Saturated hydraulic conductivity in northern peats inferred from other measurements

Morris, P.J. and Davies, M.L. and Baird, A.J. and Balliston, N. and Bourgault, M‐A. and Clymo, R.S. and Fewster, R.E. and Furukawa, A.K. and Holden, J. and Kessel, E. and Ketcheson, S.J. and Kløve, B. and Larocque, M. and Marttila, H. and Menberu, M.W. and Moore, P.A. and Price, J.S. and Ronkanen, A‐K. and Rosa, E. and Strack, M. and Surridge, B.W.J. and Waddington, J.M. and Whittington, P. and Wilkinson, S.L. (2022) Saturated hydraulic conductivity in northern peats inferred from other measurements. Water Resources Research, 58 (11). ISSN 0043-1397

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Abstract

In northern peatlands, near-saturated surface conditions promote valuable ecosystem services such as carbon storage and drinking water provision. Peat saturated hydraulic conductivity (Ksat) plays an important role in maintaining wet surface conditions by moderating drainage and evapotranspiration. Peat Ksat can exhibit intense spatial variability in three dimensions, and can change rapidly in response to disturbance. The development of skilful predictive equations for peat Ksat and other hydraulic properties, akin to mineral soil pedotransfer functions, remains a subject of ongoing research. We report a meta-analysis of 2,507 northern peat samples, from which we developed linear models that predict peat Ksat from other variables, including depth, dry bulk density, von Post score (degree of humification), and categorical information such as surface microform type and peatland trophic type (e.g., bog, fen). Peat Ksat decreases strongly with increasing depth, dry bulk density and humification; and increases along the trophic gradient from bog to fen peat. Dry bulk density and humification are particularly important predictors, and increase model skill greatly; our best model, which includes these variables, has a cross-validated r2 of 0.75, and little bias. A second model that includes humification but omits dry bulk density, intended for rapid field estimations of Ksat, also performs well (cross-validated r2 = 0.64). Two additional models that omit several predictors perform less well (cross-validated r2 ∼ 0.5), and exhibit greater bias, but allow Ksat to be estimated from less comprehensive data. Our models allow improved estimation of peat Ksat from simpler, cheaper measurements.

Item Type:
Journal Article
Journal or Publication Title:
Water Resources Research
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300/2312
Subjects:
ID Code:
178173
Deposited By:
Deposited On:
28 Oct 2022 15:40
Refereed?:
Yes
Published?:
Published
Last Modified:
30 Nov 2022 04:06