brian M. Spears, Jennifer Williamson, Annette Burden, Alan Radbourne, Zak Mitchell, Dan J. Lapworth, Christopher A. Yates, Penny J. Johnes, and Christopher D. Evans
Katarzyna Sawicka, Edwin C. Rowe, Donald T. Monteith, Amy Pickard, Brian M. Spears, Jennifer Williamson, Annette Burden, Alan Radbourne, Zak Mitchell, Dan J. Lapworth, Christopher A. Yates, Penny J. Johnes, and Christopher D. Evans
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Latest update: 10 Jul 2026
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Short summary
We developed a simple way to predict how much dissolved organic carbon moves from soils into streams, and what types of carbon are present, using widely available data. By analysing 150 small catchments across Great Britain, we found that peat-rich landscapes release more carbon, especially forms that are resistant to breakdown, while farmland releases less and simpler forms. These patterns can be mapped at large scales, helping improve carbon cycle estimates and support water management.
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