Abstract

In northern peatlands, near-saturated surface conditions promote valuable ecosystem services such as carbon storage and drinking water provision. Peat saturated hydraulic conductivity (K_sat) plays an important role in maintaining wet surface conditions by moderating drainage and evapotranspiration. Peat K_sat can exhibit intense spatial variability in three dimensions and can change rapidly in response to disturbance. The development of skillful predictive equations for peat K_sat 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 K_sat 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 and fen). Peat K_sat 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 K_sat, 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 K_sat to be estimated from less comprehensive data. Our models allow improved estimation of peat K_sat from simpler, cheaper measurements.