Saturated Hydraulic Conductivity in Northern Peats Inferred From Other Measurements. Issue 11 (8th November 2022) - Morris, P. J.; Davies, M. L.; Baird, A. J.; Balliston, N.; Bourgault, M.‐A.; Clymo, R. S.; Fewster, R. E.; Furukawa, A. K.; Holden, J.; Kessel, E.; Ketcheson, S. J.; Kløve, B.; et al.
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 r 2 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 r 2  = 0.64). Two additional models that omit several predictors perform less well (cross‐validated r 2 ∼ 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. Key Points: We report skillful statistical models to estimate saturated hydraulic conductivity in northern peats from simpler measurements Peat dry bulk density and humification (von Post score) are particularly powerful predictors Our models represent an improvement over existing pedotransfer functions for peat saturated hydraulic conductivity