Scale-dependency of hydraulic conductivity: an example from Thorne Moor, a raised mire in South Yorkshire, UK

Bromley, J., Barker, J.A. and Robinson, M. (2004) Scale-dependency of hydraulic conductivity: an example from Thorne Moor, a raised mire in South Yorkshire, UK. Hydrological Processes, 18 (5), 973-985. (doi:10.1002/hyp.1341).

Abstract

The hydraulic conductivity (K) of many low permeability materials is strongly scale-dependent. In raised mires and other types of peat deposit the effects of features such as abandoned infilled ditches, root holes and localized woody material, cause K to be heterogeneous and scale-dependent. Despite this, field measurements are routinely made using auger hole (slug) tests at the scale of only a few tens of centimetres. Such measurements are locally valid, but where the regional subsurface movement of water through peat bogs is simulated using groundwater models, typically at the scale of hundreds of metres, they give rise to a systematic underestimate of flows and an overprediction of water table elevations. Until now, techniques to obtain values at a scale sufficiently large to include the effects of localized features of higher permeability have not been applied routinely. Research at Thorne Moor, a large raised mire, demonstrates that the K of peat varies over several orders of magnitude when measured at different scales, using a variety of techniques. Laboratory and auger hole tests cannot be relied upon to provide results that represent the hydraulic conductivity of large expanses of peatland. This has significant implications for the management and long-term restoration of peatlands where both regional and local control of water levels is crucial. For groundwater models to be used successfully to plan such schemes, it is essential to apply the K values relevant to the scale of the simulation. This paper describes and tests novel techniques, using ditches, for the derivation of K at large scales which overcome many of the problems that have been identified with conventional techniques and are capable of producing estimates that are appropriate to the application of physically based regional flow models.

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